• Journal of Animal Environmental Science
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• v.20 no.3
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• pp.117-124
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• 2014

The objectives were to assess the use of near-infrared reflectance spectroscopy (NIRS) as a tool for estimating nutrient compositions of corn kernel, and to apply an NIRS-based indium gallium arsenide array detector to the system for collecting spectra and analyzing calibration equations using equipments designed for field application. Partial Least Squares Regression (PLSR) was employed to develop calibration equations based on representative data sets. The kennard-stone algorithm was applied to induce a calibration set and a validation set. As a result, the method for structuring a calibration set significantly affected prediction accuracy. The prediction of chemical composition of corn kernel resulted in the following (kennard-stone algorithm: relative) moisture ($R^2=0.82$, RMSEP=0.183), crude protein ($R^2=0.80$, RMSEP=0.142), crude fat ($R^2=0.84$, RMSEP=0.098), crude fiber ($R^2=0.74$, RMSEP=0.098), and crude ash ($R^2=0.81$, RMSEP=0.048). Result of this experiment showed the potential of NIRS to predict the chemical composition of corn kernel.

• Korean Journal of Food Science and Technology
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• v.26 no.5
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• pp.579-584
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• 1994

Near infrared reflectance(NIR) spectroscopy was used to determine the degree of retrogradation of cooked rice. Cooked rice samples were stored at $4^{\circ}C$ for 120 hours, and the degree of retrogradation was measured at every 6 hour during the storage time. Stored cooked rices were freeze-dried, milled and passed through a 100 mesh sieve. Enzymatic method using glucoamylase was used as reference method for the determination of the degree of retrogradation. Spectral differences due to retrogradation of cooked rice were observed at 1434, 1700, 1928, 2100, 2284 and 2320 nm. 32 samples of which moisture content were below 5% were used for calibration set, and 16 samples were used for validation set. High correlations were achieved between degree of retrogradation determined by conventional enzymatic method and by NIR with multiple correlation coefficient of 0.9753, and a standard error of calibration(SEC) of 3.64%. Comparable results were obtained with 3.91% of standard error of prediction(SEP), when the calibration equation was applied to independent group of samples of which moisture contents were in the range of calibration set. But when the calibration equation was applied to samples of which moisture contents were outer range of calibration set, SEP and bias were increased and correlation coefficient was decreased. The determination of degree of retrogradation was affected by sample moisture content. To determine degree of retrogradation of cooked rice by NIR using this calibration equation, it was suggested that sample moisture content should be controlled to below 5%.

• Korean Journal of Agricultural Science
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• v.39 no.1
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• pp.117-123
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• 2012

Pathogenic fungi and bacteria such as Pectobacterium atrosepticum, Clavibacter michiganensis subsp. sepedonicus, Verticillium albo-atrum, and Rhizoctonia solani were the major microorganism which causes diseases in seed potato during postharvest process. Current detection method for disease-infected seed potato relies on human inspection, which is subjective, inaccurate and labor-intensive method. In this study, a reflectance spectroscopy was used to classify sound and disease-infected seed potatoes with the spectral range from 400 to 1100 nm. Partial least square discriminant analysis (PLS-DA) with various preprocessing methods was used to investigate the feasibility of classification between sound and disease-infected seed potatoes. The classification accuracy was above 97 % for discriminating disease seed potatoes from sound ones. The results show that Vis/NIR reflectance method has good potential for non-destructive sorting for disease-infected seed potatoes.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.spc1
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• pp.42-46
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• 2006

The purpose of this study was to assess whether mechanical sensory score by Toyo Midometer can be substituted by near-infrared spectroscopy (NIRS) method in whole-grain milled rice samples. Toyo values of collected commercial brand rice (n=127) had comparatively wide ranges from 62.9 to 84.2 (Mean=70.5; S.D.=4.0). Calibration equation was developed using 73 samples. Standard error of calibration (SEC) for sensory score equation and $R^2$ were 0.95, and 0.94, respectively, however, percentage of variation in the reference method values (1-VR) which give a true indication of equation performance was slightly lower (1-VR=0.81) than calibration equation. It was demonstrated that, even though NIRS has potential as a rapid tools to predict rice sensory score, the prediction of sensory score in rice by NIRS needs to be further investigation on a large number of sample with different varieties and growing locations.

• Food Science and Preservation
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• v.18 no.2
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• pp.156-164
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• 2011

This study was conducted to develop a portable quality evaluation system of bee-honey by near infrared spectroscopic technique. Two kinds of bee-honeys from acacia and polyflower sources were tested in this study. The system consists of power supply, tungsten-halogen lamp, detector, and optical fiber probe. Performance of the system was analyzed by comparing the prediction accuracy of the laboratory spectrophotometer. Total of 346 spectra was divided into a calibration set and a prediction set. The PLS (Partial Least Squares) models were developed to predict the quality parameters of bee-honeys. Reflectance spectra, moisture contents, ash, invert sugar, sucrose, F/G ratio, HMF(hydroxy methyl furfural), and $C^{12}/C^{13}$ ratio of honeys were measured. The PLS models of the laboratory spectrophotometer showed good relationships between predicted and measured quality parameters of honeys in the wavelength range of 1.100~2.200 nm. The PLS analysis of the portable quality evaluation system showed good relationships between predicted and measured quality parameters of honeys in the wavelength range of 1.100~1.300 nm and 1.400~1.700 nm. The results showed the feasibility of the portable quality evaluation system to determine the quality parameters of bee-honey in the field during harvesting.

