Genetic control of greenhouse gas emissions

Climate change is a growing international concern and it is well established that the release of greenhouse gases (GHG) is a contributing factor. The European Union has committed itself to reduce its GHG emissions by 20% by the year 2020 relative to 1990 levels. Of the various GHG produced by ruminants, enteric methane (CH4) is the most important contributor, with a global warming potential 25 times that of carbon dioxide (CO2). Recent studies have shown that natural variation among animals exists in enteric CH4 emission. This variation can be used to breed cows with low CH4 emission, with expected progress per generation in terms of CH4 reduction ranging from 10 to 20%. Successful animal breeding strategies require measurements on a large population of animals. With the recent successful incorporation of genomic information into breeding schemes the reliance on very large populations of phenotyped animals is relaxed. The rumen is the major site of methane production in which anaerobic archaeal microorganisms convert H2 and CO2 to CH4. Methane is a natural by-product of anaerobic respiration, produced predominantly in the rumen (~90%), and to a small extent in the large intestine (~10%). The major factors that determine methane production include the amount of feed consumed by the ruminant and the digestion of that feed. As more feed is ingested, more methane is produced, but the portion of methane per kg dry matter intake (DMI) decreases with increasing feed intake. International collaboration is essential to make progress in this area. This is both in terms of sharing ideas, experiences and phenotypes, but also in terms of coming to a consensus regarding what phenotype to collect and to select for

Improved ruminant genetics: Implementation guidance for policymakers and investors

Genetics makes use of natural variation among animals. Selecting preferred animals as parents can yield permanent and cumulative improvements in the population. More efficient animals can greatly reduce greenhouse gas emissions and feed costs. Breeding, including cross-breeding between indigenous and imported species, can also improve resilience to diseases and heat stress and increase reproductive performance

Entropy of broiler activity: individual variation and consistency

Animal behaviour is complex and comparing average levels of behavioural activities is sometimes insufficient to pick up on behavioural differences between (groups of) animals. Entropy, a measure of the randomness or regularity of time series, might help us to describe aspects of behaviour better. In this study, we determined daily entropy in individual broiler activity levels over time, based on a time series of observed activity per 15 minutes across a day, to assess individual variation and consistency in entropy of activity. Activity data for calculation of entropy were available for 79 broilers for a maximum of 21 days. We observed individual variation in entropy between broilers, but the level of entropy was not very consistent across days. The individual variation in entropy indicates potential for future research to look into whether and how entropy differences relate to other traits in broilers

Developing a French FrameNet: Methodology and First results

International audienceThe Asfalda project aims to develop a French corpus with frame-based semantic annotations and automatic tools for shallow semantic analysis. We present the first part of the project: focusing on a set of notional domains, we delimited a subset of English frames, adapted them to French data when necessary, and developed the corresponding French lexicon. We believe that working domain by domain helped us to enforce the coherence of the resulting resource, and also has the advantage that, though the number of frames is limited (around a hundred), we obtain full coverage within a given domain

Heritability of daily activity over time in broilers

Individual activity is related to the health, welfare and performance of broilers. In previous work using a radio frequency identification system, we were able to collect individual activity data over time, and activity was found to be heritable. The aim of the current study was to estimate genetic parameters for activity while taking into account the effect of age. Therefore, two repeated measurement models were fitted. The model with an intercept and slope for genetic and permanent environmental effect, and a heterogeneous residual variance, yielded the best goodness-of-fit. First results showed that daily heritability varied between 7 and 30%. The heritability was lowest at the start and at the end of the production life. This study shows potential for selection on activity in broilers. Furthermore, this study shows that activity patterns (in time) can be changed, as both the intercept and slope of activity are heritable

