Call number: LD2668 .T4 1964 W17 / Master of Science

Call number: LD2668 .T4 1965 H376 / Master of Science

Digitized by Kansas Correctional Industries

No description available.

Call number: LD2668 .T4 1978 B83 / Master of Science

No description available.

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.

No description available.

The Canadian agricultural sector was recognised as a potential seller of carbon offset credits in the domestic emission trading system. A number of beneficial management practices may reduce GHG emissions while increasing production efficiency and profitability of agricultural activities. A contingent valuation survey was used to estimate the carbon offset price at which feedlot operators in Ontario would adopt two management practices that reduce GHG emissions: adding roasted soybean seeds to a cattle diet and increasing the intensity of feedlot operations. The value elicitation questions to estimate the mean WTA compensation were designed using a multiple bounded discrete choice format developed by Welsh and Poe (1998). / It was estimated that at a carbon offset price of $ 25.14/t CO2 e provided enough incentive for feedlot operators to intensify their operations and a price of $ 109.51/t CO2e to change their feeding strategies. The mean willingness to accept a cost to change a conventional practice to a greenhouse gas emissions reducing practice was estimated to be 62% of the carbon revenue. The regression analysis demonstrated that producers' willingness to accept compensation was influenced by the individual's characteristics, farm structure variables, and practice attributes. Policy makers may use these results in the design of greenhouse gas reduction strategies for the beef sector.