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Rapid detection of potassium sorbate in coconut water using near infrared hyperspectral imaging
(2026-01-01)
Tantinantrakun, Achiraya
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Kumpa, Benjaporn
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Ainkast, Pranpriya
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Thompson, Anthony Keith
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Teerachaichayut, Sontisuk
Potassium sorbate may be illegally added to fresh coconut water in order to prolong its marketable life, but this adulteration may not be identified on the product label. The aim of this research was therefore to evaluate if samples of fresh coconut water that had been adulterated with measured amounts of potassium sorbate could be detected by near infrared hyperspectral imaging (NIR-HSI). Samples of coconut water with different potassium sorbate concentrations (N = 100) and pure coconut water samples (N = 100) were used in this study with their averaged spectral data used as independent variables. The smoothing spectral pretreatment gave the highest classification accuracy of 98.48% by partial least squares discriminant analysis (PLS-DA). While support vector machine regression (SVMR) with spectral pretreatment, using the 1st derivative combined with multiplicative scatter correction (MSC), achieved the optimum condition for developing the calibration model for determining potassium sorbate concentration with the correlation coefficient of prediction (R<inf>p</inf>) of 0.818 and the root mean square error of prediction (RMSEP) of 327.86 ppm. The results showed that NIR-HSI was able to be used as a fast, reliable, economic and environmentally friendly method of detecting potassium sorbate addition to coconut water.
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Nondestructive evaluation of SW-NIRS and NIR-HSI for predicting the maturity index of intact pineapples
(2023-01-01)
Tantinantrakun, Achiraya
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Sukwanit, Supawan
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Thompson, Anthony Keith
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Teerachaichayut, Sontisuk
Determination of optimum maturity and ripeness of fruit is essential in the production of processed fruit, including pineapples, but this is difficult to achieve consistently by visual grading in commercial factories. Therefore, this study tested two nondestructive techniques for predicting the maturity index of intact pineapple. These were transmittance short wavelength near infrared spectroscopy (SW-NIRS) in the wavelength range of 665–955 nm and reflectance near infrared hyperspectral imaging (NIR-HSI) in the wavelength range of 935–1720 nm. The number of samples used for calibration was 120 for both SW-NIRS and NIR-HSI. The maturity index and spectral information of individual pineapple fruit were acquired from both techniques and analysed using the same procedure. Then, partial least squares regression (PLSR) was used to establish the models for predicting the maturity index of each intact fruit. The leave-one-out cross validation was used for evaluating the performance of the models. The results showed that both techniques gave reliable performance in predicting the maturity index of individual fruit, with a coefficient of determination considering cross validation (R<inf>cv</inf>2) for the prediction of the maturity index of 0.70 and a root mean square error in cross validation (RMSECV) of 2.16 when using SW-NIRS and R<inf>cv</inf>2 of 0.72 and RMSECV of 1.68 when using NIR-HSI. It was therefore concluded that both SW-NIRS and NIR-HSI had the potential for use in nondestructive analysis of the maturity of intact pineapple fruit in fruit processing factories.
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Detection of adulteration of tapioca starch with dolomite by near infrared hyperspectral imaging
(2020-01-01)
Khamsopha, Duangkamolrat
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Teerachaichayut, Sontisuk
Tapioca starch adulterated with dolomite is sold in markets, but this adulteration cannot be identified by normal visual inspection. Near infrared (NIR) hyperspectral imaging has been successfully used as a non-destructive method of identifying various characteristics of food, therefore it was tested to identify dolomite adulteration. Adulterated tapioca starch samples were prepared by adding dolomite in the range of 0.5-100% (wt/wt). Samples (N=400) of pure tapioca starch (0) and adulterated tapioca starch (1) were divided into calibration set (N=300) and a prediction set (N=100). All samples were scanned using NIR hyperspectral imaging (935-1720 nm) and spectra were pre-processed using Savitzky-Golay first derivative differentiation pretreatment in order to obtain the optimal conditions for establishing a classification model. Partial least squares-discriminant analysis was carried out to evaluate the accuracy of classification tapioca starch adulterated with dolomite. The results showed the total accuracy of prediction for classification was 100%. Therefore, NIR hyperspectral imaging was demonstrated to have a potential for use in detecting adulteration of tapioca starch with dolomite.
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Relationship between curriculum and instructional materials of non-formal agricultural higher education
(2019-09-01)
Musika, Araya
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Poungsuk, Pakkapong
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Siriwan, Nopakoon
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Intorrathed, Sarawut
The research was to study the conditions of agricultural education of people and the relationship in the management model for non-formal agricultural education in Thailand. The data were collected via in-depth interviews structured with 56 respondents selected via purposive sampling. The results were most of respondents were female and the management model for agricultural education in curriculum and content, the most respondents showed the non-formal agricultural education without certain curriculum and course duration, including self-learning; teaching and learning showed the learning from the agriculture specialists and leaders in the community, obtained the knowledge from real practice; instructional materials showed the learning from real practice, friends' suggestions and conversations; assessment and evaluation showed the evaluation from work's outcome; The relationship of the curriculum and content with education and occupation, the instructional materials with education, the assessment and evaluation with education, the participation with education were statistically significance.
