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三维(3D)成像技术监测荷斯坦小母牛的生长发育和估计体重:一项初步研究。

Three-Dimensional (3D) Imaging Technology to Monitor Growth and Development of Holstein Heifers and Estimate Body Weight, a Preliminary Study.

机构信息

PEGASE, INRAE, Institut Agro, 35590 Saint-Gilles, France.

Department of Animal Production, Agrifood, Nutrition (P3AN), Agro Rennes-Angers, 35042 Rennes, France.

出版信息

Sensors (Basel). 2022 Jun 19;22(12):4635. doi: 10.3390/s22124635.

Abstract

The choice of rearing strategy for dairy cows can have an effect on production yield, at least during the first lactation. For this reason, it is important to closely monitor the growth and development of young heifers. Unfortunately, current methods for evaluation can be costly, time-consuming, and dangerous because of the need to physically manipulate animals, and as a result, this type of monitoring is seldom performed on farms. One potential solution may be the use of tools based on three-dimensional (3D) imaging, which has been studied in adult cows but not yet in growing individuals. In this study, an imaging approach that was previously validated for adult cows was tested on a pilot population of five randomly selected growing Holstein heifers, from 5 weeks of age to the end of the first gestation. Once a month, all heifers were weighed and an individual 3D image was recorded. From these images, we estimated growth trends in morphological traits such as heart girth or withers height (188.1 ± 3.7 cm and 133.5 ± 6.0 cm on average at one year of age, respectively). From other traits, such as body surface area and volume (5.21 ± 0.32 m and 0.43 ± 0.05 m on average at one year of age, respectively), we estimated body weight based on volume (402.4 ± 37.5 kg at one year of age). Body weight estimates from images were on average 9.7% higher than values recorded by the weighing scale (366.8 ± 47.2 kg), but this difference varied with age (19.1% and 1.8% at 6 and 20 months of age, respectively). To increase accuracy, the predictive model developed for adult cows was adapted and completed with complementary data on young heifers. Using imaging data, it was also possible to analyze changes in the surface-to-volume ratio that occurred as body weight and age increased. In sum, 3D imaging technology is an easy-to-use tool for following the growth and management of heifers and should become increasingly accurate as more data are collected on this population.

摘要

奶牛饲养策略的选择会对产奶量产生影响,至少在初乳期是这样。因此,密切监测青年母牛的生长发育非常重要。不幸的是,由于需要对动物进行物理操作,当前的评估方法可能既昂贵又耗时,而且还很危险,因此这种监测很少在农场进行。一种潜在的解决方案可能是使用基于三维(3D)成像的工具,这些工具已在成年奶牛中进行了研究,但尚未在生长个体中进行研究。在这项研究中,之前在成年奶牛中验证过的成像方法在一个由五头随机选择的生长荷斯坦小母牛组成的试验群体中进行了测试,这些小母牛的年龄从 5 周龄到第一次妊娠结束。每个月,所有小母牛都称重并记录一个个体的 3D 图像。根据这些图像,我们估计了形态特征的生长趋势,如胸围或背高(一岁时平均分别为 188.1 ± 3.7cm 和 133.5 ± 6.0cm)。从其他特征,如体表面积和体积(一岁时平均分别为 5.21 ± 0.32m 和 0.43 ± 0.05m),我们根据体积估计了体重(一岁时为 402.4 ± 37.5kg)。图像估计的体重平均比称重记录高 9.7%(366.8 ± 47.2kg),但这种差异随年龄变化而变化(6 个月和 20 个月时分别为 19.1%和 1.8%)。为了提高准确性,为成年奶牛开发的预测模型进行了调整,并补充了青年小母牛的补充数据。使用成像数据,还可以分析体重和年龄增加时表面与体积比的变化。总之,3D 成像技术是一种易于使用的工具,可用于跟踪小母牛的生长和管理,随着对该群体收集更多数据,其准确性应该会越来越高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62c7/9228325/da539b12d67b/sensors-22-04635-g001.jpg

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