Sirisomboon, Panmanas
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Preferred name
Sirisomboon, Panmanas
Alternative Name
Sirisomboon, P.
Main Affiliation
Email
panmanas.si@kmitl.ac.th
6 results
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Item type:Publication, Evaluating limit of detection and quantification for higher heating value and ultimate analysis of fast-growing trees and agricultural residues biomass using NIRS(2023-10-09); Shrestha, Bim PrasadAccurate non-destructive assessment of biomass energy properties is essential for optimizing its use as an alternative fuel. In this study, 200 biomass samples were used to determine higher heating value (HHV) and 120 biomass samples for analyzing ultimate analysis parameters using near-infrared spectroscopy within the full wavenumber range of 12489.48 – 3594.87 cm<sup>-1</sup>. The samples were grounded, and five different types of partial least squares regression (PLSR) models were developed using traditional preprocessing, multi-preprocessing (MP) with 5 range, MP with 3 range, genetic algorithm, and successive projection algorithm. Limit of detection (LOD) and quantification (LOQ) were calculated using the best-performing model among five different PLSR models for HHV in kJ/kg, as well as the weight percentage (wt.%) of carbon (C), oxygen (O), hydrogen (H), and nitrogen (N). The LOD and LOQ for HHV were calculated as 622.42 kJ/kg and 1886.13 kJ/kg, respectively. Additionally, LOD and LOQ for ultimate analysis parameters, including C, O, H, and N were calculated as: 3.24 weight percentage (wt.%) and 9.81 wt.% for C, 2.04 wt.% and 6.18 wt.% for O, 0.35 wt.% and 1.05 wt.% for H, and 0.22 wt.% and 0.68 wt.% for N. The LOD and LOQ values for HHV, C, O, and H were lower than the minimum reference values used for model development, demonstrating the models’ high sensitivity and potential to reliably detect and precisely quantify these parameters. However, the LOD and LOQ values exceeded the minimum reference value used during model development for the N, indicating that the selected models have certain limitations in assessing the N content in biomass. The sample range should be expanded for wt.% of N to enhance the model’s performance, surpassing the LOD and LOQ values. This will improve the overall sensitivity of the model for reliable detection and quantification of N content in biomass samples. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Classification of N, P, and K concentrations in durian (Durio zibethinus murray cv. mon thong) leaves using near-infrared spectroscopy(2022-08-24); ; A good durian fruit should be supported by sufficient nutrient concentrations. If farmers can quickly determine the nutrient concentration in leaves, they can control fertilisation. Near-infrared (NIR) spectroscopy is a rapid non-destructive test for estimating nutrient concentration. Measuring nutrient concentrations requires chemical analysis and is a time-consuming process. The aim of this paper is a preliminary test for classifying the N, P, and K concentration levels to determine the possibility of creating models in the future to help farmers obtain information on durian tree nutrient requirements quickly. The models reported in this paper were created by PLS-DA, which had higher accuracy than SVM and the SIMCA method. Fresh durian leaf samples were used, and the spectra provided greater accuracy than the dried ground leaf sample spectra. The classification models had an accuracy of 88.89, 81.25, and 86.36% for predicting N, P, and K, respectively. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Improving the non-destructive maturity classification model for durian fruit using near-infrared spectroscopy(2023-03-01); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Development of the partial least-squares model to determine the soluble solids content of sugarcane billets on an elevator conveyor(2021-01-01); ; This study aimed to determine the optimum multivariate model for monitoring the soluble solids content (SSC) of sugarcane billets being transferred on a conveyor. The study covered two main issues: the exploration of an appropriate spectral range (450–900 nm versus 700–900 nm) and the assessment of the influence of different levels of cane billets on an elevator via modelling to predict the SSC values. Partial least squares regression (PLSR) was used for model development. Modelling using the range of 450–900 nm employed 4 latent variables (LVs) and showed the coefficient of determination (R<sup>2</sup>) and root mean squares error of prediction (RMSEP) of 0.83 and 0.29 °Brix, respectively. This caused the model established using the range of 700–900 nm, employed 3 LVs and provided the R<sup>2</sup> and RMSEP values of 0.81 and 0.31 °Brix, respectively, seems more appropriate. In case of assessing the different cane levels on the conveyor, the outcomes presented model performance of the full and half cane levels in predicting half and full cane datasets with R<sup>2</sup> and RMSEP of 0.52 and 0.55 °Brix and 0.53 and 0.48 °Brix, respectively. This showed that the different levels affected the SSC predictive accuracy of the model. The combined model was developed to cover variations of this difference and was used to predict two external sets. The predictions of ninety and thirty samples that were collected from the same and different growing seasons as the samples for the modelling presented the R<sup>2</sup>, RMSEP and RPD of 0.70, 0.42 °Brix and 1.83 and 0.56, 0.42 °Brix and 2.00, respectively. - Some of the metrics are blocked by yourconsent settings
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); ; 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. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Application of near-infrared spectroscopy in detection of steroids adulteration in traditional thai medicines(2022-01-01); This study aimed to focus on applying near-infrared (NIR) spectroscopy to identify the adulteration of traditional Thai medicine products (TTM) with steroids. One hundred and ten samples were prepared with pure TTM and ten different steroid concentrations (0.25-5 mg steroid/g TTM). Fourier transform near-infrared (FT-NIR) spectrometer was used to scan TTM samples. The partial least squares (PLS) regression was used for the NIR spectroscopic model development to predict the level of steroid adulteration in TTM. For classification analysis, the principal component analysis (PCA) was used to discriminate 11 groups of raw TTM spectra (220 spectra). The developed PLS model accompanied by 3 latent variables (LVs) could predict the steroid content in TTM accurately with the coefficient of determination of prediction (r<sup>2</sup>) of 98.20%, root mean square error of prediction (RMSEP) of 0.22 mg steroid/g TTM, and residual prediction deviation (RPD) of 7.46. Furthermore, the PCA approach was possible to discriminate among the groups of TTM. The study showed NIR spectroscopy's capability to be used as a powerful technique to evaluate the steroid adulterated in TTM. This report is useful for food and drug association, patients, pharmaceuticals, and medical sectors.