Next Article in Journal
Detection of Water Content in Lettuce Canopies Based on Hyperspectral Imaging Technology under Outdoor Conditions
Next Article in Special Issue
Pig Face Recognition Based on Metric Learning by Combining a Residual Network and Attention Mechanism
Previous Article in Journal
Titanium Organic Complex Improves Pollination and Fruit Development of Remontant Strawberry Cultivars under High-Temperature Conditions
Previous Article in Special Issue
Detection Method of Cow Estrus Behavior in Natural Scenes Based on Improved YOLOv5
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agriculture
Volume 12
Issue 11
10.3390/agriculture12111794
agriculture-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Live Weight Prediction of Cattle Based on Deep Regression of RGB-D Images

by
Alexey Ruchay
1,2,*,
Vitaly Kober
2,3,
Konstantin Dorofeev
1,
Vladimir Kolpakov
1,4,
Alexey Gladkov
2 and
Hao Guo
5
1
Federal Research Centre of Biological Systems and Agro-Technologies of the Russian Academy of Sciences, 460000 Orenburg, Russia
2
Department of Mathematics, Chelyabinsk State University, 454001 Chelyabinsk, Russia
3
Center of Scientific Research and Higher Education of Ensenada, Ensenada 22860, Mexico
4
Department of Biotechnology of Animal Raw Materials and Aquaculture, Orenburg State University, 460000 Orenburg, Russia
5
College of Land Science and Technology, China Agricultural University, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Agriculture 2022, 12(11), 1794; https://doi.org/10.3390/agriculture12111794
Submission received: 12 September 2022 / Revised: 25 October 2022 / Accepted: 26 October 2022 / Published: 28 October 2022
(This article belongs to the Special Issue Recent Advancements in Precision Livestock Farming)
Browse Figures
Review Reports Versions Notes

Abstract

Predicting the live weight of cattle helps us monitor the health of animals, conduct genetic selection, and determine the optimal timing of slaughter. On large farms, accurate and expensive industrial scales are used to measure live weight. However, a promising alternative is to estimate live weight using morphometric measurements of livestock and then apply regression equations relating such measurements to live weight. Manual measurements on animals using a tape measure are time-consuming and stressful for the animals. Therefore, computer vision technologies are now increasingly used for non-contact morphometric measurements. The paper proposes a new model for predicting live weight based on augmenting three-dimensional clouds in the form of flat projections and image regression with deep learning. It is shown that on real datasets, the accuracy of weight measurement using the proposed model reaches 91.6%. We also discuss the potential applicability of the proposed approach to animal husbandry.
Keywords: live body weight; prediction; image regression; cattle; deep learning live body weight; prediction; image regression; cattle; deep learning

Share and Cite

MDPI and ACS Style

Ruchay, A.; Kober, V.; Dorofeev, K.; Kolpakov, V.; Gladkov, A.; Guo, H. Live Weight Prediction of Cattle Based on Deep Regression of RGB-D Images. Agriculture 2022, 12, 1794. https://doi.org/10.3390/agriculture12111794

AMA Style

Ruchay A, Kober V, Dorofeev K, Kolpakov V, Gladkov A, Guo H. Live Weight Prediction of Cattle Based on Deep Regression of RGB-D Images. Agriculture. 2022; 12(11):1794. https://doi.org/10.3390/agriculture12111794

Chicago/Turabian Style

Ruchay, Alexey, Vitaly Kober, Konstantin Dorofeev, Vladimir Kolpakov, Alexey Gladkov, and Hao Guo. 2022. "Live Weight Prediction of Cattle Based on Deep Regression of RGB-D Images" Agriculture 12, no. 11: 1794. https://doi.org/10.3390/agriculture12111794

APA Style

Ruchay, A., Kober, V., Dorofeev, K., Kolpakov, V., Gladkov, A., & Guo, H. (2022). Live Weight Prediction of Cattle Based on Deep Regression of RGB-D Images. Agriculture, 12(11), 1794. https://doi.org/10.3390/agriculture12111794

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop