Sirisomboon, Panmanas

Preferred name

Alternative Name

Sirisomboon, P.

Main Affiliation

School of Engineering

panmanas.si@kmitl.ac.th

Now showing 1 - 10 of 102

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Deep neural networks (DNNs) chemical compositions estimation of fresh durian in-line via near infrared spectroscopy
(2025-06-01)
Posom, Jetsada
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Saenphon, Chirawan
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Ditcharoen, Sirirak
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Pitak, Lakkana
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Sirisomboon, Panmanas
Near infrared (NIR) spectroscopy and deep neural network (DNN) models were adopted for evaluating the nutritional compositions in durian pulp. The quality inspection of durians through online channels remains challenging because consumers cannot directly touch or smell the fruit. This leads to issues with substandard durians, such as unripe ones or those infested with pests. One hundred and sixty durian samples of Mon Thong varieties were used in this experiment. Then, the collected NIR spectra were augmented to improve the generalization ability of regression models. Deep neural network (DNNs) regressions were developed. The results showed that deep neural network (DNN) regression model possessed the best prediction performance, which were provided performance index. Almost all the best performance models were developed from the second derivative, except for the fat content model, which was developed from raw spectra. The best total soluble solids (TSS) model provided the coefficient of determination of calibration (R2c) and root mean square error of calibration (RMSEc) were 0.84 and 2.25 % and coefficient of determination of calibration (R2p), root mean square error of prediction (RMSEp) and ratio of performance to deviation (RPD) were 0.72 2.92 % and 1.92, respectively, and those of dry matter content (DMC) were provided R2c and RMSEc were 0.997, 0.58 %, and for prediction set provided R2p, RMSEp and RPD were 0.94, 3.13 %, and 4.21, respectively. For fat content (FC), they have also provided R2c and RMSEc were 0.84, 0.36 (g/100 g), while it provided R2p, RMSEp and RPD were 0.86, 0.50 (g/100 g), and 2.72, respectively. Moreover, for total sugar content (TSC) value, it also gave high accuracy, which provided R2c and RMSEc were 0.93, 0.49 (g/100 g) and R2p, RMSEp, and RPD were 0.91, 0.81 (g/100 g), 3.44, and for starch content (SC) also provided R2c and RMSEc were 0.93, 0.49(g/100 g) and R2p, RMSEp, and RPD were 0.76, 2.79 (g/100 g), 2.09, respectively. Therefore, the proposed method offers an ultrasensitive and effective strategy for estimation of nutritional compositions.
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Modified specific gravity method for estimation of starch content and dry matter in cassava
(2021-07-01)
Maraphum, Kanvisit
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Saengprachatanarug, Khwantri
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Wongpichet, Seree
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Phuphuphud, Arthit
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Sirisomboon, Panmanas
An empirical model for the estimation of starch content (SC) and dry matter (DM) in cassava tubers was developed as an alternative method to polarimetry and dry oven. These improved estimation equations were developed based on the specific gravity (SG) method. To improve accuracy, the one hundred-seventy-four sample were obtained from four commercial varieties of cassava in Thailand including KU50, CMR38-125-77, RY9 and RY11, respectively. The age of sample collected from four to twelve months after planting was used in this experiment. The empirical model was created from their relationships between SG obtained from small sample size (~100 g) and its SC and DM. The SG for cassava was strongly correlated with the SC and DM, with values for the coefficient of determination (R2) of 0.81 and 0.83, respectively. The SC showed a high correlation with the DM, with R2 of 0.96. To confirm that the empirical model was effective when applied to other samples, unknown samples collected from another area were tested, and the results showed a standard error of prediction (SEP) of 1.02%FW and 3.49%, mean different (MD) of -0.66%FW, -0.89% for the SC and DM, respectively. Hence, our empirical equation based on a modified SG method could be used to estimate the SC and DM in cassava tubers. It can help breeders to reduce costs and time requirements. Moreover, breeders could be used the methods to evaluate the SC and DM from the tuber formation to harvesting stage and monitoring the changes in SC and DM during breeding.
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Near infrared spectroscopy as an alternative method for rapid evaluation of toluene swell of natural rubber latex and its products
(2018-06-01)
Lim, Chin Hock
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Sirisomboon, Panmanas
Toluene swell or equilibrium swelling is universally used by rubber factories to measure the degree of crosslink of their compounded or prevulcanized latices at different stages of production. To apply near infrared spectroscopy for rapid and accurate quality control, spectral acquisition of prevulcanized latex, thin film and thick film was performed using a Fourier transform near infrared spectrometer in diffuse reflection mode across the wavenumber range of 12,500–3600 cm1. For prevulcanized latex an effective model was developed using partial least squares regression with preprocessing (first derivative + straight line subtraction method). The coefficient of determination (r2), root mean square error of cross validation and bias of the validation set were 0.71, 3.93% and 0.005%, respectively. For the thin film model the r2, root mean square error of cross validation and bias were 0.65, 4.01% and 0.028%, respectively. Whereas for the thick film model the r2, root mean square error of cross validation and bias were 0.70, 4.00% and 0.006%, respectively. Three models including prevulcanized latex, thin film and thick film were validated by 23 unknown samples, providing standard error of prediction and bias of 5.357 and 2.494, 4.565 and 1.001 and 3.641 and 0.961%, respectively, for prevulcanized latex, thin film and thick film. The model developed for the thick film spectra gave the best results.
