VOORWOORD -...

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1 VOORWOORD Resessie armoedeverligting voedselsekuriteit verhoogde landbouproduksie kosteknyptang verhoogde invoere! Hierdie woorde is tans deel van die algemene omgangstaal in landbou in die Wes-Kaap. Maar waar is die oplossings? Sommiges is moeiliker haalbaar as ander sommiges is dalk buite u beheer of invloed. Een van die oplossings vir volhoubare en winsgewende produksie is egter naby u en haalbaar om die nuutste navorsingsinligting by die kenners te kry en dit deel van u wenresep op u plaas te maak! Vandag gaan u met die kenners op die gebied van weiding- en suiwelnavorsing skouer skuur en voorpunt-inligting ontvang. Hierdie kenners is deel van die uitgebreide navorsingspan van die Departement van Landbou Wes-Kaap wat homself onderskei deur gefokusde en oplossing-soekende navorsing vir die boer van die Wes-Kaap. Die belang van landbounavorsing is vanjaar deur die Wes-Kaapse Regering as een van sy hoof prioriteite geidentifiseer, veral in die soeke na verhoogde landbouproduksie. Laasgenoemde het natuurlik verskeie raakvlakke met werkskepping, groter winsgewendheid, kompeteerbaarheid en „n groter kosmandjie vir die mense van die Wes-Kaap en Suid-Afrika, om maar „n paar te noem. Hierdie inligtingsdag is weer eens een van die hoogtepunte op die 2009 tegnologie-oordrag kalender van die Departement en ons wil u hartlik uitnooi om ons ekspertise deel van u wenboerdery te maak! Saam kan ons landbou in die Wes-Kaap volhoubaar laat groei! Dr. Ilse Trautmann DIREKTEUR: TEGNOLOGIE, NAVORSING EN ONTWIKKELINGSDIENSTE, DEPARTEMENT LANDBOU WES-KAAP

Transcript of VOORWOORD -...

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VOORWOORD

Resessie – armoedeverligting – voedselsekuriteit – verhoogde

landbouproduksie – kosteknyptang – verhoogde invoere!

Hierdie woorde is tans deel van die algemene omgangstaal in landbou in die

Wes-Kaap. Maar waar is die oplossings? Sommiges is moeiliker haalbaar as

ander – sommiges is dalk buite u beheer of invloed. Een van die oplossings

vir volhoubare en winsgewende produksie is egter naby u en haalbaar – om

die nuutste navorsingsinligting by die kenners te kry en dit deel van u

wenresep op u plaas te maak! Vandag gaan u met die kenners op die gebied

van weiding- en suiwelnavorsing skouer skuur en voorpunt-inligting ontvang.

Hierdie kenners is deel van die uitgebreide navorsingspan van die

Departement van Landbou Wes-Kaap wat homself onderskei deur gefokusde

en oplossing-soekende navorsing vir die boer van die Wes-Kaap.

Die belang van landbounavorsing is vanjaar deur die Wes-Kaapse Regering

as een van sy hoof prioriteite geidentifiseer, veral in die soeke na verhoogde

landbouproduksie. Laasgenoemde het natuurlik verskeie raakvlakke met

werkskepping, groter winsgewendheid, kompeteerbaarheid en „n groter

kosmandjie vir die mense van die Wes-Kaap en Suid-Afrika, om maar „n paar

te noem.

Hierdie inligtingsdag is weer eens een van die hoogtepunte op die 2009

tegnologie-oordrag kalender van die Departement en ons wil u hartlik uitnooi

om ons ekspertise deel van u wenboerdery te maak! Saam kan ons landbou

in die Wes-Kaap volhoubaar laat groei!

Dr. Ilse Trautmann

DIREKTEUR: TEGNOLOGIE, NAVORSING EN

ONTWIKKELINGSDIENSTE, DEPARTEMENT LANDBOU WES-KAAP

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Ontwikkeling van stikstofbemestingsnorme vir kikoejoe oorgesaai met

raaigras.

J. Labuschagne & B Zulu

1. Inleiding

Die oorsaai van meerjarige weidings soos kikoejoe met raaigras is ‟n praktyk wat

vinnig veld wen. Hierdie praktyk verseker dat addisionele droëmateriaal gedurende

die wintermaande geproduseer word wanneer die meerjarige weiding stadig groei as

gevolg van lae temperature en kort dae. Aangesien twee weigewasse waarvan die

seisoenale stikstofbehoeftes verskil, saam in een kamp voorkom, kan verwag word

dat die stikstofbehoefte van die gemengde weiding sal verskil van dié van suiwer

weidings.

Stikstofbemesting moet só beplan word dat dit net in die onmiddellike (4-6 weke)

stikstofbehoefte van die weiding sal voorsien. Daar bestaan geen voordeel om meer

stikstof toe te dien as wat die potensiaal van die weiding of kamp toelaat nie. Indien

die toegediende stikstof oor lang periodes in die grond lê, sal die kans vir

stikstofverliese as gevolg van ongunstige omgewingstoestande drasties verhoog.

Die huidige aanbeveling vir grasweidings die Suid-Kaap is 56kg N/ha na elke

beweiding. Die oorsaai van permanente weidings met raaigras het egter vrae laat

ontstaan of hierdie aanbeveling steeds geld. Verskeie proewe word tans gedoen om

hierdie behoefte aan te spreek. Die kikoejoeproewe sal kortliks hier hanteer word.

Slegs voorlopige data is beskikbaar en finale aanbevelings sal na voltooiing van die

proewe geformuleer word.

2. Proefprosedure

Op Outeniqua is ‟n kamp gevestigde kikoejoe gedurende April 2008 kort afgewei,

waarna die weiding met ‟n stokkiekapper verpulp is. Meerjarige raaigras (Bronsyn) is

vervolgens teen 20kg/ha op 28 April met ‟n Aitchison planter geplant en gevolg deur

‟n ligte landroller om goeie saad-grond kontak te verseker. Geen stikstof is tydens of

direk na die oorsaaiproses toegedien nie. Die oorgesaaide raaigras is tyd gelaat on

goed te vestig waarna dit op die 10de Julie bewei is. Stikstofbehandelings van 0, 20,

40, 60 en 80 kg N/ha is na elke beweiding gedoen. Die weiding is vervolgens lig

besproei om die toegediende stikstof in te was. Dieselfde prosedure is met

Westerworld (Jivet) en Italiaanse raaigras (Jeanne) teen 25 kg saad/ha gevolg.

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Op Elsenburg is dieselfde prosedure gebruik, die enigste verskil dat slegs meerjarige

raaigrassaad (Bronsyn) voor die stokkiekapperbewerking met die hand uitgestrooi is.

Op beide lokaliteite is die studie in twee proewe verdeel. In die eerste proef word die

verskillende stikstofbehandelings na elke beweiding aan alle persele toegedien. In

die geval van die tweede proef word die verskillende peile slegs eenmalig na ‟n

voorafbepaalde beweiding aan die spesifieke persele toegedien. ‟n Basiese

toediening van 30kg N/ha word aan alle persele, uitsluitend die wat die verskillende

N peile ontvang, toegedien. Op beide lokaliteite is slegs meerjarige raaigras in die

tweede proef gebruik.

3. Resultate

Aangesien slegs een jaar se data beskikbaar is, word hier slegs gerapporteer oor

data wat reeds ingesamel is en sal geen aanbevelings gedoen word nie.

3.1 Outeniqua

Tabel 1 gee ‟n aanduiding van die droëmateriaal geproduseer as gevolg van

verskillende stikstofpeile wat na elke beweiding gedurende 2008/9 toegedien is

(proef 1). Waar geen stikstof toegedien is nie, is 8164.1 kg droëmateriaal oor 9

weisiklusse vir die meerjarige raaigras/kikoejoe geproduseer. Met die toediening van

720 kg N/ha (80 kg N/ha x 9 toedienings) is 19 337.9 kg droëmateriaal geproduseer,

dus ‟n toename van 15.52 kg droëmateriaal per kg stikstof toegedien.

Droëmateriaalproduksie het oor die algemeen toegeneem namate stikstofpeile

verhoog is. Hierdie neiging is waargeneem by al die raaigrasspesies wat getoets is.

As gevolg van plantdatum (alle spesies is op 23 April 2008 ingesaai) was die

droëmateriaalproduksie tendens vir die raaigrasspesies gedurende die 2008/9

produksieperiode feitlik dieselfde (Fig 1).

Volgens Tabel 2 is dit duidelik dat die droëmateriaalproduksie oor tyd by ‟n spesifieke

stikstofpeil mag verskil. Gemiddelde daaglikse droëmateriaalproduksies van 37.1,

67.4, 59.4, en 42.5 kg is waargeneem op 10/7, 14/8, 1/12 en 6/1 waar 40 kg N/ha

toegedien is (weisiklusse 34-36 dae). Dit is dus duidelik dat die reaksie van ‟n

kikoejoe/raaigrasweiding op stikstofbemesting tussen seisoene kan wissel. Hierdie

verskille kan gebruik word om ‟n stikstofbemestingsprogram te ontwikkel waar

stikstofpeile gedurende seisoene mag wissel volgens die vermoë van die weiding om

op stikstofbemesting te reageer.

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Die reaksie van die oorgesaaide weiding waar die verskillende stikstofpeile eenmalig

toegedien is (proef 2), word saamgevat in figuur 2. Soos in die geval met proef 1

word ‟n tendens waargeneem dat droëmateriaalproduksie toeneem namate

stikstofpeile verhoog word. Om die netto effek van die stikstoftoediening te bepaal

moet die droëmateriaalproduksie by ‟n gegewe stikstofpeil met die produksie van

persele waar geen stikstof toegedien is, vergelyk word. Meer data is egter nodig om

sinvolle afleidings te maak.

3.2 Elsenburg

In teenstelling met Outeniqua, is slegs meerjarige raaigras op Elsenburg in kikoejoe

oorgesaai. Droëmateriaalproduksie in proef 1 was laer by Elsenburg indien vergelyk

met produksie te Outeniqua (Tabel 3). Droëmateriaalproduksie by Elsenburg het

skerp gedaal tussen November en Desember en daarna op relatief lae vlakke gebly.

Die effek van eenmalige toedienings van verskillende stikstofpeile (proef 2) te

Elsenburg word in figuur 3 aangetoon.

4. Opsomming

Die data tot ons beskikking is nie voldoende om op hierdie stadium aanbevelings te

maak nie. Ten minste drie jaar se data word vir hierdie doel benodig. Uit die resultate

wat tans beskikbaar is, is dit egter wel duidelik dat ‟n sekere stikstofpeil bv 40 kg

N/ha toegedien in Julie nie dieselfde droëmateriaalproduksie tot gevolg sal hê as

dieselfde hoeveelheid toegedien in Augustus of September nie. Hierdie resultaat kan

ons in staat stel om ‟n stikstofbemestingsprogram gebaseer op potensiële

droëmateriaalproduksie daar te stel. In praktyk sal dit dus beteken dat die aanbevole

stikstofpeile sal wissel na gelang van die seisoen waartydens geproduseer word.

5. Tabelle en figure

Tabel 1 Droëmateriaalproduksie (kg/ha) van kikoejoe oorgesaai met verskillende

raaigrasspesies soos beïnvloed deur stikstofpeile (kg N/ha) te Outeniqua (2008/9).

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Spesie N peil (kg/ha)

10-Jul 14-Aug 29-Sep 28-Oct 01-Dec 06-Jan 17-Feb 19-Mar 13-May Totaal

Italiaans 0 917.9 1237.2 1295.9 713.4 848.0 656.3 1148.3 763.0 656.8 8236.8

20 1057.9 2148.4 1224.6 1182.4 1734.2 1218.9 1258.0 986.1 768.2 11578.7

40 1079.6 2545.3 1569.2 1328.8 2109.8 1686.4 1373.5 894.3 1147.3 13734.2

60 1475.9 3211.1 1799.3 1741.0 1908.1 2415.5 1775.6 979.3 1225.2 16531.0

80 850.8 2963.2 1272.3 1697.3 2429.0 2046.2 2417.3 1052.8 1105.2 15834.1

Westerw 0 1062.6 1534.6 1012.9 924.4 1113.0 978.7 1131.9 869.2 752.4 9379.7

20 1018.4 1705.7 1268.3 833.2 1729.1 1247.6 1423.2 735.9 886.8 10848.2

40 1039.2 2510.3 1265.7 1058.7 1517.7 1351.6 1631.2 819.5 1216.3 12410.2

60 1354.6 3663.7 2134.9 1602.0 1889.2 2148.6 1766.6 876.4 1032.3 16468.3

80 1553.2 3323.4 1874.1 1655.1 2265.8 2189.0 2225.0 982.8 1168.6 17237.0

Meerjarig 0 778.0 1123.3 682.5 724.4 1258.8 977.1 1085.8 662.4 871.8 8164.1

20 1218.4 2061.2 1029.0 1303.2 1771.3 1262.7 1371.7 772.8 1346.8 12137.1

40 1297.4 2359.0 1157.8 1391.8 2018.7 1528.6 1371.9 662.8 1185.7 12973.7

60 1560.3 3615.0 1668.2 2215.9 1929.4 1994.7 1742.7 1010.0 2238.7 17974.9

80 1511.3 4192.6 2031.2 2354.9 2207.3 2248.1 1723.6 1008.4 2060.5 19337.9

Droëmateriaalproduksie (kg/ha)

Tabel 2 Droëmateriaalproduksie (kg/ha/dag) van kikoejoe oorgesaai met meerjarige

raaigras soos beïnvloed deur stikstofpeile (kgN/ha) te Elsenburg (2008/9).

Spesie N peil (kg/ha)

10-Jul 14-Aug 29-Sep 28-Oct 01-Dec 06-Jan 17-Feb 19-Mar 13-May

Meerjarig 0 22.2 32.1 14.8 25.0 37.0 27.1 25.9 21.4 15.9

20 34.8 58.9 22.4 44.9 52.1 35.1 32.7 24.9 24.5

40 37.1 67.4 25.2 48.0 59.4 42.5 32.7 21.4 21.6

60 44.6 103.3 36.3 76.4 56.7 55.4 41.5 32.6 40.7

80 43.2 119.8 44.2 81.2 64.9 62.4 41.0 32.5 37.5

Droëmateriaalproduksie (kg/ha/dag)

Tabel 3 Droëmateriaalproduksie (kg/ha) van kikoejoe oorgesaai met raaigras soos

beïnvloed deur stikstofpeile (kgN/ha) te Elsenburg (2008/9).

N peil (kg/ha)

22-Jul 12-Sep 13-Oct 18-Nov 12-Dec 13-Jan 18-Feb 18-Mar 20-Apr Totaal

0 330.2 1026.5 959.6 1131.1 110.8 498.3 258.4 586.2 456.0 5357.1

20 251.4 1634.5 1284.8 1679.4 409.5 498.8 384.3 344.4 544.8 7031.8

40 419.0 1825.3 1835.6 2488.3 1040.9 1281.3 1090.7 629.6 1269.8 11880.5

60 548.3 2811.6 1847.6 2650.4 1000.7 1350.1 1064.0 854.5 1556.4 13683.6

80 433.4 2021.8 2187.0 2632.7 1076.9 1167.2 1242.8 648.5 1680.2 13090.4

100 469.8 2648.4 2323.2 2870.7 1025.5 1532.9 1413.5 698.9 1891.6 14874.6

Droëmateriaalproduksie (kg/ha)

N peil = 60 kg/ha

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Figuur 1 Droëmateriaalproduksie tendense (kg/ha) van die verskillende raaigrasspesies met toediening van 60 kg N/ha na elke beweiding te Outeniqua (2008/9).

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Figuur 2 Droëmateriaalproduksie (kg/ha) van kikoejoe oorgesaai met meerjarige raaigras soos beïnvloed deur enkeltoedienings van verskillende stikstofpeile (kg/ha) te Outeniqua 2008/9.

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Figuur 3 Droëmateriaalproduksie (kg/ha) van kikoejoe oorgesaai met meerjarige raaigras soos beïnvloed deur enkeltoedienings van verskillende stikstofpeile (kg/ha) te Elsenburg 2008/9.

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The effect of planting method and seeding rate on the dry matter production of forage sorghum hybrids and hybrid millets. M.M. Robertson, P.R. Botha and H.S. Gerber Institute for Plant Production. Department of Agriculture Western Cape, Outeniqua Experimental Farm, P.O. Box 249, George, 6530, South Africa. Abstract The aim of this study was to determine the effect of planting methods and seeding rates on the dry matter (DM) production of Forage sorghum hybrids (Sorghum bicolor (L.) Moench x Sorghum sudanense) and hybrid millet (Pennisetum glaucum) cultivars under irrigation. Three forage sorghum hybrids (Greengrazer, Jumbo, Revolution BMR and Hunnigreen) and one hybrid millet type (Hy Pearl Millet) were planted on the 20th of November 2006 at two seeding rates (high and low) and two planting methods (conventional and reduced tillage). Weeds were not controlled. The cultivars were cut to a height of 100mm when 60% of the varieties reached a height of 1000mm. Dry matter (DM) production (kg DM ha-1), growth rate (kg DM ha-1 day-1) and DM content (%) were determined. The cultivars were fertilized at a rate of 200kg LAN ha-1, 90kg KCl ha-1 and irrigated after each cutting. Hy Pearl Millet planted at the conventional planting method and high seeding rate produced the highest total amount of DM (8387 kg DM ha-1) and the highest mean growth rate (66.49 kg DM ha-1 day-1). Planting method and seeding rate influenced the total DM production of Hy Pearl Millet but not that of the other cultivars. The mean growth rate of Hy pearl Millet (49.48 kg DM ha-1 day-1) was also the highest (P<0.05) if planting method and seeding rate is not taken into consideration. Hunnigreen (17.40%) and Revolution BMR (17.08%) attained the highest mean dry matter content, if planting method and seeding rate is not taken into consideration. Cultivar had the biggest influence on DM content. Cultivars with the lowest DM production and growth rate (Hunnigreen and Revolution BMR) had the highest DM content whereas the more productive cultivars (Hy Pearl Millet, Greengrazer and Jumbo) have the lowest DM content. Keywords Forage sorghum hybrids, hybrid millets, planting method, seeding rate, dry matter production. Introduction Forage sorghum hybrids (Sorghum bicolor (L.) Moench x Sorghum sudanense) (Viaene and Abawi 1998) and hybrid millets (Pennisetum glaucum) (Navi and Tonapi 2004) are well adapted to the Southern Cape region of South Africa (Gerber et al. 2006). These annual summer crops have the ability to produce large quantities of forage, are palatable, of high quality and therefore a popular crop for milk production (Croplan Genetics 2004; Icrisat 2006).

The aim of this study was to determine the effect of planting methods and seeding rates on the dry matter (DM) production of forage sorghum hybrids and hybrid millet cultivars. Materials and methods This study was carried out on the Outeniqua Experimental Farm near George (Altitude 201 m, 33º 58‟ 38” S and 22º 25‟ 16” E, rainfall 728 mm per year) in the Western Cape of South Africa. The study was executed under sprinkler irrigation on

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an Estcourt soil type (Soil Classification Workgroup 1991). Irrigation scheduling was done according to tensiometer readings, commencing at -25 Kpa and terminated at -10 Kpa (Botha 2002). Fertilizer was applied to raise the soil potassium (K) level to 80 mg kg-1, phosphorous (P) to 35 mg kg-1 and pH (KCl) level to 5.5. Nitrogen (N) and K was given before planting at a rate of 50kg LAN ha-1 and 150kg KCl ha-1 respectively. Establishment commenced on the 20th of November 2006. The cultivars chosen for the study were the highest producing cultivars as evaluated by Gerber et al. (2006). Three forage sorghum hybrids and one hybrid millet type were selected for evaluation. These were planted at two seeding rates and two planting methods. The different forage sorghum hybrids and hybrid millet type, cultivars, seeding rate at the two planting methods are shown in Table 1.

The two planting methods were as follows:

Method 1: Conventional planting. Plots were sprayed with glyphosate at an application rate of 3 litres per hectare. After a waiting period of seven days, the plots were tilled with a harrow disc, followed by a konskilde. Seed was broadcasted and the plots were then rolled with a land roller.

Method 2: Reduced tillage planting. Plots were sprayed with glyphosate at

a rate of 3 litres per hectare, followed by a waiting period of seven days. Seed was then planted using an Aitchison planter. After planting the plots were rolled with a land roller.

When 60% of the varieties reached a height of 1000mm, the plots were cut

down with an Agria 5400 cutter bar mower to a height of 100mm. The forage sorghum hybrids and hybrid millets were sorted from weeds and other grasses on the plots. The total plot forage mass (kg fresh material) was determined. A fresh sample of approximately 300 grams was taken from each plot and weighed. It was then placed in an oven for 72 hours at 60ºC and weighed again to determine DM production (kg DM ha-1), growth rate (kg DM ha-1 day-1) and DM content (%). After each cutting, plots were fertilized at a rate of 200kg LAN ha-1, 90kg KCl ha-1 and irrigated.

Weeds were not controlled. The forage sorghum hybrids and hybrid millets had to compete with self-sown tef (Eragrostis tef), goosegrass (Eleusine indica), purslane (Portulaca oleracea), nutgrass (Cyperus rotundus) and black night shade (Solanum nigrum).

The experimental design was a randomized block design with 3 blocks. The treatment design was a split plot design with 4 main plot treatments (2 planting densities and 2 planting methods) and 5 subplot treatments (cultivars). An appropriate analysis of variance was performed, the assumption of normality of the residuals tested to ensure valid and reliable results (Shapiro and Wilk 1965). A Student LSD (least significant difference) at 5% significance level was used to compare the treatment means (Ott 1998). The STATS module of SAS version 8.2 was used to analyze the data. Result and discussion Table 2 indicates the dry matter production (kg DM ha-1) of forage sorghum hybrids and hybrid millets cultivars over four cuttings and in total. Hy Pearl Millet planted at the conventional planting method at the high seeding rate produced the highest amount of DM during the second and fourth cutting. The DM production of Hy Pearl Millet during the first and third cuttings was similar to the DM produced by the other highest producing cultivars nl. Jumbo and Greengrazer. This resulted in Hy Pearl Millet to produce the highest (P<0.05) total amount of DM (kg DM ha-1). This observation is supported by the findings of Gerber et al. (2006) where Hy Pearl Millet

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also produced the highest amount of DM. Planting method and seeding rate influenced the total DM production of Hy

Pearl Millet but not that of the other cultivars. Revolution BMR and Hunnigreen had a lower total DM production regardless of planting method and seeding rate compared to Hy Pearl Millet and Greengrazer.

The total amount of DM produced was low compared to previous trials performed on forage sorghum hybrids and hybrid millets at Outeniqua Experimental Farm (Gerber et al. 2006). This could be attributed to the lack of weed control in this trial.

Table 3 shows the growth rate (kg DM ha-1 day-1) over four cuttings and the mean growth rate (kg DM ha-1 day-1) of forage sorghum hybrids and hybrid millet cultivars. Hy Pearl Millet planted at the conventional planting method at the high seeding rate had the highest growth rate during the second and fourth cuttings and was the same as the growth rate of Jumbo and Greengrazer at the first cutting or Green grazer during the third cutting. This resulted in Hy Pearl Millet to attain the highest mean growth rate. Revolution BMR and Hunnigreen had the lowest mean growth rate. If seeding rate is not taken into consideration, the growth rate of Hy Pearl millet with the conventional method is still the highest followed Hy Pearl Millet planted by reduced tillage and Greengrazer planted by conventional or reduced tillage methods. The growth rate of Hy Pearl Millet compared to the other cultivars was also the highest if planting method and seeding rate is not taken into consideration.

Table 4 indicates the dry matter content (%) over four cuttings and the mean dry matter content (%) of forage sorghum hybrids and hybrid millet cultivars. Hunnigreen planted at the reduced tillage method at a high seeding rate had the highest (P<0.05) DM content. Revolution BMR planted at the reduced tillage method at the lower seeding rate was the only cultivar with a similar (P>0.05) DM content. Hunnigreen and Revolution BMR attained the highest mean dry matter content, if planting method and seeding rate is not taken into consideration. Revolution BMR was the only cultivar able to achieve similar mean dry matter content as Hunnigreen, when seeding rate was not taken into consideration. Cultivar had the biggest influence on DM content. The cultivars (Hunnigreen and Revolution BMR) with the lowest DM production (Table 2) and growth rate (Table 3) had the highest DM content whereas the more productive cultivars (Hy Pearl Millet, Greengrazer and Jumbo) have the lowest DM content. Conclusions The hybrid millet cultivar, Hy Pearl Millet, planted at the conventional planting method at the high seeding rate produced the highest amount of DM (kg DM ha-1) and the highest mean growth rate (kg DM ha day-1). If only seeding rate is taken into consideration, there is no significant difference between the high and low seeding rate concerning the DM production, growth rate and DM content of forage sorghum hybrid cultivars. Cultivar had bigger influence on growth rate than planting method or seeding rate.

The cultivars with the lowest DM production and growth rate (Hunnigreen and Revolution BMR) had the highest DM content, whereas the cultivars with the highest growth rate and total DM production (Hy Pearl Millet, Greengrazer and Jumbo) had a lower DM content. Acknowledgements We would like to thank the plant production team at Outeniqua Experimental Farm, as well as Jorita Voigt and Mardé Booyse for their help and support.

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References

1. Botha PR 2002. Die gebruik van vogspanningmeters vir besproeiingskedulering by weidings. Weidingskursus 2002. Inligtingsbundel Suid-Kaap Landbou- ontwikkelingsentrum. Departement Landbou Wes-Kaap. pp 141-149.

2. Croplan Genetics 2004. Sorghum forage. [Visited on 3 July 2006] Available

online at: http://www.croplangenetics.com/sorghum_forage.asp?topic=1&sm=h_b

3. Gerber HS, Botha PR and Meeske R 2006. Die produksie van Voersorghum-

en Bastervoermannakultivars as wei- en kuilvoergewasse. Outeniqua Proefplaas Inligtingsdagbundel 2006. Bl 20, 21.

4. Icrisat 2006. Crops Gallery: Sorghum bicolor (L.) Moench [Visited on 3 July

2006] Available online at: http://www.icrisat.org/Text/coolstuff/crops/gcrops2.html

5. Navi SS and Tonapi VA 2004. Evaluation of pearl millet germplasm accessions for resistance to grain mold. Phytopathology 94:796

6. Ott RL 1998. An Introduction to Statistical methods and data analysis.

Belmont, California: Duxbury Press: pp 807-837 (pp 1-1051)

7. SAS Institute Inc. 1999. SAS/STAT User's Guide, Version 8, 1st printing, Volume 2. SAS Institute Inc, SAS Campus Drive, Cary, North Carolina 27513.

8. Shapiro SS and Wilk MB 1965. An Analysis of Variance Test for Normality (complete samples)., Biometrika, 52, 591-611.

9. Soil Classification Workgroup 1991. Soil Classification, a Taxonomic system

for South Africa. Memoirs on the Natural Agricultural Resources of South Africa. Nr 15. Department of Agricultural Development, Pretoria.

10. Viaene NM and Abawi GS 1998.Management of Meloidogyne hapla on

Lettuce in Organic soil with Sudangrass as a Cover Crop. Plant Disease 82:945-952. P 945

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Table 1 Different forage sorghum hybrids and hybrid millet types, cultivars, planting methods (reduced tillage planting and conventional planting) and seeding rate used in the trial at Outeniqua Experimental Farm.

