Sirisomboon, Panmanas

Preferred name

Alternative Name

Sirisomboon, P.

Main Affiliation

School of Engineering

panmanas.si@kmitl.ac.th

Now showing 1 - 10 of 13

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Precision test for the spectral characteristic of FT-NIR for the measurement of water content of wheat straw
(2019-09-09)
Fonseca, F. G.
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Funke, A.
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Saechua, W.
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Sirisomboon, P.
Near Infrared (NIR) Spectroscopy is widely employed as a rapid technique for the evaluation of properties of biomass materials. Precision and accuracy of the instruments is an important aspect in order to minimize error in the determination of results. The objective of this publication is to determine scanning repeatability and reproducibility of the NIR spectrometer for wheat straw (Triticum aestivum L.), using either a fixed scan or a rotating scan. The former presented marginally better repeatability but worse reproducibility. Samples in equilibrium with the local atmosphere versus samples of controlled and different moisture contents were also compared, and the latter performed better on the precision test but both fixed and rotating scans. As the ultimate objective of this test is the use of this method to determine variations between different moisture content, and as the rotating scan presents better reproducibility, this method was selected as the reference method for further NIR analyses focused on the variation of moisture content.
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2D/3D vision-based mango's feature extraction and sorting
(2006-01-01)
Chalidabhongse, Thanarat
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Yimyam, Panitnat
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Sirisomboon, Panmanas
This paper describes a vision system that can extract 2D and 3D visual properties of mango such as size (length, width, and thickness), projected area, volume, and surface area from images and use them in sorting. The 2D/3D visual properties are extracted from multiple view images of mango. The images are first segmented to extract the silhouette regions of mango. The 2D visual properties are then measured from the top view silhouette as explained in [7]. The 3D mango volume reconstruction is done using volumetric caving on multiple silhouette images. First the cameras are calibrated to obtain the intrinsic and extrinsic camera parameters. Then the 3D volume voxels are crafted based on silhouette images of the fruit in multiple views. After craving all silhouettes, we obtain the coarse 3D shape of the fruit and then we can compute the volume and surface area. We then use these features in automatic mango sorting which we employ a typical backpropagation neural networks. In this research, we employed the system to evaluate visual properties of a mango cultivar called "Nam Dokmai". There were two sets total of 182 mangoes in three various sizes sorted by weights according to a standard sorting metric for mango export. Two experiments were performed. One is for showing the accuracy of our vision-based feature extraction and measurement by comparing results with the measurements using various instruments. The second experiment is to show the sorting accuracy by comparing to human sorting. The results show the technique could be a good alternative and more feasible method for sorting mango comparing to human's manual sorting. © 2006 IEEE.
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Near infrared scanning precision analysis for intact durian fruits (cv. Chanee, Kanyao and Monthong)
(2019-09-09)
Chanachot, K.
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Saechua, W.
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Sirisomboon, P.
In order to develop a model of near infrared (NIR) spectroscopy, it is important to first perform the precision analysis of scanning of the NIR spectrometer. Therefore, it was the main aim of this paper by evaluating the scanning repeatability and reproducibility on intact durian fruit of 3 varieties including Chanee, Kanyao and Monthong using 3 spectrometers including FT-NIR spectrometer (MPA.), Long wavelength diode array spectrometer (MICRO NIR PRO) and Short wavelength diode array spectrometer (FQA NIR GUN). Results show that the lowest repeatability was of MPA for the scanning of Chanee and Kanyao. The lowest reproducibility was of the scanning by MICRO NIR PRO for all varieties. Therefore, from precision analysis of intact durian scanning, the MPA and MICRO NIR PRO could be recommended for the scanning to get the spectra for development the NIR predictive model for identify the geographic origin and variety of the durian.
