An innovative low-cost device based on hyperspectral spectroscopy in the near infrared (NIR) spectral region is proposed for the non-invasive detection of moldy core (MC) in apples. The system, based on light collection by an integrating sphere, was tested on 70 apples cultivar (cv) Golden Delicious infected by Alternaria alternata, one of the main pathogens responsible for MC disease. Apples were sampled in vertical and horizontal positions during five measurement rounds in 13 days’ time, and 700 spectral signatures were collected. Spectral correlation together with transmittance temporal patterns and ANOVA showed that the spectral region from 863.38 to 877.69 nm was most linked to MC presence. Then, two binary classification models based on Artificial Neural Network Pattern Recognition (ANN-AP) and Bagging Classifier (BC) with decision trees were developed, revealing a better detection capability by ANN-AP, especially in the early stage of infection, where the predictive accuracy was 100% at round 1 and 97.15% at round 2. In subsequent rounds, the classification results were similar in ANN-AP and BC models. The system proposed surpassed previous MC detection methods, needing only one measurement per fruit, while further research is needed to extend it to different cultivars or fruits.
The “FLEX 2018” cruise, organized by the CNR-ISMAR in frame of the ESA “FLEXSense Campaign 2018” and CMEMS project, provided a ground station for several bio-optical instruments that investigated the coastal waters of the Tyrrhenian Sea in June 2018. The field measurements were performed in time synergy with Sentinel 3A and Sentinel 3B satellites and HyPlant airborne imaging spectrometer. Active and passive fluorescence were investigated at different scales in coastal waters to support preparatory activities of the FLuorescence EXplorer (FLEX) satellite mission.
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