Time budgets, avoidance distance scores-related behaviour and milk yield of pasture-based Jersey, Friesland and crossbred cows. by Madodana Sunson Dodzi The study was conducted at the University of Fort Hare farm to determine the time budgets, the avoidance-related behaviour variables and their relationship with milk yield in three pasturebased dairy genotypes: Jersey, Friesland and crossbreed. Twenty one clinically health dairy cows aged between 52 and 55 months, in mid lactation and comprising of seven cows from each genotype were used in the study. The time spent on different activities (grazing, lying down, standing and others) at pasture was recorded using stop watches across four seasons. The behavioural responses of the three genotypes to humans were determined by recording their avoidance distance scores (AD), exit speed (ES), pen scores (PS), pen behaviour scores (PBS), plat form scores (PLS) and the occurrence of kicking (KCK) and stepping (SPG) during milking on four consecutive days in four seasons. Time spent standing was higher (P < 0.05) for Friesland compared to Jersey and crossbred during the hot-wet season. In the cool-dry season the Jersey spent more time (P < 0.05) grazing than the other breeds. The Friesland and crossbred on the other hand devoted most of their time lying down compared to Jersey in the cool- dry season (P < 0.05). There were season differences in time spent on all activities (P < 0.05). Time spent on grazing was longest in post-rainy seasonal and lowest in hot- wet season (P < 0.05). The longest lying down period was observed in the hot-dry season and lowest in hot-wet season (P < 0.05). iii Daily milk yield Varied (P < 0.05) with genotype with the Friesland and Jersey producing higher yield than the crossbred. The highest amount was produced in hot-dry and the least in hot-wet season. Milk yield was positively correlated (P < 0.05) with lying down. Standing was negatively correlated with milk yield (P < 0.05). The Friesland had the highest avoidance distance scores (P < 0.05) and the Jersey had the lowest avoidance distance scores in all seasons. There was an association (P < 0.05) between genotype and exit speed scores, pen scores and stepping behaviour scores. The Friesland exhibited the highest exit speed scores than the other breeds. The Jersey had the lowest (P < 0.05) kicking behaviour scores. There was a relationship (r = 0.64) between avoidance distance scores and exit speed. Exit speed scores were correlated with pen score(r= 0.23). Milk yield was significant related (r= 0.17) to the occurrence of kicking behaviour. The genotypes showed different levels of sensitivity to season and milk yield was influenced by breed and season. It can be concluded that time budgets vary with season and farmers need to adopt measures that buffer the effect of season on welfare of dairy cows. It can also be concluded that avoidance distance scores differs according to genotype with Jersey being more confident to humans than other two breeds. It is therefore recommended that provision of shades or cooling mechanism should be adopted to buffer the effects of hot-wet season. Improving quality of feed during the cool-dry season may be critical for Jersey cows. Finally positive handling of the dairy cows is recommended in order to improve the welfare and milk yield of pasture based dairy cows.

No description available.

M.S.

Two experiments were conducted to study the utilization of poor quality hay by ruminants. In the first experiment, several nitrogen supplements were compared under practical conditions when fed to stocker cattle receiving a hay diet. Sixty cattle were wintered on fescue hay with one of five supplements: 1) none, 2) liquid urea-molasses supplement injected into the bales, 3) liquid-supplement self-fed in lick-tank, 4) mixture of deep-stacked broiler litter and ground corn grain and 5) soybean meal. Preliminary observations showed that the liquid supplement injected into bales was poorly distributed. Highest daily weight gains were for the animals supplemented with urea-molasses self-fed, litter or soybean meal. Compensatory gains under spring-grazing conditions subsequently suppressed these differences. Feed intake was low for all treatments. Feed efficiency was best for the soybean-meal group but feed cost per unit of gain was lowest for the broiler litter supplemented group. In a second experiment, urea and carbohydrates were supplemented to a fescue hay diet fed to lambs cannulated at the rumen, abomasum and ileum. The treatment diets were: 1) hay, alone or supplemented with 2) urea, 3) urea and molasses and 4) urea and corn. Chromic oxide and Co-EDTA were used as markers. Urea supplementation improved N retention but did not affect DM, ADF and energy digestibilities. The extent and efficiency of rumen fermentations were low, with a high methane production. Supplementation did not significantly affect the partition of digestion of DM and N along the gastro-intestinal tract. ADF digestion in the large intestine was increased by urea supplementation. Mean retention time of food along the gastro-intestinal tract was similar among treatments. / M.S.

