Strategies for Genetic Improvement of Dairy Cattle Under Low, Medium and High Production Systems in Kenya

Abstract

<p>This thesis investigates and develops breeding strategies to maximise genetic improvement of dairy cattle in different production systems in Kenya. The research questions central to the study were: (1) is there heterogeneity of variance and genotype by environment interaction between the dairy production systems in Kenya?; (2) is the relative economic importance of the breeding objectives traits the same in different production systems?; (3) which selection strategies maximise genetic gain in the overall breeding goal of dairy production systems in Kenya.</p> <p>Dairy herds in Kenya vary considerably based on the level of input and output, and in the use of breeds and crosses in different systems. Data from multi-breed cows from Dairy Recoding Services of Kenya (54,775 records) were used in this study to classify environments based on production level and evaluate the performance of different genotypes within and across these environments. Herds were grouped into low, medium and high production system environments using mean 305 days milk yield and the K-means clustering method. An animal model was used to estimate variance components and genetic parameters for milk production and fertility traits within and between production systems. Genetic groups were fitted to account for the multi-breed cows and their crosses. To account for the small herd sizes contemporary group effects were fitted as random effects. Genetic correlations between traits under different production systems were used to determine the presence of genotype by environment interaction. This study found that variance components were heterogeneous across the production systems. Genetic correlations between traits in the low, medium and high production systems also suggested that sires should be selected based on genetic evaluation accounting for genotype by environment between production systems.</p> <p>Further analyses were performed to estimate genetic parameters for milk yield along the lactation trajectory and for lactation persistency (how flat the lactation curve is after the peak yield) in the first four lactations under the three production systems. The genetic association between age at first calving and test-day milk yield in different production systems was also estimated to provide knowledge that can be used to optimize the genetic improvement of milk yield and reproductive efficiency. This was done using multi-variate random regression models. This evaluation produced several key findings: 1) variance components were heterogeneous across the production systems, 2) test-day milk yield and lactation persistency were heritable and therefore genetic improvement can be realised through selection, 3) genetic correlations between test-day milk yield within lactations decreased with increase in time interval, 4) genetic improvement of later lactations could be achieved by selection in the early lactations, 5) sires may be re-ranked between production systems and 6) test-day milk yield and age at first calving are positively correlated (low to medium) at the beginning of the lactation but the correlation decreases along the lactation. This confirms the earlier recommendation that sires should be selected based on a genetic evaluation which accommodates genotype by environment between production systems.</p> <p>A deterministic bio-economic model was developed to estimate economic values for lactation milk yield, fat yield, age at first calving, calving interval, mature weight and survival under low, medium and high production systems. Economic weights were derived for each trait in the three production systems by discounting the economic values using diffusion coefficients. To allow comparison of the potential economic response in traits the economic weights were standardised using the genetic standard deviations. Traits were reranked across the production systems in order of their economic importance. After performing some sensitivity tests economic values were found to be robust to changes in input and output prices, changes in feeding strategies and milk and surplus heifer marketing strategies. Inclusion of lactation milk yield, fat yield, age-at-first calving, calving interval, mature weight and survival rate is recommended to develop breeding objectives for dairy cattle in Kenya. Selection should also be based on selection indices using estimated breeding values which account for genotype by environment interaction between production systems.</p> <p>A deterministic simulation using multi-trait selection index theory was used to predict response to selection for alternative selection strategies to maximise genetic gains in the overall breeding objective for dairy cattle under low, medium and high production systems in Kenya. Five different breeding strategies were evaluated including: 1) a breeding program with genetic evaluation and selection of candidate bulls in the high production system only (OPT-S); 2) one joint breeding program with genetic evaluation and selection of bulls in three environments (OPT-J); 3) three environment-specific breeding programs each with an independent genetic evaluation and selection of bulls within each environment (OPT-3); 4) a modified version of OPT-3 simulated to evaluate the effect of using phenotypic and genomic information (OGS-3); and 5) a modified version of OGS-3 using genomic information only (GS-3). The genetic gain in the overall objective was used to evaluate the breeding strategies with varying amounts of information on own performance and relatives.</p> <p>The OGS-3 strategies generated the highest overall economic gain with a large nucleus (5,000) while the OPT-J strategy generated the highest overall economic gain with smallsized nucleus (500).. OPT-J strategy produced the highest economic gain in the overall breeding objective among the strategies without genomic information, while the OPT-S strategy produced lower overall economic gain compared to other strategies. Genomic selection could generate higher responses compared to the conventional breeding strategies due to a reduced generation interval and higher accuracy of selection with a bigger reference population. This study, therefore, concludes that the dairy cattle industry in Kenya would benefit from a breeding strategy accounting for the differences between the production systems and genotype by environment between them.</p>