开发一种使用弹性网规范化的加工番茄食品中农药的加工因子预测模型
Yuki Yamasaki1, Kosuke Nakamura1, Nao Kashiwabara1
1Division of Foods, National Institute of Health Sciences, 3-25-26 Tonomachi, Kawasaki-ku, Kawasaki, Kanagawa 210-9501, Japan.
Food chemistry
|March 15, 2024
概括
一种新的弹性净回归模型使用农药的物理化学特性准确预测食品加工过程中农药残留物 (加工因子) 的变化. 该模型有助于评估加工食品 (如番茄产品) 中的残留物含量.
科学领域:
- 环境化学环境化学
- 食品科学 食品科学 食品科学
- 毒理学 毒理学 毒理学
- 计算化学计算化学
背景情况:
- 食品中的农药残留物是一个问题,它们的含量在加工过程中发生变化.
- 处理因子 (PF) 量化了这种变化,但预测它是复杂的.
- 来自监管机构的现有数据,如粮农组织/世卫组织关于农药残留的联合会议,显示了PF和农药特性之间的相关性.
研究的目的:
- 开发一种新的规范化的弹性净回归模型,用于预测农药加工因子 (PF).
- 在番茄加工研究中,使用农药物理化学特性评估PF值的可预测性.
- 克服农药残留分析回归建模中的多对线性问题.
主要方法:
- 开发了一种规范化的弹性净回归模型.
- 利用农药的物理化学特性作为预测变量.
- 从番茄加工研究中验证了培训和测试数据集的模型.
主要成果:
- 弹性净回归模型成功预测了在2倍范围内的80-100%测试农药的PF值.
- 预测的PF值与农药的物理化学特性之间观察到显著的相关性.
- 该模型有效地处理了预测变量之间的多对线性.
结论:
- 农药加工因子可以通过其独特的物理化学特性来准确预测.
- 开发的弹性净回归模型为估计食品加工中的PF值提供了可靠的工具.
- 这种方法有助于对加工食品中的农药残留物的风险评估和监管评估.
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