Geoff Simm

Developing breeding schemes to assist mitigation of greenhouse gas emissions.

Genetic improvement of livestock is a particularly effective technology, producing permanent and cumulative changes in performance. This paper highlights some of the options for including mitigation in livestock breeding schemes, focusing on ruminant species, and details three routes through which genetic improvement can help to reduce emissions per kg product via: (i) improving productivity and efficiency, (ii) reducing wastage in the farming system and (iii) directly selecting on emissions, if or when these are measurable. Selecting on traits that improve the efficiency of the system (e.g. residual feed intake, longevity) will have a favourable effect on the overall emissions from the system. Specific examples of how genetic selection will have a favourable effect on emissions for UK dairy systems are described. The development of breeding schemes that incorporate environmental concerns is both desirable and possible. An example of how economic valuation of public good outcomes can be incorporated into UK dairy selection indices is given. This paper focuses on genetic selection tools using, on the whole, currently available traits and tools. However, new direct and indirect measurement techniques for emissions will improve the potential to reduce emissions by genetic selection. The complexities of global forces on defining selection objectives are also highlighted.

The effect of improving cow productivity, fertility, and longevity on the global warming potential of dairy systems

This study compared the environmental impact of a range of dairy production systems in terms of their global warming potential (GWP, expressed as carbon dioxide equivalents, CO(2)-eq.) and associated land use, and explored the efficacy of reducing said impact. Models were developed using the unique data generated from a long-term genetic line × feeding system experiment. Holstein-Friesian cows were selected to represent the UK average for milk fat plus protein production (control line) or were selected for increased milk fat plus protein production (select line). In addition, cows received a low forage diet (50% forage) with no grazing or were on a high forage (75% forage) diet with summer grazing. A Markov chain approach was used to describe the herd structure and help estimate the GWP per year and land required per cow for the 4 alternative systems and the herd average using a partial life cycle assessment. The CO(2)-eq. emissions were expressed per kilogram of energy-corrected milk (ECM) and per hectare of land use, as well as land required per kilogram of ECM. The effects of a phenotypic and genetic standard deviation unit improvement on herd feed utilization efficiency, ECM yield, calving interval length, and incidence of involuntary culling were assessed. The low forage (nongrazing) feeding system with select cows produced the lowest CO(2)-eq. emissions of 1.1 kg/kg of ECM and land use of 0.65 m(2)/kg of ECM but the highest CO(2)-eq. emissions of 16.1t/ha of the production systems studied. Within the herd, an improvement of 1 standard deviation in feed utilization efficiency was the only trait of those studied that would significantly reduce the reliance of the farming system on bought-in synthetic fertilizer and concentrate feed, as well as reduce the average CO(2)-eq. emissions and land use of the herd (both by about 6.5%, of which about 4% would be achievable through selective breeding). Within production systems, reductions in CO(2)-eq. emissions per kilogram of ECM and CO(2)-eq. emissions per hectare were also achievable by an improvement in feed utilization. This study allowed development of models that harness the biological trait variation in the animal to improve the environmental impact of the farming system. Genetic selection for efficient feed use for milk production according to feeding system can bring about reductions in system nutrient requirements, CO(2)-eq. emissions, and land use per unit product.

Responses to selection for lean growth in sheep

This paper reports the selection responses achieved, and related results, following 9 years of index selection for lean growth in Suffolk sheep. The breeding goal of the index used comprised carcass lean weight and carcass fat weight at a constant age, with relative economic values of + 3 and ‐1 per kg. The selection criteria were live weight (LWT), ultrasonic fat depth (UFD) and ultrasonic muscle depth (UMD) adjusted to a constant age of 150 days. By year 9, responses in LWT, UFD and UMD in both sexes, as judged by the divergence between selection and control line performance, amounted to 4·88 kg, ‐1·1 mm and 2·8 mm respectively ; these responses are between 7 and 15% of the overall means of the traits concerned. Although selection was originally on index scores based on phenotypic records, the retrospective analyses reported here used the mixed model applications of residual maximum likelihood to estimate parameters and best linear unbiased prediction to predict breeding values. The statistical model comprised fixed effects plus random effects accounting for direct additive, maternal additive and temporary environmental variation. Estimated genetic trends obtained by regressing estimated breeding values on year of birth were similar to annual responses estimated by comparing selection and control line means. Estimates of direct heritabilities were 0·054, 0·177, 0·286, 0·561 and 0·410 for birth weight (BWT), weaning weight (WWT), LWT, UFD and UMD respectively. Corresponding estimates of maternal heritabilities were 0·287, 0·205, 0·160, 0·083 and 0·164. Phenotypic correlations between all pairs of traits were positive and usually moderately high. There were low negative direct additive correlations between BWT and WWT, and between BWT and LWT, but higher positive maternal additive correlations between all other pairs of weight traits.

