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Haghshomar, Reza, Mohammadigol, Reza, ValizadehKaji, Babak. (1404). Prediction of Qualitative Properties and Maturity Classification of Fig Fruits using Vis/SWNIR Spectroscopy. , 12(2), 523-532. doi: 10.22059/ijhst.2024.372343.774
Reza Haghshomar; Reza Mohammadigol; Babak ValizadehKaji. "Prediction of Qualitative Properties and Maturity Classification of Fig Fruits using Vis/SWNIR Spectroscopy". , 12, 2, 1404, 523-532. doi: 10.22059/ijhst.2024.372343.774
Haghshomar, Reza, Mohammadigol, Reza, ValizadehKaji, Babak. (1404). 'Prediction of Qualitative Properties and Maturity Classification of Fig Fruits using Vis/SWNIR Spectroscopy', , 12(2), pp. 523-532. doi: 10.22059/ijhst.2024.372343.774
Haghshomar, Reza, Mohammadigol, Reza, ValizadehKaji, Babak. Prediction of Qualitative Properties and Maturity Classification of Fig Fruits using Vis/SWNIR Spectroscopy. , 1404; 12(2): 523-532. doi: 10.22059/ijhst.2024.372343.774

Prediction of Qualitative Properties and Maturity Classification of Fig Fruits using Vis/SWNIR Spectroscopy

International Journal of Horticultural Science and Technology
دوره 12، شماره 2، تیر 2025، صفحه 523-532    اصل مقاله (702.7 K)
نوع مقاله: Research paper
شناسه دیجیتال (DOI): 10.22059/ijhst.2024.372343.774
نویسندگان
Reza Haghshomar1؛ Reza Mohammadigol* 2؛ Babak ValizadehKaji3
1Department of Horticulture Engineering
2Department of Biosystems Engineering, Faculty of Agriculture and Natural Resources, Arak University, 38156-8-8349 ‎Arak, Iran
3Department of Horticultural Sciences, Faculty of Agriculture and Natural Resources, Arak University, 38156-8-8349 ‎Arak, Iran
چکیده
Fruit quality is important in different sections of fruit supply chain including harvest time, packaging, processing, grading, transportation, storage and shelf life. In the present study, the potential of Vis/SWNIR spectral region of 425–950 nm coupled with Chemometrics to predict anthocyanin, taste index (SSC/TA) and flesh firmness of fig fruit was investigated. Besides, the efficiency of ANN, KNN, and DA classifiers to classifying ripe, semi-ripe, and unripe figs were compared. A total of 167 fig fruits were used to calibrate models and validation. The regression ANN and classifiers (KNN, ANN, and DA) performances with common pretreatments (MA, SNV, MSC, etc.) and combinations of them were evaluated. Results showed that MA + 1st derivative + SG combined preprocessing, has highest mean value of RPD equal to 1.55 for flesh firmness prediction (RMSEP = 1.83, rp = 0.76) and model performance for anthocyanin and taste index predicting, wasn’t acceptable. ANN and DA provided mean classification accuracy of 89.86% and 89.52%, with MA+SNV and MA + MSC combined pretreatments, respectively. This study provides necessary information in the application of spectroscopy devices (425-950 nm) for the measurements of fig fruit quality attributes.
کلیدواژه‌ها
Fig (Ficus carica L.)؛ Ripeness؛ Flesh stiffness؛ Taste index؛ Vis/SWNIR spectroscopy
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