Integrating Mid‐Infrared Spectroscopy, Machine Learning, and Graphical Bias Correction for Fatty Acid Prediction in water Buffalo Milk

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成果类型：

期刊论文

作者：

Yao, Zhiqiu;Zou, Wenna;Zhang, Xinxin;Nie, Pei;Lv, Haimiao;...

作者机构：

[Yao, Zhiqiu; Zou, Wenna; Wang, Wei; Lv, Haimiao; Yang, Ying; Nie, Pei; Zhao, Xuhong; Zhang, Xinxin; Yang, Liguo] International Joint Research Centre for Animal Genetics, Breeding and Reproduction (IJRCAGBR), Huazhong Agricultural University, Wuhan, 430070, China

[Yao, Zhiqiu; Zou, Wenna; Wang, Wei; Lv, Haimiao; Yang, Ying; Nie, Pei; Zhao, Xuhong; Zhang, Xinxin; Yang, Liguo] Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China

[Nie, Pei] College of Veterinary Medicine, Hunan Agricultural University, Changsha, 410128, China

语种：

英文

关键词：

Bland-Altman plot;FT-MIR;Fatty acid;Machine learning

期刊：

Journal of the Science of Food and Agriculture

ISSN：

0022-5142

年：

2024

DOI：

10.1002/jsfa.13471

机构署名：

本校为其他机构

院系归属：

动物医学院

摘要：

BACKGROUND: Buffalo milk, constituting 15% of global production, has higher fatty acids content than Holstein milk.Fourier transform mid-infrared spectroscopy (FT-MIR) is widely used for dairy analysis, but its application to buffalo milk, with larger fat globules, remains understudied. The ultimate goal of this study is to develop machine learning models based on FT-MIR for predicting fatty acids in buffalo milk and to assess the accuracy of commercial milk analyzers. This research provides a convenient, fast, and environmentally friendly meth...

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Integrating Mid‐Infrared Spectroscopy, Machine Learning, and Graphical Bias Correction for Fatty Acid Prediction in water Buffalo Milk

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