Rapid and non-destructive detection of insect infestations on intact mango by means of near infrared spectroscopy

Abstract

Postharvest diseases due to insect infestations are the main critical problems in mango fruit. They reduce whole fruit quality and cause severe losses. Mango fruits are exposed to disease due to wounds that are infected by pathogens after harvest. Sometimes it is difficult to detect and determine those diseases in intact form. Therefore. The main aim of this present study is to rapidly detect postharvest disease on intact mango using near infrared spectroscopy (NIRS). Diffuse reflectance spectrum of near infrared was acquired for a total of 40 intact mango samples (cv. Gadong) in wavelength range from 1000 to 2500 nm with an average increment of 0.02 nm and 32 scans co-Added per acquisition. Spectra data were enhanced using first derivative (D1) and multiplicative scatter correction (MSC) methods. Mango disorders due to postharvest diseases were detected by projecting spectra data onto principal component analysis (PCA). The results showed that infected mangos can be detected and classified precisely with total explained variance of 99% from 2 principal components (PCs). Moreover, D1 and MSC enhanced spectra data were also generated precise classification results using 2 PCs. Thus, it may conclude that NIRS can be employed to rapidly detect infected diseases on intact mango fruits with excellent results.