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L'augmentation des températures mondiales induite par le changement climatique a intensifié le stress thermique sur les bovins laitiers et contribue à la faible productivité laitière généralement observée. L'élevage sélectif visant à améliorer la capacité des animaux à résister à la hausse des températures tout en maintenant des performances optimales est crucial pour assurer l'accès futur aux produits laitiers. Cependant, les indicateurs phénotypiques de la tolérance à la chaleur ne sont pas encore effectivement pris en compte dans les objectifs de la plupart des programmes d'élevage sélectif. Cette étude a examiné la réponse de la production laitière à l'évolution de la charge thermique en tant qu'indication de la tolérance à la chaleur et l'influence de la saison de vêlage sur cette réponse chez les bovins laitiers de races multiples présents dans trois zones agroécologiques au Kenya. Le rendement laitier moyen de 7 jours de première parité (65 261 enregistrements de lait) de 1 739 vaches a été analysé. Sur la base des données météorologiques régulièrement enregistrées et accessibles en ligne, l'indice de température et d'humidité (THI) a été calculé et utilisé comme mesure de la charge calorifique. LES mesures utilisées représentaient les moyennes des mêmes périodes de 7 jours correspondant à chaque enregistrement de lait moyen de 7 jours. Les modèles de régression aléatoire, y compris les fonctions de la norme de réaction, ont été ajustés pour dériver deux indicateurs de résilience : la pente de la norme de réaction (pente) et sa valeur absolue (absolue), reflétant les changements dans le rendement du lait en réponse aux charges thermiques variables (THI 50 et THI 80). Les paramètres génétiques de ces indicateurs ont été estimés et leurs associations avec le rendement moyen en lait au jour d'essai ont été examinées. Il n'y avait pas de différences substantielles dans le modèle de réponse du rendement laitier à la charge thermique entre le vêlage des vaches en saison sèche et humide. Les animaux avec des gènes Bos taurus ≤50 % étaient les plus thermotolérants à des niveaux de charge thermique extrêmement élevés. Les animaux se produisant dans des environnements semi-arides présentaient la capacité de tolérance à la chaleur la plus élevée. Les estimations d'héritabilité pour ces indicateurs variaient de 0,06 à 0,33 et étaient pour la plupart significativement différentes de zéro (P<0,05). La pente à THI 80 avait des corrélations négatives élevées (0,64-0,71) avec le rendement laitier quotidien moyen, révélant que les vaches hautement productrices sont plus vulnérables au stress thermique et vice versa. Une corrélation positive élevée (0,63-0,74) a été observée entre le rendement laitier absolu et moyen à THI 80. Cela impliquait que les vaches à faible production laitière avaient une production laitière plus stable dans des conditions de stress thermique et vice versa. L'étude a démontré que la pente des normes de réaction et sa valeur absolue peuvent mesurer efficacement la résilience des bovins laitiers croisés à des conditions de charge thermique variables. Les implications de ces résultats sont précieuses pour améliorer la tolérance à la chaleur des espèces animales grâce à la sélection génétique. El aumento de las temperaturas globales inducido por el cambio climático ha intensificado el estrés por calor en el ganado lechero y está contribuyendo a la baja productividad de la leche generalmente observada. La cría selectiva destinada a mejorar la capacidad de los animales para soportar el aumento de las temperaturas y mantener un rendimiento óptimo es crucial para garantizar el acceso futuro a los productos lácteos. Sin embargo, los indicadores fenotípicos de tolerancia al calor aún no se han tenido en cuenta de manera