Multi-trait selection indexes for sustainable UK hill sheep production

Three selection indexes for the UK hill sheep sector are derived to suit the extremes of hill production systems. These are: (i) intensive, where all surplus lambs not required for breeding are finished for slaughter, (ii) extensive, where all surplus ‘store’ lambs are sold to other farmers for finishing, and (iii) semi-intensive, which is intermediate between the two extremes, i.e. farms finish some lambs for slaughter and sell others as store lambs. Parameters for 12 breeding goal and index traits were estimated using a total of 3962 lamb records and 5944 ewe lambing records from Scottish Blackface sheep on two Scottish Agricultural College experimental hill farms. The breeding goal comprised carcass, maternal and survival traits. The evaluation of these indexes showed that improvements in maternal traits are possible, along with more modest improvements in carcass quality traits. Responses to selection are expected to be lower for the extensive farm in general, compared with the intensive farm. Evaluations of alternative indexes show that an index using measurements of fat and muscle on ewes rather than on lambs may be more cost-effective to implement in practice, compared with the original index, although this change results in a higher (i.e. undesirable) gain in mature size. Sensitivity analyses showed that in general, the indexes are robust to changes in economic values and to changes in heritability estimates.

Quantitative trait loci for chemical body composition traits in pigs and their positional associations with body tissues, growth and feed intake

In this study, quantitative trait loci (QTL) for chemical and physical body composition, growth and feed intake in pigs were identified in a three-generation full-sib population, developed by crossing Pietrain sires with a commercial dam line. Phenotypic data from 315 F(2) animals were available for protein and lipid deposition measured in live animals by the deuterium dilution technique at 30-, 60-, 90-, 120- and 140-kg body weight. At 140-kg body weight, carcass characteristics were measured by the AutoFOM grading system and after dissection. Three hundred and eighty-six animals from 49 families were genotyped for 51 molecular markers covering chromosomes SSC2, SSC4, SSC8, SSC9, SSC10 and SSC14. Novel QTL for protein (lipid) content at 60-kg body weight and protein (lipid) accretion from 120 to 140 kg were detected on SSC9 near several previously detected QTL for lean and fat tissue in neck, shoulder and ham cuts. Another QTL for lipid accretion was found on SSC8, closely associated with a QTL for intramuscular fat content. QTL for daily feed intake were detected on SSC2 and SSC10. The favourable allele of a QTL for food conversion ratio (FCR) on SSC2 was associated with alleles for increased lean tissue and decreased fat tissue. Because no QTL for growth rate were found in the region, the QTL for FCR is most likely due to a change in body composition. These QTL provide insights into the genomic regulation of chemical or physical body composition and its association with feed intake, feed efficiency and growth.

Risk factors for culling in Holstein-Friesian dairy cows

Risk factors associated with voluntary and involuntary culling within a Holstein-Friesian dairy cow research herd were identified. Data were studied from 3498 completed lactations from the Langhill Holstein-Friesian dairy herd between January 1990 and June 2008. During this period the cows were based on two different farms in Scotland. The culling rate of the milking herd was approximately 25 per cent per annum. Approximately 68 per cent of cows culled were classified as involuntary. The association between different risk factors and the incidence of culling was investigated using a general linear mixed model. Of the 838 cows culled, 59 per cent were culled before the fourth lactation. Culling was associated with cows that had an assisted calving (P<0.01), aborted (P<0.01) and/or suffered from mastitis (P<0.05). Cows that were culled were also more likely to be older cows (P<0.01), have a low number of milking days (P<0.001) and/or a greater number of days from calving to conception (P<0.01). Culling was also associated with conception failure (r=0.752, P<0.001). Further work might help reduce the number of animals culled involuntarily, by identifying key factors associated with the incidence of an assisted calving, abortion and mastitis, and improving milking and fertility performance using detailed data from the Langhill herd.