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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, Bijendra
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Shrestha, Zenisha
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Posom, Jetsada
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Sirisomboon, Panmanas
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Shrestha, Bim Prasad
Accurate 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-1. 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.
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Application of baby corn husk as a biological sustainable feedstock for the production of cellulase and xylanase by Lentinus squarrosulus Mont.
(2023-02-01)
Vichitraka, Asanee
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Somboon, Pichayada
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Tantratian, Sumate
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Onmankhong, Jiraporn
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Sirisomboon, Panmanas
In an effort to use baby corn husk (BCH) as a sustainable feedstock for cellulase and xylanase production by the Lentinus squarrosulus Mont. isolate LS-YA (LSM-LS-YA), a suitable pretreatment method and fermentation strategies were developed. BCH pretreated with 1 M sodium hydroxide for 90 min, an alkaline pretreatment, exemplified an appropriate pretreatment method. In a 10-L external Venturi injector bioreactor, the highest cellulase and xylanase production was 4.12 ± 0.36 unit/mL and 6.15 ± 0.36 unit/mL, respectively, when 1 g/L diammonium hydrogen phosphate was used as the nitrogen source and the aeration rate was controlled at 0.2 vvm. This study provides an informative perspective on the production of cellulase and xylanase from agricultural lignocellulosic materials, which could reduce agricultural waste while supporting a zero-waste circular economy, and this fermentation process would be applicable to larger-scale production.
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Physical properties of green soybean: Criteria for sorting
(2007-03-01)
Sirisomboon, Panmanas
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Pornchaloempong, Pimpen
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Romphophak, Teeranud
The objective of this research was to explore the possibility in developing a criteria for green soybean (Glycine max variety AGS 292) sorter. Green soybean could be classified into two main categories by its usage; the perfect pods (3-seed pod and 2-big seed pod) contained 47%, the rest was imperfect pods including 2-small seed pod, 1-seed pod, atrophied pod, twisted pod, and defected pod. Some important physical characteristics were investigated including width, length, thickness, pod weight, pod projected area, apparent density, bulk density, and seed firmness. The results illustrated that the perfect pods had length, pod weight, projected area and seed firmness significantly larger than the imperfect pods. All pod groups had apparent density equal or lower than water. Among all pod groups, the 2-big seed pods had the highest bulk density, thickest pod, and the firmest seed. The application of these physical properties for green soybean sorting was also proposed. © 2006 Elsevier Ltd. All rights reserved.
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Rapid evaluation of fat content in curry soup containing coconut milk by using near infrared spectroscopy
(2018-02-01)
Cheevitsopon, Ekkapong
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Sirisomboon, Panmanas
The feasibility of a near infrared spectroscopy to evaluate the fat content in instant curry soup containing coconut milk including green curry, red curry, massaman curry and panang curry was investigated. The soup samples were collected from a processing line and as the finished product. There were also fat content-adjusted samples where the curry was made from the same recipe as in the processing line but increasing by 30, 60 and 90% coconut milk and reducing by 30, 60 and 90% coconut milk from normal. A Fourier transform near infrared spectrometer was used to collect scans. A partial least squares regression model for fat content was established using near infrared spectral data in conjunction with reference data, which was validated using a leave-one-out cross-validation and test set validation. The test set validation, using a set of unknown samples, showed better prediction performance. The best model developed using vector normalization spectral pre-treatment on 9404–7498 and 6102–5446 cm−1 provided coefficient of determination, root mean square error of prediction, bias and ratio of performance to interquartile values of 0.90, 0.9%, −0.1% and 1.2, respectively, for the validation samples. However, the model developed using samples without fat content adjusted samples gave a slightly lower coefficient of determination (0.89), but provided a lower root mean square error of prediction (0.5%) and acceptable ratio of standard error of validation to the standard deviation (3.2). In addition, the vibration bands of CH<inf>2</inf> which was in the long chain fatty acid moiety highly influenced the prediction of fat content in the curry soup. The near infrared spectroscopy protocol developed for the determination of fat could be applied in the instant curry soup production line.
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Potential of near infrared spectroscopy as a rapid method to detect aflatoxins in brown rice
(2019-06-01)
Dachoupakan Sirisomboon, C.
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Wongthip, P.
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Sirisomboon, P.