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Evaluation of pH of curry soup containing coconut milk by near infrared spectroscopy
(2019-09-09)
Thitibunjan, N.
;
Sirisomboon, P.
The pH is the important parameters to characterize the food deterioration and an indicative of food spoilage. The aim of this research was to apply the near infrared (NIR) spectroscopy to evaluate pH of curry soup containing coconut milk. The soup samples from mixing tank, water content adjusted tank, UHT pipe and laminated containers in the production line were collected. There were also the pH adjusted samples where the curry was made from the same recipe but increasing placed time for 2, 4 and 6 hr after 0 hr. There are 73 samples in total. The sample was scanned with FT-NIR spectrometer. A prediction model for pH was established using NIR spectral data in conjunction with partial least squares regression, which was validated using leave one out cross validation and test set validation. After validated by unknown samples, the leave one out cross validation model showed better prediction performance. The best model developed using first derivative spectra in 9403.8-7498.3, 6102-5446.3 and 4605.4-4242.9 cm-1 provided an coefficient of determination (r2), root mean square error of cross validation (RMSECV), bias and ratio of performance to interquartile (RPIQ) of 0.73, 0.28, 0.01 and 1.89. The model was usable for screening and some other "approximate" calibrations. The model could be improved for further development of robust model using more natural samples in evaluation of pH in the curry soup
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Overall precision test of near infrared spectroscopy on mango fruits (Mangifera indica CV. 'Nam Dok Mai Si Thong') by on-line and off-line systems
(2020-09-08)
Lekhawattana, Wachiraya
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Sirisomboon, Panmanas
The near infrared (NIR) spectroscopy both on-line and off-line scanning was applied on mango fruits (Mangifera indica CV. 'Nam dok mai-si Thong') for the overall precision test. The reference parameter was total soluble solids content (Brix value). The results showed that the off-line scanning had a higher accuracy than on-line scanning. The scanning repeatability of the off-line and on-line systems were 0.00199 and 0.00993, respectively. The scanning reproducibility of the off-line and online systems were 0.00279 and 0.00513, respectively. The reference of measurement repeatability was 0.2. The maximum coefficient of determination (R2max) of the reference measurement was 0.894.
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Rapid evaluation of moisture content in bamboo chips using diode array near infrared spectroscopy
(2018-08-14)
Shrestha, Amrit
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Sirisomboon, Panmanas
Moisture in biomass plays important role during storage, combustion and pelletization. In order to measure moisture content in bamboo chips, two diode array near-infrared instruments, NIR-Gun (600-1100 nm at 2 nm intervals) and Micro-NIR (1150-2150 nm at 7 nm intervals), were used for scanning bamboo chips. Total number of samples used for developing model after removing outliers was 252. The circumference and moisture content of bamboos used were in the range between 16-39 cm and 39-86% wet basis (wb) respectively. Partial least squares regression technique was used to develop the model to predict the moisture content in bamboo chips. The R2, SECV, SEP, bias and RPD of optimum model of NIR-Gun were found to be 0.924, 2.871% wb, 2.385% wb, -0.250% wb and 3.656, while for Micro-NIR model the values were found to be 0.743, 4.349% wb, 4.499% wb, 0.026% wb and 1.972 respectively. In prediction of moisture content in bamboo chip, both models show the effect of different constituents of bamboo more than moisture. This study indicates that the results are suitable for screening the moisture content in bamboo chips. This would be helpful for process controlling using the moisture parameter during drying, pelletization and thermochemical conversion.
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Effect of Environment Temperature and Relative Humidity on Thermal Emissivity: Study Case of Mango Fruit
(2024-01-01)
Sirisomboon, Panmanas
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Sripinyowanich Jongyingcharoen, Jiraporn
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Junto, Apiwat
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Phanomsophon, Thitima
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Dachoupakan Sirisomboon, Cheewanun