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Influence of thickness of p-type diamond Hall sensors synthesized by HFCVD on their response sensitivity to magnetic field
(2018-07-02)
Panyalert, Wasin
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Siriwongrungson, Vilailuck
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Suwanna, Prapakron
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Titiroongruang, Wisut
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Niemcharoen, Surasak
This article presents the study of the influence of thickness of p-type diamond Hall sensors, which were synthesized by HFCVD, on their response sensitivity to magnetic field. Boron was added in ethyl alcohol as the reactant to obtain p-type diamond film at B/C ratio of 10,000 ppm. The synthesis durations of 6, 12 and 36 hours at the substrate temperature of 750°C were selected to achieve the required diamond film thicknesses of 50, 100 and 150 µm, respectively. The synthetic diamond films were confirmed to be diamond using Raman spectroscopy and the cross sections were analyzed using SEM (Scanning Electron Microscopy). Then, simple p-type diamond Hall sensors were fabricated using four silver electrodes adhered on the diamond film. The ohmic of the electrodes were confirmed by the measurement of electrical properties of electrodes and magnetic field response at three different diamond thicknesses. The response sensitivity to magnetic field were 12, 9 and 6 µV/Gauss, respectively. When the thickness of the p-type diamond Hall sensor increased, the response sensitivity to magnetic field decreased.
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Non-destructive prediction of total soluble solids, titratable acidity and maturity index of limes by near infrared hyperspectral imaging
(2017-11-01)
Teerachaichayut, Sontisuk
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Ho, Huong Thanh
This study was implemented for non-destructive prediction of total soluble solids (TSS), titratable acidity (TA) and calculation of TSS/TA as a measure of maturity index in intact limes using laboratory-based push-broom hyperspectral imaging (HSI) in reflectance mode in the range of 929–1671 nm. Limes were scanned by the HSI system in order to develop calibration models for predicting TSS, TA and TSS/TA using partial least square regression (PLSR). Original spectra obtained optimal conditions for establishing the models for TSS and TA while smoothing spectra for TSS/TA. The accuracy of the models for TSS, TA and TSS/TA provided coefficient of determination of prediction (R2<inf>p</inf>) of 0.838, 0.694 and 0.775, respectively and root mean square errors of prediction (RMSEP) of 0.237%, 0.288% and 0.049, respectively. Image processing algorithms were then built up by interpreting predictive values, from the models, to colors in each pixel of the images. The predictive visualization of TSS, TA and TSS/TA in all portions of the limes based on a color scale was presented. The results showed that the HSI technique has the capability of predicting TSS, TA and TSS/TA of intact limes non-destructively and the results could be visualized by different colors of the predictive images.
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Verification of new model by comparison with actual data
(2017-10-19)
Manosukritkul, Phasapon
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Titiroongruang, Wisut
This papers shows the results of testing the power output of the solar PV system using silicon crystals used in the test. Then simulate the power output in the form of thirdgeneration model. The first generation model (1D5P) at a second series Weight Function Model and form a third model has been developed. The test system with 28 kWp The results show that the first form (1D5P) error of 14.40%. models the second error of 5.02% in the third form a models that has developed error of 1.05%.
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The new simulation model for estimating PV power output
(2017-10-19)
Manosukritkul, Phasapon
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Titiroongruang, Wisut
This paper proposed the new simulation model for estimate PV Power Output of power plant in Thailand. Our development model were used the solar irradiance and module temperature as input of model. The model has develop by using one year measured data of focus area and verified by comparison with measured data. The results shown high accuracy and error about 1.11 %.
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Implementation the performance of programmable logic controller base on embedded systems
(2012-01-01)
Gulpanich, Suphan
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Suesut, Taweepol
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Tirasesth, Kitti
This paper presents an approach to implementation for PLC used embedded application. We had created the designs base on structure model. The hardware are consist of 32-bits microcontroller (LPC2378), 4 Chanel analog I/O and 32 points digital I/O, and multi communication unit. The software considerable operating system on multitasking is called the real-time operating system (RTOS). This article discusses the scan time is very important for the PLC controller. It also shows how to calculating scan time then approach to run the user program. In the empirical study considered only the scan time operated by IL program, 20 commands. Which can be measuring respond time for appropriate the results equal to 152 μSec. while the PLC own calculation and run the program equal to 151 μSec. Both values are similar, different by 1 μSec. only © 2012 SICE.
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Effect of different pretreatments and air temperatures on drying and quality characteristics of Sauropus androgynus Merr
(2011-12-01)
Phongpipatpong, Maradee
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Wongkrajang, Karuna
Sauropus androgynus Merr. is one of the widely consumed indigenous plants in Thailand due to its high nutritional value and antioxidant compounds. Naturally, as green leafy vegetable, the Sauropus androgynus Merr. in fresh form be easily deteriorate Dried powder form is an alternative means to apply this plant as healthy supplement ingredient to increase nutritional value in bakery and snack products. In this study, the effects of different pretreatments and air temperatures on drying and quality characteristics of Sauropus androgynus Merr leaves were investigated. The pretreatment conditions before drying included 1) rinse with water, 2) blanch with hot water at 100°C for 15 second, and 3) blanch with 28 kHz of ultrasonic wave at 25°C for 15 minute. The drying process was carried out in a tray dryer with 0.25 m/s of air velocity and followed by drying with hot air at temperature of 45°C, 55°C, and 65°C. The drying kinetics was modeled based on Newton and Page equations. The results showed that the ultrasonic pretreatment could improve drying rate of the Sauropus androgynus Merr. leaves significantly faster than did the hot water blanching and the water rinse pretreatment respectively. The Newton's model gave a better fit to the experimental result than the Page's model. The kinetic parameters in the models were also presented as the function of initial leaves moisture and air temperature. Qualities of the dried product, including final moisture content, water activity, color and total phenolic content, were analyzed. The highest amount of total phenolic content of 52.70 mg GAE/ g was found in the dried product obtained from the water rinse pretreatment and dried at 45°C. However, the results also indicated that the high amount of the total phenolic content could be achieved by using the ultrasonic blanching and drying at high temperature with shorter time.

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