Brown rice is a main popular health food with high nutritional value and health benefits. As a result of poor post-harvest drying and inappropriate storage conditions, rice grains are often damaged through fungal spoilage as well as mycotoxin production. The objective of this research was to evaluate the possibility of using the near infrared spectroscopy, with a wavenumber range between 12500 and 4000 cm−1 (800–2500 nm), as a rapid method for detection of aflatoxins in brown rice. Firstly, storage trials were carried out to generate representative of samples contaminated and non-contaminated with aflatoxins. These data were used to create a partial least squares regression model using 120 brown rice samples with the required near infrared spectral data and aflatoxin concentration levels that were determined using a standard enzyme-linked immunosorbent assays method. The accuracy of developed models was externally validated using the test set. The statistical model developed from the treated spectra (vector normalization; SNV) provided the best accuracy in prediction with a coefficient of determination of prediction (r2) of 0.95, a root mean square error of prediction of 415.00 µg kg−1 and a bias −54.00 µg kg−1. The model developed showed good predictive performance which suggests that it could have practical applications as a rapid method to detect aflatoxins in brown rice.
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Physical and mechanical properties of Jatropha curcas L. fruits, nuts and kernels
(2007-06-01)
Sirisomboon, P.
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Kitchaiya, P.
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Pholpho, T.
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Mahuttanyavanitch, W.
The post-harvest physical and mechanical properties of Jatropha curcas L. fruits, nuts and kernels were investigated and reported, and their application was also discussed. The physical properties studied include moisture content, 1000-unit mass, fruit part fraction, dimensions, geometric mean diameter, sphericity, bulk density, solid density, porosity, surface area, specific surface area, static friction coefficient on various surfaces and angle of repose. The mechanical properties were rupture force, deformation at rupture point, deformation ratio at rupture point, hardness and energy used for rupture (toughness). The hull of the fruit had very high moisture content compared to nut shell and kernel. The whole fruit contained 77.03% w.b. moisture content. The sphericity values indicated that fruit shape (0.95) is close to a sphere compared to nut (0.64) and kernel (0.68), both of which are close to an ellipsoid. Bulk densities of fruits, nuts and kernels were 0.47, 0.45 and 0.42 g/cm3, the corresponding solid densities were 0.95, 1.04 and 1.02 g/cm3, and the corresponding porosities were 50.53%, 56.73% and 58.82%, respectively. The surface area of fruit was larger than those of nut and kernel, by 5.88% and 10.24%, respectively. The static coefficient of friction and angle of repose of kernels on all surfaces studied (plywood, steel, and stainless steel) were the highest as the surface is viscous and hardness is less. Rupture force, hardness and toughness of fruit, nut and kernel were 135.39, 146.63 and 67.72 N; 30.58, 69.98 and 38.52 N/mm and 300.88, 124.44 and 51.61 N mm, respectively. © 2007 IAgrE.
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Determination of dry matter and soluble solids of durian pulp using diffuse reflectance near infrared spectroscopy
(2015-01-01)
Onsawai, Phalanon
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Sirisomboon, Panmanas
Fourier transform near infrared spectroscopy was used as a non-invasive technique for the determination of dry matter and soluble solids of durian pulp. A set of 25 fruit was randomly harvested every 10 days, starting from 80 days until 127 days after the onset of fruit development covering six levels of maturity (80 days, 90 days, 100 days, 110 days, 120 days and 127 days). After applying ethephon on the fruit stems, the fruits were kept for 3 days at room temperature and allowed to ripen. Only the pulp of the durian was scanned. The dry matter and soluble solids reference values of the samples were determined by a hot-air-oven method and using a refractometer, respectively. Prediction models using half the samples related the spectral data, and dry matter and soluble solids data were subsequently established using partial least-squares regression and validated using the other half of the samples in a prediction set. A full cross-validation was also generated using all 149 samples. Both the half-of-the-samples model and the all-sample model were then validated using a true validation set of samples collected in a later year. When tested against the validation half of the samples, the halfof- the-samples model predicted dry-matter content with a coefficient of determination (r2) and root mean square error of prediction (RMSEP) of 0.89 and 3.60%, respectively, and for soluble solids content 0.55 and 1.63 °Brix (Bx), respectively. When tested on samples from a later season, the model for dry-matter content returned an r2, RMSEP and bias of 0.26, 6.10% and 2.16%, respectively, and for soluble solids content 0.27, 1.25 °Bx and 1.09 °Bx, respectively. The cross-validated model for dry matter yielded a slightly better r2 and root mean square error of cross-validation (RMSECV) of 0.90 and 3.58%, respectively, however, the model for soluble solids did not provide a better r2 and RMSECV: 0.51 and 1.81 °Bx, respectively. When tested on samples from a later season, the cross-validated models gave, r2, RMSEP and bias of 0.15, 5.17% and 1.49%, respectively, for dry-matter content, and for soluble solids content 0.37, 1.32 °Bx and 1.23 °Bx, respectively. The poor results obtained when predicting dry matter in samples in later seasons indicate that samples from several seasons must be included in the set of calibration samples. This is the first report on the application of NIR spectroscopy to evaluate the dry matter and soluble solids of durian pulp and could be useful to customers, exporters, importers and also postharvest technologists. However, prediction accuracy was not demonstrated in the model for durian pulp soluble solids, possibly because of the effect of ethephon applied after harvesting to induce ripening within 3 days to make the fruit suitable for consumption. In addition, it was found that the vibration bands of cellulose and fat, and those of aromatic, CH2 and sucrose highly affected the predictions of dry matter and soluble solids in the durian pulp, respectively.

Sirisomboon, Panmanas

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