Thesis (PhD (Agric))--University of Stellenbosch, 2005. / ENGLISH ABSTRACT: It is generally accepted that feed intake and growth (gain) are the most important economic components when calculating profitability in a growth test or feedlot. Feeding cost of animals is a major determinant of profitability in livestock production enterprises. Genetic selection to improve feed efficiency aims to reduce the cost of feeding in beef cattle production and thereby improve profitability. The objective of this study was to define a clear selection objective to enable South African beef breeders and especially the feedlot industry to select for post-weaning growth or feedlot performance and to identify factors influencing profitability in a feedlot environment. Because of the recording of individual feed intake and weight gain values in the South African Agricultural Research Councils' centralized growth tests, it was also possible to calculate a phenotypic value for feedlot profitability (R-value) for each bull tested in a centralized growth test. (Co)variances, using multitrait as well as random regression models, for and between feedlot profitability, weaning weight and other production, reproduction and efficiency traits were estimated. Residual feed intake (RFI) and feed conversion ratio (FCR) as efficiency traits were also compared to growth (average daily gain (ADG), weaning weight (WW) and shoulder height (SHD)), reproductive (scrotum circumference (SCR)) and profitability (feedlot profitability) traits measured in growth tests of young Bonsmara bulls. Consequently, a single post-weaning growth selection index value based on the economic and breeding values of different selection criteria related to feedlot profitability was composed. (Co)variance components, heritabilities and genetic correlations for and between initial weight (lW), final weight (FW), total feed intake (FI) and shoulder height (SHD) were estimated through the use of multitrait restricted maximum likelihood (REML) procedures. These breeding values (EBV s) were then used in a selection index to calculate a single economical value for each animal. This economical value is an indication of the gross profitability value or gross test value (GTV) of the animal in a post-weaning growth test. The heritability estimate of 0.36 for R-value, obtained from the multitrait analysis, shows that this trait is genetically inherited and that it can be selected for. The heritability for R-value obtained from the single trait random regression model varied between 0.57 and 0.62. The genetic correlations between the R-value and the other traits, obtained from the multitrait analysis, varied from negligible to high. The heritability estimated for FCR was 0.34 and for RFl 0.31 with a genetic correlation estimate of 0.75 between the traits. The estimated genetic correlation between profitability (R-value) and FCR and RFl were -0.92 and -0.59, respectively. The genetic correlation estimate of -0.92 between FCR and R-value is largely due to the part-whole relationship between these two traits. This is also shown in their genetic trends. The genetic correlations and expected correlated responses between RFl and FCR with R-value suggest that indirect selection for R-value through the direct selection for FCR and/or RFl will result in slower genetic progress in Rvalue than direct selection for R-value. However, where the R-value cannot be calculated and/or where direct selection for R-value is not possible, it would be better to select indirectly for R-value through the use of FCR rather than RF!. Consequently, a regression equation was developed (with an R2 of 0.82) to estimate a feed intake value for all performance-tested Bonsmara bulls which were group fed and whose feed intakes were unknown. These predicted feed intake values made it possible to calculate a feedlot or post-weaning growth profitability value (R-value) for all tested bulls even where individual feed intakes were unknown. Subsequently, an R-value for each bull was calculated in a favourable economic environment (FEE), an average economic environment (AEE) and in an unfavourable economic environment (VEE). The high Pearson and Spearman correlations between the EBV s based on AEE and the other two environments suggested that the average economic environment could be used to calculate EBVs for R-value or feedlot growth profitability. It is therefore not necessary to change the carcass, weaner or feed price on a regular basis to account for possible re-rankings based on R-value EBVs. Heritabilities for lW, FW, Fl and SHD were 0.41, 0.40, 0.33 and 0.51, respectively. The highest genetic correlations between these traits were the 0.78 (between lW and FW) and 0.70 (between Fl and FW). GTV values varied between -R192.l7 and R231.38, with an average of R9.31. The Pearson correlations between EBVs (for production and efficiency traits) and GTV range from -0.51 to 0.68. The lowest correlation (closest to zero) was 0.26 between the Kleiber ratio (KLB) and GTV. Correlations of 0.68 and -0.51 were estimated between average daily gain (ADG) and GTV and feed conversion ratio (FCR) and GTV, respectively. The heritabilities of the different traits included in the selection index suggest that it is possible to select for a GTV. The selection index can benefit feedlotting In selecting offspring of bulls with high GTV values to maximize profitability. The Pearson and Spearman correlations between the R-value EBVs and the index values (GTV) were very high (0.97). This high correlation of 97% indicates that it is not important which method is used to calculate a genetic post-weaning growth of feedlot profitability value. The selection index value is, however, more simplified than the feedlot profitability with less assumption. Therefore, it is recommended that the post-weaning selection index value be used as a selection objective in breeding programmes to improve post-weaning growth profitability rather than the more complex feedlot profitability value. / AFRIKAANSE OPSOMMING: 'N GENETIESE ANALIESE VAN DIE BIOLOGIESE EN EKONOMIESE DOELTREFFENTHEID VAN NASPEENSE GROEI IN VLEISBEESTE IN DIE VOERKRAAL: Dit word algemeen aanvaar dat voerinname en groei die twee ekonomies mees belangrike komponente in die berekening van 'n naspeense groei- of