Guo Xiaolei, Ahlawat Yogesh K, Liu Tie, Zare Alina
University of Florida, Department of Electrical and Computer Engineering, Gainesville, Florida, USA.
University of Florida, Horticultural Sciences Department, Gainesville, Florida, USA.
Plant Phenomics. 2022 May 9;2022:9761095. doi: 10.34133/2022/9761095. eCollection 2022.
Fresh fruit and vegetables are invaluable for human health; however, their quality often deteriorates before reaching consumers due to ongoing biochemical processes and compositional changes. We currently lack any objective indices which indicate the freshness of fruit or vegetables resulting in limited capacity to improve product quality eventually leading to food loss and waste. In this conducted study, we hypothesized that certain proteins and compounds, such as glucosinolates, could be used as one potential indicator to monitor the freshness of broccoli following harvest. To support our study, glucosinolate contents in broccoli based on HPLC measurement and transcript expression of glucosinolate biosynthetic genes in response to postharvest stresses were evaluated. We found that the glucosinolate biosynthetic pathway coincided with the progression of senescence in postharvest broccoli during storage. Additionally, we applied machine learning-based hyperspectral image (HSI) analysis, unmixing, and subpixel target detection approaches to evaluate glucosinolate level to detect postharvest senescence in broccoli. This study provides an accessible approach to precisely estimate freshness in broccoli through machine learning-based hyperspectral image analysis. Such a tool would further allow significant advancement in postharvest logistics and bolster the availability of high-quality, nutritious fresh produce.
新鲜水果和蔬菜对人类健康至关重要；然而，由于持续的生化过程和成分变化，它们在到达消费者手中之前质量常常会下降。我们目前缺乏任何能表明水果或蔬菜新鲜度的客观指标，这导致改善产品质量的能力有限，最终造成食物损失和浪费。在本研究中，我们假设某些蛋白质和化合物，如硫代葡萄糖苷，可以作为监测西兰花收获后新鲜度的一个潜在指标。为支持我们的研究，基于高效液相色谱法（HPLC）测量了西兰花中硫代葡萄糖苷的含量，并评估了硫代葡萄糖苷生物合成基因在采后胁迫下的转录表达。我们发现硫代葡萄糖苷生物合成途径与采后西兰花在储存期间衰老的进程一致。此外，我们应用基于机器学习的高光谱图像（HSI）分析、解混和亚像素目标检测方法来评估硫代葡萄糖苷水平，以检测西兰花采后的衰老情况。本研究提供了一种通过基于机器学习的高光谱图像分析精确估计西兰花新鲜度的可行方法。这样一种工具将进一步推动采后物流的显著进步，并增加优质、营养丰富的新鲜农产品的供应。
