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- Title
Spoilage Monitoring and Early Warning for Apples in Storage Using Gas Sensors and Chemometrics.
- Authors
Yin, Limei; Jayan, Heera; Cai, Jianrong; El-Seedi, Hesham R.; Guo, Zhiming; Zou, Xiaobo
- Abstract
In the process of storage and cold chain logistics, apples are prone to physical bumps or microbial infection, which easily leads to spoilage in the micro-environment, resulting in widespread infection and serious post-harvest economic losses. Thus, development of methods for monitoring apple spoilage and providing early warning of spoilage has become the focus for post-harvest loss reduction. Thus, in this study, a spoilage monitoring and early warning system was developed by measuring volatile component production during apple spoilage combined with chemometric analysis. An apple spoilage monitoring prototype was designed to include a gas monitoring array capable of measuring volatile organic compounds, such as CO2, O2 and C2H4, integrated with the temperature and humidity sensor. The sensor information from a simulated apple warehouse was obtained by the prototype, and a multi-factor fusion early warning model of apple spoilage was established based on various modeling methods. Simulated annealing–partial least squares (SA-PLS) was the optimal model with the correlation coefficient of prediction set (Rp) and root mean square error of prediction (RMSEP) of 0.936 and 0.828, respectively. The real-time evaluation of the spoilage was successfully obtained by loading an optimal monitoring and warning model into the microcontroller. An apple remote monitoring and early warning platform was built to visualize the apple warehouse's sensors data and spoilage level. The results demonstrated that the prototype based on characteristic gas sensor array could effectively monitor and warn apple spoilage.
- Subjects
GAS detectors; STANDARD deviations; GAS storage; COLD storage; CHEMOMETRICS; ORCHARDS; APPLES
- Publication
Foods, 2023, Vol 12, Issue 15, p2968
- ISSN
2304-8158
- Publication type
Article
- DOI
10.3390/foods12152968