voerkraalwinsgewindheidswaarde is. Voerkostes is 'n bepalende faktor van winsgewindheid in enige lewendehawe boerderypraktyk. Seleksie om voerdoeltreffendheid te verbeter, verminder dus die voerkostes in vleisbeesproduksie en gevolglik 'n verhoging in die winsgewindheid. Die doelwit van die studie was om faktore te identifiseer wat 'n invloed op winsgewindheid in die voerkraaiomgewing het asook om 'n duidelike seleksiedoelwit te formuleer wat die Suid- Afrikaanse vleisbeesteiers en veral die voerkraalbedryf instaat sal kan stelom vir naspeense groeidoeltreffendheid ofvoerkraalwinsgewindheid te selekteer. As gevolg van die aantekening en rekordhouding van weeklikse individuele voennnames en gewigstoenames van alle prestasiegetoetsde bulle, in 'n gesentraliseerde groeitoets deur die Suid- Afrikaanse Landbou Navorsingsraad getoets, was dit moontlik om vir elk van hierdie bulle 'n fenotipiese voerkraalwinsgewindheidswaarde (R-waarde) te kon bereken. (Ko)variansies is vir en tussen voerkraalwinsgewindheid, speengewig en ander produksie-, reproduksie- en doeltreffendheidseienskappe bereken deur van meereienskap en ewekansige regressie modelle gebruik te maak. Twee doeltreffendheidseienskappe naamlik residuele voerinname (RFI) en voeromsetverhouding (FCR) is ook met groei (gemiddelde daaglikse toename (ADG), speengewig (WW) en skouerhoogte (SHD)), reproduksie (skrotumomvang (SCR)) en winsgewindheidseienskappe (voerkraalwinsgewindheid (R-waarde)) vergelyk, om sodoende te bepaal watter een die mees geskikte eienskap is om indirek vir voerkraalwinsgewindheid of groei, gebaseer op teeltwaardes en ekonomiese waardes vir die verskillende eienskappe, wat 'n invloed op naspeense groei winsgewindheid het, gestruktueer. (Ko)variansiekomponente, oorerflikhede en genetiese korrelasies vir en tussen begingewig (lW), eindgewig (FW), voerinname (FI) en skouerhoogte (SHD) is bereken deur van 'n meereienskap (REML) ontleding gebruik te maak. Hierdie teelwaardes (EBVs) is vervolgens in 'n seleksie-indeks gebruik om 'n enkele ekonomies of voerkraal-winsgewindheids seleksie-indekswaarde (GTV) vir elke dier te bereken. Hierdie ekonomiese waarde is 'n aanduiding van die bruto winsgewindheidswaarde ofbruto toetswaarde (GTV) van die dier in 'n naspeentoets. Die oorerflikheid, vanuit die meereienskapontleding vir R-waarde beraam, was 0.36. Hierdie oorerflikheid dui daarop dat die eienskap oorerflik is en dat dit wel moontlik is om daarvoor te selekteer. Die ooreflikhede van R-waarde, voorspel vanuit die enkeleienskap ewekansige regressieontleding varieer tussen 0.57 en 0.62. Die genetiese korrelasie tussen R-waarde en ander eienskappe, vanuit die meereienskap ontleding beraam, varieer tussen weglaatbaar klein tot hoog. Die oorerflikheid van FeR was 0.34 en van RFI 0.31 met 'n genetiese korrelasie van 0.75 tussen die twee eienskappe. Die genetiese korrelasie tussen R-waarde en FeR, en R-waarde en RFI was onderskeidelik -0.92 en -0.59. Die rede vir die hoë negatiewe genetiese korrelasie tussen R-waarde en FeR van -0.92 is omdat dieselfde komponente in die berekening van die twee eienskappe gebruik is. Dit word ook in die genetiese tendense weerspeël. Die genetiese korrelasies en verwagte gekorreleerde responsies tussen R-waarde en FeR, en tussen R-waarde en RFI dui daarop dat stadiger genetiese vordering verkry sal word in R-waarde deur direkte seleksie vir beide FeR en RFI as wat verkry sal word deur die direkte seleksie vir R-waarde. Wanneer 'n R-waarde egter nie bereken kan word nie of waar dit nie moontlik is om direk vir R-waarde te selekteer nie, sal vinniger genetiese vordering in R-waarde gemaak word deur die direkte seleksie vir FeR as vir RF!. 'n Regressievergelyking is geformuleer (met 'n R2 van 0.82) om vir alle prestasiegetoetsde bulle, waar bulle in 'n groep gevoer is en individuele voerinnames onbekend is, 'n voerinnamewaarde te voorspel. Hierdie voorspelde voerinnames maak dit moontlik om vir elke prestasiegetoetsde bul ,'n naspeengroei- of voerkraalwinswaarde (R-waarde) te bereken, al is hulle individuele voerinnames onbekend. Vervolgens is drie verskillende R-waarde vir vleisproduksie vir elke bul bereken naamlik, in 'n gunstige ekonomiese omgewing (FEE), 'n gemiddelde ekonomiese omgewing (AEE) en 'n ongunstige ekonomiese omgewing (VEE). Die hoë Pearson en Spearman korrelasies tussen die EBVs vir R-waarde, bereken in die AEE en die EBVs in die ander twee ekonomiese omgewings, dui daarop dat die AEE gebruik kan word om EBVs vir naspeense groeiof voerkraalwins te bereken. Dit is dus nie nodig om op 'n gereelde grondslag die karkasprys, lewendige speenkalfprys of die voerprys te verander nie. Oorerflikhede, vanuit die meereienskap ontledings VIr lW, FW, FI en SHD verkry, was onderskeidelik 0.41, 0.40, 0.33 en 0.51. Die hoogste genetiese korrelasies tussen die eienskappe was 0.78 tussen lW en FW en 0.70 tussen FI en FW. GTV indekswaardes varieer tussen -Rl92.17 en R231.38 met 'n gemiddelde waarde van R9.31. Die Pearson korrelasies tussen die EBVs van produksie- en doeltreffenheidseienskappe en GTV het tussen -0.51 en 0.68 gevarieer. Die korrelasie naaste aan zero, van 0.26, was die korrelasie tussen GTV en die Kleiber-verhouding. Die korrelasies tussen GTV en ADG, en GTV en FeR was onderskeidelik 0.68 en -0.51. Die oorerflikhede van die verskillende eienskappe wat in die seleksie-indeks ingesluit is, dui daarop dat die indekswaarde weloorerflik is en dat seleksie hiervoor wel moontlik is. Hierdie indekswaarde kan deur die voerkraaiindustrie gebruik word om nageslag van diere met hoë GTV waardes te selekteer om sodoende maksimum wins uit die voerkraai te genereer. Die Pearson en Spearman korrelasies tussen R-waarde EBVs en die indekswaardes (GTV) was besonder hoog (0.97). Hierdie hoë korrelasie dui daarop dat dit geen verskil sal maak watter een van die twee metodes gebruik word in die berekeninge van 'n naspeense groei- of voerkraalwinswaarde nie. Die seleksie-indeks metode is egter minder gekompliseerd met minder aannames as in die geval van die rekeningkundige fenotipiese benadering (R-waarde). As gevolg hiervan, word die naspeense seleksie-indeks waardes (GTV) aanbeveel om te gebruik as 'n teeldoelwit in telingsprogramme om naspeense groei- of voerkraaiwins geneties te verbeter, eerder as die meer gekompliseerde fenotipiese voerkraaiwins (R-waardes) metode.

