1Crop Breeding & Cultivation Research Institute, Shanghai Academy of Agricultural Sciences, 1000 Jinqi Road, Fengxian District, Shanghai, 201403, PR China
2School of Life Sciences, Anhui Agricultural University, Hefei, 230036, PR China
3Key Laboratory of Jianghuai Agricultural Product Fine Processing and Resource Utilization of Ministry of Agriculture and Rural Affairs / Anhui Engineering Laboratory for Agro-products Processing, Anhui Agricultural University, Hefei 230036, China
4College of Food Science and Engineering, Northwest A&F University, Yangling, 712100, Shaanxi, PR China
| Received 05 Sep 2024 |
Accepted 28 Mar 2025 |
Published 05 Apr 2025 |
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.