efectiva en los objetivos de la mayoría de los programas de reproducción selectiva. Este estudio investigó la respuesta de la producción de leche a la carga de calor cambiante como una indicación de la tolerancia al calor y la influencia de la temporada de parto en esta respuesta en ganado lechero de razas múltiples que se desempeña en tres zonas agroecológicas de Kenia. Se analizó el rendimiento lechero medio de 7 días de primera paridad (65 261 registros lecheros) de 1 739 vacas. Con base en los datos meteorológicos registrados de forma rutinaria que eran accesibles en línea, se calculó el Índice de Temperatura-Humedad (THI) y se utilizó como una medida de la carga de calor. Estas mediciones utilizadas representaron promedios de los mismos períodos de 7 días correspondientes a cada registro medio de leche de 7 días. Los modelos de regresión aleatoria, incluidas las funciones de la norma de reacción, se ajustaron para derivar dos indicadores de resiliencia: pendiente de la norma de reacción (pendiente) y su valor absoluto (absoluto), que reflejan los cambios en el rendimiento de la leche en respuesta a las diferentes cargas de calor (THI 50 y THI 80). Se estimaron los parámetros genéticos de estos indicadores y se examinaron sus asociaciones con el rendimiento medio de la leche del día de prueba. No hubo diferencias sustanciales en el patrón de respuesta del rendimiento de la leche a la carga de calor entre las vacas que paren en las estaciones seca y húmeda. Los animales con ≤50% de genes de Bos taurus fueron los más termotolerantes a niveles de carga de calor extremadamente altos. Los animales que actuaban en ambientes semiáridos mostraron la mayor capacidad de tolerancia al calor. Las estimaciones de heredabilidad para estos indicadores oscilaron entre 0,06 y 0,33 y en su mayoría fueron significativamente diferentes de cero (P<0,05). La pendiente en THI 80 tuvo altas correlaciones negativas (0.64-0.71) con el rendimiento medio diario de leche, revelando que las vacas de alta producción son más vulnerables al estrés por calor y viceversa. Se observó una alta correlación positiva (0.63-0.74) entre el rendimiento absoluto y el rendimiento medio de la leche a THI 80. Esto implicaba que las vacas con baja producción de leche tienen una producción de leche más estable en condiciones de estrés por calor y viceversa. El estudio demostró que la pendiente de las normas de reacción y su valor absoluto pueden medir de manera efectiva la resiliencia del ganado lechero cruzado a diferentes condiciones de carga de calor. Las implicaciones de estos hallazgos son valiosas para mejorar la tolerancia al calor de las especies ganaderas a través de la selección genética. Climate change-induced rise in global temperatures has intensified heat stress on dairy cattle and is contributing to the generally observed low milk productivity. Selective breeding aimed at enhancing animals' ability to withstand rising temperatures while maintaining optimal performance is crucial for ensuring future access to dairy products. However, phenotypic indicators of heat tolerance are yet to be effectively factored in the objectives of most selective breeding programs. This study investigated the response of milk production to changing heat load as an indication of heat tolerance and the influence of calving season on this response in multibreed dairy cattle performing in three agroecological zones Kenya. First-parity 7-day average milk yield (65 261 milk records) of 1 739 cows were analyzed. Based on routinely recorded weather data that were accessible online, the Temperature-Humidity Index (THI) was calculated and used as a measure of heat load. THI measurements used represented averages of the same 7-day periods corresponding to each 7-day average milk record. Random regression models, including reaction norm