Type Cultivar Reduced tillage

Seeding rate (kg ha-1)

Conventional

Seeding rate (kg ha-1)

Conventional: Early Greengrazer 20 10 25 12.5

Conventional: Late Jumbo 20 10 25 12.5

BMR Revolution BMR 20 10 25 12.5

Sweet Hunnigreen 20 10 25 12.5

Pennisetum* Hy Pearl Millet 10 5 12.5 6

BMR = Brown midrib *Hybrid millet Table 2 The dry matter production (kg DM ha-1) per cutting and the total dry matter production (kg DM ha-1) of forage sorghum hybrid and hybrid millet cultivars at different planting methods and at a specific high and low seeding rate

Cultivar Planting method

Seeding rate

1st Cutting

2nd Cutting

3rd Cutting

4th Cutting

Total

Greengrazer Jumbo Revolution BMR Hunnigreen Hy Pearl Millet* LSD (0.05)

Conventional Reduced tillage Conventional Reduced tillage Conventional Reduced tillage Conventional Reduced tillage Conventional Reduced tillage

High Low High Low High Low High Low High Low High Low High Low High Low High Low High Low

1150ab

997abc

1003abc

713cdef

907abcd

833abcd

1160a

537defg

790abcd

537defg

773bcde

395efg

633cdefg

377fg

363fg

323g

1147ab

940abc

633cdefg

703cdefg

385

1470bcd

1400bcde

1200cdef

1157cdef

1033defg

1423bcde

1010defg

1040defg

653g

847fg

727fg

785fg

957efg

960efg

753fg

893fg

2300a

1790b

1570bc

1630bc

494.6

1530ab

1040bcdef

1453ab

1033bcdefg

687efgh

786cdefgh

1277bcd

723defgh

583fgh

357h

550fgh

420h

437h

430h

347h

457gh

1980a

1263bcde

1337bc

1030bcdefg

579.1

1123bcdef

1387bcde

1587bc

1553bc

1397bcde

1373bcde

1477bcd

1393bcde

320g

650efg

700defg

990cdefg

443fg

453fg

473fg

467fg

2960a

1847b

1883b

1583bc

786.9

5273bcd

4823bcd

5243bcd

4457bcd

4023cde

4417bcd

4923bcd

3693def

2347fg

2390fg

2750efg

2590efg

2470efg

2137fg

2020g

2140fg

8387a

5840b

5423bc

4947bcd

1623.2

abcde Means with no common superscript differ significantly (P<0.05) LSD = Least significant difference *Hybrid millet

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Table 3 Growth rate (kg DM ha-1 day-1), mean growth rate (kg DM ha-1 day-1) and main effects of planting method and cultivar of forage sorghum hybrid and hybrid millet cultivars (planted on the 20th November 2006) at different planting methods and seeding rates

Cultivar Planting method

Seeding rate

1st Cutting 03-01-2007

2nd Cutting 24-01-2007

3rd Cutting 23-01-2007

4th Cutting 10-04-2007

Mean Mean

planting methods

Mean cultivars

Greengrazer Jumbo Revolution BMR Hunnigreen Hy Pearl Millet* LSD (0.05)

Conventional Reduced tillage Conventional Reduced tillage Conventional Reduced tillage Conventional Reduced tillage Conventional Reduced tillage

High Low High Low High Low High Low High Low High Low High Low High Low High Low High Low

26.17ab

22.64abc

22.77abc

16.24cdef

20.60abcd

18.91abcd

26.37a

12.18defg

17.99abcd

12.20defg

17.52bcde

9.01efg 14.37cdefg

8.68fg

8.19fg

7.32g

26.10ab

21.35abc

14.49cdefg

15.98cdefg

8.786

69.98bcd

66.58bcde

56.95cdef

55.14cdef

49.20defg

67.78bcde

48.09defg

49.51defg

31.05g

40.43fg

34.62fg

37.57fg

45.60efg

45.81efg

35.96fg

42.66fg

109.48a

85.18b

74.67bc

77.50bc

23.501

51.02ab

34.66bcdef

48.49ab

34.30bcdefg

22.85efgh

26.25cdefgh

42.62bcd

24.04defgh

19.37fgh

11.86h

18.26fgh

13.91h

14.55h

11.49h

14.30h

15.17gh

65.98a

42.09bcde

44.51bc

34.47bcdef

19.269

24.37bcdef

30.09bcde

34.47bc

33.77bc

30.32bcde

29.88bcde

32.10bcd

30.24bcde

6.95g

14.18efg

15.16defg

21.55cdefg

9.65fg

9.85fg

10.23fg

10.16fg

64.40a

40.15b

40.93b

34.40bc

17.094

42.88bcd

38.49bcde

40.69bcde

34.86cde

30.74def

35.71bcde

37.30bcde

28.99efg

18.84fg

19.67fg

21.39fg

20.51fg

21.04fg

18.97fg

17.17g

18.83fg

66.49a

47.19b

43.66bc

40.59bcde

12.222

40.69bc

37.76bc

33.22c

33.14c

19.25d

21.04d

20.01d

18.00d

56.84a

42.13b

8.621

39.23b

33.18b

20.06c

19.00c

49.48a

6.091

abcde Means with no common superscript differ significantly (P<0.05) LSD = Least significant difference *Hybrid millet

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Table 4 Dry matter content (%), mean dry matter content (%) and main effects of planting method and cultivar for forage sorghum hybrid and hybrid millet cultivars at different planting methods and seeding rates

Cultivar Planting method

Seeding rate

1st Cutting 2nd

Cutting 3rd Cutting 4th Cutting Mean

Mean planting methods

Mean cultivars

Greengrazer Jumbo Revolution BMR Hunnigreen Hy Pearl Millet* LSD (0.05)

Conventional Reduced tillage Conventional Reduced tillage Conventional Reduced tillage Conventional Reduced tillage Conventional Reduced tillage

High Low High Low High Low High Low High Low High Low High Low High Low High Low High Low

15.17def

15.11def

16.95bc

14.97ef

15.35def

14.90ef

15.84cde

16.63bcd

15.63cde

15.23def

16.95bc

15.94bcde

17.50b

15.49cdef

20.36a

17.05bc

13.91f

13.64f

15.56cde

14.83ef

1.586

14.64cdef

14.48def

14.33def

15.77abcd

13.87f

13.70f

15.99abc

15.57abcde

14.90bcdef

14.47def

16.20ab

16.19ab

14.68cdef

14.39def

16.53a

14.88bcdef

13.83f

14.26ef

14.99bcdef

15.33abcde

1.450

15.87abcdef

13.49f

15.73abcdef

16.88abc

16.91abc

13.81ef

17.35ab

16.29abcd

16.69abc

14.20def

16.83abc

17.11abc

16.89abc

15.35bcdef

18.05a

15.71abcdef

14.74cdef

15.70abcdef

16.00abcde

16.09abcde

2.388

21.04abc 20.07abcd

19.22cd

19.19cd

19.63bcd

17.79d

18.86cd

19.01cd

19.07cd

22.85a

19.47cd

22.72ab

19.98abcd

20.18abcd

20.34abcd

21.03abc

18.40cd

18.62cd

20.70abcd

21.20abc

3.203

16.68cde

15.79defg

16.56cde

16.70cde

16.44cdef

15.32fg

16.74cde

16.88bcd

16.57cde

16.69cde

17.36bc

17.99ab

17.26bc

16.35cdefg

18.82a

17.17bc

15.22g

15.63efg

16.81cd

16.86bcd

1.17

16.23cde

16.63cd

15.88de

16.81bc

16.63cd

17.61ab

16.81bc

17.99a

15.42e

16.84bc

0.825

16.43b

16.34b

17.08a

17.40a

16.13b

0.583

abcde Means with no common superscript differ significantly (P<0.05) LSD = Least significant difference *Hybrid millet

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The effect of planting date on the dry matter production of annual forage sorghum hybrids and hybrid millet cultivars.

J. Voigt, P.R. Botha and H.S. Gerber

Institute for Plant Production, Department of Agriculture Western Cape, Outeniqua Experimental Farm, P.O. Box 249, George 6530, South Africa

Abstract

Forage sorghum hybrids (Sorghum bicolor (L.) Moench x Sorghum sudanense) and hybrid millets (Pennisetum glaucum) are high producing and palatable summer grasses fit for milk and beef production. New cultivars are annually placed on the market of which the production potential needs to be determined. The aim of the study was to determine the dry matter production of different cultivars of both species when planted at different planting dates. Identical cultivars were planted in a small trial during 22 September, 20 October, 21 November and 20 December 2006. The plots were, prior to planting tilled with a harrow disc followed by a kongskilde. Seed were broadcasted and the plots were rolled with a land roller. Weeds were not controlled. Plants were harvested when 60 % reached the height of 1 meter. Plant samples were taken and dried for 72 hours at 60º C to determent the dry matter (DM) content (%), DM production (kg DM ha-1) and growth rate (kg DM ha-1 day-1). During the September planting Betta Grazer (6409 kg DM ha-1), Nutrifeed (5142 kg DM ha-1), Pac 8288 (5582 kg DM ha-1) and Greengrazer (4843 kg DM ha-1) produced the highest total amount of DM per hectare. During the October planting Betta Grazer (6131 kg DM ha-1), Nutrifeed (5805 kg DM ha-

1) and Pac 8288 (6052 kg DM ha-1) produced a higher amount of DM ha-1 than most of the cultivars and only Super King (5125 kg DM ha-1) could produce a similar amount of total DM per ha. Nutrifeed produced the highest total amount of DM (5913 kg DM ha-1) per hectare during the November planting. During the December planting Hy Pearl Millet (4213 kg DM ha-1), Betta Grazer (3856 kg DM ha-1) and Nutrifeed (4574 kg DM ha-1) produced the highest amounts of total DM per hectare. Betta Grazer planted during September produced a higher amount of total DM (6409 kg DM ha-1) than most of the other cultivars planted at all the different planting dates. Pac 8288 planted during September or October, Nutrifeed planted during October or November and Betta Grazer planted during October could produce a similar amount of DM than Betta Grazer planted during September. Cultivar had a significant influence on DM production. Betta Grazer, Nutrifeed, Pac 8288, Greengrazer, Hy Pearl Millet and Super King were the most prominent cultivars and produced a higher total DM production than most of the other cultivars if compared to planting date and the frequency of cutting.

Keywords: Forage sorghum hybrids, hybrid millets, dry matter production, planting date. Introduction

The use of forage sorghum hybrids (Sorghum bicolor (L.) Moench x Sorghum sudanense) (Viaene and Abawi 1998) and hybrid millets (Pennisetum glaucum) as summer and autumn pasture have became very popular during recent years. This is

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because forage sorghums hybrids and hybrid millets have low water requirement, high dry matter (DM) productions and rapid growth over a short season (Renato et al. 2001; Butler et al. 2003). Unfortunately no information is available on when to establish these pastures and if some cultivars can be planted earlier than others. It is important during establishment to choose the most effective planting date to ensure optimal growth. The wrong planting date could lead to insufficient germination and uneven growth.

The aim of the study was to determine the effect of planting dates of different cultivars on the DM production of forage sorghum hybrids (Sorghum bicolor (L.) Moench x Sorghum sudanense) and hybrid millets (Pennisetum glaucum)

Material and methods

An experiment using four different planting dates was conducted at Outeniqua Experimental farm with forage sorghum hybrids and hybrid millet cultivars. The farm is situated near George in the Western Cape (altitude of 210 m, 33º 58‟ 38” S and 22º 25‟ 16” E,) (Botha, 2003) with an annual rainfall of 730 mm (Anonymous 1990).

Ten cultivars were selected according to previous sorghum trail results (Gerber et al. 2006). The cultivars were planted at four different planting dates. The planting dates were 22 September 2006, 20 October 2006, 21 November 2006 and 20 December 2006. Table 1 indicates the different types of forage sorghums hybrids and hybrid millet cultivars that were selected. The cultivars were planted on an Estcourt type of soil. Sixteen paddocks sized 138 m² each was each divided into 10 blocks. The size of these blocks was 11,5 m².Soils were sprayed with glyphosate (2 liter ha-1) 2 weeks before planting. Soils were tilled with a disc harrow (1,5 m) followed by a kongskilde. Seeds were broadcasted on plots and then rolled with a land roller (2,33 m width, 30 rollers, Cambridge type). The seeding rate of forage sorghums hybrids and hybrid millets were 30 kg ha-1 and 15 kg ha-1 respectively. Irrigation was scheduled according to a tensiometer reading. Irrigation commenced at a tensiometer reading of –25 Kpa and terminated at –10 Kpa (Botha 2003). Fertilizer was applied to raise the soil potassium (K) level to 80 mg kg-1, phosphorous (P) to 35 mg kg-1 and pH (KCl) level to 5.5. Nitrogen (N) and K was applied before planting at a rate of 50 kg LAN ha-1 and 150 kg KCl ha-1 respectively. Four weeks after emergence a top dressing of 200 kg ha-1 of 4:3:4 (33) was applied and after each cutting 200 kg ha-1 LAN. and 90 kg ha-1 KCl were given.

Plants were harvested when 60 % of plots reached a height of 1 meter. It was cut down with an Agria 5400 cutter (1,27 m width) to a height of 100 mm. Sorghums were separated from weeds to determine plot weight. Samples of approximately 300 grams were taken from each plot to be weight and dried for 72 hours at 60º C, this was used to determine DM production (kg DM ha-1), growth rate (kg DM ha-1 day-1) and DM content (%).

The experimental design was a split-plot with 4 main plot treatments (planting dates) and 10 split plot treatments (cultivars). To select the treatments, which performed the best, a monthly average was calculated for each variable. An appropriate analysis of variance was conducted. Student „s LSD (least significant difference) at a 5 % significance level was used to compare the treatment means (Ott, 1998) The assumption of normality of the residuals was tested by a Shapiro Wilk test before the analysis of variance could be called reliable and valid. The “LSTATS” module of SAS program version 8.2 was used to analyze the data (SAS 1999).

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Result and Discussion

Table 2 indicates the total DM production (kg DM ha-1) of frequently cut forage sorghum hybrids and hybrid millet cultivars planted during September 2006. Betta Grazer produced the highest amount of DM during the first two cuttings. During the third and fourth cutting Betta grazer, Nutrifeed, Pac 8288 and Greengrazer produced similar amounts of DM. This resulted in Betta Grazer, Nutrifeed, Pac 8288 and Greengrazer to produce the highest total amount of DM per hectare (kg ha-1). Table 3 shows the total DM production (kg DM ha-1) of frequently cut forage sorghum hybrids and hybrid millet cultivars planted during October 2006. Betta Grazer, Nutrifeed, Pac 8288 and Super King had high DM productions throughout the majority of the first four cuttings. Nutrifeed produced the highest amount of DM during the fifth cutting. This resulted in Betta Grazer, Nutrifeed and Pac 8288 to produce a higher amount of DM ha-1 than most of the cultivars and only Super King could produce a similar amount of total DM ha-1.

Table 4 indicates the total DM production (kg DM ha-1) of frequently cut forage sorghum hybrids and hybrid millet cultivars planted during November 2006. During the first cutting Nutrifeed had a higher DM production than most of the cultivars and only Betta Grazer and Hy Peal Millet had a similar DM production. The fact that Nutrifeed had a higher DM production during each cutting than most of the other cultivars and only similar to that of Betta Grazer during the third cutting, resulted in Nutrifeed to produce the highest total amount of DM per hectare. Table 5 shows the total DM production (kg DM ha-1) of frequently cut forage sorghum hybrids and hybrid millet cultivars planted during December 2006.Hy Pearl Millet and Nutrifeed produced similar amounts of DM during each of the three cuttings followed the December planting date. The similarity of DM produced by Betta Grazer compared to that of Hy Pearl Millet and Nutrifeed during the first and third cut resulted in these three cultivars to produce a higher total amount of DM per hectare than most of the cultivars.

Table 6 shows the total DM production (kg DM ha-1) of frequently cut forage sorghum hybrids and hybrid millet cultivars planted on 4 different planting dates.Betta Grazer planted during September produced a higher amount of total DM than most of the other cultivars. Only Pac 8288 planted during September or October, Nutrifeed planted during October or November and Betta Grazer planted during October could produce a similar amount of DM than Betta Grazer planted during September.

Conclusion Cultivar had a significant influence on DM production. Betta Grazer, Nutrifeed, Pac 8288, Greengrazer, Hy Pearl Millet and Super King were the most prominent cultivars and produced a higher total DM production than most of the other cultivars if compared to planting date and the frequency of cutting. Betta Grazer, Nutrifeed and Pac 8288 are recommended for the September and October planting date, Nutrifeed for the November planting date and Nutrifeed, Hy Pearl Millet and Betta Grazer for the December planting date.

Acknowledgement

We would like to thank the Plant Production team at Outeniqua Experimental farm, as well as Mardè Booyse and Dalena Robertson for their help and support.

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References Anonymous 1990. Beskrywing van boerderygebiede. Suidkussubstreek Landbou-ontwikkelingsprogram, Elsenburg Landbou-ontwikkelingsinstituut vir die winterreëngebied, 4. 126-127 Bates G. 1995 Summer Annual Grasses. The University of Tennessee, Agricultural Extension Service. http://www.utextension.utk.edu/publications/spfiles/SP434A.pdf

Botha P.R. 2003. Studiegebied en eksperimentele prosedure. Die produksiepotensiaal van oorgesaaide kikoejoeweiding in die gematigde kusgebied van die Suid-Kaap. 3. 72. Butler T., Bean B., 2003. Forage Sorghum Production Guide, http://foragesoftexas.tamu.edu/pdf/FORAGESorghum.pdf Gerber H.S., Botha P.R., Meeske R. 2006. Die produksie en kwaliteit van Voersorghum- en Bastervoermannakultivars as wei- en Kuilvoergewasse. Information day Outeniqua Experiment Farm, The production potential of Crops for Milk and Beef Production 2006. P17-23 Ottman M.J., Husman S.H., Gibson. R.D., Rogers M.T. 1998. Planting Date and Sorghum Flowering at Mariopa, Forage and Grain Agriculture Report, Publication AZ1059. 1997 http://cals.arizona.edu/pubs/crops/az1059/az105921.html Ott, R.L. (1998) An Introduction to Statistical methods and data analysis. Belmont, California:Duxbury Press: pp 807-837 (pp 1-1051) Peterson P. R. 1998. Plant combinations for Extended Dairy Pasture Production. Feed and Nutritional Management Cow College. January 7-8. http://www.dasc.vt.edu/extension/nutritioncc/peterson98.pdf#search=%22Plant%20Combinations%20for%20Extended%20Dairy%20Pasture%20Production%22 Renato S. F., Sollenberger L.E., Staples C.R. 2001. Yield, Yield Distribution, and Nutritive Value of Intensively Managed Warm-Season Annual Grasses, Agronomy Journal 93: 1257-1262 January 2001 http://agron.scijournals.org/cgi/content/full/agrojnl;93/6/1257?maxtoshow=&HITS=10&hits=10&RESULTFORMAT=&searchid=1&FIRSTINDEX=0&minscore=5000&resourcetype=HWCIT SAS Institute, Inc. (1999), SAS/STAT User's Guide, Version 8, 1st printing, Volume 2. SAS Institute Inc, SAS Campus Drive, Cary, North Carolina 27513. Shapiro, S. S. and Wilk, M. B. (1965) ; An Analysis of Variance Test for Normality (complete samples)., Biometrika, 52, 591-611. Viaene NM and Abawi GS 1998.Management of Meloidogyne hapla on Lettuce in Organic soil with Sudangrass as a Cover Crop. Plant Disease 82:945-952. P 94

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Table 1: The types of forage sorghum hybrids and hybrid millets and cultivars evaluated

.

Table 2: The DM production (kg DM ha-1) of frequently cut forage sorghum hybrids

and hybrid millet cultivars planted during September 2006.

Cultivar 1st cutting 11 Dec

2nd cutting 8 Jan

3rd cutting 6 Feb

4th cutting 12 Mar

5th cutting 25 Apr

Total DM production

Betta Grazer 440a 1615a 1854a 1054ab 1446a 6409a

Hy Pearl Millet* 67e 453cd 940cd 608cd 644cd 2712cd

Nutrifeed* 117cde 803bc 1681ab 1168a 1373a 5142ab

Pac 8288 265bc 1204b 1767a 1171a 1175ab 5582ab

Greengrazer 281b 1143b 1609ab 837abc 973bc 4843ab

Super King 228bcd 1007b 1155bc 790bc 896bc 4076bc

Revolution BMR

46e 382d 322e 180e 151e 1080e

Kow Kandy 12e 226d 74e 23e 35e 369e

Hunnigreen 78e 502cd 371de 134e 162e 1247de

Jumbo 83de 531cd 580cde 351de 327de 1872de

LSD (0.05) 148.2 402.5 586.9 345.8 347.5 1618.5 abcde Means with no common superscript differ significantly (P<0.05)1 Hybrid millet*

Type of sorghum Cultivar

Conventional:

Late

Jumbo

Pac 8288

Early Greengrazer

Super King

BMR Revolution BMR

Kow Kandy BMR

Sweet Hunnigreen

Betta Grazer

Hybrid millet (Pennisetum) Hy Pearl Millet

Nutrifeed

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Table 3: The DM production (kg DM ha-1) of frequently cut forage sorghum hybrids

and hybrid millet cultivars planted during October 2006.

Cultivar 1st cutting 19 Dec

2nd cutting 18 Jan

3rd cutting 16 Feb

4th cutting 27 Mar

5th cutting 14 May

Total DM production

Betta Grazer 711a 1357a 1330a 2128a 604b 6131a

Hy Pearl Millet* 206d 725d 667de 1145c 401bcd 3145de

Nutrifeed* 379cd 995c 1243ab 1909ab 1279a 5805a

Pac 8288 694a 1257ab 1498a 2044a 559bc 6052a

Greengrazer 462bc 1037bc 919bcd 1525bc 404bcd 4346bc

Super King 631ab 1031bc 1124abc 1796ab 544bc 5125ab

Revolution BMR

303cd 747d 480ef 636d 194de 2359e

Kow Kandy BMR

198d 400e 114f 135e 42e 888f

Hunnigreen 250cd 575de 523e 546d 195de 2090e

Jumbo 446bc 1031bc 758cde 1133c 343cd 3710cd

LSD (0.05) 226.8 243.1 380.1 401.8 256.6 1109 abcde Means with no common superscript differ significantly (P<0.05)1 Hybrid millet* Table 4: The DM production (kg DM ha-1) of frequently cut forage sorghum hybrids

and hybrid millet cultivars planted during November 2006.

Cultivar 1st cutting 11 Jan

2nd cutting 8 Feb

3rd cutting 15 Mar

4th cutting 4 May

5th cutting Total DM production

Betta Grazer 1314abc 775b 1032a 1172bc - 4293bc

Hy Pearl Millet* 1456ab 1543a 751bc 1095bc - 4845b

Nutrifeed* 1597a 1712a 795ab 1809a - 5913a

Pac 8288 930cd 831b 1009ab 1264b - 4034bc

Greengrazer 1031bcd 653bc 484d 654de - 2822d

Super King 958cd 770b 779abc 1031bcd - 3538cd

Revolution BMR

357e 374c 217e 326ef - 1274e

Kow Kandy BMR

257e 398c 50e 74f - 780e

Hunnigreen 264e 385c 194e 400ef - 1244e

Jumbo 647de 621bc 528cd 804cd - 2599d

LSD (0.05) 459.0 371.1 259.8 383.9

1055.2 abcde Means with no common superscript differ significantly (P<0.05)1 Hybrid millet*

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Table 5: The DM production (kg DM ha-1) of frequently cut forage sorghum hybrids

and hybrid millet cultivars planted during December 2006.

Cultivar 1st cutting 1 Feb

2nd cutting 28 Feb

3rd cutting 17 Apr

4th cutting 5th cutting Total DM production

Betta Grazer 1397a 924b 1536ab - - 3856abc

Hy Pearl Millet* 1051ab 1579a 1583a - - 4213ab

Nutrifeed* 1188ab 1686a 1700a - - 4574a

Pac 8288 954b 957b 1325ab - - 3236bc

Greengrazer 1219ab 818b 804cd - - 2841c

Super King 961b 875b 1050bc - - 2886c

Revolution BMR

229c 290c 284e - - 802d

Kow Kandy BMR

160c 148c 71e - - 379d

Hunnigreen 296c 319c 199e - - 814d

Jumbo 273c 394c 376de - - 1044d

LSD (0.05) 412.0 367.7 494.8 1067.8 abcde Means with no common superscript differ significantly (P<0.05)1 Hybrid millet* Table 6: The total DM production (kg DM ha-1) of frequently cut forage sorghum hybrids and hybrid millet cultivars planted on 4 different planting dates.

Cultivars 22 September 20 October 21 November 20 December

Betta Grazer 6409xx 6131x 4293 3856

Hy Pearl Millet* 2712 3145 4845 4213

Nutrifeed* 5142 5805x 5913x 4574

Pac 8288 5582x 6052x 4034 3236

Greengrazer 4843 4346 2822 2841

Super King 4076 5125 3538 2886

Revolution BMR

1080 2359 1274 802

Kow Kandy 369 888 780 379

Hunnigreen 1247 2090 1244 814

Jumbo 1872 3710 2599 1044

1LSD (0.05) 1618.5 1109.0 1055.2 1067.8 2LSD (0.05) 1193.0 1LSD within planting date 2LSD over planting dates xxHighest value (P<0.05) LSD = 1193.0 xDiffer not from highest value (P>0.05) LSD = 1193.0 Hybrid millet*

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The production of forage sorghum hybrids and hybrid millet cultivars as

silage crops.

L.B. Steyn and P.R. Botha Institute for Plant Production. Department of Agriculture Western Cape, Outeniqua Research Abstract The aim of the study was to determine the dry matter production of forage sorghum hybrids (Sorghum bicolor (L.) Moench x Sorghum sudanense) and hybrid forage millet (Pennisetum glaucum) cultivars for silage production under sprinkler irrigation on an Estcourt soil type. Twenty-one cultivars consisting of 16 forage sorghum hybrids, three hybrid millet and two brown mibrib (BMR) cultivars were planted on the 24th November 2008. Fertilizer was applied during soil preparation to raise the soil potassium (K) level to 80 mg kgˉ¹, phosphorous (P) to 35 mg kgˉ¹ and pH (KCl) level to 5.5. Four weeks after emergence, a topdressing of 210 kg LAN haˉ¹ and 110 kg KCl haˉ¹ were applied. Plants were cut when a DM content of 30% was reached. Nutrifeed, Hunnigreen, HSS 8002, Big Kahuna and Big Kahuna Plus produced a similar (P>0.05) amount (19 000 – 22 000 kg DM haˉ¹) of dry matter. Nutrifeed (22 019 kg DM haˉ¹) and Hunnigreen (20 660 kg DM haˉ¹), when harvested at 163 days after planting, produced a similar (P>0.05) amount of dry matter than HSS 8022 (19 137 kg DM haˉ¹), Big Kahuna (19 103 kg DM haˉ¹) and Big Kahuna Plus (19 103 kg DM haˉ¹) at 128 days. Key Words: forage sorghum hybrids, hybrid millets, dry matter production, silage production. Introduction Forage sorghum hybrids (Sorghum bicolor (L.) Moench x Sorghum sudanense) and hybrid forage millets (Pennisetum glaucum) are annual grasses suitable for silage production (Bosman et al., 2000). These species are high producing, palatable forages, popular in dairy cattle fodder flow programs (Macgregor, 2000). The aim of the study was to determine the dry matter production of forage sorghum hybrids and hybrid forage millet as silage crops. Materials and Methods The study was carried out as a small plot trail under irrigation on an Estcourt soil type (Soil Classification Workgroup, 1991) at the Outeniqua Research Farm near George (altitude of 210m, 33° 58‟ 38” S and 22° 25‟ 16” E, annual rainfall 728mm per year) in the Western Cape of South Africa. Irrigation scheduling was done according to tensiometer readings, commencing at – 25 kPa and terminated at – 10 kPa (Botha, 2002).

The camps were four weeks prior to establishment sprayed with glyphosate at a rate of 3 litres per haˉ¹. Fertilizer was applied to raise the soil potassium (K) level to 80 mg kgˉ¹, phosphorous (P) to 35 mg kgˉ¹ and pH (KCl) level to 5.5. The planting areas were scarified twice, disc and followed by a kongskilde.

The trail was planted on the 24th November 2008. Four weeks after emergence a topdressing of 210 kg haˉ¹ (LAN) and 110 kg haˉ¹ (KCl) were applied. Each cultivar was cut down to a height of 100mm with an Agria 5400 width bar cutter when a dry matter (DM) content of 30% was reached. All the plant material was weighed and chopped with a silage chopper. A wet sample of approximately 600

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grams were taken and dried at 60ºC for 72 hours to determine the dry matter (DM) production. Weeds were not controlled. The forage sorghum hybrid and hybrid millet cultivars had to compete with weeds such as Yellow nutsedge (Cyperus esculentus) and Crab finger grass (Digitaria sanguinalis).

The experimental design was a complete randomized block design. Twenty one cultivars were randomly allocated to three blocks. The data was analysed to the described design. An analysis of variance (ANOVA) was performed using SAS version 9.1.3 (SAS 2003). A Shapiro – Wilk test was performed to test for non – normality (Shapiro and Wilk, 1965). Student‟s t-Least Significant Difference was calculated at the 5% confidence level to compare treatment means (Ott, 1998). Results and Discussion Table 1 shows the cultivar, type, days to harvest, DM content and total DM production of forage sorghum hybrids and hybrid millet cultivars for silage production during the 2008/2009 growth season.The cultivar Nutrifeed, produced a similar (P>0.05) amount of DM as HSS 8002, Big Kahuna and Big Kahuna Plus and was more productive than any of the other cultivars. Nutrifeed and Hunnigreen at 163 days after planting produced a similar (P>0.05) amount of DM than cultivars HSS 8002, Big Kahuna and Big Kahuna Plus when harvested at 128 days. The dry matter content (%) was over estimated and was in reality under 30% when harvested. In comparison with a similar trail done at the same location (Gerber et al., 2007) Nutrifeed and Hunnigreen produced a higher amount of DM. Conclusion Nutrifeed, HSS 8002, Big Kahuna and Big Kahuna Plus produced a similar (P>0.05) amount of DM, while Nutrifeed was more productive than any other cultivar. Nutrifeed and Hunnigreen produced a similar (P>0.05) amount of dry matter when cut at 163 days after planting and did not differ from the DM produced from HSS 8002, Big Kahuna Plus and Big Kahuna at 128 days.

