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Data mining and decision support systems for efficient dairy production

机译:高效乳制品生产的数据挖掘和决策支持系统

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摘要

Gainful livestock farming requires selective breeding of animals with certain heritable desirable traits which gives profitability in terms of farm produce. Modern dairy animals are selected for traits which directly or indirectly contribute to high milk production. The concept of “feed conversion efficiency” in terms of milk production is now vigorously taken up by researchers and farm managers for recognizing and breeding efficient milk-producing animals. The whole concept of economic farming thus requires identification of “elite” animals, meeting above criteria as base population for the farm enterprise. Farmers and animal traders have been selecting best animals based on certain physical characters, which were also accepted by the breeding scientists as phenotypes. Data mining allows uncovering of hidden patterns in the data for better understanding of data relationship for developing suitable models for further improvements. Along with artificial intelligence techniques, data mining has opened new avenues for achieving high resource utilization efficiency and sustainable profitability in livestock production systems. The present review discusses and summarizes various data mining techniques and decision support systems for scientific dairy farming.
机译:收益牲畜养殖需要选择性育种动物,具有某些可遗义的理想性状,这在农产品方面提供了盈利能力。选择现代乳制品用于直接或间接促进高牛奶生产的特质。研究人员和农场管理人员正在大力接受“饲料转换效率”的概念,以识别和育种牛奶生产动物的培养和养殖。因此,经济农业的整个概念需要识别“精英”动物,以上标准的标准作为农场企业的基础人口。农民和动物贸易商一直在基于某些物理特征选择最佳动物,这些人也被育种科学家作为表型接受。数据挖掘允许揭示数据中的隐藏模式,以便更好地了解为进一步改进开发合适模型的数据关系。随着人工智能技术,数据挖掘开设了新的途径,以实现畜牧生产系统的高资源利用效率和可持续盈利能力。本综述讨论并概述了科学乳制品农业各种数据挖掘技术和决策支持系统。

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