functions, were fitted to derive two resilience indicators: slope of the reaction norm (Slope) and its absolute value (Absolute), reflecting changes in milk yield in response to the varying heat loads (THI 50 and THI 80). The genetic parameters of these indicators were estimated, and their associations with average test-day milk yield were examined. There were no substantial differences in the pattern of milk yield response to heat load between cows calving in dry and wet seasons. Animals with ≤50% Bos taurus genes were the most thermotolerant at extremely high heat load levels. Animals performing in semi-arid environments exhibited the highest heat tolerance capacity. Heritability estimates for these indicators ranged from 0.06 to 0.33 and were mostly significantly different from zero (P<0.05). Slope at THI 80 had high (0.64-0.71) negative correlations with average daily milk yield, revealing that high-producing cows are more vulnerable to heat stress and vice versa. A high (0.63-0.74) positive correlation was observed between Absolute and average milk yield at THI 80. This implied that low milk-producing cows have a more stable milk production under heat-stress conditions and vice versa. The study demonstrated that the slope of the reaction norms and its absolute value can effectively measure the resilience of crossbred dairy cattle to varying heat load conditions. The implications of these findings are valuable in improving the heat tolerance of livestock species through genetic selection. أدى الارتفاع الناجم عن تغير المناخ في درجات الحرارة العالمية إلى تكثيف الإجهاد الحراري على الماشية الحلوب ويسهم في انخفاض إنتاجية الحليب بشكل عام. إن التربية الانتقائية التي تهدف إلى تعزيز قدرة الحيوانات على تحمل ارتفاع درجات الحرارة مع الحفاظ على الأداء الأمثل أمر بالغ الأهمية لضمان الوصول في المستقبل إلى منتجات الألبان. ومع ذلك، فإن مؤشرات النمط الظاهري لتحمل الحرارة لم تؤخذ بعد في الاعتبار بشكل فعال في أهداف معظم برامج التكاثر الانتقائية. بحثت هذه الدراسة في استجابة إنتاج الحليب لتغير الحمل الحراري كمؤشر على تحمل الحرارة وتأثير موسم الولادة على هذه الاستجابة في الماشية الحلوب متعددة السلالات التي تعمل في ثلاث مناطق زراعية إيكولوجية في كينيا. تم تحليل متوسط إنتاج الحليب لمدة 7 أيام (65261 سجل حليب) من 1739 بقرة. استنادًا إلى بيانات الطقس المسجلة بشكل روتيني والتي يمكن الوصول إليها عبر الإنترنت، تم حساب مؤشر درجة الحرارة والرطوبة (THI) واستخدامه كمقياس للحمل الحراري. تمثل هذه القياسات المستخدمة متوسطات لنفس فترات 7 أيام المقابلة لكل سجل حليب متوسط لمدة 7 أيام. تم تركيب نماذج الانحدار العشوائي، بما في ذلك وظائف معيار التفاعل، لاستخلاص مؤشرين للمرونة: ميل معيار التفاعل (المنحدر) وقيمته المطلقة (المطلق)، مما يعكس التغيرات في إنتاجية الحليب استجابة للأحمال الحرارية المتفاوتة (THI 50 و THI 80). تم تقدير المعلمات الوراثية لهذه المؤشرات، وتم فحص ارتباطاتها بمتوسط إنتاجية الحليب في يوم الاختبار. لم تكن هناك اختلافات جوهرية في نمط استجابة غلة الحليب للحمل الحراري بين الأبقار التي تلد في المواسم الجافة والرطبة. كانت الحيوانات التي تحتوي على ≤50 ٪ من جينات الثور البوس هي الأكثر تحملاً للحرارة عند مستويات حمل حراري عالية للغاية. أظهرت الحيوانات التي تعمل في البيئات شبه القاحلة أعلى قدرة على تحمل الحرارة. تراوحت تقديرات التوريث لهذه المؤشرات من 0.06 إلى 0.33 وكانت في الغالب مختلفة بشكل كبير عن الصفر (P<0.05). كان للمنحدر عند THI 80 ارتباطات سلبية عالية (0.64-0.71) مع متوسط إنتاج الحليب اليومي، مما يكشف عن أن الأبقار عالية الإنتاج أكثر عرضة للإجهاد الحراري والعكس صحيح. لوحظ وجود ارتباط إيجابي مرتفع (0.63-0.74) بين إنتاج الحليب المطلق والمتوسط عند 80. وهذا يعني أن الأبقار ذات الإنتاج المنخفض للحليب لديها إنتاج حليب أكثر استقرارًا في ظل ظروف الإجهاد الحراري والعكس صحيح. أظهرت الدراسة أن منحدر معايير التفاعل وقيمته المطلقة يمكن أن يقيس بشكل فعال مرونة الماشية الحلوب المهجنة لظروف الحمل الحراري المتفاوتة. إن الآثار المترتبة على هذه النتائج ذات قيمة في تحسين تحمل الحرارة لأنواع الماشية من خلال الانتقاء الجيني.