Acknowledgements

I would like to express my gratitude towards the plant production team at the Outeniqua Research Farm for all their hard work as well as Dr. P. Botha, Mr. H. Gerber, and Prof. R. Meeske for all their help and support.

References

Bosman MJC Webb EC Cilliers HG and Steyn HS 2000. Growth, carcass and sensory characteristics of m. longissimus lumborum from wethers fed silage diets from maize or various sorghum varieties. South African Journal of Animal Science, pp 36 Botha PR 2002. Die gebruik van vogspanningmeters vir besproeiingskedulering by weidings. Weidingskursus 2002. Inligtingsbundel Suid – Kaap Landbou – ontwikkelingsentrum. Departement Landbou Wes Kaap. Pp 141 –149

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Gerber HS Botha PR Meeske R 2006. Die produksie en kwaliteit van Voersorghum- en Bastervoermannakultivars as wei- en kuilvoergewasse. Outeniqua Proefplaas. Inligtingsdagbundel 2006. Bl 17-21

Hanna WW and Torres – Cardana S 2000. Pennisetums and Sorghums in an Integrated feeding Systems in the Tropics. Pp. 193 in: Tropical Forage Plants – Development in Use, Sotomay – Riós and Pitman W.D. ed. CRC Publishers 1 edition Macgregor C 2002. Directory of feeds and feed ingredients – Third Edition: Sorghum – Sudangrass forage, Hoard‟s Dairyman Publishers, Fort Atkinson, WI 53538.pp 69

Ott RL 1998. An Introduction to Statistical methods and data analysis. Belmont, California: Duxbury Press. pp 807-837 (pp.1 – 1051)

SAS Institute Inc. 2003. SAS/STAT Version 9.1.3. SAS Institute Inc, SAS Campus Drive, Cary, North Carolina 27513. Shapiro SS and Wilk MB 1965. An Analysis of Variance Test for Normality (complete samples), Biometrika, 52, pp 591-611 Soil Classification Workgroup 1991. Soil Classification, a Taxonomic system for South Africa. Memoirs on the Natural Agricultural Resources of South Africa. Nr 15. Department of Agricultural Development, Pretoria

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Table 1 shows the cultivar, type, days to harvest, DM content and total production of forage sorghum hybrids and hybrid millet cultivars for silage production during the 2008/2009 growth season.

Type Cultivar Days to harvest

DM content (%)

Total DM Production (kg

DM haˉ¹)

FSH FSH FSH FSH FSH FSH FSH FSH FSH FSH HM HM FSH HM FSH FSH FSH FSH BMR BMR FSH

1. HSS 7001 B 2. HSS 7002 B 3. HSS 7003 4. HSS 7004 5. HSS 8002 6. Superdan 7. Hunnigreen 8. SAC 710 9. SAC 500 10. Haygrazer 11. Hy Pearl Millet 12. Nutrifeed 13. Sugargraze 14. Milkstar 15. Bulkmaster 16. Pan 888 17. Pan 841 18. Big Kahuna 19. Big Kahuna Plus * 20. Sweetfeed * 21. Sweetfeed

128 143 121 128 128 121 163 143 121 121 121 163 143 121 143 121 128 128 128 143 128

25.15fg

29.94abc

29.41abcd 29.38abcd

28.77abcd

26.77defg

28.59abcd

31.24a

29.33abcd

28.42bcde 29.73abc

29.37abcd

28.35bcde

27.77cdef

29.54abc

29.94abc

24.90g

27.79cdef 25.78efg

30.89ab

24.52g

15920de

12593fg

18118bcde

15884de

19137abc

16966cde

20660ab

18623bcd

17035cde

12009g

11246g

22019a

16885cde

12803fg

19022bc 15503ef

17368cde

19103abc

19103abc

17822bcde

11523g

* LSD (0.05) 2.7281 2936 abcde Means with no common superscript differ significantly LSD (0.05) = Least significant difference FSH = Forage Sorghum HM = Hybrid Millet * BMR = Brown Midrib

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The effect of seeding rate on the dry matter production of forage sorghum hybrids and hybrid forage millet cultivars for silage production.

L.B. Steyn and P.R. Botha¹ Institute for Plant Production. Department of Agriculture Western Cape, Outeniqua Research Abstract The aim of the study was to determine the effect of seeding rate on the dry matter production of forage sorghum hybrids (Sorghum bicolor (L.) Moench x Sorghum sudanense) and hybrid forage millet (Pennisetum glaucum) cultivars for silage production under irrigation. Hy Pearl Millet, Nutrifeed, Hunnigreen, Sugargraze, Sac 710 and Superdan were each planted on the 25th November 2008 at a seeding rate of 5, 10, 15, 20 and 25 kg haˉ¹. Plants were cut at a DM content of 30%. Nutrifeed at 25 kg haˉ¹ was more productive than Hy Pearl Millet and Superdan. Sugargraze (19 129 kg DM haˉ¹) and Sac 710 (21 013 kg DM haˉ¹) sown at 25 kg haˉ¹ 147 days after planting produced a similar (P>0.05) total DM as Nutrifeed (23 868 kg DM haˉ¹) and Hunnigreen (20 660 kg DM haˉ¹) at a similar seeding rate at 164 days. Key Words: forage sorghum hybrids, hybrid millets, seeding rate, silage production. Introduction Forage sorghum hybrids (Sorghum bicolor (L.) Moench x Sorghum sudanense) are considered the fifth and Pearl Millet (Pennisetum glaucum) the sixth most important cereals worldwide (Sparks, 1998 ; Hanna and Torres - Cardona, 2000). Sorghum and Pennisetum species are utilized in regions where environmental conditions are too harsh to establish maize (Zea mays L.) (Hanna and Torres - Cardona, 2000). As a silage crop, forage sorghum can produce high yields on limited amount of land to uphold livestock during periods of little or no forage availability (Fritz and Pedersen, 2000). The aim of the study was to determine the effect of seeding rate on the dry matter production of forage sorghum hybrids and hybrid millet cultivars for silage production. Materials and methods The trial was planted under irrigation on an Estcourt soil type (Soil Classification Workgroup, 1991) at the Outeniqua Research Farm near George (altitude of 210m, 33° 58‟ 38” S and 22° 25‟ 16” E, annual rainfall 728mm per year) in the Western Cape of South Africa. The cultivars selected were the most outstanding producers from previously conducted trials (Gerber et al., 2007), with a seeding rate variation between 5 – 25 kg haˉ¹.

Irrigation scheduling was done according to tensiometer readings, commencing at – 25k Pa and terminated at – 10 kPa (Botha, 2002). The camps were four weeks prior to establishment sprayed with glyphosate at a rate of 3 litres per haˉ¹. Fertilizer was applied to raise the soil potassium (K) level to 80 mg kgˉ¹, phosphorous (P) to 35 mg kgˉ¹ and pH (KCL) level to 5.5. The planting areas were scarified twice, disc, followed by a konskilde.

The trail was planted on the 25th November 2008. Seeds were broadcasted and covered by raking. Four weeks after planting a topdressing of 210 kg LAN haˉ¹ and 110 kg KCl haˉ¹ were applied. All the plant material was cut down to a height of 100mm. Each cultivar was weighed and chopped separately with a silage chopper

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when they reached a dry matter (DM) content of 30%. A wet sample of approximately 600 grams were taken and dried at 60ºC for 72 hours to determine the dry matter production (DM). Weeds were not controlled. The forage sorghum hybrid and hybrid millet cultivars had to compete with weeds such as Yellow nutsedge (Cyperus esculentus) and Crab finger grass (Digitaria sanguinalis).

The experimental design was a complete randomized block design. Treatment design was a factorial with two factors, cultivar and sowing densities randomly allocated to three blocks. The data was analysed to the described design. An analysis of variance (ANOVA) was performed using SAS version 9.1.3 (SAS 2003). A Shapiro – Wilk test was performed to test for non – normality (Shapiro and Wilk, 1965). Student‟s t-Least Significant Difference was calculated at the 5% confidence level to compare treatment means (Ott, 1998).

Results and Discussion

Table 1 shows the cultivar, type, days to harvest, DM content and total DM production of forage sorghum hybrids and hybrid millet cultivars for silage production during the 2008/2009 growth season. Nutrifeed sown at 25 kg haˉ¹ produced a similar (P>0.05) total DM as Nutrifeed at 5, 10, 15 kg haˉ¹, Sac 710 at 15 and 25 kg haˉ¹, Sugargraze at 10, 20, 25 kg haˉ¹ and Hunnigreen at 15 and 25 kg haˉ¹. Nutrifeed at 25 kg haˉ¹ was more productive than Hy Pearl Millet and Superdan. Sugargraze and Sac 710 at a 25 kg haˉ¹ produced at 147 days after planting a similar total DM as Nutrifeed and Hunnigreen at 164 days. The dry matter content (%) was over estimated and was in reality under 30% when harvested. Conclusion Nutrifeed at 25 kg haˉ¹ was more productive than Hy Pearl Millet and Superdan. Depending on the seeding rate Sugargraze, Hunnigreen and Sac 710 produced similar (P>0.05) total DM than Nutrifeed. The days from planting to harvest differ between the highest producing cultivars and can play an important role in a fodder flow system. Variation within replicates was high resulting in limited significant differences (P> 0.05) between seeding rates.

Acknowledgements

I would like to thank the Plant Production team at the Outeniqua Research farm as well as a special thanks to Dr. P. Botha, Mr. H. Gerber and Prof. R Meeske for all their help and support. References Botha PR 2002. Die gebruik van vogspanningmeters vir besproeiingskedulering by weidings. Weidingskursus 2002. Inligtingsbundel Suid – Kaap Landbou – ontwikkelingsentrum. Departement Landbou Wes Kaap. Pp 141 –149 Fritz OJ and Pedersen FJ 2000. Forages and Fodder – Chapeter 4.5. pp. 798 in: Sorghum: Origin, History, Technology, and Production, edited by Smith W.C. and frederiksen A.R. Publisher – John Wiley & Sons, Inc. Gerber HS Botha PR Meeske R 2006. Die produksie en kwaliteit van Voersorghum- en Bastervoermannakultivars as wei- en kuilvoergewasse. Outeniqua Proefplaas.

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Inligtingsdagbundel 2006. Bl 17-21 Hanna WW and Torres – Cardana S 2000. Pennisetums and Sorghums in an Integrated feeding Systems in the Tropics. Pp. 193 - 194 in: Tropical Forage Plants – Development in Use, Sotomay – Riós and Pitman W.D. ed. CRC Publishers 1 edition

Ott RL 1998. An Introduction to Statistical methods and data analysis. Belmont, California: Duxbury Press. pp 807-837 (pp.1 – 1051)

SAS Institute Inc. 2003. SAS/STAT Version 9.1.3. SAS Institute Inc, SAS Campus Drive, Cary, North Carolina 27513. Shapiro SS and Wilk MB 1965. An Analysis of Variance Test for Normality (complete samples), Biometrika, 52, pp 591-611 Soil Classification Workgroup 1991. Soil Classification, a Taxonomic system for South Africa. Memoirs on the Natural Agricultural Resources of South Africa. Nr 15. Department of Agricultural Development, Pretoria Sparks LD 1998. Advances in Agronomy: Volume 64. Introduction pp. 2. Publisher – Academic Press

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Table 1 shows the cultivar, type, days to harvest, DM content and total DM production of forage sorghum hybrids and hybrid millet cultivars for silage production during the 2008/2009 growth season.

Cultivar and Type

SR Days to harvest DM Content % Total DM Production (kg

DM haˉ¹)

Hy Pearl Millet

(HM)

5 10 15 20 25

122 122 122 122 122

29.12defghi

26.21ghijk

23.92jk

27.12fghijk

24.71jk

12 266ijk

11 980jk

10 816k

12 388ijk

10 768k

Nutrifeed

(HM)

5 10 15 20 25

164 164 164 164 164

30.39bcdefg

28.83efghi

28.69efghij

25.13hijk

27.36fghijk

21 799ab

21 443abc

21 650ab

15 934defghijk

23 868a

Hunnigreen

(FSH)

5 10 15 20 25

164 164 164 164 164

26.91fghijk

27.86fghijk

28.27fghij

27.34fghijk

29.35cdefghi

18 804abcdefg

18 049bcdefgh

19 415abcdefg

18 238bcdefgh

20 660abcde

Sugargraze

(FSH)

5 10 15 20 25

147 147 122 147 147

31.09abcdef

30.73abcdefg

26.70fghijk

29.43cdefghi

30.33bcdefg

16 930bcdefghij

21 123abcd

17 262bcdefghij

19 363abcdefg

19 129abcdefg

Sac 710

(FSH)

5 10 15 20 25

147 147 147 147 147

34.08abc

35.53a 34.73ab

33.83abcd

33.09abcde

14 022fghijk

15 372efghijk

19 512abcdef

17 342bcdefghij

21 013abcd

Superdan

(FSH)

5 10 15 20 25

122 122 122 122 122

30.47bcdefg

28.35efghij

29.62cdefgh

29.57cdefgh

23.28k

13 121hijk

17 710bcdefghi

17 598bcdefghi

15 976cdefghijk

13 973ghijk

* LSD (0.05) 4.811 5508.5 abcde Means with no common superscript differ significantly (P< 0.05) LSD (0.05) = Least significant difference FSH = Forage Sorghum HM = Hybrid Millet

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The effect of seeding rates on the dry matter production of forage sorghum hybrids and hybrid millet cultivars. S. Terblanche and P.R. Botha

Institute for Plant Production. Department of Agriculture Western Cape, Outeniqua Research Farm. Abstract The effect of seeding rates on the dry matter production of various cultivars of forage sorghum hybrids (Sorghum bicolor (L.) Moench x Sorghum sudanese) and hybrid millets (Pennisetum glaucum) cultivars were evaluated. The cultivars Hy Pearl Millet, Nutrifeed, SAC 710, Superdan, Sugergraze and Hunnigreen were each planted at 5, 10, 15, 20 and 25 kg ha-1. The trail was planted on an Estcourt soil type under irrigation in a small plot trail. Planting date was 25th November 2008. Weeds were not controlled. Four weeks after emergence and after each cutting plots were top dressed with 210 kg ha-1 limestone ammonium nitrate (LAN) and 110 kg ha-1 potassium chloride (KCl). Harvesting took place when the first cultivar reached a height of one meter. Dry Matter (DM) production (kg DM ha-1) and DM content (%) were determined. Cultivar and seeding rate influenced DM production. Nutrifeed produced similar (P>0.05) total DM at a seeding rate of 20 kg ha-1 and 25 kg ha-1 and was more productive than any other cultivar sown at any seeding rate. The DM content (%) of the different cultivars sown at different seeding rates differ and varied between 12-20 %. Keywords: Forage sorghum hybrid, hybrid millet, seeding rate, dry matter production. Introduction Forage sorghum hybrids (Sorghum bicolor (L.) Moench x Sorghum sudanese) and hybrid millets (Pennisetum glaucum) are high producing, palatable annual summer growing grasses used as forage for dairy and beef cattle. New cultivars are released regularly and the production potential needs to be determined (Botha et al., 2007). Seeding rates have an influence on production and production costs (Marsalis, 2006). The aim of the study was to determine the effect of seeding rates on the dry matter production of various cultivars of forage sorghum hybrids and hybrid millets cultivars. Materials and Methods A trail was conducted at Outeniqua Research Farm near George in the Western Cape of South Africa (Altitude 210 m, 33°58‟38” S and 22°25‟16” E, rainfall 728 mm year-1).

Six cultivars were planted under irrigation on an Estcourt soil type (Soil Classification Workgroup, 1991) at five different seeding rates in a small plot trail. The cultivars Hy Pearl Millet, Nutrifeed, SAC 710, Superdan, Sugergraze and Hunnigreen were each planted at 5, 10, 15, 20 and 25 kg ha-1.

Weeds were controlled by spraying glyphosate at 3 litre ha-1 two weeks before establishment. Fertilizer was applied during soil preparation according to soil analysis to raise the pH (KCl) to 5.5, soil potassium (K) to 80 mg kg-1 and phosphorus (P) to 35 mg kg-1. The plants were top dressed with 210 kg ha-1 limestone ammonium nitrate (LAN) and 110 kg ha-1 potassium chloride (KCl) four weeks after emergence

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and after each cutting. Seedbed preparation was undertaken by means of a scarifier, disc (John Shearer) and kongskilde.

Planting date was 25th November 2008. Irrigation was scheduled according to tensiometer readings. Irrigation commenced at -25 kPa and terminated at -10 kPa (Botha, 2002). Weeds were not controlled during the trail, thus forage species had to compete with crab finger grass (Digitaria sanquinalis), yellow nutsedge (Cyperus esculentus) and slender amaranth (Amaranthus viridis).

The plants were cut to a height of 100 mm with an Agria 3600B cutter when the first cultivar reached a height of one meter. During each cutting the weeds were separated from the forage species. A representative grab sample taken by hand of approximately 500 grams wet plant material was taken from each plot to determine the DM production (kg DM ha-1) and DM content (%). This was calculated by drying the wet plant material in an oven at 60°C for 72 hours.

The experimental design was a complete randomised block design. Treatment design was a factorial with two factors, cultivar and sowing densities randomly allocated to 3 blocks. The data was analysed according to the described design. The data was continuous, therefore an analysis of variance (ANOVA) was performed using SAS version 9.1.3 (SAS, 2003). A Shapiro-Wilk test was performed to test for non-normality (Shapiro & Wilk, 1965). Student's t-Least Significant Difference was calculated at the 5% confidence level to compare treatment means (Ott, 1998). Results and Discussion Table 1 shows the total dry matter (DM) production (kg DM ha-1) of forage sorghum hybrid and hybrid millet cultivars during each cutting and over the trail period under irrigation at different seeding rates (SR) (kg ha-1) during the summer and autumn (Jan–April) 2008/2009. Cut 1 (43 days after planting) shows that Nutrifeed, sown at 20 kg ha-1 or 25 kg ha-1, SAC 710 at 25 kg ha-1 and Sugergraze at 25 kg ha-1 produced similar (P>0.05) amounts of DM. The total DM production of Nutrifeed sown at 25 kg ha-1 was higher (P≤0.05) than the DM produced by any of the other cultivars, irrespective of the seeding rate.

In Cut 2 (33 days after the 1st cut) Nutrifeed sown at 5, 10, 15, 20 and 25 kg ha-1, SAC 710 at 5 kg ha-1 and 20 kg ha-1 produced similar (P>0.05) amounts of DM. DM production of Nutrifeed sown at 10 kg ha-1 was higher (P≤0.05) than the DM production for any other cultivar sown at any seeding rate.

The data in Cut 3 (31 days after the 2nd cut) shows that Nutrifeed sown at 10, 15, 20 or 25 kg ha-1 produced similar (P>0.05) amounts of DM. Nutrifeed sown at 20 kg ha-1 produced the highest (P≤0.05) amount of DM than any other cultivar sown at any seeding rate.

Cut 4 (47 days after the 3rd cut) shows that Nutrifeed sown at a seeding rate of 10, 15, 20 or 25 kg ha-1 produced similar (P>0.05) amounts of DM but higher (P≤0.05) than any other cultivar sown at any seeding rate.

The total DM production shows that Nutrifeed produced similar (P>0.05) amounts of DM at a seeding rate of 20 kg ha-1 and 25 kg ha-1 but was more productive than any other cultivar sown at any seeding rate. The total DM production was lower than in previous trails (Gerber et al., 2006). The reason can be attributed to climatic conditions, weeds and soil fertility.

Table 2 shows the total dry matter (DM) production (kg DM ha-1) of forage sorghum hybrid and hybrid millet cultivars over the trail period under irrigation at different seeding rates (SR) (kg ha-1) during the summer and autumn (Jan–April) 2008/2009. Hy Pearl Millet produced a similar (P>0.05) amount of DM when sown at 10, 15, 20 and 25 kg ha-1. Nutrifeed was more productive at a seeding rate of 20 kg ha-1 and 25 kg ha-1. SAC 710 produced a similar (P>0.05) amount DM sown at 15, 20 and 25 kg ha-1. The production of Superdan did not differ (P>0.05) at any of the

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seeding rates. Sugergraze was most productive if planted at a seeding rate of 25 kg ha-1. Hunnigreen produced an optimum amount DM at seeding rates of 10, 15, 20 and 25 kg ha-1.

Table 3 shows the dry matter (DM) content (%) of forage sorghum hybrids and hybrid millet cultivars cut at a height of 1 meter under irrigation at different seeding rates (SR) (kg ha-1) during the summer and autumn (Jan–April) 2008/2009. The DM content (%) of the different cultivars sown at different seeding rates differ and varied between 12.8% and 16.7% in Cut 1, 13.9% and 17.1% in Cut 2, 14.3% and 19.8% in Cut 3 and 15.7% and 20.1 in Cut 4. Conclusion Cultivar and seeding rate had a significant influence on the DM production. Nutrifeed sown at 20 kg ha-1 and 25 kg ha-1 produced similar (P>0.05) total DM and production was higher (P≤0.05) than any other cultivar sown at any seeding rate. Acknowledgements I would like to thank the Plant Production team at the Outeniqua Research Farm as well as a special thanks to Dr Philip Botha for his assistance during the trail. References Botha PR 2002. Die gebruik van vogspanningmeters vir besproeiingskedulering by weidings. Weidingskurses 2002 Inligtingsbundel. Suid-Kaap Landbou-ontwikkelingsentrum, Departement Landbou Wes-Kaap. pp 141-149 Botha PR Gerber HS Meeske R 2007. The production and quality of forage sorghum and hybrid forage millet cultivars as pasture crops. Joint 42nd Annual Congress of the Grassland Society of South Africa and 4th Annual Meeting of the Thicket Forum. Eden Grove, Rhodes University, Grahamstown, South Africa. Programme and Abstracts, 16th – 20th July 2007, pp 123 Gerber HS Botha PR Meeske R 2006. Die produksie en kwaliteit van Voersorghum- en Bastervoermannakultivars as wei- en kuilvoergewasse. Inligtingsdagbundel 2006. Outeniqua Proefplaas. pp 17-21 Marsalis MA 2006. Sorghum Forage Production in New Mexico. New Mexico State University, Cooperative Extension Service. Available from: http://aces.nmsu.edu/pubs/_a/a-332pdf [Accessed 12 May 2009]. Ott RL 1998. An Introduction to Statistical methods and data analysis. Belmont, California: Duxbury Press. pp 807-837 SAS Institute, Inc. (2003) SAS/STAT Version 9.1.3. SAS Institute Inc, SAS Campus Drive, Cary, North Carolina 27513. Shapiro SS Wilk MB 1965. An Analysis of Variance Test for Normality (complete samples), Biometrika, 52, pp 591-611 Soil Classification Workgroup 1991. Soil Classification, a Taxonomic system for South Africa. Memoirs on the Natural Agricultural Resources of South Africa. Nr 15. Department of Agricultural Development, Pretoria

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Table 1: Total dry matter (DM) production (kg DM ha-1) of forage sorghum hybrid and hybrid millet cultivars during each cutting and over the trail period under irrigation at different seeding rates (SR) (kg ha-1) during the summer and autumn (Jan–April) 2008/2009.

Cultivar and abbreviation

SR Cut 1 07 Jan 09

Cut 2 09 Feb 09

Cut 3 12 Mar 09

Cut 4 28 Apr 09

Total Jan - Apr

Hy Pearl Millet (HM)

5 10 15 20 25

850l

1752efghij

1959defgh

2006defgh

2261cde

2121bcdef

2117bcdef

1956cdefg

1718defgh

1681defghi

389klm

528jklm

1285bcde

1138cdef

1225bcdef

296cde

314cde

391cde

401cde

415cde

3656klm

4711efghij

5591de

5263defg

5582de

Nutrifeed (HM)

5 10 15 20 25

1557hijk

2123cdefg

2260cde

2852ab

2920a

2556abc

2864a

2675ab

2706ab

2753ab

1011defg

1360abcd

1435abc

1701a

1581ab

1562b

2086a

2071a

2291a

2170a

6686c

8433b

8442b

9552a

9424a

SAC 710 (FSH)

5 10 15 20 25

1194kl

1356ijkl

1678fghijk

2210cdef

2418abcd

2340abcd

2089bcdef

1976cdefg

2292abcde

1582fghi

360klm

503jklm

828fghij

616ghijkl

992defgh

293cde

501cde

601cd

615c

459cde

4187ijkl

4450ghijk

5082defghi

5733cd

5451def

Superdan (FSH)

5 10 15 20 25

2103cdefgh

1991defgh

2340bcd

1982defgh

2206cdef

1938cdefg

1984cdefg

1535fghi

1731defgh

1695defghi

484jklm

441jklm

662ghijk

933efghi

598hijkl

482cde

314cde

321cde

551cde

434cde

5006defghij

4704efghij

4858defghij

5197defgh

4932defghij

Sugergraze (FSH)

5 10 15 20 25

1288jkl

1579ghijk

2026cdefgh

2249cde

2565abc

1076hi

1390ghi

1003i

1287ghi

1610efghi

183m

305klm

257lm

487jklm

558ijklm

124de

114e

114e

152cde

258cde

2672n

3388lmn

3400lmn

4176ijkl

4990defghij

Hunnigreen (FSH)

5 10 15 20 25

991l

1741efghijk

1927defgh

1899defghi

2152cdef

1617efghi

1895cdefg

1626efghi

2146bcdef

1784defg

166m

263klm

399klm

326klm

320klm

231cde

143cde

290cde

199cde

177cde

3006mn

4042jkl

4242hijkl

4569ghijk

4433ghijk

* LSD (0.05) 555.14 697.48 400.15 480.24 997.71 abcd Means with no common superscript differ significantly (P≤0.05). * LSD (0.05) = Compared within cuttings, over cultivars and seeding rates. FSH = Forage Sorghum Hybrid HM = Hybrid Millet

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Table 2: Total dry matter (DM) production (kg DM ha-1) of forage sorghum hybrid and hybrid millet cultivars over the trail period under irrigation at different seeding rates (SR) (kg ha-1) during the summer and autumn (Jan–April) 2008/2009.

Cultivar and abbreviation

SR Total Jan - Apr

* LSD (0.05)

Hy Pearl Millet (HM)

5 10 15 20 25

3656b

4711ab

5591a

5263a

5582a

1333.5

Nutrifeed (HM)

5 10 15 20 25

6686c

8433b

8442b

9552a

9424ab

998.86

SAC 710 (FSH)

5 10 15 20 25

4187b

4450b

5082ab

5733a

5451a

906.5

Suprdan (FSH)

5 10 15 20 25

5006a

4704a

4858a

5197a

4932a

836.96

Sugergraze (FSH)

5 10 15 20 25

2672d

3388c

3400c

4176b

4990a

478

Hunnigreen (FSH)

5 10 15 20 25

3006b

4042a

4242a

4569a

4433a

749.56

abcd Means with no common superscript differ significantly (P≤0.05). * LSD (0.05) = Compared within cultivars over seeding rates. FSH = Forage Sorghum Hybrid HM = Hybrid Millet

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Table 3: The dry matter content (%) of forage sorghum hybrids and hybrid millet cultivars cut at a height of 1 meter under irrigation at different seeding rates (SR) (kg ha-1) during the summer and autumn (Jan–April) 2008/2009.

