Zhang Ruoyan, Zhong Yu, Wang Dangfeng, Gong Liang, Yang Linnan, Guo Feng, Zhou Guoping, Deng Yun
Department of Food Science and Technology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China.
South China Botanical Garden, Chinese Academy of Sciences, 723 Xingke Road, Guangzhou, Guangdong 510650, China.
Food Chem. 2025 Apr 1;470:142679. doi: 10.1016/j.foodchem.2024.142679. Epub 2024 Dec 31.
Atemoya fruit deteriorates rapidly during post-harvest storage. A complete understanding of the metabolic mechanisms underlying this process is crucial for developing effective preservation strategies. Metabolomic approaches combined with machine learning offer new opportunities to identify quality-related biomarkers. This study compared atemoya quality stored at 25 °C and 10 °C using untargeted metabolomics integrated with generative adversarial network (GAN) and random forest (RF) analysis. It was found that GAN successfully amplified the metabolomic dataset 10-fold, enabling robust RF-based identification of 20 quality change-related biomarkers. These biomarkers were primarily involved in energy metabolism, reactive oxygen species regulation and primary metabolic pathways including amino acids, lipids and carbohydrates. Low-temperature storage inhibited respiration, preserved cell structure and altered specific glycerophospholipid metabolic pathways. These findings provide molecular insights into low temperature preservation mechanisms and establish a novel framework for metabolomic data analysis in postharvest research.
番荔枝在采后储存期间迅速变质。全面了解这一过程背后的代谢机制对于制定有效的保鲜策略至关重要。代谢组学方法与机器学习相结合为识别与品质相关的生物标志物提供了新机会。本研究使用与生成对抗网络（GAN）和随机森林（RF）分析相结合的非靶向代谢组学，比较了在25°C和10°C下储存的番荔枝品质。研究发现，GAN成功地将代谢组学数据集放大了10倍，从而能够基于RF可靠地识别20种与品质变化相关的生物标志物。这些生物标志物主要参与能量代谢、活性氧调节以及包括氨基酸、脂质和碳水化合物在内的初级代谢途径。低温储存抑制了呼吸作用，保留了细胞结构，并改变了特定的甘油磷脂代谢途径。这些发现为低温保鲜机制提供了分子见解，并为采后研究中的代谢组学数据分析建立了一个新框架。