Early locomotor activity in broilers and the relationship with body weight gain

Fast-growing broilers are relatively inactive and this is thought to be a result of selection for high growth rates. This reduced activity level is considered a major cause of leg weakness and associated leg health problems. Increased activity, especially early in life, is suggested to have positive effects on leg health, but the relationship between early activity and growth is unclear. A clearer understanding of the relationship between activity early in life and body weight gain could help determine how selecting on increased early activity could affect body weight gain in broilers. Here, a radio frequency identification (RFID) tracking system was implemented to record daily individual broiler activity throughout life, in 5 production rounds. As mean activity levels alone do not capture the variation in activity over time, multiple (dynamic) descriptors of activity were determined based on the individual birds’ daily distances moved, focusing on the period from 0 to 15 days old. The mean, skewness, root mean square error (RMSE), autocorrelation, and entropy of (deviations in) activity were determined at the individual level, as well as the average daily gain (ADG). Relationships between activity descriptors and ADG were determined for 318 birds. Both when combining the data from the different production rounds and when taking production round and start weight into account, a negative relationship between ADG and RMSE was observed, indicating that birds that were more variable in their activity levels had a lower ADG. However, the activity descriptors, in combination with recording round and start weight, explained only a small part (8%) of the variation in ADG. Therefore, it is recommended for future research to also record other factors affecting ADG (e.g., type of feed provided and feed intake) and to model growth curves. Overall, this study suggests that increasing early activity does not necessarily negatively affect body weight gain. This could contribute to improved broiler health and welfare if selecting for increased activity has the expected positive effects on leg health

Integrating heterogeneous across-country data for proxy-based random forest prediction of enteric methane in dairy cattle

Publication history: Accepted - 9 February 2022; Published online - 26 March 2022Direct measurements of methane (CH4) from individual animals are difficult and expensive. Predictions based on proxies for CH4 are a viable alternative. Most prediction models are based on multiple linear regressions (MLR) and predictor variables that are not routinely available in commercial farms, such as dry matter intake (DMI) and diet composition. The use of machine learning (ML) algorithms to predict CH4 emissions from across-country heterogeneous data sets has not been reported. The objectives were to compare performances of ML ensemble algorithm random forest (RF) and MLR models in predicting CH4 emissions from proxies in dairy cows, and assess effects of imputing missing data points on prediction accuracy. Data on CH4 emissions and proxies for CH4 from 20 herds were provided by 10 countries. The integrated data set contained 43,519 records from 3,483 cows, with 18.7% missing data points imputed using k-nearest neighbor imputation. Three data sets were created, 3k (no missing records), 21k (missing DMI imputed from milk, fat, protein, body weight), and 41k (missing DMI, milk fat, and protein records imputed). These data sets were used to test scenarios (with or without DMI, imputed vs. nonimputed DMI, milk fat, and protein), and prediction models (RF vs. MLR). Model predictive ability was evaluated within and between herds through 10-fold cross-validation. Prediction accuracy was measured as correlation between observed and predicted CH4, root mean squared error (RMSE) and mean normalized discounted cumulative gain (NDCG). Inclusion of DMI in the model improved within and between-herd prediction accuracy to 0.77 (RMSE = 23.3%) and 0.58 (RMSE = 31.9%) in RF and to 0.50 (RMSE = 0.327) and 0.13 (RMSE = 42.71) in MLR, respectively than when DMI was not included in the predictive model. When missing DMI records were imputed, within and between-herd accuracy increased to 0.84 (RMSE = 18.5%) and 0.63 (RMSE = 29.9%), respectively. In all scenarios, RF models out-performed MLR models. Results suggest routinely measured variables from dairy farms can be used in developing globally robust prediction models for CH4 if coupled with state-of-the-art techniques for imputation and advanced ML algorithms for predictive modeling.This paper is the result of the concerted effort of all participants and support from the networks of COST Action FA1302 “METHAGENE: Large-scale methane measurements on individual ruminants for genetic evaluations.” The authors thank all individuals and groups who have directly or indirectly contributed to this work; special thanks are due to the technical and financial support from the COST Action FA1302 of the European Union. In addition, all financial and technical support from all participating countries and research centers involved in this work is greatly acknowledged

Trends in cattle diversity and cattle production in Europe: from popular to niche

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Towards self-sustainable European Regional Cattle Breeds - Breed demonstration cases

This report describes the process to re-develop the breed conservation and development strategy in Belgium, France, Spain and the Netherlands with involvement of multi-stakeholdersEUREC