Cultivar and abbreviation

SR Cut 1 07 Jan 2009

Cut 2 09 Feb 09

Cut 3 12 Mar 09

Cut 4 28 Apr 09

Hy Pearl Millet (HM)

5 10 15 20 25

13.53bcd

12.80cd

13.18bcd

13.58bcd

13.70bcd

15.64abcd

15.95abcd

16.92ab

15.98abcd

16.95ab

17.04bcdefg

17.60abcdef

17.54abcdef

18.47abcd

18.80abc

19.76ab

18.79abcd

18.47abcde

19.74ab

19.89a

Nutrifeed (HM)

5 10 15 20 25

14.53abcd

13.63bcd

13.12bcd

14.87abc

14.89abc

14.42bcd

16.02abcd

15.06abcd

15.70abcd

16.07abcd

14.34h

16.20defgh

14.93gh

15.39fgh

15.54fgh

16.35efg

15.97fg

16.63defg

15.99fg

15.95fg

SAC 710 (FSH)

5 10 15 20 25

13.99bcd

14.71abcd

15.24ab

16.73a

13.87bcd

15.01abcd

14.29cd

16.91ab

17.09a

16.88abc

17.58abcdef

16.53bcdefgh

19.05ab

17.57abcdef

17.67abcdef

17.82abcdefg

17.96abcdefg

17.90abcdefg

18.69abcde

15.72g

Superdan (FSH)

5 10 15 20 25

14.24bcd

13.62bcd

13.11bcd

13.63bcd

13.40bcd

14.14d

16.22abcd

16.23abcd

15.24abcd

14.84abcd

17.23abcdefg

19.79a

16.89bcdefgh

17.47abcdefg

17.07bcdefg

17.02cdefg

20.06a

18.93abcd

18.97abcd

19.50ab

Sugergraze (FSH)

5 10 15 20 25

12.62cd

13.25bcd

12.40d

12.86bcd

12.97bcd

14.74abcd

15.11abcd

14.84abcd

15.70abcd

13.90d

15.64efgh

18.14abcde

15.48fgh

17.20bcdefg

18.15abcde

17.72abcdefg

19.38abc

18.07abcdefg

19.60ab

18.63abcde

Hunnigreen (FSH)

5 10 15 20 25

14.36abcd

13.34bcd

14.93abc

14.29bcd

14.42abcd

16.79abc

14.67abcd

16.50abcd

14.74abcd

15.66abcd

16.30cdefgh

16.04defgh

18.95ab

16.55bcdefgh

16.03defgh

16.57defg

17.37bcdefg

17.07cdefg

18.22abcdef

18.81abcd

* LSD (0.05) 2.42 2.61 2.57 2.42 abcd Means with no common superscript differ significantly (P≤0.05). * LSD (0.05) = Compared within cuttings, over cultivars and seeding rates. FSH = Forage Sorghum Hybrid HM = Hybrid Millet

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Production and grazing capacity of kikuyu/taaipol pasture over-sown with different mixtures of grass and legume species in a low input pasture system for beef cattle. Philip Botha, Maria Lombard, Sunnet Vermeulen-Fenthum and Robin Meeske. Department of Agriculture Western Cape, Outeniqua Research Farm. 1. Introduction

Beef cattle farming in the Western Cape have increased due to continuous sheep theft, high capital investment of new dairy enterprises, the declining vegetable industry and the low vitality of other alternative agriculture industries. The absence of pasture production data for beef cattle led to beef cattle farmers using pasture production systems developed for dairy cattle. Because these systems are not economical viable for beef cattle, farmers tend to use untested pasture systems. This led to the overgrazing of palatable species resulting in the reduction of production and quality of pasture.

Research at Outeniqua has shown that a spectrum of grass and legume species can be persistent under non irrigated and highly grazed pastoral systems. It was also found that these species can be strategically over-sown with different grass species. The practice of over-sowing a pasture base with other pastures species resulted in increased seasonal production and carrying capacity of a pasture production unit. The over-sowing of existing pasture can play an important role in the establishment of a pasture production system on small pieces of land, as currently the case with small-scale farmers. The development of a grazing production system with a pasture base that is persistent under non irrigated and intensive grazing conditions and which can be strategically over-sown, will mean that the pasture production and grazing capacity of the areas used by small scale farmers can be increased without enlarging the land area.

A study was carried out to determine the dry matter (DM) production and grazing capacity of four different beef cattle pasture systems focusing on the unique needs of commercial or small-scale farmers. 2. Methods

The study was carried out at Outeniqua Research Farm near George (altitude 201 m, 33º 58‟ 38” South and 22º 25‟ 16” East, rainfall 728 mm year-1) between July 2008 and April 2009. The area has a temperate climate with a mean minimum and maximum air temperatures varying between 7 °C – 15 °C and 18 °C – 25 °C respectively. Twenty-four hectares under non-irrigated kikuyu (Pennisetum clandestinum) / taaipol (Eragrostis plana) pasture were divided into 24 paddocks. The 24 paddocks were divided into 6 blocks. Each block was divided into four experimental paddocks and pasture treatments were randomly allocated to paddocks.

Kikuju/taaipol pastures were over-sown with four different pasture mixtures. The different cultivars, species, seeding densities (kg ha–1) and over-sowing methods used in the beef trial pasture treatments are shown in Table 1. Treatment one and two consisted of annual ryegrass (Lolium multiflorum), bromus (Bromus wildenowii) and birdsfoot trefoil (Lotus corniculatus) planted into kikuyu/taaipol using hand broadcasting or the mulcher method. Treatment three consisted of perennial ryegrass (L. perenne), Cocksfoot (Dactylis glomerata), fescue (Festuca

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arundinaceae) and white clover (Trifolium repens) planted with a mulcher-planter combination. Treatment four consisted of fescue planted into kikuyu/taaipol. The planting date was May 2008. Winter was indicated by August; Spring by September, October, November; Summer by December, January, February and Autumn by March and April.

Fertilizer was applied to raise the phosphorus level to 35 mg kg-1, the potassium to 80 mg kg-1 and the pH (KCl) to 5.5. Nitrogen was applied four times a year at 50 kg N ha-1 (total 200 kg N ha-1). Dry matter production (kg DM ha-1), grazing capacity, stocking density and botanical composition were determined. Dry matter production was estimated through the clipping of a certain amount of small plots (quadrates - 0.25 m2) representative of the sample area (Vermeulen-Fenthum et al. 2009). The grazing system was a put and take system.

Sixty Jersey cows have been artificially inseminated with Nguni semen and calved from November 2007. The Nguni calves (28 male and 28 female) were allocated to the four pasture treatments resulting in 12 animals per treatment. The number of animals per paddock was adjusted weekly to ensure a forage availability of 3% of their bodyweight per day. When pasture supply is higher than pasture demand additional Jersey heifers with a comparable live weight were added to the experimental groups. The experimental animals grazed on the pasture for a period of 12 months (from 6 months to 18 months of age). A new group of calves started grazing in July of 2008. Nguni x Jersey crossbred oxen and heifers grazed for seven days on each paddock, resulting in a thirty-five day grazing cycle.

The experiment was a randomized complete block design with four treatments randomly replicated. To determine the best performing treatments the means over seasons and years was calculated for each variable and then subjected to a two-way analysis of variance. The experimental animals were used as replications for the analysis of beef production data. 3. Results The monthly average maximum temperature (oC), monthly rainfall (mm), long term monthly rainfall (mm) (30 years) and monthly evapotranspiration (mm) for the trial period are shown in Table 2 and Figure 1. Under average rainfall for seven out of eleven months has been recorded. The total rainfall for the trial period was only 99 mm lower than the long term average. The distribution of the rainfall shows extended periods of under average rainfall (September and October 2008) followed by floods (November 2009). Pasture growth was negatively influenced by the lower than average rainfall during five of the seven months when the mean temperature was higher than 20 0C.

The botanical composition (%) for the different treatments is shown in Table 3. Taaipol and kikuyu were present in all camps. Treatment and season has an influence on the presence of the different species planted as a pasture mixture into kikuyu and taaipol. Treatments with ryegrass and Bromus had a bigger (P<0.05) fraction of these species during winter and spring than during summer and autumn. The Fescue component in the C treatment was less (P<0.05) than in the D treatment during winter, spring and summer. The D treatment had the highest (P<0.05) component of “other” species during winter and spring. The other species consisted of Chickweed (Stellaria media), Bahia grass (Paspalum notatum), Corn spurry (Spergula arvensis) Cape marigold (Arctotheca calendula) and Buckhorn plantain (Plantago lanceolata).

The total *herbage biomass (kg DM ha-1) and average grazing capacity (LSU ha-1) for the different treatments are shown in Table 4. The herbage biomass of treatment A was higher (P<0.05) than treatment C but did not differ (P>0.05) from treatment B and D. Oppose to this, the grazing capacity (LSU ha-1) of treatment A was lower (P<0.05) than treatment D and did not differ (P>0.05) from treatments B

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and C. The reason for this was that the herbage biomass of treatment A consisted of unpalatable taaipol and was measured as available pasture. However, it did not contribute to the grazed component and therefore had a low grazing capacity resulted in a lower grazing capacity of the treatment. Treatment D had a similar (P>0.05) herbage biomass but a higher (P<0.05) grazing capacity indicating that a bigger component of the herbage biomass was available as pasture. This resulted in a higher (P<0.05) grazing capacity.

The average start and end live weight (kg) and average daily gain (g day-1) for Nguni/Jersey calves on the different treatments are shown in Table 5 and Figure 2. The average live weight of the animals increased but the ADG (average daily gain) decreased. The main reason for this was the availability of high quality fodder. The lack of rain resulted in the high quality and palatable species planted into the kikuyu and taaipol pasture base not to be persistent. The dominance of taaipol and kikuyu resulted in a high herbage biomass but a lower grazing capacity. The average ADG over treatments varied between 408 and 960 g day-1. The animals were withdrawn from the pastures at the end of fourth cycle due to a lack of available fodder caused by below average rainfall during the trial period. 4. Conclusion. Pasture growth was negatively influenced by the lower than average rainfall. Treatment and season have an influence on the presence of the different species planted as a pasture mixture into kikuyu and taaipol. Ryegrass and Fescue contributed more to the winter and spring production than summer and autumn production. The grazing capacity was high under the circumstances. The risk to produce beef from non irrigated areas is high. Farmers must be prepared to provide extra fodder during dry spells. 5. References Vermeulen S, Botha PR, Meekse R and Snyman H 2009. The evaluation of methods to determine herbage biomass of beef cattle pastures. Information Day Proceedings. Outeniqua Research Farm, PO Box 249, George, 6530. * Herbage biomass: herbage taken collectively or total above ground biomass of herbaceous plants regardless of grazing preference or availability. Forage biomass is defined as: herbage that is available and may provide food for grazing animals or can be harvested for feed.Beef cattle farmers, grazing pastures consisting of mixed species swards, should remember that the amount of herbage biomass measured is usually not all available for utilization. The main problem with determining feed available for livestock is that the most methods available for measuring production of cultivated pastures, measure the amount of herbage biomass present at a given time. Forage biomass is most directly related to the amount of herbage biomass measured in (near) monospecific swards. However, in mixed swards the value of forage depends largely on two factors: (i) the botanical composition (ratio palatable versus non-palatable species) and the amount of dead material accumulated through under grazing and trampling. Documentation of sward characteristics or the fractioning of clipped samples into different categories can assists with this problem. Table 1: Cultivars, species, seeding densities (kg ha–1) and over-sowing methods used in the beef trial pasture treatments.

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Treatments

Cultivars over-sown into taaipol/kikuyu

Species

Seeding density

Over-sowing methods

A Annual ryegrass cv. Energa Lolium multiflorum Lam. 1. Broadcast Seed

var. westerwoldicum 15 kg ha-1

2. Land Roller

Bromus cv. Matoa Bromus wildenowii 20 kg ha-1

B Annual ryegrass cv. Energa Lolium multiflorum Lam. 1. Broadcast Seed

var. westerwoldicum 15 kg ha-1

2. Mulcher

Bromus cv. Matoa Bromus wildenowii 20 kg ha-1

3. Roller

Trefoil cv. San Gabriël Lotus corniculatus 4kg ha-1

C Perennial ryegrass cv. Bronsyn Lolium perenne Lam. 5kg ha-1

1. Mulcher

Cooksfoot cv. Cambria Dactylis glomerata 5kg ha-1

2. Planter

Fescue cv. Fuego Festuca arunidnaceae 5 kg ha-1

3. Land Roller

Witklawer cv. Haifa Lotus hispidus 5 kg ha-1

D Fescue cv. Fuego Festuca arunidnaceae 20 kg ha-1

1. Spray herbicide

2. Planter

Table 2: The monthly average maximum temperature (oC), monthly rainfall (mm), long term monthly rainfall (mm) (30 years) and monthly evapotranspiration (mm) for the trial period.

Average maximum temperatu

re (oC)

Monthly rainfall (mm)

Long term monthly

rainfall (mm)

Monthly evapotranspiration (mm)

Jun '08 19 83 40 51

Jul 19 17 43 63

Aug 19 68 58 76

Sep 19 25 56 104

Oct 20 41 79 121

Nov 21 194 69 102

Dec 23 3 67 111

Jan '09 24 14 63 115

Feb 25 64 56 100

Mar 26 12 72 125

Apr 24 54 71 112

TOTAL - 575 674 -

Figure 1: The monthly monthly rainfall (mm), long term monthly rainfall (mm) (30 years), monthly evapotranspiration (mm) and average maximum temperature (oC), for the trial period.

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Table 3: Botanical composition (%) for treatment A and B (taaipol, kikuyu, ryegrass, bromus, trefoil), treatment C (taaipol, kikuyu, ryegrass, cocksfoot, fescue, clover) and treatment D (taaipol, kikuyu, fescue) for winter, spring, summer and autumn between August 2008 and April 2009. (Winter = Aug; spring = September, October, November; Summer = December, January, February; autumn = March, April)

Treatment Season Taaipol Kikuyu Ryegrass Bromus Trefoil Cocksfoot Fescue Clover Other

A Winter 37.43a 31.25

bcdef 12.91

bc 3.83

ab 8.59

ab -- -- -- 6.01

bc

Spring 22.92abc

50.45abcd

13.56bc

4.94ab

2.66b -- -- -- 5.47

bc

Summer 32.53ab

52.66abc

2.96c 0.67

b 6.61

ab -- -- -- 4.57

bc

Autumn 44.01a 52.05

abc 0.00

c 0.27

b 1.86

b -- -- -- 1.81

c

B Winter 23.12abc

23.16def

34.89a 3.85

ab 7.70

ab -- -- -- 7.29

bc

Spring 26.03abc

17.82f 36.24

a 8.69

a 6.01

ab -- -- -- 5.20

bc

Summer 30.93ab

27.34cdef

9.94c 0.80

b 13.83

a -- -- -- 17.17

b

Autumn 38.37a 42.29

bcdef 0.00

c 0.00

b 4.18

b -- -- -- 15.16

bc

C Winter 22.46abc

29.57bcdef

27.06ab

-- -- 13.75a 0.88

b 1.99

a 4.29

bc

Spring 18.34abc

37.03bcdef

15.43bc

-- -- 12.64ab

1.94b 1.57

a 13.06

bc

Summer 24.84abc

50.39abcd

2.38c -- -- 13.13

a 1.64

b 0.12

a 7.51

bc

Autumn 30.24ab

56.73ab

0.00c -- -- 4.75

b 2.66

b 0.10

a 5.52b

c

D Winter 0.00c 21.63

fe -- -- -- -- 34.00

a -- 44.37

a

Spring 5.64bc

30.55bcdef

-- -- -- -- 24.69a -- 39.12

a

Summer 4.57bc

47.84abcde

-- -- -- -- 33.11a -- 14.48

bc

Autumn 4.21bc

73.48a -- -- -- -- 15.91

ab -- 6.4

bc

LSD (0.05) 30.16 28.73 15.82 6.45 9.01 8.17 21.56 2.84 14.46

Means with no same superscript differ significantly (P<0.05) LSD(0.05) compares within species

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Table 4 Total herbage biomass (kg DM ha-1) and average grazing capacity (LSU ha-1) for treatment A (taaipol, kikuyu, ryegrass, bromus, trefoil), treatment B (taaipol, kikuyu, ryegrass, bromus, trefoil), treatment C (taaipol, kikuyu, ryegrass, cocksfoot, fescue, clover) and treatment D (taaipol, kikuyu, fescue).

Treatment *Herbage biomass (kg DM ha

-

1)

grazing capacity (LSU ha-1

)

A: tai,kik,rye,brom,tre B: tai,kik,rye,brom,tre C: tai,kik,rye,coc,fes,clo D: tai,kik,fes

11819a

9138ab

8107b

8941ab

1.14b

1.28ab

1.22ab

1.34a

LSD (0.05) 3144 0.16

Means with no same superscript differ significantly (P<0.05) LSD(0.05) compares within columns Table 5 Average start and end live weight (kg) and average daily gain (g day-1) for Nguni/Jersey calves on treatment A (taaipol, kikuyu, ryegrass, bromus, trefoil), treatment B (taaipol, kikuyu, ryegrass, bromus, trefoil), treatment C (taaipol, kikuyu, ryegrass, cocksfoot, fescue, clover) and treatment D (taaipol, kikuyu, fescue).

Treatment A:

tai,kik,rye,brom,tre B:

tai,kik,rye,brom,tre C:

tai,kik,rye,coc,fes,clo D:

tai,kik,fes

Cycle Weight ADG Weight ADG Weight ADG Weight ADG

Aug - Sept 147 677 146 982 147 960 145 871

Sept - Oct

651

710

829

800

Oct - Nov 516 843 595 706

Dec - Jan 243 525 265 504 258 408 256 575

Feb Animals withdraw: lack of fodder. Mrt - Apr

average 592 760 698 723

Figure 2 The average live weight (kg) and average daily gain (g day-1, from wean to slaughter) for animals on treatment A (taaipol, kikuyu, ryegrass, bromus, trefoil), treatment B (taaipol, kikuyu, ryegrass, bromus, trefoil), treatment (taaipol, kikuyu, ryegrass, cocksfoot, fescue, clover) and treatment D (taaipol, kikuyu, fescue).

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High fibre concentrates for Jersey cows grazing kikuyu/ryegrass pasture

R. Meeske, P.C. Cronje & G.D. van der Merwe

Department of Agriculture Western Cape, Outeniqua Research Farm, George,

Republic of South Africa.

Introduction

The cost of maize grain and soybean oilcake has increased drastically during the

past year. Conventional dairy concentrates contain 70 to 80 % maize grain and 8 to

12% soybean oilcake. Partial replacement of maize and soybean oilcake with high

fibre by-products like hominy chop, maize gluten and bran could be very cost

effective if milk production can be maintained. Meijs (1986) found that feeding high

fibre concentrates to cows grazing perennial ryegrass instead of high starch

concentrates increased pasture intake and milk production. Sayers et al. (2003)

showed that maize, barley and wheat can be replaced by citrus pulp, sugar-beet

pulp, wheat middlings and cottonseed in the concentrate for dairy cows grazing

perennial ryegrass without affecting milk production. The aim of the study was to

determine the effect of replacing maize and soybean oilcake with hemi-cellulose rich

by-products like hominy chop, gluten 20 and wheat bran in the concentrate fed to

Jersey cows grazing high quality ryegrass pasture from September to October.

Materials and Methods

Three concentrates were formulated to contain a high (80.4%), medium (40.7%) and

low (20.7%) maize grain content as shown in Table 1. Maize grain was replaced by

hominy chop, wheat bran and gluten 20. As by-products replaced maize in the

concentrate the starch content decreased from 57% to 36% and the hemicellulose

content increased from 6% to 18%.

Forty five Jersey cows were divided in 15 blocks. The milk production, days in

milk and lactation number of cow within each block were similar. Cows within blocks

were randomly allocated to treatments resulting in 15 cows/treatment. Cows were fed

6kg as is, of dairy concentrate per day (3kg at each of two milkings). Milk production

was recorded daily and milk composition every 14 days. Cows grazed as one group

on ryegrass (cv Energa at 20kg/ha over-sown into kikuyu during March 2008) with a

28 day grazing cycle from September to October. Pasture was fertilized with 56kg N

(LAN) after each grazing. Cows were weighed and condition scored (1-5 scale) on

two consecutive days at the start and end of the experimental period. The

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experimental period consisted of an adaptation period of 10 days and a

measurement period of 40 days (Sept to October).

Table 1. Ingredients and composition of dairy concentrates with different levels of

by-products.

Ingredient High maize Medium Maize Low maize

Maize 80.37 40.67 20.67

Hominy chop 0 25 35

Wheat bran 0 11 18

Gluten 20 0 11 18

Soybean oilcake 11 4 0

Molasses 4 4 4

Feed lime 2 2.2 2.2

MCP 0.5 0 0

Salt 1 1 1

Sodium bicarbonate 0.5 0.5 0.5

MgO 0.3 0.3 0.3

Premix 0.33 0.33 0.33

91.37 91.67 91.67

Nutrient

DM (%) 89.1 88.9 88.7

CP (%) 13.0 13.0 13.0

RUP (% of CP)1 60.2 54.2 50.3

ME (MJ/kg) 12.7 11.6 11.0

NDF (%) 11.1 22.0 27.8

ADF (%) 5.08 8.16 9.84

Hemicellulose (%) 6.04 13.78 17.98

NFC (%)2 64.1 52.0 45.4

Starch (%) 57.1 43.7 36.4

Fat (%) 4.53 5.95 6.5

Ca (%) 0.98 0.94 0.94

P (%) 0.43 0.50 0.60 1RUP: Rumen undegradable protein, 2NFC: Non fibre carbohydrate

Results

The milk production, milk composition, live weight and condition score is shown in

Table 1. Milk production did not differ between treatments. The milk fat % of cows on

the low maize concentrate was higher (P<0.05) than that of cows on the high maize

treatment. This resulted in a higher fat corrected milk production for the low maize

treatment. Milk protein and milk urea nitrogen did not differ between treatments. Live

weight and condition score was not affected by concentrate treatments. Depending

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on the price of maize and by-products the cost of a concentrate may be reduced

when maize is replaced with by-products.

Table 2: Milk production, milk composition, live weight and condition score of cows

supplemented with 6 kg of concentrate with a low, medium or high level of

hemicellulose while grazing annual ryegrass pasture (n=15).

Parameter High Maize Medium Maize Low Maize LSD1

Milk production (kg/day) 21.0 20.8 20.1 1.37

FCM (kg/day) 19.9b 20.7ab 21.3a 1.37

Milk fat % 3.66b 4.03 ab 4.41 a 0.451

Milk protein % 3.45 3.55 3.42 0.168

MUN mg/dl 17.8 17.8 18.1 1.22

Live weight at start (kg) 385 a 354 b 358 b 27.3

Live weight at end (kg) 409 382 385 28.5

Live weight change (kg) 24 28 27 9.16

Condition score start (1-5) 2.38 a 2.27 ab 2.17 b 0.190

Condition score end (1-5) 2.40 2.27 2.23 0.207

Condition score change 0.02 0.00 0.06 0.142

1LSD = Least significant difference, ab Means in the same row with different

superscripts differ significantly (P<0.05)

Conclusions

It is concluded that lowering the starch content and increasing the hemicellulose

content of a dairy concentrate by replacing 75% of maize grain with hominy chop,

wheat bran and gluten 20 increased 4% fat corrected milk production and milk fat

content. Including high fibre feeds like hominy chop, wheat bran and gluten 20 in

dairy concentrates for cows grazing high quality ryegrass pasture seems promising.

References

Meijs, J.A.C., 1986. Concentrate supplementation of grazing dairy cows. 2. Effect of

concentrate composition on herbage intake and milk production. Grass and Forage

science, 41, 229-235.

Sayers, H.J., Mayne, C.S. & Bartram, C.G., 2003. The effect of level and type of

supplement offered to grazing dairy cows on herbage intake, animal performance

and rumen fermentation. Anim. Sci., 76: 439-454.

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Milk production of Jersey and Jersey/Fleckvieh crosses on a kikuyu/ryegrass pasture system R. Meeske, P.C. Cronje & G.D. van der Merwe Department of Agriculture Western Cape, Outeniqua Research Farm, George, 6530, South Africa. Introduction The dairy farmer in the Southern Cape has come under financial pressure with the reduction in milk price and increased input costs. The success of farming business is determined by profit per hectare and return on assets. The Fleckvieh may contribute to this when crossed with the Jersey by higher milk production (+15%) per cow and higher income from bull calves. Fleckvieh X Jersey cows are however expected to be 25% heavier than Jerseys. Live weight is correlated with intake and therefore fewer cows per hectare can be carried when cows are heavier. Cows per ha and milk production per cow are key profit drivers for the pasture based system in the Southern Cape. The aim of the study was to determine milk production per cow and milk production per hectare of Jersey and Jersey X Fleckvieh cows (F1) during the first lactation on a Kikuyu/ryegrass pasture system in the Southern Cape. Materials and methods Jersey cows were paired (Similar breeding value and milk production during previous lactation) and randomly allocated to be inseminated with Jersey or Fleckvieh semen during January, February and March 2006. Semen of three Jersey (Rocket, Blair and Sultan) and three Fleckvieh (Hippo, Engadin and Regio) bulls were used. Calves were born from September to December 2007. Calves were intensively reared and inseminated from 11 to 13 months of age. Calves were weighed at birth and with monthly intervals there after. An area of 7.38 ha of kikuyu over-sown with Westerwolds ryegrass under permanent irrigation was divided into forty paddocks of 0.1845ha. The forty paddocks were divided into 20 blocks consisting of two paddocks each which were randomly allocated to the Jersey or Jersey X Fleckvieh farmlet system (3.69ha/farmlet). The two paddocks in each block were always grazed simultaneously by either Jersey or jersey/Fleckvieh crosses. A fresh strip of pasture was allocated to cows after each milking. Cows were milked twice daily and were fed 4kg of dairy concentrate (ME 11.5 MJ/kg, CP 12 %) per day. Milk samples were taken monthly and milk fat, milk protein, MUN and SCC were determined. The grazing cycle varied from 24 to 28 days depending on pasture growth and paddoks were divided in four to five grazings depending on pasture available. Fertiliser was applied at 56kg N as LAN after each grazing. Pasture available on each paddock before and after grazing was estimated using the rising plate meter (RPM) by taking 100 readings. This was done to ensure that grazing intensity was similar on the two farmlets. Twenty two Jerseys and 17 Jersey X Fleckvieh cows calved during August and September 2008 and were allocated to the pasture systems. The average live weight at calving was 273kg for Jerseys (6006 kgLW/farmlet) and 353kg for Jersey X Fleckvieh (6001kg LW/farmlet) cows. At the start of the study the planned stocking rate was 5.96 and 4.61cows/ha for the Jersey and Jersey X Fleckvieh farmlets respectively. The farmlets were reduced depending on pasture growth. When pasture available above 3cm reached 1.2 ton DM/ha, cows returned to the first block. The remainder of the farmlet was then grazed within 2 days by other cows. The average farmlet size for both treatments over 9 grazing cycles was 2.79 ± 0.557 ha.

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Cows completed lactations by the end of May 2009. Economic analysis of data was done. Results and discussion Animal production, reproduction and pasture management data of the Jersey and Jersey X Fleckvieh farmlet systems is shown in Table 1. Table 1: Milk production, milk composition of Jersey and Jersey X Fleckvieh primiparous cows grazing on kikuyu/ryegrass pasture farmlets under irrigation.

Parameter Jersey Jersey X Fleckvieh LSD

Birth weight (kg) 24.2b 33.8a 2.36

Age at calving (months) 21.3 21.7 0.75

ADG g/day birth to calving 0.428b 0.537a 0.025

BW before calving (kg) 302b 377a 16.8

BW end of lactation (kg) 330b 408a 23.9

BCS before calving (1-5) 2.4b 2.8a 0.23

BCS end of lactation (1-5) 2.24 2.25 0.24

Shoulder height before calving (cm) 119b 123a 1.95

Shoulder height at end of lactation (cm) 122b 128a 1.7

Milk production (kg/day) 11.6b 12.7a 0.86

4% FCM production (kg/day) 12.2b 13.0a 0.68

Fat corrected milk production (kg/lactation)

3702b 3959a 262

FCM kg/kg body weight over lactation 11.8a 10.1b 0.92

Milk fat % 4.32 4.16 0.304

Milk protein % 3.69a 3.46b 0.102

Milk urea N (mg/dl) 12.9 13.4 0.75

Somatic cell count x 1000 cells/ml 141 129 61.7

Days open 78 75 15.2

AI per conception 1.18 1.29 0.251

Stocking rate (cows/ha) 7.93a 6.13b 0.295

RPM before grazing 26.0 26.2 1.02

RPM after grazing 14.1 14.8 0.92

Pasture available above 3cm (kgDM/ha) 1344 1328 66

Pasture left above 3cm (kgDM/ha) 557 605 61.7

The crossbred animals were heavier at birth, at calving and at the end of lactation compared to the Jerseys. Body condition score was higher at calving for the crossbreds but at the end of lactation body condition score did not differ between groups. Jerseys X Fleckvieh cows produced 6.7% more fat corrected milk per cow than Jerseys but were 24.2% heavier. The milk protein content of Jerseys was higher than that of the crossbreds. Both Jerseys and crossbreds were pregnant before 80 days is milk and less than 1.3 straws were used per conception. The Jersey farmlet carried more cows than the Jersey X Fleckvieh farmlet and the pasture available

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before and after grazing was similar for both systems. Economic analysis of the different farmlets is given in Table 2. Table 2. Economic analysis of Jersey and Jersey X Fleckvieh farmlets

Parameter Jersey Jersey X Fleckvieh

Cows/ha 7.93 6.13

LSU/ha (450 kg) 4.62 4.61

Farmlet size (ha) 2.89 2.89

Milk production (kg/ha) 28024 23723

Milk price (R/kg) R3.11 R2.98

Milk income (R/ha) R87157 R70695

Total feed cost (R/ha) R48958 R41931

Concentrate 4kg/cow/day @R3.20 R/ha/year R30958 R23931

Pasture cost R/ha/year R18000 R18000

Margin over feed cost R/ha/year R38198 R28763

Fixed cost, labour ext. R/ha (R140/cow/month) R8582 R8582

Variable costs,Medicine, AI, misc R/ha (R80/c/month)

R6344 R4904

Total cost R/ha/year R63885 R55418

Margin over specified cost R/ha/year R23272 R15277

Value bull calves (R/calf) (R/ha)

R0 -

R400 +R1226

Value cull cows (R/cow) 20% cull rate (R/ha)

R2000 +R3172

R3500 +R4291

Cost replacement (R/cow) (R/ha)

R6000 R9516

R6600 R8092

Margin over specified cost R/ha/year R16928 R12703

Margin over specified cost R/cow R2623 R2660

Margin over specified cost R/LSU R4503.40 R3533.99

Pasture cost included fertiliser, planting of pasture, irrigation and depreciation on irrigation system. Conclusions The Fleckvieh crosses were larger and produced more milk per cow than the Jersey cows. Jersey cows produced more milk per ha than the Jersey X Fleckvieh crossbreds. The margin over specified cost per hectare was higher on the Jersey farmlet compared to Jersey X Fleckvieh farmlet.

