奶牛场生产系统中生物和经济指标的效率

Luis Fernando Fernando Londoño Franco, P. Marini
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摘要

畜牧系统的效率是农村地区最大的社会和经济利益因素之一。该项目的目的是评估不同的生物和经济指标,以便在补充了安蒂奥基亚-哥伦比亚奶牛盆地的放牧系统中确定最有效的奶牛。2009年至2019年的回顾性数据来自各市(Entrerríos、圣佩德罗和贝尔米拉)的奶牛场。这些生产系统呈现了分布在安蒂奥基亚北部的大多数乳制品公司的共同特征,它们的特点是放牧乳制品系统具有不同的补充制度。这些农场有自己的记录,数据来自合作社或协会的官方牛奶控制。根据产犊数对生产类别进行排序,在每个亚组中按每次泌乳总升数从小到大排序,记录所评估奶牛的生产、繁殖、健康和经济变量。然后进行削减;获得相似尺寸的三分之二,从而形成低、中、高产量三大类。可以确定显示四组变量(品种、泌乳产奶量、开放天数和青贮)的模型,它们具有100%的重要相关性,并且对升奶成本的行为有更大的贡献,获得R2为0.91 (p <0.05),预测误差为每升奶(0.0076美元)。综上所示,在很少的生物和经济预测指标的情况下,可以识别出放牧系统中最有效的奶牛,这些指标被集成到一个简单且易于执行的web应用模块中,可以显著预测生产影响。乳品公司的可持续发展决策。
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Efficiency of Biological and Economic Indicators in Production Systems in Dairy Farms
The efficiency of the livestock system is one of the factors of greatest social and economic interest in rural areas. The objective of the project was to evaluate different biological and economic indicators that allow identifying the most efficient dairy cows in grazing systems with supplementation of the dairy basin of Antioquia-Colombia. Retrospective data from 2009 to 2019 were used from dairy farms in the municipalities (Entrerríos, San Pedro and Belmira). These production systems present characteristics common to most of the dairy companies distributed in the north of Antioquia, they are characterized by being grazing dairy systems with different supplementation regimes. The farms have their own records and official milk control from the cooperatives or associations from which the data were obtained. The productive categories were ordered according to the number of calving and within each subgroup they were ordered by the total liters per lactation in ascending order, productive, reproductive, health and economic variables of the cows evaluated were recorded. Then cuts were made; obtaining three thirds of similar size, thus forming three categories: low, medium and high production. It was possible to determine the model that showed four groups of variables (breed, milk production by lactation, days open and silage), with an important correlation of 100% and greater contribution to the behavior of the cost of the liter, obtaining an R2 of 0.91 (p <0.05) and a prediction error of (US $ 0.0076) per liter of milk in the farms evaluated. It is concluded that, with few biological and economic predictive indicators, it was possible to identify the most efficient cows in grazing systems, these indicators were integrated into a simple and easy-to-execute web application module, which allows to significantly predict the productive impact. And, Decision-making on the sustainability of dairy companies.
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