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利用高通量和新型传感表型提高奶牛饲料效率的机会。

Opportunities to Harness High-Throughput and Novel Sensing Phenotypes to Improve Feed Efficiency in Dairy Cattle.

作者信息

Siberski-Cooper Cori J, Koltes James E

机构信息

Department of Animal Science, Iowa State University, Ames, IA 50011, USA.

出版信息

Animals (Basel). 2021 Dec 22;12(1):15. doi: 10.3390/ani12010015.

Abstract

Feed for dairy cattle has a major impact on profitability and the environmental impact of farms. Sustainable dairy production relies on continued improvement in feed efficiency as a way to reduce costs and nutrient loss from feed. Advances in breeding, feeding and management have led to the dilution of maintenance energy and thus more efficient dairy cattle. Still, many additional opportunities are available to improve individual animal feed efficiency. Sensing technologies such as wearable sensors, image-based and high-throughput phenotyping technologies (e.g., milk testing) are becoming more available on commercial farm. The application of these technologies as indicator traits for feed intake and efficiency related traits would be advantageous to provide additional information to predict and manage feed efficiency. This review focuses on precision livestock technologies and high-throughput phenotyping in use today as well as those that could be developed in the future as possible indicators of feed intake. Several technologies such as milk spectral data, activity, rumen measures, and image-based phenotypes have been associated with feed intake. Future applications will depend on the ability to repeatably measure and calibrate these data across locations, so that they can be integrated for use in predicting and managing feed intake and efficiency on farm.

摘要

奶牛饲料对农场的盈利能力和环境影响有着重大影响。可持续的奶牛生产依赖于饲料效率的持续提高,以此作为降低成本和减少饲料养分流失的一种方式。育种、饲养和管理方面的进步导致维持能量的稀释,从而使奶牛更高效。尽管如此,仍有许多额外的机会来提高个体动物的饲料效率。诸如可穿戴传感器、基于图像和高通量表型分析技术(如牛奶检测)等传感技术在商业农场中越来越普及。将这些技术用作采食量和与效率相关性状的指示性特征,将有利于提供额外信息以预测和管理饲料效率。本综述重点关注当今使用的精准畜牧技术和高通量表型分析,以及未来可能开发的作为采食量潜在指标的技术。诸如牛奶光谱数据、活动量、瘤胃测量和基于图像的表型等几种技术已与采食量相关联。未来的应用将取决于能否在不同地点重复测量和校准这些数据,以便将它们整合用于预测和管理农场的采食量及效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b396/8749788/711ba9d55bdf/animals-12-00015-g001.jpg

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