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The effect of over-sowing kikuyu with italian, westerwolds or perennial ryegrass on pasture yield and milk production J van der Colf1, PR Botha1, R Meeske1 & WF Truter2

1Department of Agriculture Western Cape, Outeniqua Research Farm, P.O. Box 249, George, 6530, South Africa

2Department of Plant Production and Soil Science, University of Pretoria, Pretoria, 0002, South Africa.

1. Introduction Kikuyu (Pennisetum clandestinum) is a C4 pasture specie that is well adapted to the main milk producing areas of the Western Cape Province of South Africa. Kikuyu is highly productive during summer and autumn but winter and spring dry matter (DM) production is low. Forage quality of kikuyu pasture is low and consequently milk production per cow compared to temperate grass (C3) species is low (Marais 2001).

The strategic incorporation of temperate grasses like westerwolds ryegrass (Lolium multiflorum var. westerwoldicum), italian ryegrass (L. Multiflorum var. Italicum) and perennial ryegrass (L. perenne) into kikuyu pasture can increase the seasonal DM production and quality of the pasture (Botha et al., 2008a, Botha et al., 2008b). Dairy

farmers have to make decisions on the species (annual or perennial) and variety (italian or westerwolds) of ryegrass as well as the system to over-sow these ryegrasses into kikuyu. These decisions have a major impact on the profitability of dairy farming. At present no applicable scientific data comparing different systems with annual or perennial ryegrass and grazed by dairy cows is available to assist farmers to make these decisions. Farmers requested an in depth evaluation on the over-sowing systems using annual and perennial ryegrass as the correct pasture system. The aim of the study is to quantify the dry matter yield, growth rate, grazing capacity and milk production potential of kikuyu over-sown with westerwolds ryegrass (WR), italian ryegrass (IR) or perennial ryegrass (PR).

2. Material and methods 2.1 Project layout and treatments The study was carried out over two years on the Outeniqua Research Farm near George in the Western Cape. Nine hectares of an Estcourt soil type (Soil Classification Workgroup 1991) under irrigated kikuyu pasture was divided into eight blocks. Each block was divided into three experimental paddocks. One of the three pasture treatments was randomly allocated to an experimental paddock within a block. Each experimental paddock was divided into two grazing strips. Jersey cows strip-grazed each grazing strip for two days and each experimental paddock for four days. Cows are on the trial area for a total of 32 days, but while one block is being grazed the other seven blocks are being rested, resulting in a 28 day grazing cycle. Irrigation was scheduled by means of tensiometers where irrigation commenced at a tensiometer reading of -25 Kpa and was terminated at a reading of -10 Kpa (Botha 2002). Westerwolds ryegrass was over-sown into kikuyu at 25 kg ha-1 during March using a mulcher (1.6 meter Nobili with 24 blades). Italian ryegrass was planted into mulched kikuyu using an Aitchison seeder at 25 kg ha-1 during March. Perennial ryegrass was planted into mulched kikuyu using an Aitchison seeder during April at 20 kg ha-1. Table 1 shows the treatments, cultivars, seeding densities, abbreviations

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and over-sowing methods used in the trial. Winter is defined as the months of June, July and August; spring as September, October and November; summer as December, January and February and autumn as March, April and May. Fertiliser was applied to raise the soil phosphorus level to 35 mg kg-1, potash level to 80 mg kg-1 and the pH (KCl) to 5.5. The treatments were top dressed monthly with nitrogen at 55 kg N ha-1.The number of animals per paddock was adjusted daily using a put and take system based on DM availability. 2.2 Pasture measurements

Dry matter production, growth rate, botanical composition and forage quality of all pasture treatments were determined. Dry matter production was estimated using the difference between pre- and post-grazing mass estimated with the Ellinbank rising plate meter (RPM) (Stockdale 1984; Fulkerson 1997). The RPM was calibrated by developing a linear regression that relates the height of the pasture measured by the RPM to herbage DM mass. Calibration of the RPM was undertaken at 10-day intervals before and after grazing at a height of 30 mm. During each calibration a total of 18 samples of 0.098m² were cut per treatment. Six samples at a low, six at a medium and six at a high pasture height. Plant material was dried for 72 hours at 60ºC and then weighed to determine the DM yield per cutting. The calibration equation y = mx +b was used for predicting pasture mass where y = yield (kg DM ha-

1), m = factor, x = RPM height and b=constant. A cumulative regression equation was used throughout the study to estimate DM production of pastures. Dry matter production was determined by taking 100 discmeter readings per grazing strip before grazing.

For methods regarding the determination of botanical composition refer to the article “Methods to determine botanical composition of cultivated pastures” (Vermeulen et al., 2008). 2.3 Animal measurements

Forty-five jersey cows were blocked using calving date, 4% fat corrected 305 day milk production for the previous lactation and lactation number. Cows within blocks were allocated randomly to treatments, with 15 trial cows per treatment. Cows were on the trial for the duration of a complete lactation (305 days), with a new group of cows allocated during year 2 of the trial. Milk production was measured on the italian and westerwolds treatments from June to March and on the perennial treatment from July to April. Cows were weighed and condition scored at calving and monthly there after, after the morning milking. Cows were milked twice daily at 07:30 and 14:00 with a 20 point swing-over milk machine (Dairymaster). The automated machine allowed milk yield to be measured on a daily basis. Milk samples were taken on a monthly basis to determine milk composition (fat, protein, lactose and MUN). The milk samples were analyzed with a MilkoScan FT 6 000 analyzer according to the International IDF standard 141B (IDF 1996). Cows received 2 kg of concentrate during each milking (4 kg day-1) in addition to the 9 kg pasture day-1.

3. Results and discussion 3.1 Monthly growth rate (kg DM ha-1 day-1) The average monthly growth rates (kg DM ha-1 day-1) is given in table 2 (year 1) and table 3 (year 2). During both years the lowest (P<0.05) growth rates occurred during the winter months of June and July. The highest (P<0.05) overall growth rate during

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year 1 was achieved by the WR treatment during February, with the PR treatment during February and the WR treatment during January reaching similar (P>0.05) growth rates. During year 2 the highest (P<0.05) overall growth rate occurred during October for PR, with the growth rates of WR during December and January and PR during November and December being similar (P>0.05). During both year 1 and 3 WR had a significantly lower (P<0.05) growth rate than IR during November, as well as during October of year 2. The IR treatment had lower growth rates (P<0.05) than the WR and PR treatments during January and February in year 1 and December and January of year 2. There were no differences (P>0.05) in growth rates between treatments within the months June, July, August, September, December and March during year 1. During year 2 the growth rates between treatments was similar (P>0.05) during July and August. Growth rates varied over and within months for all investigated species.

3.3 Botanical composition (%)

The botanical composition for the different treatments during year 2 is given in Table 6. The ryegrass component remained high in the PR treatment from spring to autumn relative to the IR and WR treatments. The kikuyu component increased from spring to autumn in the WR treatment and from summer to autumn in the IR treatment. The WR treatment appears to favour the growth of the kikuyu component, especially during summer, whereas the PR treatment seems to favour the growth of the ryegrass component. 3.4 Forage Quality (% CP, ME, NDF, Ca:P) The seasonal crude protein percentage (%CP) of kikuyu over-sown with italian, westerwolds or perennial ryegrass is given in table 7.

CP content for all treatments decreased from winter to summer, falling below the recommended level of 20% during the summer for all treatments. CP levels again increased above the recommended level of 20% for all treatments during autumn.

The seasonal neutral detergent fibre (%NDF) of all treatments during year 1 is given in Table 8. The NDF content of all treatments increased from winter to summer, then decreased slightly during autumn.

The seasonal metabolisable energy (ME) content (MJ kg-1 DM) for year one is given in Table 9. The ME content of all pasture treatments decreased from winter to autumn. The ME content of WR and PR during summer and autumn as well as IR during autumn fell below 10 MJ kg-1. Such low ME values could limit milk production. The forage quality of all treatments tended to decline from winter to summer in terms of CP and ME. This could possibly be attributed to the increase in the kikuyu component from winter to summer and the very high growth rates of kikuyu during summer. The Ca:P ratio was unfavourable throughout the trial period ranging from 1.08 to 0.87:1.

Forage quality for all three treatments decreased from winter to summer.

3.5 Monthly mean grazing capacity (cows ha-1)

The mean monthly grazing capacities are presented in table 11 (year 1) and table 12 (year 2). The grazing capacities followed a similar trend to the growth rates, with the lowest grazing capacities occurring during the winter months of June and July in both year 1 and 2. The highest (P<0.05) grazing capacity during year 1 occurred during February for WR, with similar (P>0.05) values obtained from WR in January and PR in February. During year 2 WR had the highest (P<0.05) grazing capacities during

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both December and January with similar (P>0.05) values reached by PR during October, December and January. WR had significantly lower (P<0.05) grazing capacities than PR and IR during November of year 1, as well as during October and November in year 2. PR and WR had higher (P<0.05) grazing capacities than IR during January and February of year 1 and December and January during year 2. The WR treatment had a higher (P<0.05) grazing capacity than both IR and PR during March of year 2. Grazing capacities were similar (P>0.05) for all treatments during June, July, September and March for year 1 and during June and August for year 2.

3.6 Milk production

The milk production (kg milk ha-1), fat corrected milk production (kg FCM ha-1) and milk solids (kg MS ha-1) per hectare are given in Table 14. The PR treatment produced more milk ha-1 than both IR and WR during year 1, with no differences (P>0.05) in the kg FMC ha-1 or kg MS ha-1 between treatments. During year 2 PR produced higher (P<0.05) milk, FCM and MS ha-1 than WR and IR.

Average 305 day milk production per cow (kg milk cow-1), 305 day 4%fat corrected milk production per cow (kg FCM cow-1), butterfat percentage and protein percentage of kikuyu oversown with italian, westerwolds and perennial ryegrass is given in table 13. The 305 day milk production and FCM production per cow was similar (P>0.05) for all treatments in year 1. The IR treatment had the highest (P<0.05) protein percentage in year 1, but there were no significant differences in milk composition during year 2. The PR treatment had a lower (P<0.05) production per cow than IR and WR during year 2. Although PR gave lower production values per cow in year 2, it gave higher production values per hectare during year 2 due to the higher average grazing capacity during the ten months when milk production was measured. 4. Conclusions The growth rate of different species varied over months. The low growth rate of the westerwolds ryegrass treatment (WR) during November resulted in an increase in the kikuyu component during spring, summer and autumn. The opposite occurred in the italian (IR) and perennial ryegrass (PR) treatments where the growth rate during November was high resulting in a lower kikuyu component during summer. The PR treatment showed higher growth rates during the winter and spring of year 2 due to the carry-over effect of plants from year one that survived into year 2. All treatments showed simmiliar (P>0.05) levels of annual dry matter production (kg DM ha-1) during year one, but PR had a higher (P<0.05) annual dry matter production rate than both IR and WR during year 2. Forage quality tended to decline for all pasture treatments from winter to summer as the kikuyu component present in pasture increased. PR had higher milk production values per hectare than WR and IR during year 1 and 2. Although PR did not produce significantly (P>0.05) higher milk than WR and IR per cow during year one or two, it had a higher (P<0.05) grazing capacity over the ten month lactation period. 5. Take home message Kikuyu over-sown with perennial ryegrass obtained the highest pasture and milk production per hectare.

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6. References Botha PR 2002. Die gebruik van vogspanningmeters vir besproeiingskedulering by weidings. Weidingskursus Inligtingsbundel 2002. Suid Kaap Landbou-ontwikkelinsentrum, Departement Landbou Wes-Kaap. pp 141-149.

Botha PR, Meeske, R. and Snyman, H.A. 2008a. Kikuyu over-sown with ryegrass and clover: dry matter production, botanical composition and nutritional value. African Journal of Range and Forage Science. 25(3), 93-101. Botha PR, Meeske, R. and Snyman, H.A. 2008b. Kikuyu over-sown with ryegrass and clover: grazing capacity, milk production and milk composition. African Journal of Range and Forage Science. 25(3), 103-110. IDF 1996. International Dairy Federation, International IDF Standard 141B, 1996. IDF General Secretariat May 1996. Fulkerson WJ 1997. Use of the rising plate meter to allocate pasture. Research to Farm. NSW Agriculture. Wollungbar Agricultural Institute, May 1997.

Marais JP 2001. Factors affecting the nutritive value of kikuyu grass(Pennisetum clandestinum) - a review. Tropical Grasslands35: 65-84. Stockdale CR 1984. Evaluation of techniques for estimating the yield of irrigated pastures intensively grazed by dairy cows. II. The rising plate meter. Australian Journal of Experimental Agriculture and Animal Husbandry 24: 305-311. Soil Classification Workgroup 1991. Soil Classification, a Taxonomic system for South Africa. Memoirs on the Natural Agricultural Resources of South Africa. Nr 15. Department of Agricultural Development, Pretoria.

Vermeulen, S., Botha, PR., Meeske R. & Snyman, HA. 2008. Methods to determine botanical composition of cultivated pastures. The production potential of pastures for milk and beef production 2008. Outeniqua Research Farm Information Day 2008.

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Table 1. Treatments, cultivars, seeding densities, abbreviations and over-sowing methods used in the trial.

Table 2. The mean monthly growth rate (kg DM ha-1 day-1) of kikuyu over-sown with Italian (IR), westerwolds (WR) or perennial ryegrass (PR) for year 1.

Means with no same superscript differ significantly (P<0.05) LSD(0.05) compares over month and treatment

Treatment Scientific Name

Cultivars Seeding Density

Abbrev. Over sowing method

Perennial ryegrass

Lolium perenne

Bronsyn 20 kg ha-1

PR 1. Graze to 50 mm

2. Mulch 3. Seeder 4. Land roller

Italian ryegrass Lolium multiflorum var. italicum

Jeanne 25 kg ha-1

IR 1. Graze to 50 mm

2. Mulch 3. Seeder 4. Land roller

Westerworlds ryegrass

Lolium multiflorum

var. westerworldic

um

Jivet 25 kg ha-1

WR 1. Graze to 50mm

2. Broadcast seed

3. Mulcher 4. Land roller

Year 1 IR WR PR

June 31pqr 30pqr 0 July 31pqr 27qrs 18s

August 38op 40opq 45no

September 65jklm 60lm 55mn October 85cdef 61klm 65ijklm November 77efgh 57m 71ghijkl December 79efg 76efghi 91bcd

January 70ghijkl 95abc 86bcde

February 81defg 106a 98ab

March 66hijklm 73ghijk 74fghij

April 0 0 58m

May 26rs 28qrs 0

LSD (0.05) 11.73

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Table 3. The mean monthly growth rate (kg DM ha-1 day-1) of kikuyu over-sown with Italian (IR), westerwolds (WR) or perennial (PR) ryegrass for year 2.

Year 2 IR WR PR

June 29l 33l 20m

July 36kl 34l 33l

August 43jk 44ij 50ghij

September 54efgh 47hij 60cdef

October 75ab 54efgh 77a

November 63cd 55efgh 72ab

December 57defg 72ab 72ab

January 51ghij 72ab 63cd

February 48hij 61cde 52fghi

March 60cdef 68bc 59def April 0 0 34l

LSD (0.05) 8.09

Means with no same superscript differ significantly (P<0.05) LSD(0.05) compares over month and treatment Table 4. The total seasonal dry matter production (kg DM ha-1 season-1) of Kikuyu over-sown with Westerwolds (WR), Italian (IR) or perennial ryegrass (PR) for year 1

Means with no same superscript differ significantly (P<0.05) LSD(0.05) compares over season and treatment within a year Table 5. The total annual dry matter production (kg DM ha-1 year-1) of kikuyu over-sown with Italian (IR), westerwolds (WR) or perennial (PR) ryegrass.

Year IR WR PR LSD

1 18767a 18880a 18083a 819 2 13479b 14040b 16202a 713

Means with no same superscript differ significantly (P<0.05) LSD (0.05) compares over treatments within a year

Year 1 IR WR PR

Winter 3512d 3422d 2084e

Spring 6073b 4774c 5117c Summer 6161b 7412a 7380a Autumn 3022d 3272d 3502d

LSD(0.05)=780

Year 2 IR WR PR

Winter 2864de 2958de 3273d

Spring 4980ab 4149c 5610a

Summer 4385bc 5516a 5044ab Autumn 1428g 1621fg 2275ef

LSD(0.05)=687

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Table 6. Seasonal botanical composition (%DM) of kikuyu over-sown with Italian (IR), westerwolds (WR) or perennial (PR) ryegrass for year 2.

IR WR PR

Winter

Kikuyu 11 18 3 Ryegrass 80 73 77 Other 9 9 19

Spring

Kikuyu 4 11 2 Ryegrass 93 67 78 Other 3 22 21

Summer

Kikuyu 45 64 26 Ryegrass 40 12 59 Other 15 25 15

Autumn

Kikuyu 95 87 51 Ryegrass 2 1 33 Other 3 12 16

Table 7. Crude protein content (% DM) of kikuyu over-sown with Italian (IR), westerwolds (WR) or perennial (PR)l ryegrass for year 1.

Table 8. Neutral detergent fibre (% DM) of kikuyu over-sown with Italian (IR), westerwolds (WR) or perennial (PR) ryegrass for year 1.

Table 9. Metabolisable energy (MJ kg-1 DM) of kikuyu over-sown with Italian (IR), westerwolds (WR) or perennial (PR) ryegrass for year 1.

IR WR PR

Winter 30.45 32.25 25.80

Spring 22.73 22.50 22.00 Summer 19.67 19.13 17.87 Autumn 22.30 23.00 23.05

IR WR PR

Winter 37.9 37.4 40.8

Spring 45.9 48.9 48.7 Summer 56.8 62.1 59.0 Autumn 57.9 58.6 57.4

IR WR PR

Winter 12.0 12.0 12.0 Spring 10.9 10.6 11.1 Summer 10.0 9.4 9.2 Autumn 9.9 9.7 9.2

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Table 10. Calcium: Phosphorous ratio of kikuyu over-sown with Italian (IR), westerwolds (WR) or perennial (PR) ryegrass.

Table 11.Monthly grazing capacity (cows ha-1 month-1) of the kikuyu over-sown with Italian (IR), westerwolds (WR) or perennial (PR) ryegrass for year 1.

Year 1 IR WR PR

June 6.10ghijk 5.71hijkl 0 July 3.10op 2.65p 3.16op

August 3.88no 4.07mno 4.50lmn

September 6.29ghij 5.64hijkl 5.42ijkl

October 8.17cd 6.42fghij 6.75efgh November 7.48def 5.53ijkl 7.05defg

December 7.77cde 7.49def 8.93bc

January 7.02defg 9.45ab 8.71bc

February 7.90cde 10.29a 9.51ab

March 6.54fghi 7.78defg 7.39def

April 0 0 6.04ghijk

May 5.06klmn 5.21jklm 0

LSD(0.05) 1.22

LSD (0.05) compares over treatments and months Means with no common superscript differ significantly (P<0.05) Table 12.Monthly grazing capacity (cows ha-1 month-1) of the kikuyu over-sown with Italian (IR), westerwolds (WR) or perennial (PR) ryegrass for year 2.

Year 2 IR WR PR

June 3.22po 3.20po 3.96lmno

July 3.79mno 3.46npo 2.88p

August 4.37klm 4.40jklm 4.92hijk

September 5.21ghij 4.64ijkl 5.86efg

October 7.41ab 5.28ghi 7.62a

November 6.55cde 5.64fgh 7.46ab

December 5.99defg 7.65a 7.52ab

January 5.66fgh 7.83a 6.74bcd

February 5.36ghi 6.46cdef 5.89efg

March 6.36cdef 7.18abc 6.32def

April 0 0 4.22klmn

LSD(0.05) 0.83

LSD (0.05) compares over treatments and months Means with no common superscript differ significantly (P<0.05)

IR WR PR

Winter 0.87:1 0.88:1 1.01:1 Spring 1.03:1 1.06:1 1.03:1 Summer 0.91:1 0.95:1 0.96:1 Autumn 0.97:1 0.92:1 1.08:1

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Table 13. Average 305 day milk production per cow (kg milk cow-1), 305 day 4% fat corrected milk production per cow (kg FCM cow-1), butterfat percentage and protein percentage of kikuyu over-sown with Italian (IR), westerwolds (WR) or perennial (PR) ryegrass.

Kg milk cow-1 Kg FCM cow-1 Fat % Protein %

Year 1

IR 4829a 5504a 4.94a 3.84a

WR 5025a 5728a 4.94a 3.74ab

PR 4944a 5396a 4.63a 3.64b

LSD(0.05) 352 403 0.38 0.17

Year 2

IR 5410a 5773a 4.50a 3.55a

WR 5131ab 5696a 4.75a 3.61a

PR 4916b 5186b 4.40a 3.53a

LSD(0.05) 380 346 0.39 0.15

LSD (0.05) compares over treatments within years Means with no common superscript differ significantly (P<0.05) Table 14.Total annual milk production (kg milk/ha), 4 % fat corrected milk (kg FCM/ha), milk solids (kg milk solids/ha) and average grazing capacity (cows/ha) of kikuyu over-sown with Italian (IR), westerwolds (WR) or perennial (PR) ryegrass.

Kg milk/ha Kg FCM/ha Kg milk solids/ha Cows/ha

Year 1

IR 30446b 34556a 2627a 6.44b

WR 29761b 34057a 2566a 6.49b

PR 32288a 35268a 2639a 6.93a

LSD(0.05) 1540 1699 128 0.27

Year 2

IR 28073b 30087b 2246b 5.34b

WR 27032b 30052b 2258b 5.52b

PR 31385a 33086a 2457a 5.96a

LSD(0.05) 1253 1462 107 0.35

LSD (0.05) compares over treatments within years Means with no common superscript differ significantly (P<0.05)

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Kikuyu over-sown with different ryegrass species or clover: recent research. Philip Botha. Department of Agriculture Western Cape, Outeniqua Research Farm, P.O. Box 249, George, 6530, South Africa. E-mail: [email protected] 1. Introduction Kikuyu comprises the greater part of irrigated summer and autumn pasturage for milk production in the Southern Cape of South Africa. Well managed kikuyu has a high dry matter (DM) yield which support high stocking rates and milk production per hectare (Reeves 1997). Compared to temperate pasture species, the forage quality of kikuyu is low and consequently, milk production per cow is also low (Marais 2001). The main nutritional limitation is a low digestible energy content and low digestibility of structural carbohydrates (Marais 2001). Due to a lack of readily digestible non-structural carbohydrates and high structural carbohydrate content, energy is the major limiting factor for milk production (Marais 2001). Kikuyu contains oxalic acid, which binds calcium (Ca), rendering it largely unavailable to the grazing animal (Marais 1998; Marais 2001). Kikuyu is also deficient in sodium (Na) (Marais 1998; Miles et al. 1995; Marais 2001) and prone to Ca:phosphate (P) and potassium (K):Ca + magnesium (Mg) imbalances (Miles et al. 1995). The nutritive quality of kikuyu is determined by its unique morphology, physiology and chemical composition which could change depending on the growth stage and environmental conditions during growth (Marais 2001). Due to the fact that kikuyu produces stem material for the duration of the growing season, its nutritive value is influenced by stage of re-growth. When fertilised with high levels of nitrogen (N) it accumulates NO3 which may have a negative impact on digestion and animal performance (Reeves 1997; Marais 2001). Reeves (1997) found that modest applications of N (50 kg N ha-1 per dressing) provide enough protein to uphold DM production and increase protein concentration to meet the needs of a lactating cow. Subsequently high levels of N will increase nitrate concentration which may reduce rumen microbial activity and disrupt rumen function (Reeves 1997). Concentrate supplements are used to obtain satisfactory performance from animals fed on kikuyu (Marais 2001). However, these supplements are expensive and increase the cost of milk production. Other strategies such as over-sowing kikuyu with grasses or legumes for improving animal production on kikuyu were hampered by difficulties regarding establishment (Pottinger et al. 1993) and persistency of species (Marais 2001). If succesfull, the strategic incorporation of legumes and other grasses into a kikuyu pasture can increase the seasonal dry matter (DM) production and quality of the pasture, with a reduction in N fertilizer needs.

Botha et al. (2008a), Botha et al. (2008b) and Van der Colf et al. (2009) reported on studies where kikuyu was over sown with different ryegrass species and/or clover. The aim of these studies was to determine the persistence and the seasonal dry matter yield, botanical composition, nutritional value grazing capacity, milk production and milk composition of irrigated kikuyu over-sown with ryegrass and/or clovers. Although these studies were conducted in different years (Study 1: 1999 until 2002 [Botha et al. 2008a and Botha et al. 2008b] and Study 2: 2007 until 2009 [Van der Colf et al. 2009]) and thus statistical not comparable, they were carried out on the same site using the same camps. Similar methods regarding measuring pasture production and milk production as

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well as using the same techniques and laboratories for determining the nutritional composition of the pasture and milk composition were used. Because this information is important to dairy farmers in this area and can be used as indicators for decision making reasons, relevant data is shown in adjacent tables, without comparing in a direct way. Scientific papers on these studies can be revised for in dept information. 2. Methods Study 1 and Study 2 were carried out on the Outeniqua Research Farm near George in the Western Cape of South Africa. The area has a temperate climate with mean minimum and maximum air temperatures varying between 7 0C -15 0C and 18 0C - 25 0C respectively. The trials were carried out on nine hectares of an Estcourt soil type (Soil Classification Workgroup 1991) under sprinkler irrigated kikuyu pasture. The treatments of each study consisted of three pasture systems. The selection of the systems was based on a request from commercial dairy farmers to evaluate existing pasture systems in terms of production potential and nutritional value. The main commercial systems were perennial or annual ryegrass over-sown annually into kikuyu. In trial 1 perennial white and red clover was over-sown into kikuyu. The rationale in evaluating a legume against a grass is in the nutritional value of the species and cost saving on nitrogen fertilizer on legume pastures. Different methods are needed to over-sow ryegrass or clovers into an existing kikuyu pasture. The intensive cultivation method used to plant clover into kikuyu and the subsequent negative effect on kikuyu growth make it important to evaluate the system as a perennial pasture with optimum seasonal production, kikuyu rectification and 30% clover content as objectives within the system.

Table 1 shows the pasture species and cultivars used in the trials. Table 2 shows the different treatments, botanical composition of the treatments, seeding rate and over-sowing methods used in the trials. The Kikuyu/clover pasture was established using a rotavator (Botha et al. 2008). The kikuyu was grazed to 50mm, mulched to ground level and rotavated afterwards to a depth of 100 mm. The seedbed was then rolled once with a cambridge land roller, the seed was broadcast by hand, rolled again and irrigated. The Kikuyu/westerwolds ryegrass was established using a using a mulcher (Botha et al. 2008). The kikuyu was grazed down to 50mm and annual ryegrass seed broadcasted over the remaining kikuyu pasture. The kikuyu pasture was then mulched to ground level without the blades touching the soil. The mixture of mulched plant material and seed was then rolled once with a Cambridge land roller and irrigated. The kikuyu-perennial and kikuyu-italian ryegrass was established using an Aitcheson planter. The kikuyu was grazed to 50mm, mulched to ground level, planted with the planter and rolled once with a Cambridge roller (Van der Colf et al. 2009).

Irrigation was scheduled by means of tensiometers. Irrigation commenced at a tensiometer reading of -25 Kpa and was terminated at a reading of -10 Kpa. Fertiliser was applied to raise the soil phosphorus level to 35 mg kg-1 (citric acid), potash level to 80 mg kg-1 (citric acid) and the pH (KCL) to 5.5. No nitrogen was applied to the KC1st year, KC2nd year and KRC pastures. The K and KR pastures systems were fertilised at a rate of 560 kg N ha-1 in ten applications of 56 kg N ha-1. Dry matter production was estimated by the Ellinbank rising plate meter (RPM) mass (Stockdale 1984; Fulkerson 1997). The RPM was calibrated by developing a linear regression between meter reading and herbage DM. A different regression was developed for the various treatments for each season of every year. Pasture height was estimated daily by taking RPM readings before and after grazing (Botha et al. 2008 and Van der Colf et al. 2009).

