Nondestructive estimation of beef carcass yield using digital image analysis-Reference-Cited by-同舟云学术

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Nondestructive estimation of beef carcass yield using digital image analysis

Published:2022-03 Issue: Volume:194 Page:106769
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Wakholi Collins,Kim Juntae,Kwon Kyung-Do,Mo Changyeon,Seo Youngwook,Cho Suhyun,Lim Jongguk,Lee Wang-Hee,Cho Byoung-Kwan

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference40 articles.

1. Relationships among carcass shape, tissue composition, primal cuts and meat quality traits in lambs: A PLS path modeling approach;Araújo;Small Ruminant Res.,2020

2. Calkins, C. R. (2019). An On-Line System to Assess Beef Quality Characteristics.

3. Dual-component video image analysis system (VIASCAN) as a predictor of beef carcass red meat yield percentage and for augmenting application of USDA yield grades;Cannell;J. Anim. Sci.,1999

4. A Computational Approach to Edge Detection;Canny;IEEE Trans. Pattern Anal. Mach. Intell.,1986

5. Prediction of intramuscular fat levels in Texel lamb loins using X-ray computed tomography scanning;Clelland;Meat Sci.,2014

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1. Compact imaging system and deep learning based segmentation for objective longissimus muscle area in Korean beef carcass;Meat Science;2023-12

2. VIS/NIR hyperspectral imaging with artificial neural networks to evaluate the content of thiobarbituric acid reactive substances in beef muscle;Journal of Food Engineering;2023-08

3. Application of Visible and Shortwave Near Infrared Spectroscopy Combined with PCA-LDA and PLS-DA to Distinguish Sirloin and Shank Beef;Proceedings of the 3rd International Conference on Smart and Innovative Agriculture (ICoSIA 2022);2023

4. Meat marketing | Market requirements and specifications;Reference Module in Food Science;2022

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