Effect of breeding for milk yield, diet and management on enteric methane emissions from dairy cows

Enteric methane production from livestock is an important source of anthropogenic greenhouse gas emissions. The aim of the present study was to (1) assess the effect of long-term breeding for kilograms of milk fat plus protein production and (2) investigate the influence of parity, genetic line and diet on predicted enteric methane emissions of Holstein Friesian dairy cows. Analyses were based on 17 years of experimental data for lactating and dry cows, housed and at pasture. Restricted maximum likelihood (REML) was used to assess the effects of parity, genetic line and diet on the predicted enteric methane output of lactating and dry cows. A non-linear equation based on metabolisable energy intake (MEI) was used to predict daily enteric methane output. The present study found that selection for kilograms of milk fat plus protein production, zero-grazing low-forage diets and maintaining persistently high-yielding older cows can reduce a cow’s enteric methane emissions per kilogram milk by up to 12%, on average. Comparing the first 5 years to the most recent 5 years of the study period showed that large savings of 19% and 23% in enteric methane per kilogram milk were made in cows selected for milk fat plus protein or selected to remain close to the average genetic merit for milk fat plus protein production for all animals evaluated in the UK, respectively. Additionally, management to minimise the length of the drying-off period can help reduce enteric methane emissions during a cow’s lactation period.

Relationships between quantitative and reproductive fitness traits in animals

The relationships between quantitative and reproductive fitness traits in animals are of general biological importance for the development of population genetic models and our understanding of evolution, and of great direct economical importance in the breeding of farm animals. Two well investigated quantitative traits—body weight (BW) and litter size (LS)—were chosen as the focus of our review. The genetic relationships between them are reviewed in fishes and several mammalian species. We have focused especially on mice where data are most abundant. In mice, many individual genes influencing these traits have been identified, and numerous quantitative trait loci (QTL) located. The extensive data on both unselected and selected mouse populations, with some characterized for more than 100 generations, allow a thorough investigation of the dynamics of this relationship during the process of selection. Although there is a substantial positive genetic correlation between both traits in unselected populations, caused mainly by the high correlation between BW and ovulation rate, that correlation apparently declines during selection and therefore does not restrict a relatively independent development of both traits. The importance of these findings for overall reproductive fitness and its change during selection is discussed.

Assessing beef carcass tissue weights using computed tomography spirals of primal cuts

More than 800 beef primal cuts from 44 Aberdeen Angus and Limousin-cross steers carcasses were scanned using spiral computed tomography (CT) and dissected. Thresholds for the segmentation of fat, muscle and bone in the CT spirals were estimated with the objective of assessing the weight of these tissues in the primal cuts and in the entire carcasses. Thresholds were estimated using half of the dataset (DBE) and then validated in the other half (DBV). Automatic image analysis procedures were used to assess tissue weights. The R(2) of the regression between primal tissue weight by dissection and CT were high in both datasets for fat (DBE, 0.89; DBV, 0.92), muscle (DBE, 0.99; DBV, 0.99) and bone (DBE, 0.95; DBV, 0.97). The estimation of total carcass tissue weights were also very accurate for the three tissues (R(2) values of 0.95 to 0.96), indicating that CT scanning may deliver very accurate information on beef carcass composition faster and with lower cost than physical dissection and without damaging or depreciating the primal joints.

Predicting beef carcass composition using tissue weights of a primal cut assessed by computed tomography

The potential of the composition of the forerib measured by X-ray computed tomography (CT) as a predictor of carcass composition was evaluated using data recorded on 30 Aberdeen Angus and 43 Limousin crossbred heifers and steers. The left sides of the carcasses were split into 20 cuts, which were CT scanned and fully dissected into fat, muscle and bone. Carcass and forerib tissue weights were assessed by dissection and CT. Carcass composition was assessed very accurately by CT scanning of the primal cuts (adj-R2 = 0.97 for the three tissues). CT scanning predicted weights of fat, muscle and bone of the forerib with adj-R2 of 0.95, 0.91 and 0.75, respectively. Single regression models with the weights of fat, muscle or bone in the forerib measured by CT as the only predictors to estimate fat, muscle or bone of the left carcass obtained by CT showed adjusted coefficients of determination (adj-R2) of 0.79, 0.60 and 0.52, respectively. By additionally fitting breed and sex, accuracy increased to 0.85, 0.73 and 0.67. Using carcass and forerib weights in addition to the previous predictors improved significantly the prediction accuracy of carcass fat and muscle weights to adj-R2 values of 0.92 and 0.96, respectively, while the highest value for carcass bone weight was 0.77. In general, equations derived using CT data had lower adj-R2 values for bone, but better accuracies for fat and muscle compared to those obtained using dissection. CT scanning could be considered as an alternative very accurate and fast method to assess beef carcass composition that could be very useful for breeding programmes and research studies involving a large number of animals, including the calibration of other indirect methods (e.g. in vivo and carcass video image analysis).