Jersey cows strip grazed pasture treatments in a 28 day grazing cycle. Cows were fed two kg of dairy concentrate (composition: 11.5 MJ ME, 12% crude protein (CP),

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13% NDF, 1.2% calcium (Ca), 0.4% phosphorus (P) during each milking and were milked twice daily (4 kg dairy concentrate per cow per day). The number of cows per paddock was adjusted daily to ensure a forage availability of 10 kg DM cow-1 day-1. 3. Results The data shown focus on aspects important for farmers in their decision making regarding fodder flow and management. 3.1 Growth rate The mean monthly growth rate (kg DM ha month) of kikuyu over-sown with clover, westerwolds, Italian or perennial ryegrass is shown in Figure 1. The growth rate of different species varied over months. Kikuyu/ryegrass, fertilized with nitrogen fertilizer, had a dry matter production rate similar to that of kikuyu-clover from August to December but higher from January to April. As the kikuyu content of the Kikuyu-clover pastures increased and the clover content decreased, the seasonal growth rate changed from a higher spring/summer growth rate in the first year to a higher summer/autumn growth rate in the second year. The growth of Kikuyu-clover during winter was low compared to the spring, summer and autumn growth. Kikuyu-ryegrass has a higher growth rate than Kikuyu-clover during spring, summer and autumn (Botha et al. 2008a). The mean monthly growth rate (kg DM ha-1 day-1) of kikuyu over-sown with clover 1st year of growth, clover 2nd year of growth, Italian, westerwolds or perennial ryegrass, is shown in Table 3. The growth rate of kikuyu-clover was low during winter and varied between 56 and 60 kg DM ha-1 day-1 during August and January.

The low growth rate of the westerwolds ryegrass treatment during November resulted in an increase in Kikuyu component during spring, summer and autumn. The opposite occurred in the italian ryegrass and perennial ryegrass treatments where the growth rate during November was high resulting in a lower kikuyu component (Van der Colf et al. 2009). 3.2 Botanical composition Table 4 shows the mean seasonal kikuyu, ryegrass and clover content (%) of kikuyu over-sown with a different ryegrass varieties, white and red clovers over a period of two years. The ryegrass-kikuyu ratio of the pasture has an important influence on the seasonal DM production and quality of the pasture. The clover content of the kikuyu/clover remained at levels higher than 30% for more than two years. The grass content of the kikuyu-westerwold ryegrass pasture varied from ryegrass dominant in winter and spring to kikuyu dominant in autumn (Botha et al. 2008a).

The ryegrass component remained high in the perennial ryegrass treatment from spring to autumn relative to the Italian and westerwolds ryegrass treatments. The kikuyu component increased from spring to autumn in the westerwolds ryegrass treatment and from summer to autumn in the Italian ryegrass treatment. The westerwolds ryegrass treatment appears to favour the growth of the kikuyu component, especially during summer, whereas the perennial ryegrass treatment seems to favour the growth of the ryegrass component (Van der Colf et al. 2009). 3.3 Dry matter production

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The total seasonal dry matter (kg DM ha-1 season-1) and total annual dry matter (kg DM ha-1 year-1) production of two trials where kikuyu were over-sown with ryegrass or clover over two years, are shown in Table 5. The lowest annual total DM yield was produced by Kikuyu-clover during the first year of growth (Botha et al. 2008a). 3.4 Metabolisable energy (ME) Table 6 shows the mean seasonal metabolisable energy (ME) (MJ/kg DM) of two trials where kikuyu were over-sown with ryegrass or clover over two years. The seasonal ME content of the grass pastures or pastures where the grass component increased to the detriment of the clover content, had a lower ME content than the clover-dominant pasture. Kikuyu-clover was the only pasture that could provide sufficient energy for higher producing dairy cows. The ME content of the kikuyu-clover pasture decreased seasonally as the grass content increased. The ME content of the kikuyu-ryegrass pasture was high during spring but decreased during summer and autumn when kikuyu became more dominant. The low ME content of kikuyu is according to Reeves and Fulkerson (1995) the first limiting factor for milk production from kikuyu (Botha et al. 2008a). The ME content of westerwolds ryegrass and perennial ryegrass during summer and autumn as well as Italian ryegrass during autumn was below 10 MJ kg-1. Such low ME values could limit milk production. The forage quality of all treatments tended to decline from winter to summer in terms of CP and ME. This could possibly be attributed to the increase in the kikuyu component from winter to summer and the high growth rates of kikuyu during summer (Van der Colf et al. 2009). 3.5 Crude protein (CP) The mean seasonal crude protein (CP) content (%) of two trials where kikuyu were over-sown with ryegrass or clover over two years is shown in Table 7. The CP content in all the pastures was in excess of what is needed by dairy cows (NRC 1989) for optimum milk production. 3.6 Neutral detergent fibre (NDF) content Table 8 shows the mean seasonal neutral detergent fibre (NDF) content (%) of kikuyu of two trials where kikuyu were over-sown with ryegrass or clover over two years. The grass pastures had the highest NDF content (%) while pastures with high clover content had the lowest NDF content. The botanical composition of pasture affected its NDF content. The transforming of the kikuyu-ryegrass pasture from ryegrass-dominant in spring to kikuyu dominant in summer and only kikuyu in autumn led to a seasonal increase in NDF. The NDF content of kikuyu-ryegrass pasture was higher than 60% during summer and autumn. With this high fibre content of the pasture a low digestibility can be expected (Butterworth 1967). The kikuyu-clover pastures had a NDF content of lower than 50% during most of its production period. This will have a positive effect on the DM intake and digestibility of the pasture (Botha et al. 2008a). 3.7 Grazing capacity The mean seasonal grazing capacity (cows ha-1 season-1) of two trials where kikuyu were over-sown with ryegrass or clover over two years, is presented in Table 9. The seasonal grazing capacity of the pastures was high compared to similar pastures (Rethman 1975; Dugmore 1998). Kikuyu-ryegrass fertilized with nitrogen had a higher

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summer and autumn growth rate (Botha et al. 2008a) and therefore a higher grazing capacity than kikuyu-clover pastures not receiving nitrogen applications. The grazing capacity of the kikuyu-clover pasture was the highest during the spring and summer, decreased during autumn and reached the lowest grazing capacity during winter. The autumn grazing capacity of kikuyu-clover pasture was higher during the second year of growth because of increased kikuyu growth (Botha et al. 2008a). The seasonal variation in grazing capacity of the kikuyu-ryegrass pastures was less than that of the clover based pasture (Botha et al. 2008b). Van der Colf et al. (2009) has found that the grazing capacities a similar trend to the growth rates of the species followed, with the lowest grazing capacities occurring during the winter months of June and July.

The annual grazing capacity of the grass dominant pasture was higher than that of the clover pasture (Botha et al. 2008b). Kikuyu over-sown with ryegrass increased the annual grazing capacity of kikuyu (Botha et al. 2003). This finding is supported by Van Heerden (1986) who has found that pure grass pasture, or pasture with a high grass component, has got a higher grazing capacity than pure clover or pastures with a high clover content The annual grazing capacity of kikuyu-clover was lower than kikuyu-ryegrass. Taking into account that no nitrogen was applied on the kikuyu-clover pastures while kikuyu-ryegrass received 600 kg N ha-1, the grazing capacity of the clover based pastures was still high.

3.8 Milk production and milk composition The mean milk production per cow (kg milk cow day), 4% fat corrected milk per cow (kg FCM cow day), butterfat percentage and protein percentage of two trials where kikuyu were over-sown with ryegrass or clover over two years are presented in Table 10. Milk production per cow from kikuyu-clover was higher than from kikuyu-ryegrass pasture during summer and autumn in year 1 of production (Botha et al. 2008b). Cows produced more milk per day from kikuyu-ryegrass during the first of growth than from kikuyu-ryegrass pasture during the autumn. This may be a result of the lower fibre and higher ME content of clover pasture during autumn (Botha et al. 2008a). Botha et al. (2008a) also found an indication that the milk production from kikuyu over-sown with high quality fodder crops resembling ryegrass or clover, can be higher that from a pure kikuyu pasture. The low milk production of the kikuyu, kikuyu-ryegrass and kikuyu-clover pastures were the result of annual ryegrass dying during early summer resulting in pure kikuyu stands and the increase of the kikuyu component during the second year in the clover based pastures (Botha et al. 2008a).

The differences in milk fat content between pastures during the corresponding seasons were small. This finding is comparable to that of Caradus et al. (1996) who have found a similar milk fat content of 5.26% and 5.29% on ryegrass and white clover pasture respectively. Harris et al. (1997) supports this finding and reported that the milk fat content of milk produced from ryegrass-clover pasture with a 20%, 50% and 80% clover content did not differ significantly and contained a milk fat content of 5.88%, 5.73% and 5.65% respectively.

There was no indication that the clover content of the pastures influenced the seasonal protein content of milk. Botha et al. 2008b found that the protein content of all the treatments over a period of three years varied between 3.41% and 3.73%. This is similar to the protein assessment of 3.64% calculated as norm by the Agricultural Research Council for Jerseys (ARC 2002). According to Muller (2002) registered Jersey cows in South Africa produce annually 4 944 kg milk with 3.6% protein content.

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Table 11 shows the total annual milk production (kg milk ha), 4% fat corrected milk (kg FCM ha), milk solids (kg milk solids ha) average grazing capacity (cows ha-1 season-1) of two trials where kikuyu were over-sown with ryegrass or clover over two years. The total annual milk production (kg ha-1) from the different pastures was high. In similar studies milk production from kikuyu varied between 12 820 kg ha-1 for Jersey cows (Cross 1979; Dugmore 1998) and 15 000 kg ha-1 for Friesland cows (Olney and Albertsen 1984) which is lower than the milk production obtained in this studies. Small differences between the total annual milk production from grass- and clover pastures during matching years, were found. During the first year the total annual milk production between treatments were similar. The reasons for this are that the grass and clover pastures reached either a high grazing capacity (cows ha-1) or a high milk production per cow which resulted in a small variation in milk production per hectare between pastures. 4. Discussion: Study 1: The incorporation of annual ryegrass or perennial clover into kikuyu pasture changed the seasonal fodder availability and increased the spring dry matter production of kikuyu (Botha et al. 2008b). The over-sowing of kikuyu with annual ryegrass during May had no effect on the dry matter production of kikuyu during the summer and autumn (Botha et al. 2008a). Kikuyu/ryegrass fertilized with nitrogen fertilizer, had a higher dry matter production rate than kikuyu/clover during the first and second year of growth. The ryegrass-kikuyu ratio of the pasture has an important influence on the seasonal DM production and quality of the pasture. The clover content of the kikuyu/clover maintained at levels higher than 30% for more than two years.

The over-sowing of kikuyu with clover resulted in lower NDF values and higher CP and ME values. The ME value of kikuyu/clover pasture was high during spring. The lower ME content of kikuyu-ryegrass pastures during summer and autumn will be a limiting factor for milk production from kikuyu. The lowest CP content in kikuyu-ryegrass pasture was found during summer and autumn. The CP content of the concentrate supplement fed to cows should be increased during summer and autumn when cows graze kikuyu dominant pasture. Both the kikuyu-ryegrass and kikuyu-clover systems were persistent under good management conditions. The differences between the systems were the higher seasonal DM production and lower nutritional value of the kikuyu-ryegrass system compared the kikuyu-clover system. These factors will not only have an influence on the seasonal grazing capacity of the system but also on the production potential of the individual grazing animal. Subsequently these factors will also affect the animal production per hectare. The choice of system will be influenced by a number of factors. In favour of the kikuyu-ryegrass system will be the fact that it has a high seasonal DM production potential, is easy to execute and manage, requires fewer and less expensive implements, is a no till system executed only when kikuyu is dormant and because of that has no influence on the summer and autumn production potential of kikuyu pasture. The lower nutritional value and dependence of nitrogen fertilizer are the main aspects which can negatively influence the preference of the kikuyu-grass system. The high nutritional value and independency of nitrogen fertilizer is in favour of the kikuyu-clover system. The negative factors are: the lower seasonal DM production, the need to cultivate the soil with an expensive implement not popular in seedbed preparation (rotavator), the set back of the kikuyu production potential during the first year because of the intensive cultivation method, the overshadowing effect of the clover

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on the kikuyu delays kikuyu growth and the competition for soil nutrients between the clovers and kikuyu during the active grow period of kikuyu. The cost of nitrogen fertiliser as well as the milk price will determine the preferred system.

The high grazing capacity (cows ha-1) and milk production per cow (kg cow-1 ha-1) resulted in a high milk production per ha-1. The clover content of the pasture did not influence the milk protein or milk fat content. Milk production per cow was the highest on pasture with high clover content and the grazing capacity of pasture increased as the grass component increased. Kikuyu-ryegrass pasture obtained a similar or a higher seasonal grazing capacity than kikuyu-clover pasture. Kikuyu-ryegrass pasture, compared to that of kikuyu-clover pasture provided a more even seasonal fodder availability resulting in less variation in grazing capacity and milk production. Study 2: Van der Colf et al. (2009) noted that the growth rate of different species varied over months. The low growth rate of the westerwolds ryegrass treatment during November resulted in an increase in kikuyu component during spring, summer and autumn. The opposite occurred in the italian and perennial ryegrass treatments where the growth rate during November was high resulting in a lower kikuyu component. Although perennial ryegrass did not produce significantly higher milk than westerwolds and Italian per cow during year one or two, it had a higher grazing capacity over the ten month lactation period (Van der Colf et al. 2009). Perennial ryegrass showed higher growth rates during the winter and spring of year 2 due to the carry-over effect of plants from year one that survived into year 2. Forage quality tended to decline for all pasture treatments from winter to summer as the kikuyu component present in pasture increased. Perennial ryegrass had higher milk production values per hectare than westerwolds and Italian ryegrass during year 1 and 2. 5. Conclusion and take home message Milk production per ha was similar for clover over-sowed into kikuyu compared to kikuyu-ryegrass pasture. Kikuyu-clover reduced input cost. 6. References ARC, 2002. Herd profile, Agricultural Research Council Livestock Improvement. Private Bag X2, Irene, 0062. Botha PR 2003. Die produksiepotensiaal van oorgesaaide kikoejoeweiding in die

gematigde kusgebied van die Suid-Kaap. PhD. Verhandeling. Universiteit van die Vrystaat.

Botha PR, Meeske R and Snyman HA 2008a. Kikuyu over-sown with ryegrass and clover:

Dry matter production, botanical composition and nutritional value. African Journal of Range & Forage Science 2008, 25(3): 93-101

Botha PR, Meeske R and Snyman HA 2008b. Kikuyu over-sown with ryegrass and clover: Grazing capacity, milk production and milk composition. African Journal of Range & Forage Science 2008, 25(3): 103-110

Butterworth MH 1967. The digestibility of tropical grasses. Nutrition abstracts and reviews 37: 349-368.

Caradus JR, Harris SL and Johnson RJ 1996. Increased Clover Content For Increased Milk Production. Proceedings of the Ruakura Farmers Conference 48:42-49.

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Cross GW 1979. Maintaining the nutritive value of Pennisetum clandestinum for milk production. Proceedings of the Grassland Society of Southern Africa. 14: 61-63.

Dugmore TJ 1998. Dairy production from kikuyu. Proceedings of a kikuyu technology day. KwaZulu-Natal Department of Agriculture, Pietermaritzburg, South Africa. pp 34-35. Fulkerson WJ 1997. Use of the rising plate meter to allocate pasture. Research to farm.

NSW Agriculture. Wollungbar Agricultural Institute May 1997. Harris SL, Clark DA and Jansen EBL 1997. Optimum white clover content for milk

production. Proceedings of the New Zealand Society of Animal Production 57: 169-171.

Marais JP 2001. Factors affecting the nutritive value of Kikuyu grass (Pennisetum clandestinum) – a review. Tropical Grasslands 35: 65-84.

Miles N, De Villiers and Dugmore TJ 1995. Macro mineral composition of kikuyu herbage relative to the requirements of ruminants. Tydskrif Suid-Afrikaanse veeartsenykundige Vereniging 66 (4): 206-212.

Muller CJC 2002. Faktore wat die vastestofinhoud van melk beïnvloed. Suid-Kaap Landbounavorsingsvereniging. Melkvastestowwe-taakspan. Departement Landbou, Privaatsak X1, Elsenburg.

Rethman NFG 1975. Kikoejoe vir beweiding in somer en winter. In: Bekker MJ 1985. Diereproduksie vanaf kikoejoeweiding. Agrivaal 7 (3): 7-14. Soil Classification Workgroup 1991. Soil Classification, a Taxonomic system for South

Africa. Memoirs on the Natural Agricultural Resources of South Africa. Nr 15. Department of Agricultural Development, Pretoria.

Stockdale CR 1984. Evaluation of techniques for estimating the yield of irrigated pastures intensively grazed by dairy cows. II. The rising plate meter. Australian Journal of Experimental Agriculture and Animal Husbandry 24: 305-311.

Harris SL, Clark DA and Jansen EBL 1997. Optimum white clover content for milk production. Proceedings of the New Zealand Society of Animal Production 57: 169-171.

Marais JP 1998. Anti quality factors. Proceedings of a kikuyu technology day. KwaZulu-Natal Department of Agriculture, Pietermaritzburg, South Africa. pp17-21.

NRC 1989. Nutrient requirements of dairy cattle. 7th Revised edition (National Academy of Press: Washington D.C.).

Pottinger RP, Lane PMS and Wilkens JR 1993. Introduction. Pasture Renovation Manual. AgResearch. New Zealand Pastoral Agricultural Research Institute. Reeves M 1997. Milk production from kikuyu (Pennisetum clandestinum) grass pasture.

PhD thesis. Department of Animal Science. Univ. of Sydney. Reeves M and Fulkerson WJ 1995. Management and productivity of kikuyu grass

(Pennisetum clandestinum). I. Determination of the optimum grazing interval for kikuyu grass pasture. II. A comparison of the quality of temperate (ryegrass) and subtropical (kikuyu) grass species for dairy production. In: Fulkerson WJ ed. Research Results 1994/1995. NSW Agriculture Dairy Research Institute. pp 19-26.

Van der Colf J, Botha PR, Meeske R and Truter WF 2009. The effect of over-sowing kikuyu with italian, westerwolds or perennial ryegrass on pasture yield and milk production. Information Day Proceedings. October 2009. Outeniqua Research Farm, PO Box 249, George, 6530.

Van Heerden JM 1986. Potential of established pastures in the Winter Rainfall Region. Ph.D. thesis. University of Natal.

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Table 1 The pasture species and cultivars used in the trials.

Pasture species Cultivars Kikuyu (Pennisetum clandestinum) Annual ryegrass (Lolium multiflorum var. westerwoldicum) Study 1: Study 2: Annual ryegrass (Lolium multiflorum var. italicum) Study 2: Perennial ryegrass (Lolium perenne) Study 2: White clover (Trifolium repens) Study 1: Red clover (Trifolium pratense) Study 1:

Local strain (Southern Cape, South Africa) Energa Jivet Jeanne Bronsyn Mixture of Haifa and Waverley Mixture of Kenland and Cherokee

Table 2 The different treatments, botanical composition of the treatments, seeding rate and over-sowing methods used in both studies.

Treatment Specie Seeding rate kg ha-1

Over-sowing methods

Kikuyu clover

Kikuyu white clover red clover

Existing stand 5

6

Grazed to 50 mm Mulcher Rotavator Cambridge roller Broadcast seed Cambridge roller

Kikuyu- West. rye

Kikuyu annual ryegrass

Existing stand 25

Grazed to 50 mm Broadcast seed Mulcher Cambridge roller

Kikuyu- Italian ryegrass

Kikuyu- Italian ryegrass

Existing stand 25

Grazed to 50 mm Mulcher Aicheson Planter Cambridge roller

Kikuyu- perennial ryegrass

Kikuyu Perennial ryegrass

Existing stand 20

Grazed to 50 mm Mulcher Aicheson Planter Cambridge roller

Botha et al. 2008a and Van der Colf et al. 2009

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Figure 1 The mean monthly growth rate (kg DM ha month) of kikuyu over-sown with clover, westerwolds, Italian or perennial ryegrass.

Botha et al. 2008a and Van der Colf et al. 2009

Table 3. The mean monthly growth rate (kg DM ha-1 day-1) of kikuyu over-sown with clover (1st year of growth). Clover 92nd year of growth), Italian, westerwolds or perennial ryegrass.

Botha et al. 2008a and Van der Colf et al. 2009

Months Kik/west. rye Kik/clover 1

st year

growth

Kik/clover 2

nd year

growth

Kik/west. rye

Kik/ital. rye Kik/peren. rye

Study 1 Study 2 Jun - 18 29 32 30 20 Jul - 15 39 31 34 26 Aug 54 56 50 42 41 48 Sep 51 50 61 54 60 58 Oct 61 64 54 58 80 71 Nov 73 68 56 56 70 72 Decr 64 58 53 74 68 82 Jan 74 60 61 84 61 75 Feb 84 48 45 84 65 75 Mar 84 43 (over sow) 71 63 67 Apr 58 33 (over sow) 0 (over sow) 0 (over sow) 46 May - 33 (over sow) 28 26 0 (over sow)

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Table 4: The mean seasonal kikuyu, ryegrass and clover content (%) of kikuyu over-sown with a different ryegrass varieties, white and red clovers over a period of two years.

Study 1 Winter Spring Summer Autumn

Kik/west. rye kikuyu na na na na ryegrass

Kik/clover 1st year growth

kikuyu na

9 14 30 clover 83 84 69

Kik/clover 2nd year growth

kikuyu 31 26 45 56 clover 66 68 51 42

Study 2 Winter Spring Summer Autumn

Kik/west. rye kikuyu 18 12 64 87 ryegrass 73 66 12 1 other 9 22 25 12

Kik/ital. rye kikuyu 11 3 45 95 ryegrass 80 93 40 2 other 9 3 15 3

Kik/peren. rye kikuyu 3 2 26 51 ryegrass 77 79 59 33 other 19 20 15 16

Botha et al. 2008a and Van der Colf et al. 2009

Table 5: The total seasonal dry matter (kg DM ha-1 season-1) and total annual dry matter (kg DM ha-1 year-1) production of two trials where kikuyu were over-sown with ryegrass or clover over two years.

Study 1 Winter Spring Summer Autumn Total Kik/west. rye na 4879 5904 6183 16966 Kik/clover 1st year growth

na 4902 5006 3395 13303

Kik/clover 2nd year growth

1787 3440 4875 4468 14570

Study 2 Winter Spring Summer Autumn Total Kik/west. rye 3190 4461 6465 2473 16461 Kik/ital. rye 3188 5527 5273 2252 16123 Kik/peren. rye 2679 5364 6212 2894 17143

Botha et al. 2008a and Van der Colf et al. 2009

Table 6: The mean seasonal metabolisable energy (ME) (MJ/kg DM) of two trials where kikuyu were over-sown with ryegrass or clover over two years.

Study 1 Winter Spring Summer Autumn Kik/west. rye na 11.5 9.53 8.0 Kik/clover 1st year growth

na 11.3 10.9 10.6

Kik/clover 2nd year growth

11.6 11.1 9.9 8.4

Study 2 Winter Spring Summer Autumn Kik/west. rye 12.2 11.2 9.7 9.5 Kik/ital. rye 11.9 11.4 10.4 9.9 Kik/peren. rye 12.5 11.4 9.7 9.2

Botha et al. 2008a and Van der Colf et al. 2009

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Table 7: The mean seasonal crude protein (CP) content (%) of two trials where kikuyu were over-sown with ryegrass or clover over two years.

Study 1 Winter Spring Summer Autumn

Kik/west. rye na 21 20 21

Kik/clover 1st year growth

na 28 27 26

Kik/clover 2nd year growth

30 26 20 18

Study 2 Winter Spring Summer Autumn

Kik/west. rye 31 27 19 22

Kik/ital. rye 30 26 20 22

Kik/peren. rye 27 23 19 21

Botha et al. 2008a and Van der Colf et al. 2009

Table 8: The mean seasonal neutral detergent fibre (NDF) content (%) of kikuyu of two trials where kikuyu were over-sown with ryegrass or clover over two years.

Study 1 Winter Spring Summer Autumn

Kik/west rye na 48.1 62.7 67.7

Kik/clover 1st year growth

na 36.4 39.8 45.9

Kik/clover 2nd year growth

36.5 40.8 54.2 64.4

Study 2 Winter Spring Summer Autumn

Kik/west. rye 38 42.4 60.8 59.4

Kik/ital. rye 38.6 41.2 54.6 57.9

Kik/peren. rye 39.4 45.3 56.7 58.1

Botha et al. 2008a and Van der Colf et al. 2009

Table 9: The mean seasonal grazing capacity (cows ha-1 season-1) of two trials where kikuyu were over-sown with ryegrass or clover over two years.

Study 1 Winter Spring Summer Autumn

Kik/west rye na 6.7 7.8 9.5

Kik/clover 1st year growth

na 6.7 7.0 5.2

Kik/clover 2nd year growth

3.2 4.3 5.9 6.6

Study 2 Winter Spring Summer Autumn

Kik/west. rye 3.9 5.5 8.2 4.3

Kik/ital. rye 4.1 6.9 6.6 3.9

Kik/peren. rye 3.4 7.0 7.9 4.5

Botha et al. 2008b and Van der Colf et al. 2009

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Table 10: The mean milk production per cow (kg milk cow day), 4% fat corrected milk per cow (kg FCM cow day), butterfat percentage and protein percentage of two trials where kikuyu were over-sown with ryegrass or clover over two years.

Study 1 Kg milk cow2 Kg FCM cow2 Fat % Protein

Kik/west rye 15.9 17 4.5 3.5

Kik/clover 1st year growth

16.6 17.8 4.5 3.5

Kik/clover 2nd year growth

17.0 17.5 4.2 3.6

Study 2

Kik/west. rye 16.7 18.5 4.85 3.68

Kik/ital. rye 16.8 18.5 4.72 3.70

Kik/peren. rye 16.2 17.3 4.52 3.59

Botha et al. 2008b and Van der Colf et al. 2009

Table 11: The total annual milk production (kg milk ha), 4% fat corrected milk (kg FCM ha), milk solids (kg milk solids ha) average grazing capacity (cows ha-1 season-1) of two trials where kikuyu were over-sown with ryegrass or clover over two years.

Study 1 Kg milk ha Kg FCM ha Kg milk solids Cows ha

Kik/west rye 30489 32627 2434 7.94

Kik/clover 1st year growth

30277 32932 2452 5.53

Kik/clover 2nd year growth

23455 24103 1816 5.57

Study 2

Kik/west. rye 28397 32055 2412 5.99

Kik/ital. rye 29260 32322 2437 5.87

Kik/peren. rye 31837 34177 2548 5.86

Botha et al. 2008b and Van der Colf et al. 2009

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Economics of milk production from kikuyu/ryegrass pasture systems R. Meeske1, J. van der Colf1,2, P.R. Botha1 and W.F Truter2 1Department of Agriculture Western Cape, Outeniqua Research Farm, P.O. Box 249, George,

6530, South Africa. 2Department of Plant Production and Soil Science, University of Pretoria,

0002, South Africa

The aim of the study was to compare the profitability kikuyu pasture systems over-sown with Italian, Westerwold or perennial ryegrass. Approximately nine hectares of irrigated kikuyu pasture was divided into three farmlets. The pasture treatments were kikuyu over-sown with Italian (cv. Jeanne), Westerwolds (cv. Jivet) or perennial ryegrass (cv. Bronson). Stocking rate, milk production and milk composition were measured over lactation. Jersey cows were fed 4kg of concentrate per day during milking. The study was repeated and the average data over two years was used. Table 1. The economics of milk production from kikuyu over-sown with Italian (IR), Westerwolds (WR) or perennial ryegrass (PR).