Increasing the concentration of dietary lipid is a promising strategy for reducing methane (CH4) emissions from ruminants. This study investigated the effect of replacing grass silage with brewers' grains on CH4 emissions of pregnant, non-lactating beef cows of two breeds. The experiment was a two×two factorial design comprising two breeds (LIMx, crossbred Limousin; and LUI, purebred Luing) and two diets consisting of (g/kg diet dry matter (DM)) barley straw (687) and grass silage (301, GS), or barley straw (763) and brewers' grains (226, BG), which were offered ad libitum. Replacing GS with BG increased the acid-hydrolysed ether extract concentration from 21 to 37 g/kg diet DM. Cows (n=48) were group-housed in equal numbers of each breed across two pens and each diet was allocated to one pen. Before measurements of CH4, individual dry matter intake (DMI), weekly BW and weekly body condition score were measured for a minimum of 3 weeks, following a 4-week period to acclimatise to the diets. CH4 emissions were subsequently measured on one occasion from each cow using individual respiration chambers. Due to occasional equipment failures, CH4 measurements were run over 9 weeks giving 10 observations for each breed×treatment combination (total n=40). There were no differences between diets for daily DMI measured in the chambers (9.92 v. 9.86 kg/day for BG and GS, respectively; P>0.05). Cows offered the BG diet produced less daily CH4 than GS-fed cows (131 v. 156 g/day: P0.05). However, when expressed as a proportion of metabolic BW (BW0.75), LUI cows had greater DMI than LIMx cows (84.5 v. 75.7 g DMI/kg BW0.75, P<0.05) and produced more CH4 per kg BW0.75 than LIMx cows (1.30 v. 1.05 g CH4/kg BW0.75; P<0.01). Molar proportions of acetate were higher (P<0.001) and propionate and butyrate lower (P<0.01) in rumen fluid samples from BG-fed compared with GS-fed cows. This study demonstrated that replacing GS with BG in barley straw-based diets can effectively reduce CH4 emissions from beef cows, with no suppression of DMI.

Livestock production is a major contributor to greenhouse gas (GHG) emissions, so will play a significant role in the mitigation effort. Recent literature highlights different strategies to mitigate GHG emissions in the livestock sector. Animal welfare is a criterion of sustainability and any strategy designed to reduce the carbon footprint of livestock production should consider animal welfare amongst other sustainability metrics. We discuss and tabulate the likely relationships and trade-offs between the GHG mitigation potential of mitigation strategies and their welfare consequences, focusing on ruminant species and on cattle in particular. The major livestock GHG mitigation strategies were classified according to their mitigation approach as reducing total emissions (inhibiting methane production in the rumen), or reducing emissions intensity (Ei; reducing CH4 per output unit without directly targeting methanogenesis). Strategies classified as antimethanogenic included chemical inhibitors, electron acceptors (i.e. nitrates), ionophores (i.e. Monensin) and dietary lipids. Increasing diet digestibility, intensive housing, improving health and welfare, increasing reproductive efficiency and breeding for higher productivity were categorized as strategies that reduce Ei. Strategies that increase productivity are very promising ways to reduce the livestock carbon footprint, though in intensive systems this is likely to be achieved at the cost of welfare. Other strategies can effectively reduce GHG emissions whilst simultaneously improving animal welfare (e.g. feed supplementation or improving health). These win-win strategies should be strongly supported as they address both environmental and ethical sustainability. In order to identify the most cost-effective measures for improving environmental sustainability of livestock production, the consequences of current and future strategies for animal welfare must be scrutinized and contrasted against their effectiveness in mitigating climate change.

Improved animal health can reduce greenhouse gas (GHG) emissions intensity in livestock systems while increasing productivity. Integrated modelling of disease impacts on farm-scale emissions is important in identifying effective health strategies to reduce emissions. However, it requires that modellers understand the pathways linking animal health to emissions and how these might be incorporated into models. A key barrier to meeting this need has been the lack of a framework to facilitate effective exchange of knowledge and data between animal health experts and emissions modellers. Here, these two communities engaged in workshops, online exchanges and a survey to i) identify a comprehensive list of disease-related model parameters and ii) test its application to evaluating models. Fifty-six parameters were identified and proved effective in assessing the potential of farm-scale models to characterise livestock disease impacts on GHG emissions. Easy wins for the emissions models surveyed include characterising disease impacts related to feeding.

