Development of a method for using an optical module to determine the biometric parameters of the udder

Author:

Pavkin D. Yu.1ORCID,Yurochka S. S.1ORCID

Affiliation:

1. Federal Scientific Agroengineering Center VIM

Abstract

The purpose of the study is to develop and test the performance of the method of using the optical module for determining the biometric parameters of the udder. There have been developed: a scheme of test stand with a 3-D camera of the optical module for taking 3-D images in the system of digital valuation of the udder of dairy cows; a mathematical model for determining the biometric parameters of the udder and teats, namely: length, diameter of the angles of inclination in two planes of the teats, distance between the teats, scattering from the optical module to the teats, 26 parameters in total. An algorithm for determining the biometric parameters of the udder has been developed. Experiments with the stand and processing of field data were carried out in the Animal Husbandry Department of the FSAC VIM in 2022. In addition, field data were collected on farms: IP KFH Sirota (Moscow region), FSUE Grigorievskoye (Yaroslavl region), Farm Ryabtsevo LLC (Kaluga region) – in total, natural material for 192 animals has been collected. The performance of the developed method was tested on an artificial udder. The mode of operation in determining the biometric parameters of the teats was carried out: the speed of obtaining threedimensional udder maps was 5 frames per 1 second. The angle of rotation of the camera relative to the teats in the 0ZX plane was 30º. According to the results of the experimental studies it has been established that the measured results for 24 out of 26 parameters have an error of less than 5%, the diagonal distance between the teats has an error of 6.0 %, the lateral left distance between the anterior and posterior row of teats has an error of 12.7 %. The measurement error of the distance to the tip of the teats is in the range from -0.004 m to -0.007 m on the Z axis.

Publisher

FARC of the North-East named N.V. Rudnitskogo

Subject

General Medicine

Reference14 articles.

1. Kirsanov V. V., Tsoy Yu. A. Trends in the Development of Biotechnical Systems in Animal Husbandry. Sel'skokhozyaystvennye mashiny i tekhnologii = Agricultural Machinery and Technologies. 2020;14(3):27-32. (In Russ.). DOI: https://doi.org/10.22314/2073-7599-2020-14-3-27-32

2. Kharchenko A. V., Feyzullaev F. R., Lepekhina T. V. The exterior features of the Kazakh white-headed cattle. Glavnyy zootekhnik = Head of Animal Breeding. 2022;(6-1):62-64. (In Russ.). URL: https://www.elibrary.ru/item.asp?id=48575944

3. Sitdikov F. F., Tsoy Yu. A., Ziganshin B. G. Main directions and problems of digitalization of agricultural complex. Vestnik Kazanskogo gosudarstvennogo agrarnogo universiteta = Vestnik of the Kazan State Agrarian University. 2019;14(3(54)):112-115. (In Russ.). DOI: https://doi.org/10.12737/article_5db97473887137.67106533

4. Chindaliev A. E., Kalimoldinova A. S., Alipov A. U., Baimukanov A. D. the use of linear evaluation of body conformation of cows. Glavnyy zootekhnik = Head of Animal Breeding. 2019;(8):32-38. (In Russ.). URL: https://www.elibrary.ru/item.asp?id=41098038

5. Gorbunova O. S., Brazhnik M. V. Human capital of agriculture and problem of his growth. Agrarnoe obrazovanie i nauka = Agrarian education and science. 2018;(1):4. (In Russ.). URL: https://www.elibrary.ru/item.asp?id=36525559

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3