Professor Jiyong Shi, School of Food and Biological Engineering, Jiangsu University published a research paper recently entitled “A visible colorimetric sensor array based on chemo-responsive dyes and chemometric algorithms for real-time potato quality monitoring systems” in the journal “Food Chemistry (Q1, IF: 9.231)”. A graduate student of the year 2021, “Yuqing Wu,”, is the first author of the paper. Professor Jiyong Shi is the corresponding authors of the paper.
Potato resistance, adaptability, short growth cycle, high nutritional value and long industrial chain, has become an important pillar of China's poverty alleviation, western development, the main vegetables and export of high-efficiency crops, food and industrial starch processing of important raw materials, to increase China's food production, promote farmers to increase income, made a great contribution. However, potatoes are susceptible to dry rot, ring rot, soft rot, black heart disease and other hazards, to the potatoes of fresh food and processing bring great economic losses, storage disease caused by storage losses of up to 30% to 50%, has become a bottleneck affecting the potato storage and preservation of the problem. Therefore, with the advancement of the potato industry and the popularity of potato processing products, to protect the quality of potatoes in the storage and transportation process, for the future development of the potato industry is of great significance.
The colorimetric sensor array real-time monitoring system with multivariate analysis was established for discrimination of potato varieties with different types and degrees of corruption. The characteristic volatile compounds of fresh, dry rot and soft rot potatoes was identified by Gas Chromatography-Mass Spectrometry and the 3 × 4 array was fabricated to capture the characteristics volatile compounds. The sensor array system produced a visible color difference map upon its exposure to volatile compounds of potato. Discrimination of potatoes with the same types or different degrees of corruption was subsequently achieved using principal component analysis and hierarchical clustering analysis dendrogram. The k-nearest neighbor algorithm for potato classification provided the best results with 100% discrimination on both the calibration and prediction sets. The linear discriminant analysis model achieved a 99.76% calibration set and a 99.31% prediction set for potato grading. An online warning device based on array was devised to realize unmanned monitoring for potato quality.
Figure 1. Color difference diagram of different gas-sensitive materials
Figure 2. Qualitative analysis of potatoes with different spoilage ratios
Professor Jiyong Shi has long been engaged in the research on Qualitative analysis of potatoes with different spoilage ratios. He was awarded the “Distinguished Younng Scholars of Jiangsu Province” in 2022, the “Jiangsu Specially Appointed Proressor” in 2020.