A total of 114,351 Holstein first lactation records collected by the Quebec Dairy Herd Analysis Service (DHAS-PATLQ) between September, 1979 and January, 1994 were used to study the effects of adjusting records for linear and quadratic effects of 90- and 305-d feed intake measures (total energy, total protein and total dry matter) on estimation of heritabilities of and genetic correlations among yield and composition traits. Genetic parameters of feed intake measures, relationships between feed intake and age and weight at calving, and feed conversion efficiency traits were also examined in a series of studies. A sire model fitted by REML estimated heritabilities of 305-d milk, fat and protein yields, fat and protein percents as .45 +/- .04, .48 +/- .04, .44 +/- .03, .92 +/- .06, and .88 +/- .05, respectively. Correction of 305-d records for differences among cows in feed intake levels reduced heritabilities of milk, fat and protein yields to .35 +/- .03, .52 +/- .04, and .38 +/- .03, respectively. Heritabilities of composition traits (fat and protein percents) remained unchanged. Genetic and phenotypic correlations for yield traits were also reduced (48--170%, and 16--51%, respectively) which may indicate that genetic associations between yield traits are less than what we believed them to be. Heritabilities of 305-d total energy, total protein, total DM intake, grain energy, grain protein, grain DM, base energy, base protein, and base DM were .30 +/- .03, .24 +/- .02, .35 +/- .03, .23 +/- .02, .23 +/- .02, .23 +/- .02, .31 +/- .03, .26 +/- .02, and .40 +/- .03, respectively. Genetic correlations between feed intake measures were very high; they were approaching unity in some cases. Therefore, any one of these feed intake measures can represent the others. A multi-trait REML analysis estimated heritabilities of age and weight at first calving as .11 +/- .01 and .37 +/- .03, respectively. Age at calving was negatively associated with yield traits and with total e

