开发一种动态预测模型,用于在温度波动下对草的质量变化
Wenming Xing1, Lu Liu2, Shaohua Xing1
1School of Food Engineering, Ludong University, Yantai, China.
Journal of food science
|April 4, 2025
概括
这项研究开发了一种动态模型,用于预测储存期间草质量变化. 该模型根据温度准确预测了保质期,确保了整个供应链的草安全性.
科学领域:
- 食品科学 食品科学 食品科学
- 农业工程 农业工程
- 供应链管理 供应链管理
背景情况:
- 在供应链中保持草质量和安全性至关重要.
- 预测模型有助于理解和管理收获后的质量变化.
研究的目的:
- 为草质量变化开发一个动态预测模型.
- 确保草在整个供应链中的安全性和质量.
- 为确定草的保质期提供参考.
主要方法:
- 草在不同的温度 (4,10,20,30°C) 保存.
- 分析了质量参数,包括减肥,坚硬度,总溶性固体 (TSS),可定位酸度 (TA) 和维生素C (Vc).
- 用零级反应动力学和阿雷尼乌斯方程来建模质量变化.
主要成果:
- 体重减轻增加,而性,TSS和Vc含量在储存期间下降.
- 固度和Vc变化被零级反应动力学模型准确地描述.
- 阿雷尼乌斯方程有效地预测了R2>0.900的反应速率 (k).
结论:
- 成功建立了集成反应动力学和阿雷尼乌斯方程的动态预测模型.
- 这些模型准确地预测了4-30°C物流范围内的草质量变化.
- 这项研究为优化草保质期的确定提供了宝贵的工具.
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