We investigated the ripening and skin greasiness of “Hongro” apples during storage at 20 °C. Postharvest treatment using 100 μLL ethylene accelerated ripening and increased greasiness, whereas treatment using 1 μLL 1-methylcyclopropene delayed ripening and reduced greasiness. Scanning electron microscopy showed changes in cuticular wax structure linked to greasiness. Metabolic analysis identified specific metabolites related to greasiness, which varied upon postharvest treatment. Greasiness was positively associated with ethylene production and butyl-9,12-octadecadienoate content. Random forest modeling predicted greasiness levels with high accuracy, with root mean square error values of 0.322 and 0.362 for training and validation datasets, respectively. These findings illuminate the complex interplay between postharvest treatment, apple ripening, wax composition, and skin greasiness. The application of predictive models exemplifies the potential for technology-driven approaches in agriculture and aids in the development of postharvest strategies to control greasiness and maintain fruit quality.

中文翻译：

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采后“红罗”苹果果皮油脂与角质层蜡质的关系

我们研究了“Hongro”苹果在 20°C 储存期间的成熟度和果皮油腻程度。使用 100 μLL 乙烯的采后处理加速了成熟并增加了油腻感，而使用 1 μLL 1-甲基环丙烯的处理则延迟了成熟并减少了油腻感。扫描电子显微镜显示角质层蜡结构的变化与油腻有关。代谢分析确定了与油腻性相关的特定代谢物，这些代谢物因采后处理而异。油腻感与乙烯产量和9,12-十八碳二烯酸丁酯含量呈正相关。随机森林模型可以高精度预测油腻程度，训练数据集和验证数据集的均方根误差值分别为 0.322 和 0.362。这些发现阐明了采后处理、苹果成熟、蜡成分和皮肤油脂之间复杂的相互作用。预测模型的应用体现了技术驱动方法在农业中的潜力，并有助于制定采后策略来控制油腻和保持水果质量。