Investigation of Mango Flesh Disorder Using Near-Infrared Spectroscopy (NIRS)

Authors

  • Katthareeya Sonthiya Department of Plant and Soil Sciences, Faculty of Agriculture, Chiangmai University, Chiang Mai, Thailand
  • Patomporn Chaiya Department of Plant and Soil Sciences, Faculty of Agriculture, Chiangmai University, Chiang Mai, Thailand
  • Jutamas Sanguansub Department of Plant and Soil Sciences, Faculty of Agriculture, Chiangmai University, Chiang Mai, Thailand
  • Chantalak Tiyayon Department of Plant and Soil Sciences, Faculty of Agriculture, Chiangmai University, Chiang Mai, Thailand
  • Phonkrit Maniwara Postharvest Technology Research Center, Faculty of Agriculture, Chiangmai University, Chiang Mai, Thailand
  • Pimjai Seehanam Postharvest Technology Innovation Center, Science, Research and Innovation Promotion and Utilization Division Office of the Ministry of Higher Education, Science, Research and Innovation, Bangkok, Thailand

DOI:

https://doi.org/10.14456/jare-mju.2025.51

Keywords:

nondestructive evaluation, chemometrics, internal breakdown, spongy tissue

Abstract

Export quality of ‘Nam Dok Mai Sithong’ mango has been reduced due to internal disorders that are undetectable by visual inspection. These flaws lead to loss of export value and importer’s trust. Therefore, this research aimed to investigate the feasibility of using NIRS and advanced chemometrics to detect internal disorders of the mangoes. A total of 38 fruits of ‘Nam Dok Mai Sithong’ mango, aged 115–120 days after flowering were harvested. Different areas of fruit peel were designated into different categories for near-infrared (NIRS) spectra measurement, consisting of 100 normal flesh spots, 100 internal breakdown spots, and 97 spongy tissue spots. Interactance measurement was used in wavenumbers of 4,000–12,500 cm-1. Classification models were developed using Self-Organizing Map (SOM) and classification accuracies were evaluated. Results from Principal Component Analysis (PCA) were unable to distinguish among the 3 different characteristics of mango flesh. On the other hand, classification models of SOM with 25,000 iterations were able to classify mango flesh into 2 classes (normal and disorder) and 3 classes (normal, internal breakdown, and spongy tissue), providing correct classification rates (%CC) of 83.1 and 82.4%, respectively. Therefore, application of near-infrared spectroscopy using SOM model provided more than 80% classification accuracy for classifying mango flesh into normal, internal breakdown, and spongy tissue symptoms.

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Figure 1 Images of cut-open in mango with of normal flesh (A), internal breakdown (B), and spongy tissue (C) symptoms

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Published

2025-12-20

How to Cite

Sonthiya, K. ., Chaiya, P. ., Sanguansub, J. ., Tiyayon, C. ., Maniwara, P. ., & Seehanam, P. . (2025). Investigation of Mango Flesh Disorder Using Near-Infrared Spectroscopy (NIRS). Journal of Agricultural Research and Extension, 42(3), 141–150. https://doi.org/10.14456/jare-mju.2025.51

Issue

Vol. 42 No. 3 (2025): September - December 2025

Section

Research Article

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