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Updated: May 20, 2025

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基于新鲜度的包装蔬菜大豆的分类 通过代谢学与卷积神经网络相结合的代谢学
Yoshio Makino1, Yuta Kurokawa2, Kenji Kawai2
1Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 1138657, Japan.
Metabolites
|March 26, 2025
概括
改性大气 (MA) 包装通过减缓呼吸和减少代谢分解来保持蔬菜大豆的新鲜度. 卷积神经网络 (CNN) 准确地使用代谢物数据对新鲜度进行分类.
科学领域:
- 农业科学 农业科学
- 食品科学 食品科学 食品科学
- 生物技术是生物技术.
背景情况:
- 保持蔬菜大豆的新鲜度对于质量和减少收获后损失至关重要.
- 传统的保存方法往往不能有效地延长保质期.
- 了解与新鲜度相关的代谢变化是开发先进保存策略的关键.
研究的目的:
- 评估修改大气 (MA) 包装在保持蔬菜大豆新鲜度方面的有效性.
- 在MA条件下研究植物大豆发生的代谢变化.
- 开发一个基于数据的模型,使用代谢学来准确地分类新鲜度.
主要方法:
- 植物大豆在修改大气 (低氧,高二氧化碳) 和常态毒性条件下储存.
- 通过监测表面色调角和分析关键代谢物度来评估新鲜度.
- 卷积神经网络 (CNN) 用于根据62种代谢物对新鲜度水平进行分类.
主要成果:
- MA包装显著减缓了呼吸,并减少了pectin和脂肪酸的分解.
- 在MA条件下,关键的代谢途径,包括酸氧化,在MA条件下较不活跃,表明保存的新鲜度.
- 在分类蔬菜大豆新鲜度方面,CNNs获得了92.9%的准确性,超过了线性差异分析的14.3%.
结论:
- 修改大气的包装通过调节代谢活动,有效地延长了蔬菜大豆的新鲜度.
- 代谢分析与机器学习相结合,为客观的新鲜度评估提供了一个强大的工具.
- 这项研究为进一步研究园艺作物的新陈代谢与新鲜度关系提供了基础.
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