Phetpan, Kittisak

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Phetpan, Kittisak
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kittisak.ph@kmitl.ac.th

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    Item type:Publication,
    Near-infrared hyperspectral imaging combined with machine learning for physicochemical-based quality evaluation of durian pulp
    (2023-06-01)
    Sharma, Sneha
    ;
    Sirisomboon, Panmanas
    ;
    K.C, Sumesh
    ;
    Terdwongworakul, Anupun
    ;
    Phetpan, Kittisak
    This research reports on the application of near-infrared hyperspectral imaging (NIR-HSI) system for predicting the physicochemical properties; dry matter (DM), total soluble solids (TSS), and fat content (FC) of durian. Partial least squares regression (PLSR), support vector machine (SVM), random forest (RF), and 1D convolution neural network (CNN) models: custom, U-Net, and VGG19; were developed to predict DM, TSS, and FC of durian pulp. Feature wavelengths were selected using a genetic algorithm (GA) and successive projection algorithm (SPA). The selected wavelengths were then validated based on the algorithms for regression model development. GA-PLSR model was compelling to predict the DM and FC in durian pulp, which obtained the coefficient of determination for the test set (r<sup>2</sup>) and root mean square error of prediction (RMSEP) of 0.97 and 1.12% for DM and 0.86 and 0.64% for FC, respectively. The GA-PLSR model provided the best result for the TSS prediction with r<sup>2</sup>, and RMSEP of 0.90 and 1.40%, respectively, whereas the SPA-PLSR model based on only thirteen wavelengths attained fair result with the r<sup>2</sup> and RMSEP of 0.79 and 2.03%, respectively. The above results show that the pushbroom NIR-HSI system achieved promising results for estimating DM, TSS, and FC in durian pulp. This research identified the featured wavelengths that can be used to develop a portable and reliable HSI or multispectral system to be installed at durian packaging firms for quality inspection and grading.
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    Item type:Publication,
    Evaluation of physiological properties and texture traits of durian pulp using near-infrared spectra of the pulp and intact fruit
    (2021-04-01)
    Onsawai, Phalanon
    ;
    Phetpan, Kittisak
    ;
    Khurnpoon, Lampan
    ;
    Sirisomboon, Panmanas
    This study aimed to investigate the feasibility of non-destructively predicting physiological properties (color, dry matter, and soluble solids) and texture properties (initial firmness, average firmness, rupture force, rupture distance, toughness, average penetrating force, and penetrating energy) of ‘Monthong’ durian using Fourier transform near-infrared spectroscopy of the pulp of the largest locule, the intact fruit at the largest locule, and the stylar end of the intact fruit. Based on partial least squares regression modeling, the internal quality evaluation of durian obtained by scanning the pulp could provide rough screening capability, with coefficient of determination of validation (r<sup>2</sup>), root mean square error of prediction (RMSEP), and the ratio of standard error of validation to standard deviation (RPD) values for the dry matter content, average penetrating force, and rupture force of 0.89, 3.60%, and 3.27; 0.73, 5.53 N, and 1.95; and 0.74, 6.15 N, and 1.96, respectively. Only the dry matter content of the pulp could be reasonably predicted based on scanning the intact durian fruit at the largest locule, with r<sup>2</sup>, RMSEP, and RPD values of 0.79, 5.23%, and 2.18, respectively. This finding could be applied at the first stage of trade between durian agriculturalists and exporters to prevent the exportation of immature durian and would be helpful for the industries producing frozen durian pulp and intact durian fruit for export.