| Summary: | Table grapes are very popular for their high nutritional and therapeutic value. The objective of this work was to study the effect of table grapes’ quality property in cold chain logistics for improving the transparency and traceability of table grapes’ cold chain logistics and ensuring the table grapes’ quality and safety. Temperature and relative humidity are monitored by adopting the wireless sensor network (WSN) as the fundamental network infrastructure and adaptive optimal weighted data fusion (AOW) for the adaptive data fusion. The cold chain process, firmness quality and adaptive data fusion of temperature and relative humidity were evaluated in an actual cold chain logistics. The results indicate that the WSN and AOW methods could effectively reflect the real-time temperature and relative humidity information and quality property, improve the transparency and traceability in the cold chain and ensure the preservation of the quality and safety of table grapes. The AOW performance analysis shows that the AOW, whose mean absolute error and mean relative error of the temperature data are 0.06 °C and 8.61% and relative humidity data are 0.12% and 0.23%, respectively, could fuse the sensor data accurately, efficiently and adaptively and meet the actual application requirements.
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