Parameter IR WR PR

Pasture production (Kg DM/ha) 16602 16975 18341

Milk production (kg/ha) 29259 28397 31837

Stocking rate (cows/ha) 5.88 5.99 6.35

Milk fat % 4.72 4.86 4.52

Milk protein % 3.70 3.68 3.59

Milk price R/kg 3.25 3.26 3.14

Total income R/ha 97442 94969 102505

Milk income (R/ha) 95092 92573 99967

Cull cows sold (R/ha) Cull 20% @ R2000/cow 2350 2396 2538

Total pasture cost (R/ha) 18354 17630 18316

Establishment cost (R/ha) 2134 1410 2096

Fertilizer cost (R/ha) 11187 11187 11187

Irrigation cost (R/ha) (720mm applied including depreciation) 5033 5033 5033

Pasture cost (R/kg DM) 1.11 1.04 1.00

Concentrate cost (R/ha) (4kg X 305 days X R3.20 X cows/ha) 22936 23385 24771

Margin over feed cost (R/ha) 56152 53954 59418

Fixed cost (R/ha) (Labour + R140/CIH/month) 10198 10198 10198

Variable cost (R/ha) (Medicine +AI + Misc R80/CIH/month) 5640 5750 6091

Cost of replacement of 20% of cows @ R6500/cow 7638 7787 8249

Cost feeding dry cows (9kg pasture R0.60/kg, 60 days; 2kg concentrate at R3.20 for 30 days) 3032 3091 3274

Margin over specified costs (R/ha) 29645 27128 31607

Stocking rate (cows/ha) and milk production per cow are key drivers determining profitability of milk production from pasture systems. The perennial ryegrass system obtained the highest margin over specified cost per hectare. Compared to the perennial

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ryegrass system the margin over specified cost was 6.2% and 14.2% lower on the Italian and Westerwold ryegrass systems respectively.

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The production and nutritional value of annual winter growing grass and legume species.

PR Botha, HS Gerber and R Meeske Department of Agriculture Western Cape, Outeniqua Research Farm,

Abstract

The dry matter (DM) production and quality of ryegrass (Lolium multiflorum var. westerwoldicum), oats (Avena sativa), Triticale (Triticosecale), Serradella (Ornithopus sativus) and Vetch (Vicia dasycarpa) as annual winter (June, July and August) growing grasses and legumes planted at different planting dates in pure stands and mixtures, were investigated. Planting date influenced winter DM production. The earliest first grazing varied between 46-50 days if planted during February or March and 61-77 days when planted during April or May. February and March were the best planting dates to plant annual crops for winter production. The growth rate of oats (58-65 kg DM ha-1 day-

1) or oats-triticale (60-78 kg DM ha-1 day-1) planted during February were high making it suitable as a late autumn (May) early winter (June) pasture crop. Annual ryegrass planted during February or March had a DM production rate during winter (45-89 kg DM ha-1 day-1) which was higher or similar to any of the other species evaluated. The mean CP content (>20%) and mean IVOMD (>70%) of the different annual producing pasture crops were high making it suitable as pasture crop for high productive animals like dairy cows.

Keywords: crude protein, in vitro organic matter digestibility, Avena sativa, Triticosecale, Lolium multiflorum , Vicia dasycarpa, Ornithopus sativus.

Introduction

The provision of nutritious, palatable fodder during winter is an essential feature of an efficient fodder flow program. The fodder flow program for dairy and beef cattle production units in the coastal region of the Southern Cape of South Africa consist mainly of combinations of perennial pastures like lucerne (Medicago sativa), Kikuyu (Pennisetum clandestinum), ryegrass- (Lolium perenne and L. multiflorum) and clover species (Trifolium repens en T. pratense). The dry matter (DM) production rate of these crops differ during spring, summer and autumn but reach a mutual low during winter (Van Heerden et al. 1989). This results in over production of fodder during spring, summer and autumn and shortage during winter (June, July and August), limiting the production potential and profitability of milk or beef production from planted pastures (Dawe & Lattimore 1986). In an effort to overcome the problem of low winter grazing capacity of perennial irrigated pastures (Van Heerden et al. 1989), farmers in the Southern cape traditionally plant annual ryegrass (Lolium multiflorum spp.) or oats (Avena sativa) in pure stands or in mixtures as winter pastures. Data regarding the production potential and nutritional value of winter producing grasses and legumes planted specifically as pasture during the winter (June, July and August) for high producing dairy cattle is inadequate for fodder flow planning. The aim of this study was to increase the dry matter production and quality of fodder produced during winter by evaluating different annual winter growing grass and legume species in pure stands and mixtures at different planting dates.

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Procedures The study was carried out during the winter of 2005 and 2006 on the Outeniqua Research Farm near George (altitude 201 m, 33° 58' 38" S and 22° 25' 16" E, rainfall 729 mm year-1) in the Western Cape of South Africa. The area has a temperate climate with mean minimum and maximum air temperatures varying between 7 0C -15 0C and 18 0C - 25 0C respectively. The results were obtained from a small-plot trial on an Estcourt soil type (Soil Classification Workgroup 1991) under irrigation and grazed by jersey cows. Plot sizes were 150 m2 (10 m x 15 m). Irrigation was applied by means of a permanent overhead sprinkler system in one or two applications per week at rates of 10 -15 mm based on tensiometer readings. Irrigation commenced at a tensiometer reading of -25 kPa and was terminated at a reading of -10 kPa. Annual ryegrass (L. multiflorum cv. Energa), oats (A. sativa cv. SSH421), triticale (Triticosecale cv. Bacchus) in pure stands or in mixtures with legumes resembling serradella (Ornithopus sativus cv. Emena) and vetch (Vicia dasycarpa cv. Max) were evaluated. The composition of the pastures which were evaluated and the sowing rates are summarized in Table 2. The legume seed was treated against insects and inoculated with the specific strain of Rhizobium needed for effective nodulation and nitrogen fixation (Staphorst & Strijdom 1974; Allen & Allen 1981; Langenhoven 1986).

Fertiliser was based on soil analysis and applied to raise the soil phosphorus level to 35 mg kg-1 (citric acid), potash level to 80 mg kg-1 (citric acid) and the pH (KCL) to 5.5. Nitrogen (N) was applied to the grass and grass-legume pastures at 55 kg N ha-1 month-1. Pure legume stands were not fertilized with N. A mixture of Molybdenum (Mo) and an insecticide (ometoaat) were four weeks after germination applied as a foliar application on the legume pastures at 130 gm ha-1 and 40 ml ha-1 respectively (Langenhoven 1986; Lowther 1987).

The crops were planted at four planting dates nl. 15 February, 15 March, 15 April and 15 May. No seedbed was prepared. Eragrostis teff was planted during November of the previous year and grazed throughout the summer with Jersey cows. Four weeks before planting the winter crops, the teff was grazed down to 30 mm and sprayed with an herbicide (glyphosate) at 3 litre ha-1. The different crops were then planted, without the prior working of the soil, into the dead plant material with an Aitchison planter.

The crops were every 28-35days grazed down to a height of 50 mm when the ryegrasses reached the three leave stage or when overshadowing of the growing points of grasses occurred (Fulkerson & Donaghy 2001). The dry matter (DM) production was calculated before grazing by harvesting six 0.099 m2 quadrants at a cutting height of 50 mm in each paddock. The dry matter content was determined by drying samples at 60 0C for 72 hours. A pooled sample of two kg dry material obtained from the six samples was used for quality analyses. Samples were milled through a 1mm sieve and analysed for in vitro organic matter digestibility (IVOMD) (Tilley and Terry 1963), crude protein (CP) and neutral detergent fibre (NDF) (Van Soest et al. 1991).

The trial was laid out as a randomized complete block design with four main-plot treatments (Sowing time – Feb, Mar, Apr and May) randomly allocated within each of the three block replicates. The 12 sub-plot treatments (Cultivar and sowing density combinations) randomly allocated within each main-plot. Standard univariate Split-plot analysis of variance (ANOVA) was performed on all measurements using SAS version 9.13 statistical software (SAS, 1999). The Shapiro-Wilk‟s test was performed on the residuals to test for deviations from normality (Shapiro and Wilk 1965). Student's t-LSD (Least significant difference) was calculated at a 5% significance level to compare

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means of significant effects. Table 1 shows the pasture species and cultivars used in the trial. Table 2 shows the different treatments, species, botanical composition of the treatments and seeding rate used in the trial. Results The monthly dry matter production rate (kg DM ha-1 day-1) of different annual winter producing pastures crops planted during February 2005 and February 2006 is shown in Table 3 and Table 4 respectively. The first grazing was 46 days (31 March 2005) and 50 days (4 April 2006) after planting. The growth rate of oats/triticale during the first grazing (2005) was higher (P<0.05) than ryegrass, triticale or mixtures containing ryegrass or triticale during 2005. The trend continues during 2006 where pure stands of oats, triticale, or mixtures containing oats or triticale had the highest growth rate during the first grazing. The growth rate of ryegrass was during both years (2005 and 2006) from May until November higher (P<0.05) or similar (P>0.05) than any of the other species. The growth rate of the ryegrass mixtures varied monthly and was from July higher (P<0.05) than the growth rate of oats, triticale or mixtures containing oats and triticale. The monthly dry matter production rate (kg DM ha-1 day-1) of different annual winter producing pastures crops planted during March 2005 and March 2006 is shown in Table 5 and Table 6 respectively. The first grazing was on the 4th of May, 49 days after planting. The growth rate of oats and triticale during the first grazing (May) was higher (P<0.05) than that of a pure ryegrass stand. However, the growth rate of ryegrass from June onwards was higher (P<0.05) or similar (P>0.05) to the other species or mixtures. The growth rate of ryegrass or ryegrass mixtures was from August 2005 and June 2006 higher (P<0.05) than that of oats mixtures or triticale mixtures. The monthly dry matter production rate (kg DM ha-1 day-1) of different annual winter producing pastures crops planted during April 2005 and April 2006 is shown in Table 7 and Table 8 respectively. The first grazing was 61 days (14 June 2005) and 74days (27 June 2006) after planting. The dry matter production rate of the highest producing crops during June nl. Oats and triticale were low and varied between 22.6 and 44.8 kg DM/ha. The growth rate of ryegrass was from during July 2005 and August 2006 until November higher (P<0.05) or similar (P>0.05) than any of the other species. The growth rate of ryegrass from September until November was higher (P<0.05) than that of oats, triticale or mixtures of oats/triticale,oats/serradella, oats/vetch, triticale/serradella or triticale/vetch was during both years (2005 and 2006). The monthly dry matter production rate (kg DM ha-1 day-1) of different annual winter producing pastures crops planted during May 2005 and May 2006 is shown in Table 9 and Table 10 respectively. The first grazing was during July, 51 days and 77 days after planting. The growth rate of ryegrass mixtures was higher (P<0.05) or similar (P>0.05) to the other species or mixtures. The total annual dry matter production (kg DM ha-1) of different annual winter producing pasture crops planted during February, March, April and May 2005 and 2006 is shown in Table 11 and 12 respectively. The total DM production of the 2005 trial shows that ryegrass planted during February had a higher (P<0.05) total annual DM production than any of the other species or mixtures planted during March, April or May. Only ryegrass in mixtures with oats, triticale or serradella produced statistically a similar amount of DM when planted during February. The total annual DM production of the 2006 trial indicated that mixtures of ryegrass/triticale, ryegrass/oats and ryegrass planted during March produced more (P<0.05) total DM than any of the other species or mixtures planted during April or May.

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Ryegrass planted during February or March produced a similar (P>0.05) total annual DM production. Ryegrass/triticale planted during February had a higher (P<0.05) total annual DM production than ryegrass or any other specie or mixture planted during February, April or May but was similar (P>0.05) to the production of ryegrass/oats and ryegrass planted during February. The mean monthly and mean seasonal crude protein (CP) content (%) of different annual winter producing pasture crops planted during February, March, April and May 2005 is shown in Tables 13, 14, 15 and 16 respectively. The CP content was in general high (above 20%). The CP of the ryegrass and mixtures containing ryegrass was at the February, March and April planting dates for the first five grazings, higher than 20%. The CP content of ryegrass legume pasture was not increased compared to ryegrass. The CP content tended to be lower during October and November. The mean monthly and mean seasonal in vitro organic matter digestibility (IVOMD) (%) of different annual winter producing pasture crops planted during February, March, April and May 2005 is shown in Tables 17, 18, 19 and 20 respectively. The IVOMD was high (70-86%) and tended to decrease from June to November. The inclusion of legumes did not increase the IVOMD of pasture. Conclusions Planting date influenced winter DM production. The earliest first grazing varied between 46-50 days if planted during February or March. February and March were the best planting dates to plant annual crops for winter (June, July and August) production. The high growth rate of oats or oats-triticale planted during February or March makes it suitable as late autumn (May) early winter (June) pasture crop. Annual ryegrass or annual ryegrass-oats mixtures planted during February or March, increased winter production. Annual ryegrass planted during February or March has a DM production rate during winter that is higher or similar to any of the other species evaluated. The mean CP content (>20%) and mean IVOMD (>70%) of the different annual producing pasture crops were high making it suitable as a pasture crop for highly productive animals like dairy cows. Comment Results have shown that these crops have a higher winter DM production rate than most perennial grasses used as planted pastures for dairy cows (kikuyu; perennial ryegrass) in this area. However, if compared with the summer and autumn DM production ability of kikuyu and perennial ryegrass, the DM production potential of these annual winter growing crops is not high enough to prevent winter fodder shortages.

Literature Allen ON and Allen EK 1981. The genus Rhizobium. In: The leguminosae: a source book of characteristics, uses and nodulation, Macmillan, London Dawe ST and Lattimore ME 1986. Integrated irrigated pasture systems for southern New SouthWales. Department of Agriculture, Agricultural Institute, Yanco 2703. 495-497. Fulkerson WJ and Donaghy 2001. Plant-soluble carbohydrate reserves and senescences – key criteria for developing an effective grazing management system for

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ryegrass-based pasture: a review. Australian Journal of Experimental Agricultures. 41: 261-275. Langenhoven JD 1986. Establishment of legume pastures in the Winter Rainfall Region. Farming in South Africa, A.4, Division of Agricultural Information. Lowther WL 1987. Application of molybdenum to inoculants, lime coated white clover seed. New Zealand Journal Exp. Agric. 15: 271-275. Soil Classification Workgroup 1991. Soil Classification, a Taxonomic system for South Africa. Memoirs on the Natural Agricultural Resources of South Africa. Nr 15. Department of Agricultural Development, Pretoria. SAS Institute, Inc. (1999), SAS/STAT User's Guide, Version 9, 1st printing, Volume 2. SAS Institute Inc, SAS Campus Drive, Cary, North Carolina 27513. Shapiro SS and Wilk M B (1965). An Analysis of Variance Test for Normality (complete samples)., Biometrika, 52: 591-611. Staphorst JL and Strijdom JL 1974. Effect of treatment with a dimethoate insecticide on nodulation and growth of L. Plant Protection Research Institute, Pretoria. Phytophylactica 6: 205-208. Tilley JM and Terry RA 1963. Atwo stage technique for the in vitro digestion of forage crops. Journal of the British Grassland Society 18:104 -111. Van Heerden JM 1986. Potential of established pastures in the Winter Rainfall Region. Ph.D thesis Univ. Natal. Van Heerden JM, Tainton NM and Botha PR 1989. A comparison of grass and grass/legume pastures under irrigation in the Outeniqua area of the southern Cape. Tydskrif Weidingsvereniging van Suid Afrika. 6 (4). p 220-224. Van Soest PJ, Robertson JB and Lewis BA 1991. Symposium: Carbohydrate methology, metabolism and nutritional implications in dairy cattle. Journal Dairy Science74: 3583-3597.

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Table 1 The pasture specie and cultivars used in the trial.

Pasture species Cultivar

Ryegrass (Lolium multiflorum var. westerwoldicum) Oats (Avena sativa) Triticale (Triticosecale) Serradella (Ornithopus sativus) Vetch (Vicia dasycarpa)

Energa SSH421 Bacchus Emena Max

Table 2 The different treatments, species, botanical composition of the treatments and seeding rate used in the trial.

Treatment Species, botanical composition and seeding rate (kg/ha)

Abbreviations

1 2 3 4 5 6 7 8 9 10 11 12

Ryegrass (25) Oats (100) Triticale (130) Ryegrass (15) + oats (60) Ryegrass (15) + triticale (100) Ryegrass (15) + serradella (10) Ryegrass (15) + vetch (10) Oats (50) + triticale (80) Oats (50) + serradella (15) Oats (50) + vetch (15) Triticale (90) + serradella (15) Triticale (90) + vetch (15)

rye oat tri rye/oat rye/tri rye/ser rye/vet oat/tri oat/ser oat/vet tri/ser tri/vet

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Table 3: The monthly dry matter production rate (kg DM ha-1 day-1) of different annual winter producing pastures crops planted during February 2005.

Treatment 31 Mar 3 May 7 Jun 13 Jul 17 Aug 22 Sep 25 Oct

1. rye 28.1d 57.8abc 45.3ab 56.4a 74.3abc 98.3a 100.9a

2. oat 57.7ab 65.0ab 36.9abc 32.3ef 54.2bcd 48.9b 20.4c

3. tri 40.4bcd 48.8bc 19.3d 33.6def 27.7ef 3.1c 0c

4. rye/oat 33.2cd 50.7bc 49.6a 51.6ab 72.1abc 87.1a 67.7b

5. rye/tri 34.3cd 57.7abc 38.2abc 51.9ab 75.8ab 87.6a 80.2ab

6. rye/ser 35.4cd 46.1bc 42.2abc 38.4cdef 88.8a 91.9a 71.1ab

7. rye/vet 27.0d 55.5abc 35.9abcd 45.3abc 61.2bcd 89.2a 72.8ab

8. oat/tri 60.2a 78.1a 42.0abc 44.0bcd 56.3bcd 54.6b 23.6c

9. oat/ser 51.3abc 56.4abc 30.0bcd 34.5cdef 45.5de 38.6b 17.8c

10. oat/vet 44.1abcd 54.7abc 40.7abc 39.7cde 49.0cde 53.3b 19.6c

11. tri/ser 30.3d 44.2bc 26.9cd 27.1f 12.2f 3.7c 0c

12. tri/vet 39.2cd 36.1c 40.3abc 35.0cdef 27.2ef 5.9c 0c

LSD 18.20 26.25 17.90 11.33 25.99 19.95 29.96 abcde Means with no common superscript in columns differ significantly (P<0.05) LSD (0.05) compare within columns. Table 4: The monthly dry matter production rate (kg DM ha-1 day-1) of different annual winter producing pastures crops planted during February 2006.

Treatment 4 Apr 8 May 12 Jun 13 Jul 17 Aug 21 Sep 24 Oct 28 Nov

1. rye 19.8c 52.6ab 60.0ab 56.3a 88.8a 93.3ab 87.7a 54.3a 2. oat 57.2a 63.0a 42.5abcd 39.4b 38.3c 36.4cd 59.3b 7.46b 3. tri 58.2a 21.0d 31.4cd 20.0cd 22.9de 16.3de 13.3d 2.48b 4. rye/oat 56.8a 57.5ab 65.9a 70.2a 89.9a 75.4b 88.8a 50.3a 5. rye/tri 51.8ab 51.7abc 61.2ab 59.8a 75.1b 104.1a 90.4a 53.9a 6. rye/ser 24.2c 49.9abc 53.8abc 55.5a 74.1b 101.8a 82.3a 58.4a 7. rye/vet 27.8c 41.0bc 60.5ab 62.8a 90.3a 74.1b 80.6a 54.3a 8. oat/tri 59.3a 46.4abc 41.3bcd 32.9bc 37.6c 48.2c 44.0bc 7.13b 9. oat/ser 49.0ab 50.9abc 42.1bcd 32.3bc 35.7c 17.0de 34.3c 5.47b 10. oat/vet

52.7ab 39.7bc 42.3abcd 36.0b 34.6cd 26.9de 37.6c 10.6b

11. tri/ser 42.0b 18.5d 29.2d 16.1d 8.50f 6.66e 5.42d 2.71b 12. tri/vet 52.1ab 33.6cd 27.7d 17.9cd 19.3ef 20.3de 12.8d 7.24b

LSD 14.01 18.16 23.58 14.97 12.28 21.26 19.71 10.28 abcde Means with no common superscript in columns differ significantly (P<0.05) LSD (0.05) compare within columns.

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Table 5: The monthly dry matter production rate (kg DM ha-1 day-1) of different annual winter producing pastures crops planted during March 2005.

Treatment Mar 3 May 7 Jun 13 Jul 17 Aug 22 Sep 25 Oct

1. rye 29.9d 48.5a 50.2ab 63.2a 84.0a 49.1ab

2. oat 49.1abc 41.5a 48.0ab 37.6cd 54.8b 56.0a

3. tri 46.3abc 43.7a 39.2abc 13.7e 7.3c 3.89cd

4. rye/oat 49.5ab 40.3a 35.7abc 57.1ab 84.2a 65.3a

5. rye/tri 38.8cd 46.6a 49.3ab 54.1abc 88.6a 54.9a

6. rye/ser 31.4d 39.6a 53.0a 62.9a 85.8a 60.6a

7. rye/vet 31.1d 41.7a 45.8abc 57.7ab 83.9a 55.6a

8. oat/tri 52.3a 39.7a 44.7abc 41.7bcd 60.5b 25.2bc

9. oat/ser 40.0bcd 41.8a 28.2bc 33.8d 45.3b 23.3cd

10. oat/vet 39.3bcd 37.4a 33.6bc 41.0bcd 49.1b 19.2cd

11. tri/ser 49.2abc 46.7a 37.0abc 12.4e 3.7c 0.4d

12. tri/vet 46.7abc 43.3a 52.2ab 27.1de 3.5c 5.0cd

LSD 10.58 20.37 19.36 17.37 20.06 24.57 abcde Means with no common superscript in columns differ significantly (P<0.05) LSD (0.05) compare within columns. Table 6: The monthly dry matter production rate (kg DM ha-1 day-1) of different annual winter producing pastures crops planted during March 2006.

Treatment Apr 4 May 6 Jun 10 Jul 14 Aug 20 Sep 23 Oct 27 Nov

1. rye 34.6d 54.4ab 89.3a 73.4abcd 115.8a 147.3a 50.8ab 2. oat 49.9abc 35.0cde 40.8c 35.2def 34.9cd 64.0c 15.0c 3. tri 54.4ab 22.7ef 38.6c 20.1ef 14.9de 17.2de 6.65c 4. rye/oat 53.2ab 46.5bcd 73.5ab 88.4ab 105.8ab 151.2a 48.2b 5. rye/tri 55.8ab 67.1a 83.9ab 79.8abc 102.2ab 166.6a 68.6a 6. rye/ser 32.4d 56.9ab 65.1b 96.3a 94.6ab 148.3a 55.0ab 7. rye/vet 30.9d 48.5cd 76.7ab 79.5abc 90.3b 99.3b 49.6ab 8. oat/tri 59.9a 30.9ef 37.8c 39.0cdef 40.6c 63.6c 15.7c 9. oat/ser 46.4bc 27.0def 39.4c 51.5bcde 20.1cde 42.7cd 12.2c 10. oat/vet 49.9abc 37.4cde 36.5c 27.0ef 34.1cde 53.6c 18.6c 11. tri/ser 40.8cd 16.1f 24.8c 13.6ef 15.3de 13.1e 6.03c 12. tri/vet 50.3abc 27.0ef 30.8c 9.35f 8.78e 12.0e 6.17c

LSD (0.05) 10.32 16.60 22.48 41.4 25.28 27.10 20.11 abcde Means with no common superscript in columns differ significantly (P<0.05) LSD (0.05) compare within columns.

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Table 7: The monthly dry matter production rate (kg DM ha-1 day-1) of different annual winter producing pastures crops planted during April 2005.

Treatment Apr May 14 Jun 27 Jul 01 Sep 01 Oct 02 Nov

1. rye 15.6d 40.2ab 62.3abc 88.9ab 73.4a

2. oat 25.6ab 35.0abc 48.8cde 76.1bcd 43.7b

3. tri 22.6abc 22.1c 27.1f 5.21e 7.8c

4. rye/oat 25.7ab 36.5ab 62.1abc 83.8abc 75.1a

5. rye/tri 22.2bcd 34.8abc 73.1a 87.5ab 80.8a

6. rye/ser 17.7cd 48.6a 73.5a 109.8a 94.0a

7. rye/vet 17.2cd 39.1ab 70.3ab 90.3ab 78.9a

8. oat/tri 29.1a 32.4bc 57.0abcd 69.2bcd 25.7bc

9. oat/ser 20.5bcd 37.8ab 53.4bcd 51.7d 12.8c

10. oat/vet 21.5bcd 40.7ab 54.1bcd 56.2cd 23.6bc

11. tri/ser 24.8ab 29.7bc 31.7ef 7.5e 6.3c

12. tri/vet 25.7ab 40.1ab 41.3def 6.8e 6.39c

LSD 6.771 13.79 17.57 27.58 26.37 abcde Means with no common superscript in columns differ significantly (P<0.05) LSD (0.05) compare within columns. Table 8: The monthly dry matter production rate (kg DM ha-1 day-1) of different annual winter producing pastures crops planted during April 2006.

Treatment Apr May 27 Jun 7 Aug 11 Sep 11 Oct 14 Nov

1. rye 30.5c 68.9a 65.8ab 114.1a 178.9a 2. oat 44.8a 57.9ab 31.9de 55.1cd 75.2de 3. tri 42.1a 64.5ab 30.2de 61.3bcd 23.3f 4. rye/oat 42.3a 58.0ab 52.2bc 142.4a 172.7ab 5. rye/tri 41.2ab 61.6ab 72.6a 140.4a 174.3ab 6. rye/ser 29.8c 59.2ab 44.9cd 101.9ab 110.6cd 7. rye/vet 26.9c 58.7ab 69.3ab 113.7a 141.4bc 8. oat/tri 42.9a 72.0a 37.2cd 67.7bc 69.7e 9. oat/ser 33.4bc 52.0b 26.1de 48.3cd 47.2ef 10. oat/vet 39.3ab 62.2ab 37.1cd 69.3bc 62.6e 11. tri/ser 41.9a 48.6b 14.4e 21.1d 13.5f 12. tri/vet 29.3c 64.5ab 42.6cd 46.6cd 13.5f

LSD 7.95 16.13 19.55 40.94 36.99 abcde Means with no common superscript in columns differ significantly (P<0.05) LSD (0.05) compare within columns.

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Table 9: The monthly dry matter production rate (kg DM ha-1 day-1) of different annual winter producing pastures crops planted during May 2005.

Treatment Apr Mei Jun 05 Jul 6 Sep 10 Oct 25 Nov

1. rye 36.4ab 69.2abc 100.5a 86.1a

2. oat 27.8b 61.8abc 83.3a 32.1b

3. tri 44.0a 58.8bcd 37.8b 10.8bc

4. rye/oat 35.8ab 76.3a 93.4a 83.5a

5. rye/tri 42.8a 79.2a 104.8a 94.0a

6. rye/ser 33.5ab 66.0abc 83.9a 90.0a

7. rye/vet 37.8ab 71.3ab 102.0a 77.3a

8. oat/tri 34.0ab 54.2bcd 83.9a 25.1bc

9. oat/ser 36.0ab 67.7abc 90.8a 18.2bc

10. oat/vet 31.5ab 52.2cd 83.2a 13.6bc

11. tri/ser 40.1ab 43.4d 49.0b 3.6c

12. tri/vet 43.2a 63.6abc 41.5b 4.6c

LSD 13.69 17.44 24.00 22.45 abcde Means with no common superscript in columns differ significantly (P<0.05) LSD (0.05) compare within columns. Table 10: The monthly dry matter production rate (kg DM ha-1 day-1) of different annual winter producing pastures crops planted during May 2006.

Treatment Apr May Jun 31 Jul 7 Sep 9 Oct 13 Nov

1. rye 20.8bc 57.4a 139.8a 163.4a 2. oat 22.9abc 26.4b 61.3b 68.8b 3. tri 26.8ab 30.6b 54.7b 29.3cd 4. rye/oat 24.3abc 57.6a 121.9a 148.7a 5. rye/tri 29.3a 65.2a 135.8a 157.6a 6. rye/ser 23.1abc 60.8a 115.2a 158.8a 7. rye/vet 23.0abc 51.1a 115.1a 154.5a 8. oat/tri 23.7abc 21.6b 62.3b 64.0b 9. oat/ser 17.7c 20.2b 34.8b 31.8cd 10. oat/vet 20.3bc 24.1b 48.0b 51.1bc 11. tri/ser 21.9abc 16.6b 39.1b 22.7d 12. tri/vet 22.0abc 25.1b 68.0b 27.4cd

LSD 8.133 15.76 33.28 26.47 abcde Means with no common superscript in columns differ significantly (P<0.05) LSD (0.05) compare within columns.

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Table 11: The total dry matter production (kg DM ha-1) of different annual winter producing pastures crops planted during February, March, April and May 2005.

