Journal
APPLIED SCIENCES-BASEL
Volume 9, Issue 18, Pages -Publisher
MDPI
DOI: 10.3390/app9183895
Keywords
'Korla' fragrant pears; cold chain logistic; the multi-sensor technology; back propagation neural network
Categories
Funding
- National Natural Science Foundation of China [71261021]
- Development and Innovation Support Plan of Divisions of Xinjiang Production and Construction Corps [2018BB041]
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Korla fragrant pear is prestigious for its special texture and unique flavor but suffers storage and supply chain difficulties for its deterioration-prone properties. In order to improve the storage quality of Korla fragrant pears during the whole cold chain from the orchard to the customers, the paper deeply researches multiple influencing factors of cold chain logistics and home storage of Korla fragrant pears with multi-sensor technology (MST), such as the temperature, relative humidity, concentrations of oxygen (O-2), carbon dioxide (CO2) and ethylene (C2H4). Cold chain logistics are assessed by sensory evaluation and physiological index measurement, and home storage environments are classified by using back propagation neural network (BPNN) in both refrigerators and ordinary rooms. Experimental results show that the MST-based detectors can improve the accuracy of continuous sensor data acquisition, such that the preservation quality of Korla fragrant pears is effectively enhanced by data analysis on gas contents, firmness, pH, and total soluble solids. These results indicate that Korla fragrant pears stored in refrigerators have a higher acceptance for customers.
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