Excessive dietary protein may affect MP use because of energetic costs of excreting excess N. Amino acids also may influence post-ruminal digestion. Therefore, two experiments were designed to evaluate the effects of MP intake and post-ruminal flow of AA on growth performance and pancreatic digestive enzymes. In experiment 1, treatments supplied different amounts of MP intake to cattle and the effects on growth performance and feeding behavior were evaluated. In experiment 2, duodenal infusion of glutamate or casein was examined and the effects on pancreatic enzymes were measured. Experiment 1 suggests that feeding steers 906 g MP/d in finishing diets supplied enough MP for the greatest growth performance and carcass characteristics. Interestingly, MP intake caused different responses on feeding behavior with greater effects on steers fed 626 and 1444 g MP/d. In experiment 2, casein infusion increased α-amylase activity but not trypsin activity. Glutamate did not influence pancreatic digestive enzymes.

No description available.

Equations to predict daily dry matter intake (DMI) of individual animals were developed with 118 Holstein heifers fed totally mixed rations (TMR). Animals grouped according to body weight (136, 227, 317 kg) were fed TMR (corn silage, ground hay, high moisture corn, soybean meal) once daily for 28 days. Rations were balanced to mean body weight according to National Research Council (NRC) recommendations for protein, vitamins and minerals, and to 85, 95, 105, and 115% of recommendation for energy. Independent variables were body weight (BWT, kg/day) daily body weight gain (GAIN, kg), environmental temperature (AMBT, °C), ration acid detergent fiber (ADF, percent of dry matter), neutral detergent fiber (NDF, percent of dry matter), net energy for maintenance and gain (NEM, NEG, megacalories), total digestible nutrients (TDN, percent of dry matter), and bulk density (BULK, g/ml as fed). Squared terms, appropriate interaction terms, and metabolic body weight (MBWT, kg^.75) were included in the model. Stepwise regression was utilized to generate two models, simplified and expanded. Simplified model was: DMI (kg/day) = -29.86 + (-.54E-05 * BWT²) + (.157 * MBWT) + (2.090 * GAIN) + (-.118 * GAIN²) + (.730 * TDN) + (-.005 * TDN²) + (-.001 * BWT * GAIN) + (-.019 * TDN * GAIN); n = 4797, r² = .59, s_y.x = 1.18. Expanded model was: DMI (kg/ day) = -1906.91 + (-0.04 * BWT) + (0.37 * MBWT) + (32.36 * ADF) + (2305.51 * NEM) + (-664.06 * NEG) + (-0.08 * AMBT) + (-0.13 * ADFSQ) + (-637.68 * NEMSQ) + (42.31 * NEGSQ) + (-5.35 * BULKSQ) + (0.001 * AMBTSQ) + (-1.56E-04 * BWT * ADF) + (8.873E-05 * BWT * AMBT) + (246.30 * NEM * NEG) + (-21.30 * NEM * ADF) + (7.83 * NEG * ADF) + (0.04 * NEG * AMBT) + (0.01 * GAIN * ADF) + (-0.01 * GAIN * AMBT); n = 4429, r² = .65, s_y.x = 1.09. Predicted intakes by simplified equation agree with those of NRC at TDN recommended by NRC and .7 kg/day. Computerized ration formulation systems were developed using simplified model. Expanded model requires further refinement prior to incorporation into a ration formulation system. / Ph. D.

No description available.