Treatment February March April May

1. rye 16198a 12105efghij 9878klmnopq 11902efghijk

2. oat 11446efghijk 10966ghijkl 8396mnopqrs 8462mnopqrs

3. tri 6313stuvwx 6186tuvwx 3616xy 7193rstuvw

4. rye/oat 14586abcd 12600cdefgh 10189jklmnop 11807efghijk

5. rye/tri 15040ab 12438defgh 10601hijklm 13195bcdef

6. rye/ser 14664abc 12416defghi 12047efghijk 11136fghijkl

7. rye/vet 13634bcde 11770efghijk 10422hijklmn 11821efghijk

8. oat/tri 12929bcdefg 10221ijklmno 8004pqrstu 8372nopqrst

9. oat/ser 9925jklmnop 8182opqrstu 6672stuvw 9040lmnopqr

10. oat/vet 10831ghijkl 8465mnopqrs 7361rstuv 7674qrstu

11. tri/ser 5243vwxy 6059uvwx 4260xy 6419stuvwx

12. tri/vet 6776stuvw 7110rstuvw 5084wxy 7232rstuvw

abcde Means with no common superscript in columns and rows differ significantly (P<0.05) LSD (0.05) = 2206 (compare over months) Table 12: The total dry matter production (kg DM ha-1) of different annual winter producing pastures crops planted during February, March, April and May 2006.

Treatment February March April May

1. rye 17726cdef 20048abc 16679fgh 13952ij 2. oat 12371ijkl 10199lmno 10750klmn 7111qrstu 3. tri 7062rstu 6837rstuv 9193mnopqr 5973stuv 4. rye/oat 19579bcd 20380ab 17229defg 13145ijk 5. rye/tri 19330bcde 22326a 18006bcdef 14567hi 6. rye/ser 17357defg 19399bcde 12842ijk 13312ij 7. rye/vet 17079defgh 16889efgh 14874ghi 12775ijk 8. oat/tri 11531jklm 10687klmn 11570jklm 6850rstuv 9. oat/ser 9676mnop 9060mnopqr 8369nopqrs 4340v 10. oat/vet 10183lmno 9596mnopq 10726klmn 5781tuv 11. tri/ser 4929uv 5099uv 6433stuv 4344v 12. tri/vet 7173pqrstu 5713tuv 7979opqrst 5766tuv abcde Means with no common superscript in columns and rows differ significantly (P<0.05) LSD (0.05) = 2519 (compare over months)

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Table 13: The mean monthly and mean seasonal crude protein (CP) content (%) of different annual winter producing pasture crops planted during February 2005.

Treatment 31 Mrt 3 May 7 Jun 13 Jul 17 Aug 22 Sep

25 Oct

STD mean

1. rye 27.9 22.6 24.6 25.8 24.4 20.8 19.5 2.90 23.0 2. oat 23.7 20.7 27.2 28.0 22.9 24.5 17.0 2.37 23.4 3. tri 21.1 21.2 23.0 21.5 23.3 16.7 na 3.77 21.1 4. rye/oat 24.8 25.3 24.8 22.2 23.9 21.8 18.4 2.44 22.7 5. rye/tri 25.2 24.1 30.5 26.2 23.8 20.7 20.8 3.37 24.4 6. rye/ser 26.6 20.4 25.9 26.0 24.2 22.2 19.7 2.82 23.1 7. rye/vet 28.9 23.1 29.2 24.2 22.7 20.3 20.9 3.57 23.4 8. oat/tri 24.0 21.5 26.6 23.3 23.6 22.5 17.2 2.88 22.5 9. oat/ser 27.8 21.0 27.2 23.0 24.1 22.3 17.3 3.62 22.5 10. oat/vet 28.3 20.4 26.4 26.9 24.0 23.9 16.5 4.11 23.0 11. tri/ser 23.8 17.9 22.7 20.8 19.6 15.6 na 3.04 19.3 12. tri/vet 26.8 19.0 25.2 24.6 27.4 18.9 20.7 3.63 22.6

STD 2.36 2.08 2.29 2.27 1.74 2.68 1.73 1.29

na = not available Table 14: The mean monthly and mean seasonal crude protein (CP) content (%) of different annual winter producing pasture crops planted during March 2005.

Treatment Apr 4 May 8 Jun 14 Jul 23 Aug 26 Sep 31 Oct STD mean

1. rye 29.7 28.8 27.1 22.9 23.2 18.7 4.02 25.1 2. oat 21.9 24.5 25.4 24.8 21.9 18.6 2.57 22.9 3. tri 22.1 20.6 22.1 20.1 17.3 na 1.97 20.4 4. rye/oat 23.1 27.3 29.9 26.7 24.0 21.7 3.05 25.5 5. rye/tri 26.7 24.3 29.4 27.2 24.6 21.6 2.72 25.6 6. rye/ser 29.9 28.1 27.5 26.8 26.0 22.5 2.49 26.8 7. rye/vet 30.6 25.8 23.8 24.0 24.3 22.0 2.96 25.1 8. oat/tri 25.7 22.9 27.6 23.7 25.9 17.4 3.58 23.9 9. oat/ser 26.8 26.0 27.4 24.5 21.6 16.1 4.28 23.7 10. oat/vet 25.6 25.0 28.7 24.5 22.0 22.5 2.41 24.7 11. tri/ser 25.0 22.2 26.5 18.9 21.7 na 2.97 22.9 12. tri/vet 27.4 22.6 23.5 24.2 16.4 na 4.02 22.8

STD 2.93 2.52 2.43 2.51 3.02 2.44 1.71

na = not available

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Table 15: The mean monthly and mean seasonal crude protein (CP) content (%) of different annual winter producing pasture crops planted during April 2005.

Treatment Apr May 14 Jun 27 Jul 01 Sep 01 Oct 02 Nov STD mean

1. rye 24.2 23.5 26.7 24.8 24.7 1.19 24.8 2. oat 25.1 25.2 27.2 24.5 16.6 4.11 23.7 3. tri 26.2 23.2 22.4 20.2 17.6 3.23 21.9 4. rye/oat 24.2 23.6 26.6 25.5 22.9 1.49 24.6 5. rye/tri 27.8 25.9 25.6 23.7 23.2 1.85 25.2 6. rye/ser 26.3 25.7 26.5 26.2 24.3 0.89 25.8 7. rye/vet 28.4 25.8 24.8 26.3 23.5 1.82 25.8 8. oat/tri 25.4 26.1 22.3 23.5 18.1 3.17 23.1 9. oat/ser 28.3 24.3 26.4 24.9 16.8 4.38 24.1 10. oat/vet 29.4 25.6 26.1 22.9 18.6 4.04 24.5 11. tri/ser 26.9 21.9 23.9 20.3 na 2.84 23.3 12. tri/vet 25.8 23.2 24.4 22.7 21.0 1.81 23.4

STD 1.69 1.39 1.68 2.02 3.17 1.17

na = not available Table 16: The mean monthly and mean seasonal crude protein (CP) content (%) of different annual winter producing pasture crops planted during May 2005.

Treatment Mei Jun 28 Jul 6 Sep 10 Oct 25 Nov STD mean

1. rye 21.3 24.2 26.2 20.6 2.60 23.1 2. oat 21.8 21.0 16.7 14.8 3.37 18.6 3. tri 22.7 22.4 17.7 15.1 3.71 19.5 4. rye/oat 22.1 24.1 20.1 18.1 2.58 21.1 5. rye/tri 24.6 24.4 21.1 19.8 2.40 22.5 6. rye/ser 19.6 22.2 16.4 20.2 2.41 19.6 7. rye/vet 22.1 25.4 25.1 20.5 2.38 23.3 8. oat/tri 20.0 22.6 17.0 14.1 3.68 18.4 9. oat/ser 22.3 22.1 17.1 15.6 3.43 19.3 10. oat/vet 24.1 25.1 21.6 15.4 4.36 21.6 11. tri/ser 18.0 21.8 17.2 na 2.46 19.0 12. tri/vet 19.8 23.7 19.3 17.0 2.78 20.0

STD 1.91 1.41 3.32 2.54 1.76

na = not available

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Table 17: The mean monthly and mean seasonal in vitro organic matter digestibility (IVOMD) (%) of different annual winter producing pasture crops planted during February 2005.

Treatment 31 Mrt 3 May 7 Jun 13 Jul 17 Aug

22 Sep 25 Oct STD mean

1. rye 80.1 77.1 71.2 80.1 75.8 69.8 68.6 4.81 74.7 2. oat 78.6 77.5 75.8 82.9 69.3 74.7 77.5 4.14 76.6 3. tri 76.9 76.6 75.4 77.7 79.7 70.4 na 3.14 76.1 4. rye/oat 76.9 80.8 72.0 77.5 n/a 67.4 70.6 5.02 74.2 5. rye/tri 78.5 74.2 80.6 76.7 84.0 68.6 65.9 6.46 75.5 6. rye/ser 80.4 74.5 76.5 66.0 79.9 72.5 69.2 5.35 74.2 7. rye/vet 78.2 74.2 77.9 84.1 78.7 68.1 72.6 5.13 76.3 8. oat/tri 76.2 70.5 72.8 78.3 77.5 73.6 71.4 3.04 74.3 9. oat/ser 80.9 69.9 77.8 76.7 78.1 73.2 73.3 3.74 75.7 10. oat/vet 78.2 71.2 76.2 81.0 79.5 72.4 71.2 4.09 75.7 11. tri/ser 80.2 69.1 72.8 75.3 78.1 70.9 na 4.27 74.4 12. tri/vet 80.4 71.9 74.3 76.7 79.1 75.2 71.5 3.39 75.6

STD 1.60 3.57 2.78 4.58 2.04 2.60 3.08 0.87

na = not available Table 18: The mean monthly and mean seasonal in vitro organic matter digestibility (IVOMD) (%) of different annual winter producing pasture crops planted during March 2005.

Treatment Apr 4 May 8 Jun 14 Jul 23 Aug

26 Sep 31 Oct STD mean

1. rye 78.3 78.0 84.0 82.8 74.3 73.5 4.28 78.5 2. oat 74.6 83.4 85.9 82.5 83.5 74.2 5.00 80.7 3. tri 68.6 78.2 78.1 79.8 76.1 na 4.43 76.1 4. rye/oat 75.0 85.1 85.3 83.8 80.5 73.8 5.10 80.6 5. rye/tri 71.9 78.9 85.3 83.2 80.9 76.2 4.86 79.4 6. rye/ser 77.0 82.2 83.8 82.0 80.1 76.7 2.92 80.3 7. rye/vet 78.6 83.9 82.8 85.9 79.9 77.1 3.38 81.4 8. oat/tri 73.4 82.6 82.1 85.5 84.2 76.6 4.71 80.7 9. oat/ser 77.9 83.6 85.8 86.2 83.0 76.8 3.98 82.2 10. oat/vet 74.8 83.8 83.8 86.8 81.8 77.7 4.98 81.4 11. tri/ser 77.3 78.9 86.5 80.7 80.8 na 4.43 80.8 12. tri/vet 73.3 79.8 78.8 82.4 73.7 76.6 3.48 77.4

STD 2.98 2.58 2.71 2.23 3.45 1.50 1.79

na = not available

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Table 19: The mean monthly and mean seasonal in vitro organic matter digestibility (IVOMD) (%) of different annual winter producing pasture crops planted during April 2005.

Treatment Apr May 14 Jun 27 Jul 01 Sep 01 Oct 02 Nov STD mean

1. rye 89.2 81.5 79.5 75.8 75.1 5.67 80.2 2. oat 87.7 81.3 83.0 79.8 73.5 5.16 81.1 3. tri 85.5 83.9 75.5 75.4 71.5 6.04 73.4 4. rye/oat 86.0 79.8 78.7 76.1 69.1 6.13 77.9 5. rye/tri 84.8 82.3 82.0 76.1 73.8 4.63 79.7 6. rye/ser 87.1 82.8 80.0 72.3 67.7 7.88 78.0 7. rye/vet 87.7 83.5 77.8 71.6 73.1 6.80 78.7 8. oat/tri 82.3 81.9 79.6 80.1 75.1 2.87 79.8 9. oat/ser 86.1 82.2 83.6 79.1 77.0 3.61 81.6 10. oat/vet 84.0 81.9 76.9 81.3 78.4 2.84 80.5 11. tri/ser 80.4 78.1 79.3 76.1 75.2 2.17 77.8 12. tri/vet 82.7 77.5 80.7 70.2 74.3 5.00 77.1

STD 2.57 1.98 2.39 3.52 3.04 2.22

Table 20: The mean monthly and mean seasonal in vitro organic matter digestibility (IVOMD) (%) of different annual winter producing pasture crops planted during May 2005.

Treatment May Jun Jul 05 Jul 6 Sep 10 Oct 25 Nov STD mean

1. rye 83.3 82.5 76.6 73.2 4.83 78.9 2. oat 86.8 83.2 83.8 73.1 5.96 81.7 3. tri 79.7 76.2 76.0 75.3 1.97 76.8 4. rye/oat 85.6 81.4 78.0 71.3 6.04 79.1 5. rye/tri 81.5 79.2 80.0 72.0 4.23 78.2 6. rye/ser 83.3 81.1 76.2 74.7 4.05 78.9 7. rye/vet 82.8 81.8 78.0 72.6 4.62 78.8 8. oat/tri 83.1 83.3 82.5 74.3 4.35 80.8 9. oat/ser 82.3 85.3 80.6 71.8 5.80 80.0 10. oat/vet 83.6 83.4 79.8 74.9 4.08 80.4 11. tri/ser 82.5 79.0 76.3 na 3.11 79.3 12. tri/vet 79.0 76.1 79.8 71.6 3.71 76.6

STD 2.16 2.89 2.56 1.44 1.50

na = not available

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The evaluation of methods to determine herbage biomass and botanical composition of mixed species beef pastoral systems.

Vermeulen-Fenthum S1&2

, PR Botha1, R Meeske

1 & HA Snyman

2

1Department of Agriculture Western Cape, Outeniqua Research Farm, P.O. Box 249, George, 6530, South Africa 2Department of Animal, Wildlife and Grassland Science, University of the Free State,

P.O. Box 339, Bloemfontein, 9300, South Africa 1. Introduction

South Africa‟s Western Cape region has the potential to produce efficient forage for beef cattle consumption (Botha 2009). Most of the studies at Outeniqua Research Farm on pastures for beef cattle concern the ideal pastures that should be sown, or the pastures that are present on the research station soon after those mixtures have been sown. However, this large volume of scientific information is of little value if one cannot monitor the pasture parameters. Key pasture parameters is herbage biomass and botanical composition. Estimation of herbage biomass is useful to: (i) determine stocking rates, (ii) evaluate different pasture mixtures, (iii) more effectively manipulate pasture production and botanical composition, (iv) estimate fertilization needs and costs and (v) calculate return on investment. The botanical composition of vegetation, especially in mixed pastoral systems, is also a primary determinant of forage supply because plants species generally vary widely in their productivity, acceptability, digestibility and nutrient content.

There are a variety of methods, both destructive and non-destructive in nature, to estimate herbage biomass and botanical composition (Cook & Stubbendieck 1986). All these methods have benefits and drawbacks and vary in their overall level of difficulty. Researchers and farm managers should be aware of their existence, applicability and limitations. The standard for most scientific research for assessing herbage biomass and botanical composition is to clip, separate, dry and weigh samples of a known area. Many researchers agree that clipping provides the most accurate measurements of herbage biomass and botanical composition (Benkobi et al. 2000; Holecheck et al. 2001). However, for many farm managers destructive sampling is not a practical tool because of the money and time investment required for accurate estimates. Faster methods that require less time and labor would help farm managers to monitor herbage biomass and botanical composition in pastures on a daily basis. Researchers have investigated and proposed a number of non-destructive methods over the years (Haydock & Shaw 1975; Murphy et al. 1995; Harmoney et al. 1997; Virkajarvi 1999; Benkobi et al. 2000; Sanderson et al. 2001). Non-destructive methods use a double sampling function by developing a regression relationship of herbage biomass or botanical composition to predictive variables such as height, leaf area, vegetation density, age cover or visual obstruction through a small amount of destructive sampling (Cochran 1977). Among these non-destructive methods are the comparative yield method, the measuring stick and the pasture plate meter for determining herbage biomass and the dry-weight-rank method for determining botanical composition. The objective of our study were to (i) evaluate these four simple, cost-effective methods for determining herbage biomass or botanical composition on mixed

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species pastoral systems for beef cattle and (ii) to identify the method, if any, that would be most reliable in each particular system.

2. Methods The study was conducted at Outeniqua Research Farm near George, which forms part of Department Agriculture Western Cape, South Africa. The farm lies at 201 m above sea level and extends from latitudes 33°58‟38‟‟ south and longitudes 22°25‟16‟‟ east. The area has a mean annual rainfall (35 years) of 729 mm and a mean minimum and maximum air temperatures varying between 7°C – 15°C and 18° - 25°C respectively (Agronet Weather Data Basis 2002). Approximately twenty-four hectares of existing non-irrigated kikuyu / taaipol (Eragrostis plana) pastures were divided into twenty-four paddocks. The twenty-four paddocks were divided into six blocks consisting of four experimental paddocks. Four different pasture treatments were randomly allocated to the experimental paddocks in each block, resulting in six replications for each treatment. Treatment I and II consisted of annual ryegrass, Bromus (Bromus wildenowii) and birdsfoot trefoil (Lotus corniculates) planted into kikuyu / taaipol pastures at 15 kg ha-1, 20 kg ha-1, 4 kg ha-1, respectively, during May 2008 using the mulcher or the hand broadcasting method. Treatment III consisted of perennial ryegrass, cocksfoot (Dactylis glomerata), fescue (Festuca arundinaceae) and white clover (Trifolium repens) planted at 5 kg ha-1 each with a mulcher-planter combination. Treatment IV consisted of fescue planted into kikuyu / taaipol pastures at 20 kg ha-1. Table 1 describes the cultivars, species, seeding densities and over-sowing methods used in the beef pastoral systems. Fertilizer was applied to raise the soil phosphorus level to 35 mg kg-1, potash level to 80 mg kg-1 and the pH (KCl) to 5.5. Treatments were top dressed four times a year with nitrogen at 50 kg N ha-1. Nguni X Jersey crossbred oxen and heifers grazed for seven days on each paddock, resulting in a thirty-five grazing day cycle.

The comparative yield method (CYM), measuring stick (MS), pasture plate meter (PPM) and dry-weight-rank (DWR) method were evaluated on the four different beef pastoral treatments, sampled on eighteen dates between August 2008 and April 2009. Sampling took place one day prior to the cattle entering the paddock. In each sampled paddock, locations for measurements were selected approximately at random by tossing a metal quadrate, measuring 0.5 m x 0.5 m (0.25 m2), sixteen times into the paddock. An area was rejected only if the quadrate landed in animal manure. Al measurements in the field were made in order from least to most destructive (CYM, DWR, PR, PPM, clipping of samples) to minimize errors that arise from manipulating the vegetation within the quadrate. At each sampled quadrate, herbage biomass and botanical measurements were taken using the following procedure.

2.1 Herbage biomass Sward height was determined by measuring the tallest part of the herbage that touched the MS at each of the four corners and in the middle of the quadrate. In total five height measurements were taken in each quadrate. A mean value from the five measurements, representing the value for the quadrate was used for regression analysis. Furthermore, herbage biomass in each quadrate was visually estimated, using the CYM (Haydock & Shaw 1975). Herbage biomass rating ranged from standard one to standard five, where standard one represented a typically low biomass quadrate area, standard five a typically high biomass quadrate area, and standard two, three and four intermediate biomasses. A measurement of compressed sward height using the PPM

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was also taken at the center of each quadrate. The Filip‟s folding PPM, consisting of a shaft and a circular metal plate with a diameter of 0.098 m2 and an overall mass of 1.014 kg, was used for experimental purposes. When taking measurements the shaft were held vertically and placed softly in the grass. The distance between the plate and the soil surface, a measure of the height of the herbage, were read on the marked part of the shaft. The total herbage biomass in the quadrate was determined by harvesting the herbage to a height of 3 cm with hand clippers. Clipped herbage was dried at 60ºC for at least 72 h before being weighed dry to the nearest gram. On each sampling date, the herbage biomass data consisted of three estimation data sets and a validation data set. Herbage biomass estimated by each method was compared with the herbage biomass derived from hand-clipped samples for each sampled paddock. 2.1 Botanical composition For each sampled quadrate the quadrate were ranked by the DWR method („t Mannetjie & Haydock 1963). The three most abundant species in each quadrate were given a rank of one, two or three (one indicating the most abundant). If only one species were present, all three species ranks were given to that species. If one species contributed more than 85% of the standing herbage in a quadrate, that species were given both rank one and two and the second most abundant species were given rank three. Rankings were converted to dry weight species composition by multiplying the proportion of occurrences of each rank for species by multipliers of 0.70, 0.21 and 0.09 for the first, second and third ranked species respectively („t Mannetjie & Haydock 1963). Quadrates were clipped and samples were hand separated into different species. Individual species were oven dried at 60ºC for at least 72 h before being weighed. True species composition was assigned to the known weights. Percentage DWR of each species was compared to the true percentage species composition. 3. Results 3.1 Herbage biomass Table 2 shows the r2-values between herbage biomass estimated through the three non-destructive methods (PPM, CYM, MS) and herbage biomass determined through clipping. R2-values ranged between 0.5 and 0.84. For treatment I, II and III the PPM resulted in the highest r2-values. For treatment IV the MS resulted in the highest r2-value. 3.2 Botanical composition Table 3 shows the r2-values between the percentage species estimated through the DWR method and the true species values determined through clipped and separated samples. Dominant species were kikuyu and ryegrass and/or taaipol in treatment I, II and III and kikuyu in treatment IV for the study period (Botha 2009). The largest difference between the estimated species percentage and the true species percentage were for treatment III. 4. Conclusion 4.1 Herbage biomass

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All three methods studied were quick and easy to use. However, none of these non-destructive methods were accurate or precise, and error levels ranged from 16% - 25%. Sanderson et al. (2001) calculated that economic analysis of error levels indicated that an error level of <10% is necessary to justify a farmers investment in the labor and tools for measuring herbage biomass on pastures. This study demonstrated how difficult it is to find an accurate, consistent method for predicting herbage biomass in mixed species pastures for beef cattle. We found that we were not able to identify a method that was consistently accurate that could be recommended for making herbage biomass estimates in any of these treatments. Each method evaluated has to be calibrated for each specific sampled date and paddock. The only way of estimating herbage biomass accurately for these treatments will involve the paradox of taking more samples for calibrations than would be needed for destructive sampling process itself. Therefore, to estimate herbage biomass in mixed species pasture systems, standard quadrate harvesting remains the most reliable method, provided enough quadrates are clipped to adequately represent a given area.

Beef cattle farmers, grazing pastures consisting of mixed species swards, should also remember that the amount of herbage biomass measured is usually not all available for utilization. The main problem with determining feed available for livestock is that clipping quadrates of cultivated pastures, measure the amount of herbage biomass present at a given time. Herbage biomass is defined as “total above ground biomass of herbaceous plants regardless of grazing preference of availability” and forage is “herbage which are available and may provide food for grazing animals or be harvested for feed”. Forage is most directly related to the amount of herbage biomass measured in (near) monospecific swards. However, in mixed swards the value of forage depends largely on two factors: the botanical composition (ratio palatable versus non-palatable species) and the amount of dead material accumulated through under grazing and trampling. Documentation of sward characteristics, or the fractioning of the clipped sample into different categories can assist with this problem. So when taking measurements, remember to take these in consideration to avoid false predictions. 4.2 Botanical composition The DWR method and hand clipping gave very similar estimates of species composition in three out of four of the beef pastoral treatments, even though the multipliers used were derived from a quite different ecosystem. Kikuyu, cocksfoot, fescue and white clover were estimated with a > 40% error in trial III. Vegetation components consisting of several species such as treatment III were over under or over-estimated. This was due to a failure to adequately lump the weights of several species together when making comparison with a single species such as kikuyu or taaipol. These results are similar to those of t‟Mannetjie & Haydock (1963) and reinforce the fact that any estimating procedure requires careful systematic observer training. Species with high prevalence were well predicted; whereas species with low prevalence were either over- or underestimated. Over- or underestimation of these species were mainly due to: (i) difference in dry matter content between the different species, (ii) some of the species were more prominent to the eye than other, (iii) a constant relationship existed between species dominance and quadrate herbage biomass.

The overall r2 values for treatment I, II and IV were high and it indicates that the DWR method is an accurate method for measuring botanical composition, within these trials. It can be concluded that the DWR method is and efficient, less tedious and faster method to use than clipping and separating samples, when determining the botanical composition for these treatments.

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5. Reference

Benkobi L, DW Uresk, G Schenbeck & RM King. 2000. Protocol for monitoring standing cop in grassland using visual obstruction. Journal of Range Management. 53: 627 – 633. Botha PR, M Lombard, S Vermeulen-Fenthum & R Meeske. 2009. Production and grazing capacity of kikuyu/taaipol pasture over-sown with different mixtures of grass and legume species in a low input pasture system for beef cattle. Milk production from kikuyu over-sown with Italian, Westerwold or perennial ryegrass. The production potential of pastures for milk and beef production 2009. Outeniqua Research Farm Information Day 2009. Cochran WG. 1977. Sampling techniques. John Wiley & Sons, New York. Cook CW & J Stubbendieck. 1986. Range Research: Basic problems and Techniques. Society for Range Management. Denver Colorado. Harmoney KR, KJ Moore, JR George, EC Brummer & JR Russel. 1997. Determination of pasture biomass using four indirect methods. Agronomy Journal. 89: 665 – 672. Haydock KP & NH Shaw. 1975. The comparative yield method for estimating dry matter yield of pasture. Australian Journal of Experimental and Animal Husbandry. 15: 663 – 670. Holechek JL, M Vavra & RD Pieper. 1982. Methods for determeing the nutritive quality of range ruminant diets: A review. Journal of Animal Science. 54L 364 – 376. „t Mannetjie L & KP Haydock. 1963. The dry-weight-rank method for the botanical analysis of pasture. Journal of the British Grassland Society. 18: 268 – 275. Murphy WM, JP Silman & AD Meana Barreto. 1995. A comparison of quadrate, capacitance meter, HFRO sward stick, and rising plate for estimating herbage mass in a smooth-stalked, meadowgrass dominant white clover sward. Grass and Forage Science. 50: 452 – 455. Sanderson MA, CA Rotz, SW Fultz & EB Rayburn. 2001. Estimating forage mass with a commercial capacitance meter, rising plate meter and pasture ruler. Agronomy Journal. 93: 1281 – 1286.

Virkajarvi P. 1999. Comparison of three indirect methods for prediction of herbage mass on timothy-meadow fescue pastures. ACTA Agriculture Scandinavica. 49: 74 – 81.

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Table 1: Cultivars, species, seeding densities (kg ha–1) and over-sowing methods used

in the beef pastoral treatments (BPT).

BPT

Cultivars over-sown into

kikuyu/taaipol

Species

Seeding

density

Over-sowing

method

I Annual ryegrass cv. Energa

Lolium multiflorum

Lam var.

westerwoldicum 15

1) Broadcast

seed

Bromus cv. Matoa Bromus wildenowii 20 2) Land roller

Trefoil cv. San Gabriel Lotus corniculatus 4

II Annual ryegrass cv. Energa

Lolium multiflorum

Lam var. westerwoldicum 15

1) Broadcast

seed

Bromus cv. Matoa Bromus wildenowii 20 2) Mulcher

Trefoil cv. San Gabriel Lotus corniculatus 4 3) Roller

III

Perennial ryegrass cv.

Bronsyn Lolium perenne Lam. 5 1) Mulcher

Cocksfoot cv. Cambria Dactylis glomerata 5 2) Planter

Fescue cv. Fuego Festuca arunidnaceae 5 3) Land roller

White clover cv. Haifa Lotus hispidus 5

IV Fescue cv. Fuego Festuca arunidnaceae 20

1) Spray

herbicide

2) Planter

3) Land roller

Table 2: R2-values for each method (pasture plate meter, comparative yield method,

measuring stick) for treatment I, treatment II, treatment III and treatment IV. See

treatment specifications in table 1.

Treatment

Pasture plate meter

Comparative yield method

Measuring stick

I 0.82 0.81 0.76

II 0.75 0.71 0.55

III 0.88 0.68 0.8

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IV 0.5 0.64 0.84

Table 3: R2 - values for each species for kikuyu (treatment I, II, III, IV), taaipol (treatment

I, II, III, IV), ryegrass (treatment I, II, III, IV), bromus (treatment I, II), trefoil (treatment I,

II), cocksfoot (treatment III), fescue (treatment III, IV), and clover (treatment III); overall r2

– values for each treatment. See treatment specification in table 1.

Treatment I II III IV

Kikuyu 0.95 0.87 0.53 0.79

Taaipol 0.98 0.87 0.86 0.9

Ryegrass 0.65 0.79 0.6 N/A

Bromus 0.23 0.67 N/A N/A

Trefoil 0.86 0.79 N/A N/A

Cocksfoot N/A N/A 0.59 N/A

Fescue N/A N/A 0 0.64

Clover N/A N/A 0.05 N/A

Overall r2 value for each

treatment 0.74 0.74 0.44 0.78