• Journal of Biosystems Engineering
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• v.42 no.4
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• pp.301-313
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• 2017

Purpose: This study was conducted to discriminate between normal hulled barley and Fusarium (Fusarium asiaticum and Fusarium graminearum) infected hulled barley by using the near-infrared spectroscopy (NIRS) technique. Methods: Fusarium asiaticum and Fusarium graminearum were artificially inoculated in hulled barley and the reflectance spectrum of the barley spike was obtained by using a near-infrared spectral sensor with wavelength band in the range 1,175-2,170 nm. After obtaining the spectrum of the specimen, the hulled barley was cultivated in a greenhouse and visually inspected for infections. Results: From a partial least squares discriminant analysis (PLS-DA) prediction model developed from the raw spectrum data of the hulled barley, the discrimination accuracy for the normal and infected hulled barley was 99.82% (563/564) and 100% (672/672), respectively. Conclusions: NIRS is effective as a quick and nondestructive method to detect whether hulled barley has been infected with Fusarium. Further, it expected that NIRS will be able to detect Fusarium infections in other grains as well.

• Applied Biological Chemistry
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• v.41 no.2
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• pp.153-159
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• 1998

A possibility of evaluation of the major internal quality factors-Brix, moisture contents, firmness and acid content in the Korean domestic 'Fuji'apple fruits by near-infrared reflectance spectroscopic (NIRS) methods were investigated. A multiple linear regression(MLR) analysis between the data obtained by physico- chemical analysis method using refractometer, freeze drier, texture analyzer and titrater and NIR spectral data was carried out to make a calibration. The standard error of prediction(SEP) of Brix, moisture, firmness and acid content were $0.50^{\circ}Brix,\;0.64%,\;0.14kg/cm^2$ and 0.07%. It is concluded that NIRS methods can be used to evaluate Brix and moisture contents of in a apple non-destructive and rapid way but the accuracy for determination of firmness and acid content was slightly low.

• Korean Journal of Food Science and Technology
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• v.22 no.6
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• pp.675-680
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• 1990

A near-infrared reflectance spectroscopic(NIRS) method which has been recently developed for a non-destructive method for measuring ingredients in foods and agricultural products especially was evaluated for the determination of capsanthin, total sugar, capsaicin and moisture contents in Korean domestic red peppers. A multiple linear regression analysis with the data obtained by standard-laboratory methods(capsaicin by GC, capsanthin by Colorimetry, total sugar by HPLC and moisture by Vacuum drying method) and NIRS method was carried out to make a calibration. The accuracy of the NIRS method was found to be adequate when the standard-laboratory values for a set of sample that were not included in the calibration, were compared. It is concluded that the NIRS method is suitable for the determination of total sugar and capsanthin.

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.883-902
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• 2023

Water is critical to the health and productivity of fruit trees. Efficient monitoring of water stress is essential for optimizing irrigation practices and ensuring sustainable fruit production. Short-range sensing can be reliable, rapid, inexpensive, and used for applications based on well-developed and validated algorithms. This paper reviews the recent advancement in fruit tree water stress detection via short-range sensing, which can be used for irrigation scheduling in orchards. Thermal imagery, near-infrared, and shortwave infrared methods are widely used for crop water stress detection. This review also presents research demonstrating the efficacy of short-range sensing in detecting water stress indicators in different fruit tree species. These indicators include changes in leaf temperature, stomatal conductance, chlorophyll content, and canopy reflectance. Short-range sensing enables precision irrigation strategies by utilizing real-time data to customize water applications for individual fruit trees or specific orchard areas. This approach leads to benefits, such as water conservation, optimized resource utilization, and improved fruit quality and yield. Short-range sensing shows great promise for potentially changing water stress monitoring in fruit trees. It could become a useful tool for effective fruit tree water stress management through continued research and development.

• Journal of Biosystems Engineering
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• v.39 no.3
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• pp.184-193
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• 2014

Purpose: The aim of this study was to develop a technique for the non-destructive and rapid prediction of the moisture content in red pepper powder using near-infrared (NIR) spectroscopy and a partial least squares regression (PLSR) model. Methods: Three red pepper powder products were separated into three groups based on their particle sizes using a standard sieve. Each product was prepared, and the expected moisture content range was divided into six or seven levels from 3 to 21% wb with 3% wb intervals. The NIR reflectance spectra acquired in the wavelength range from 1,100 to 2,300 nm were used for the development of prediction models of the moisture content in red pepper powder. Results: The values of $R{_V}{^2}$, SEP, and RPD for the best PLSR model to predict the moisture content in red pepper powders of varying particle sizes below 1.4 mm were 0.990, ${\pm}0.487%$ wb, and 10.00, respectively. Conclusions: These results demonstrated that NIR spectroscopy and a PLSR model could be useful techniques for measuring rapidly and non-destructively the moisture content in red pepper powder.