Animal nitrogen (N) partitioning is a key parameter for profitability and sustainability of ruminant production systems, which may be predicted from N isotopic discrimination or fractionation (Δ15N). Both animal genetics and feeding level may interact and impact on N partitioning. Therefore, this study aimed to assess the interactive effects of genetic merit (G) and feed allowance (F) on N partitioning and Δ15N in sheep. The sheep were drawn from two levels of G (high G vs. low G; based on New Zealand Sheep Improvement Limited (http://www.sil.co.nz/) dual (wool and meat) growth index) and allocated to two levels of F (1.7 (high F) vs. 1.1 (low F) times Metabolisable Energy requirement for maintenance) treatments. Twenty-four Coopworth rams were divided into four equal groups for a N balance study: high G × high F, high G × low F, low G × high F, and low G × low F. The main factors (G and F) and the interaction term were used for 2-way ANOVA and regression analysis. Higher F led to higher N excretions (urinary N (UN); faecal N (FN); manure N), retained N, N use efficiency (NUE), and urinary purine derivatives excretion (P < 0.05). On the other hand, higher UN/N intake, and plasma Δ15N were observed with the lower F (P < 0.05). Higher G led to increased UN, FN, manure N, apparent N digestibility, and urinary purine derivatives excretion (P < 0.05). Higher F only increased UN in high G sheep, with no effect on low G sheep (P < 0.05). Regression analysis results demonstrated potential to use plasma Δ15N to reflect the effects of G and F on NUE and UN/N intake. Further research is urged to study interactive effects of genetic and feeding level on sheep N partitioning.

Breeding objectives of livestock and other agricultural species are usually profit maximising. The selection emphasis placed on specific traits to achieve a breeding objective is often informed by the financial value of a trait to a farm system. However, there are alternative, and complementary approaches to defining both the breeding objective and the selection emphasis placed on traits that are included in associated selection tools. These are based on the preferences of stakeholders, which are often heterogeneous and include broader values and motivations than profit. In this regard, stated preference methods are useful when considering traits that have either no discernible market value or whose value is not fully transferred via the market. Such approaches can guide more appropriate breeding decisions that are amenable to changing societal values, for example with reduced negative environmental externalities. However, while stated preference methods offer promising conceptualisations of value in genetic improvement programmes, there is still a substantial knowledge gap in terms of the current state of research and a catalogue of publications to date. This paper reviews publications of stated preference approaches in the field of livestock breeding (and some relevant crop breeding examples), providing a knowledge base of published applications and promoting their continued development and implementation towards the formulation of appropriate breeding objectives and selection indices. A systematic review of 84 peer-reviewed publications and an aggregate ranking of traits for the most commonly studied subject (cattle) reveals uncertainty in preference estimates which may be driven by (i) a diverse set of non-standardised methodologies, (ii) common oversights in the selection, inclusion and description of traits, and (iii) inaccurate representations of the respondent population. We discuss key considerations to help overcome these limitations, including avoiding methodological confinement to a disciplinary silo and reducing complexity so that the values of broader respondent groups may be accounted for.

The livestock sector is one of the fastest growing subsectors of the agricultural economy and, while it makes a major contribution to global food supply and economic development, it also consumes significant amounts of natural resources and alters the environment. In order to improve our understanding of the global environmental impact of livestock supply chains, the Food and Agriculture Organization of the United Nations has developed the Global Livestock Environmental Assessment Model (GLEAM). The purpose of this paper is to provide a review of GLEAM. Specifically, it explains the model architecture, methods and functionality, that is the types of analysis that the model can perform. The model focuses primarily on the quantification of greenhouse gases emissions arising from the production of the 11 main livestock commodities. The model inputs and outputs are managed and produced as raster data sets, with spatial resolution of 0.05 decimal degrees. The Global Livestock Environmental Assessment Model v1.0 consists of five distinct modules: (a) the Herd Module; (b) the Manure Module; (c) the Feed Module; (d) the System Module; (e) the Allocation Module. In terms of the modelling approach, GLEAM has several advantages. For example spatial information on livestock distributions and crops yields enables rations to be derived that reflect the local availability of feed resources in developing countries. The Global Livestock Environmental Assessment Model also contains a herd model that enables livestock statistics to be disaggregated and variation in livestock performance and management to be captured. Priorities for future development of GLEAM include: improving data quality and the methods used to perform emissions calculations; extending the scope of the model to include selected additional environmental impacts and to enable predictive modelling; and improving the utility of GLEAM output.