使用出生体重和窝内出生体重变化作为易于测量的代理预测因子来预测仔猪断奶前的存活率

IF 4 2区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE
J.M. Mbuthia , C. Kasper , M. Zenk , G. Bee , C.C. Metges , G. Daş
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引用次数: 0

摘要

仔猪个体初生重(BW0)和窝内初生重变异(BWvar)严重影响断奶前存活率。商业养猪业中的仔猪死亡率引起了重大的经济和伦理问题,以及动物福利问题。本研究的目的是利用logistic回归方法评估体重0、体重var以及其他潜在的母猪和环境因素(包括胎次、性别、产仔数、年份、季节和农场)对仔猪从出生到断奶期成活率的影响。该研究确定了BW0和BWvar的临界阈值,无论是单独的还是用于预测断奶前生存的综合指数。这是通过受试者工作特征(ROC)曲线分析完成的。数据包括来自两个研究农场的1661头母猪的68394头仔猪记录;德国的农场动物生物学研究所和瑞士的Agroscope。体重0和体重var显著影响仔猪出生时的存活率,但其影响随仔猪年龄和交叉饲养等管理干预而改变。体重对成活率的影响最大,成活率随体重的增加呈曲线上升趋势。一个重要的观察结果是,在决定仔猪出生存活率方面,BWvar比产仔数更重要。ROC分析显示,与体重较重的仔猪相比,体重小于1.18 kg(精确度= 0.73)的仔猪出生时存活率较低。由于截断值为0.277 g(准确度为0.50),出生仔猪中BWvar预测存活率的准确性较低。低BW0和高BWvar窝产仔猪的成活率最低。因此,我们提出了两个新的指标,即出生体重-变异比和出生体重-变异复合指数,以提供仔猪生存能力的综合评估。结果表明,与单纯依靠BW0或BWvar相比,使用衍生指标预测仔猪存活的信息量更大(准确率为0.89)。本研究展示了一种利用基本和易于测量的出生体重特征来识别低存活率仔猪的可靠方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting piglet survival until weaning using birth weight and within-litter birth weight variation as easily measured proxy predictors
Individual piglet birth weight (BW0) and within-litter birth weight variability (BWvar) strongly affect preweaning survival. Piglet mortality in commercial pig operations poses significant economic and ethical concerns, as well as animal welfare implications. The objective of this study was to evaluate the effects of BW0, BWvar and other potential sow and environmental factors, including parity, sex, litter size, year, season and farm, on piglet survival from birth to weaning age using a logistic regression approach. The study determined the critical threshold values for BW0 and BWvar, both separately and for a combined index to predict preweaning survival. This was done through a receiver operating characteristic (ROC) curve analysis. Data consisted of 68 394 piglet records from 1 661 sows obtained from two research farms; the Research Institute for Farm Animal Biology in Germany and Agroscope in Switzerland. The BW0 and BWvar significantly influenced piglet survival at birth, but their influence changed with piglet age and management interventions such as cross-fostering. The BW0 exerted the greatest effect on survival, with the probability of survival increasing with increasing BW0 following a curvilinear trend. A significant observation was that BWvar was more important than litter size in determining piglet survival at birth. The ROC analysis revealed that piglets below a BW0 cut-off value of 1.18 kg (accuracy = 0.73) had a lower survival probability at birth compared to their heavier counterparts. With a cut-off value of 0.277 g (accuracy = 0.50), the BWvar amongst total piglets born predicted survival less accurately. Piglets with low BW0 and born in litters with high BWvar had the lowest survival probabilities. Consequently, two novel indexes were developed, namely the birth weight-to-variation ratio and the birth weight-to-variation composite index, to offer a comprehensive assessment of piglet viability. The results suggest that using the derived indexes for predicting piglet survival was more informative (accuracy = 0.89) than relying solely on BW0 or BWvar. This study demonstrates a robust methodology for the identification of low-viability piglets using fundamental and easy-to-measure birth weight traits.
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来源期刊
Animal
Animal 农林科学-奶制品与动物科学
CiteScore
7.50
自引率
2.80%
发文量
246
审稿时长
3 months
期刊介绍: Editorial board animal attracts the best research in animal biology and animal systems from across the spectrum of the agricultural, biomedical, and environmental sciences. It is the central element in an exciting collaboration between the British Society of Animal Science (BSAS), Institut National de la Recherche Agronomique (INRA) and the European Federation of Animal Science (EAAP) and represents a merging of three scientific journals: Animal Science; Animal Research; Reproduction, Nutrition, Development. animal publishes original cutting-edge research, ''hot'' topics and horizon-scanning reviews on animal-related aspects of the life sciences at the molecular, cellular, organ, whole animal and production system levels. The main subject areas include: breeding and genetics; nutrition; physiology and functional biology of systems; behaviour, health and welfare; farming systems, environmental impact and climate change; product quality, human health and well-being. Animal models and papers dealing with the integration of research between these topics and their impact on the environment and people are particularly welcome.
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