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Updated: Sep 15, 2025

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
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Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements

Published on: June 28, 2016

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人工智能驱动的食品质量预测:应用机器学习组合模型进行猪肉pH和肉色变化的动态预测

Xidi Yang1, Liangyu Zhu1, Wenyu Jiang1

  • 1State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China.

Food chemistry
|July 15, 2025
PubMed
概括

这项研究使用食品化学和机器学习来预测猪肉质量,重点关注pH值和肉色. 早期的pH值和肌肉特征是关键预测因素,改善了肉类生产质量控制.

关键词:
组合学习学习 组合学习机器学习模型的机器学习模型肉的颜色是肉的颜色.肌球蛋白的氧化状态猪肉质量预测预测蛋白质变性化动力学 蛋白质变性化动力学在pH值的动态上,pH值的动态

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