NIR based wireless sensing approach for fruit monitoring
Meng Wang, D. Luo, Yunyue Yang, Marina Ņikitina, Xiaoshuan Zhang, Xinqing Xiao
Abstract
Monitoring the storage phase of grapes is a key issue as it is closely related to berry quality, so it is essential to investigate a rapid and comprehensive method of non-destructive wireless inspection applied to the berry storage process. In this study, a cost-effective optical measurement system was designed, built, and tested to determine optimal storage results. NIR spectral measurement system covers 6 separate on-device filters from 610 nm to 860 nm. The experiments were performed on Kyoho grapes. In addition, each sample was analyzed for soluble solids content (SSC) by conventional laboratory methods and used as a reference parameter. The results showed that the use of the artificial neural network (ANN) (RMSEP = 0.62 and Rp2 = 0.69) worked best and could be used for preliminary screening of fruit quality.