Insights of freshness phenotype detection for postharvest fruit and vegetables

文献类型： 外文期刊

第一作者： Wang, Qiankun

作者： Wang, Qiankun;He, Hui;Liu, Chenxia;Wang, Chunfang;Chen, Bingjie;Wang, Xiao;Qiao, Yongjin;Liu, Hongru;Niu, Qingfeng;Wang, Ke;Zhu, Wenxin

作者机构：

关键词： Intelligent packaging; Nondestructive testing; Shelf-life prediction; Quality indicators; Difference between quality and freshness

期刊名称：PLANT PHENOMICS （ 影响因子：6.4； 五年影响因子：7.1 ）

ISSN： 2643-6515

年卷期： 2025 年 7 卷 2 期

页码：

收录情况： SCI

摘要： The freshness phenotype of fruit and vegetables is a critical determinant of consumer satisfaction, selection, and public health, which plays a pivotal role in postharvest quality management. This paper presents a review of the definition and detection techniques used to assess and maintain this vital freshness phenotype. Advanced intelligent packaging technologies, that incorporate sensors, indicators, and data carrier systems, and their roles in dynamically monitoring the freshness phenotype during storage and transportation are discussed. The integration of nondestructive testing (NDT) methods such as near-infrared spectroscopy (NIR), hyperspectral imaging (HSI), machine vision, and light detection and ranging (LiDAR) offers real-time, precise assessments of the freshness phenotype without compromising the integrity of the produce. By understanding the underlying mechanisms of the fruit and vegetable freshness phenotype, this paper discusses the definition, detection technologies, and gaps that require further research. The integration of advanced quantitative models with NDT and intelligent packaging solutions has the potential to reduce food waste. This advancement will lead to better quality control, extended shelf life, and increased consumer confidence in fresh produce, driving innovation and application within the food industry.

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