This research was to study the effect of the environment condition during image captured including temperature and relative humidity in the packaging house of the mango exporting factory and in the orchard on the emissivity of mango fruit. The result showed that in the controlled environment of the packaging house in factory, the emissivity was increased (the mango emitted more energy) when the surface temperature was lower and the emissivity of mango is 0.71-0.84 and in the uncontrolled environment of open-air packaging yard in the mango orchard, the different transpiration rates of mango effected mainly by ambient temperature and relative humidity make the morning condition emissivity of 0.44-0.66 and the afternoon condition of 0.72-0.98. There was the effect of the different measured positions on the fruits where the physiology was different and the fluctuated environment in the latter condition made the wide range of emissivity of mangoes. This indicated the shortcoming of thermal imaging of horticultural product if the correct emissivity varied and difficult to set in the thermal camera setting, hence the inaccurate thermogram to be obtained.
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Transflection Near-infrared Spectroscopy Combined with Machine Learning for Mechanical Stability Time Evaluation in Concentrated Rubber Latex
(2023-01-01)
Suttho, Pisit
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Phetpan, Kittisak
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Sirisomboon, Panmanas
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Lim, Chin Hock
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Ruttanadech, Nuttapong
This study aims to apply near-infrared spectroscopy (NIRS) in transflection mode combined with a machine learning approach to evaluate the mechanical stability time (MST) in Para concentrated rubber latex. Four supervised learning algorithms, including principal component regression (PCR), partial least squares regression (PLSR), support vector regression (SVR) and random forest regression (RFR), were employed to relate the NIR spectra with the MST degree of the latex samples. A comparison of predictive performance among these different algorithms was performed. The RFR model exhibited the best fitting performance with a coefficient of determination for calibration (R2) and root mean square error of calibration (RMSEC) of 0.95 and 37 seconds, respectively. In addition, the RFR-based model outperformed all others with its predictive performance, presenting coefficient of determination for prediction (r2) and root mean square error of prediction (RMSEP) of 0.64 and 91 seconds, respectively. Based on these results, this study could imply that the relationship between the NIR spectra and the change in the MST degree of the samples tends to be nonlinear.
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The overall precision test for near infrared scanning and reference method for the determination of soluble solids content and pH of mango for processing factory
(2020-09-08)
Saksangium, Nphatsanan
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Sirisomboon, Panmanas
Near infrared (NIR) spectroscopy is a rapid technique for nondestructive testing. Mango is popular fruit in Thailand. Therefore, The main aim of this paper is to report an overall precision of the NIR spectroscopy instruments and reference methods for determination at the beginning of the experiment for prediction models development to be in the mango applied processing factory. Results showed that the repeatability of FT-NIR spectrometer and UV-VIS-NIR spectrometer were 0.00191 and 0.00529, respectively. The reproducibility of FT-NIR spectrometer and UV-VIS-NIR spectrometer were 0.00323 and 0.03561, respectively. Repeatability of reference test of TSS and pH were 0.1657 and 0.0827. Therefore, the R2max of TSS and pH were 0.9825 and 0.9504 which indicates that it is possible to develop NIR model for prediction of total soluble solids and pH.
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Precision test for scanning of soil in durian orchard using near-infrared spectroscopy
(2019-09-09)
Phanomsophon, T.
;
Sirisomboon, P.
Near infrared (NIR) spectroscopy is a rapid technique for non destructive testing. Durian is popular fruit in Thailand. Growing durian is not easy. It needs to provide proper nutrients. Therefore, this paper aims to test the repeatability and reproducibility of NIR scanning before conducting the feasibility test of creating the equation to predict the N P K value in the soil for the durian trees. Results showed that the repeatability of FT-NIR spectrometer and Micro-NIR spectrometer for fresh soil were 0.064 and 0.075, respectively and for soil powder, they were 0.039 and 0.048, respectively. The reproducibility of FT-NIR spectrometer and Micro-NIR spectrometer for fresh soil were 0.048 and 0.051, respectively and for soil powder were 0.051 and 0.046, respectively.

Sirisomboon, Panmanas

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