Dijkstra Eveline, Santman-Berends Inge, de Haan Tara, van Schaik Gerdien, van den Brom René, Stegeman Arjan
Department of Small Ruminant Health, Royal GD, Arnsbergstraat 7, 7418 EZ Deventer, The Netherlands.
Department of Research and Development, Royal GD, Arnsbergstraat 7, 7418 EZ Deventer, The Netherlands.
Animals (Basel). 2025 Jun 3;15(11):1653. doi: 10.3390/ani15111653.
Optimising kid rearing is essential for sustainable dairy goat farming, yet validated parameters and practical benchmark data are lacking. This study aimed to develop and evaluate a set of key performance indicators (KPIs) for monitoring kid-rearing practices through a participatory approach. Researchers, veterinarians and five dairy goat farms participated developed a prototype set of KPIs covering birth, colostrum management, average daily gain (ADG), and mortality, which were stratified across four rearing phases: perinatal (first 48 h), postnatal (birth to weaning), postweaning (weaning to 12 weeks), and final rearing (12 weeks to mating). The set of KPIs was subsequently tested for its added value but also for its feasibility in practice on the five participating farms as proof of principle. On these farms, data were gathered over a six-month period (June 2020-January 2021), combining routine census data with on-farm records. Only three out of five farms returned complete datasets encompassing data from 715 kids. Results revealed significant variation in rearing outcomes across farms, particularly in birth weights and postweaning growth. Birth weight emerged as a key predictor for ADG, while differences in weaning strategies had the greatest impact on postweaning performance. Although the farmers acknowledged the added value of the developed KPIs, collection of these data during the kidding season was challenging and required further automation to simplify data collection on the farm. This study demonstrates the feasibility and value of individual-level data collection in dairy goat systems and underscores the need for practical tools to support routine monitoring and data-driven management.
优化幼畜饲养对于可持续奶山羊养殖至关重要，但目前缺乏经过验证的参数和实用的基准数据。本研究旨在通过参与式方法开发和评估一套用于监测幼畜饲养实践的关键绩效指标（KPI）。研究人员、兽医和五个奶山羊养殖场共同参与制定了一套KPI原型，涵盖出生、初乳管理、平均日增重（ADG）和死亡率，并将其分为四个饲养阶段：围产期（前48小时）、产后（出生至断奶）、断奶后（断奶至12周）和最终饲养（12周至配种）。随后对这套KPI进行了测试，以验证其附加值以及在五个参与养殖场实际应用的可行性，作为原理验证。在这些养殖场，收集了为期六个月（2020年6月至2021年1月）的数据，将常规普查数据与农场记录相结合。五个农场中只有三个返回了完整的数据集，涵盖了715只幼畜的数据。结果显示，各养殖场的饲养结果存在显著差异，尤其是出生体重和断奶后生长情况。出生体重成为ADG的关键预测指标，而断奶策略的差异对断奶后性能影响最大。尽管养殖户认可所开发KPI的附加值，但在产羔季节收集这些数据具有挑战性，需要进一步自动化以简化农场的数据收集。本研究证明了奶山羊系统中个体水平数据收集的可行性和价值，并强调了需要实用工具来支持常规监测和数据驱动的管理。
