Near‐Infrared ( NIR ) Spectroscopy: An Innovative Approach for Detecting Infestation by Ceratitis capitata in Grapes

ABSTRACT The species, Ceratitis capitata (Wiedemann, 1824), is a quarantine pest for markets such as the USA and Japan, necessitating that Brazil implement management protocols to export fresh fruits. Near‐infrared (NIR) spectroscopy has been investigated as a rapid, non‐destructive method for pest detection, offering a potential alternative to the destructive fruit sampling in packing houses. The study aimed to evaluate the efficacy of NIR spectroscopy for detecting infestation (eggs and larvae) of C. capitata in ‘Itália’ grapes ( Vitis vinifera L.) and to assess the chemical changes in the fruits resulting from larval feeding over time. Two experimental datasets were established, each containing samples of healthy grapes and grapes infested with C. capitata . Spectra were collected from 240 samples in Dataset 1 and from 40 samples in Dataset 2 at 2, 4, 6, 8, 10, and 12 days after the start of the experiment. Fruits from Dataset 1 were also analyzed for titratable acidity (TA), soluble solids (SS) content, and pH. In Dataset 1, lower mean acidity values were found in infested fruits at 4 (0.27 g 100 mL −1 ) and 6 (0.26 g 100 mL −1 ) days, and in non‐infested fruits at 8 (0.29 g 100 mL −1 ) and 10 (0.24 g 100 mL −1 ) days. Higher mean SS values were found at 2 (13.82 g 100 mL −1 ) and 12 (14.32 g 100 mL −1 ) days. The partial least squares discriminant analysis (PLS‐DA) successfully classified samples and achieved high performance metrics for Datasets 1 and 2, with accuracies of 97% and 100%, a precision of 100%, sensitivities of 93% and 100%, and a specificity of 100%, respectively. In Dataset 2, there was variation in the chemical composition of the grapes over time, with 100% correct classification of the samples. The study demonstrates that NIR spectroscopy is a viable and accurate method for the early detection of C. capitata infestation in grapes and for monitoring the associated chemical changes in fruit composition over time, offering a powerful tool for postharvest quality control.