• Journal of the Korean Society of Food Science and Nutrition
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• v.26 no.3
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• pp.514-520
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• 1997

The purpose of this study is to provide the reference data for estimating body composition and developing equations for prediction of percent body fat. This study was designed of two aspects: Comparison of percent body fat measurements between two operators. comparison of percent body fat measurements among four instruments. Percent body fat of college girls(n=71) aged 18-24 was measured by skinfold thickness, near-infratred interactance(Futrex-5000), and bioelectrical impedance analysis (TBF-105, Spectrum II). All measurements were duplicated & measured by two operators. The results are summarized as follows: Percent body fat observed from two operators had no significant difference. There was significant difference from four instruments. However, we found close relation between Skinfold thickness & TBF-105, Spectrum II & Near-infrared interactance. Four instruments have several assumptions and limitations. Therefore, many researches for developing new equations are required for Korean people.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1242-1242
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• 2001

The use of fibre optic probes for NIR quality control in the industry is becoming very important, as it provides a powerful tool to reduce sample analysis time and it facilitates the implementation of on-line analyses. However, most of the applications of fibre optics and probes have been done on suspensions, clear liquids and films, chemical and pharmaceutical products and also on fruits and animal products. Traditional applications of near infrared spectroscopy in agriculture have been developed in reflectance mode and calibration transfer could be an interesting way to reduce efforts. Classical methods for calibration transfer between different instruments involve the use of sealed reference cups, but, as fibre optic analysis does not use cups, it is necessary to develop new methods for calibration transfer without standards (Blank et al., 1996). In this paper, we have studied how the most used mathematical pretreatments (three methods of Multiplicative Scatter Correction, Standard Normal Variate, Detrending and derivatives) and their combinations applied to calibration development can contribute to reduce spectral differences between instruments. Calibration equations were obtained for three sets of cereals (barley, wheat and maize) scanned in reflectance mode and then they were validated with samples analysed in reflectance and interactance-reflectance mode (fibre optic). Preliminary results show how some combination of pretreatments reduce the differences in the predicted values, measured as standard error of differences, facilitating the use of calibrations obtained in reflectance for samples analysed by interactance-reflectance. However, the application of pretreatments is not enough to satisfy the control limits for calibration transfer suggested by Shenk et al. (1992), and it should be necessary to combine them with a specific algorithm for instruments standardization.

• Journal of Biosystems Engineering
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• v.37 no.3
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• pp.177-183
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• 2012

Purpose: In near infrared spectroscopy, interactance configuration of a light source and a spectrometer probe can provide more information regarding fruit internal attributes, compared to reflectance and transmittance configuration. However, there is no through study on the parameters of interactance measurement setup. The objective of this study was to investigate the effect of the parameters on the estimation of soluble solids content (SSC) and firmness of muskmelons. Methods: Melon samples were taken from greenhouses at three different harvesting seasons. The prediction models were developed at three distances of 2, 5, and 8 cm between the light source and the spectrometer probe, three measurement points of 2, 3, and 6 evenly distributed on each sample, and different number of fruit samples for calibration models. The performance of the models was compared. Results: In the test at the three distances, the best results were found at a 5 cm distance. The coefficient of determination ($R_{cv}{^2}$) values of the cross-validation were 0.717 (standard error of prediction, SEP=$1.16^{\circ}Brix$) and 0.504 (SEP=4.31 N) for the estimation of SSC and firmness, respectively. The minimum measurement point required to fully represent the spectral characteristics of each fruit sample was 3. The highest $R_{cv}{^2}$ values were 0.736 (SEP=$0.87^{\circ}Brix$) and 0.644 (SEP=4.16 N) for the estimation of SSC and firmness, respectively. The performance of the models began to be saturated when 60 fruit samples were used for developing calibration models. The highest $R_{cv}{^2}$ of 0.713 (SEP=$0.88^{\circ}Brix$) and 0.750 (SEP=3.30 N) for the estimation of SSC and firmness, respectively, were achieved. Conclusions: The performance of the prediction models was quite different according to the condition of interactance measurement setup. In designing a fruit grading machine with interactance configuration, the parameters for interactance measurement setup should be chosen carefully.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1021-1021
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• 2001

Sample presentation, which means how to set samples to an NIR instrument, is very important in Near Infrared (NIR) Spectroscopy. When sample presentation is not suitable for the samples that you use, very good spectra can not be obtained even if you use a sophisticated NIR instrument. In my presentation, various NIR sample presentations for agricultural products such as intact fruits, single grains, vegetable juice and the others will be explained. In case of peaches with thin peel, the fiber optics of Interactance can be used. However, the fiber optics are not suitable for oranges with relatively thick peel. In this case, transmittance method is useful. As for a small sample such as single grains, a specially designed cell is needed. The cell in transmittance mode has been developed and then applied to single kernels of rice and soybean. In this case we also used the fiber optics. As regards liquid type of sample, a cuvette cell made of quartz in transmittance mode is popular. However, it is time-consuming to wash and dry it. In order to compensate this disadvantage the sample presentation using normal test tubes as sample cells have been developed and applied to milk, rumen juice and urine of a milking cow. An individual test tube can be used for each sample if you use the calibration equation with sample cell compensation. The test tube cell has also been applied to spinach juice for determination of undesirable constituents. It is concluded that sample presentation is most important for NIR Spectroscopy.

• Journal of Nutrition and Health
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• v.23 no.2
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• pp.93-107
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• 1990

The purposes of this investigation were to determine the validity of various methods (available anthropometric equations and near-infrared light interactance) for estimating body fat and to develop multiple regression equations for the prediction of body fat. Thirty-eight healthy males(age: 20.87$\pm$7.17 yrs) and 12 females(19.58$\pm$2.19 yrs) underwent hydrostatic weighing to determine body fat. Anthropometric measurements were taken of height, weight, nin skinfolds and thirteen circumferences. The results obtained are summarized as follows: 1) Relative body fat determined by underwater weighing was 12.08$\pm$5.21% for the males and 17.97$\pm$5.75% for the females. 2) Circumference and skin fold that had the highest correlation with the body fat were waist girth in males and females(r=0.60, r=0.96, respectively), and subscapular in males(r=0.68) and triceps in females(r=0.96). 3) Corss-validation of 18 selected equations on males revealed total errors ranging from 3.76% to 5.06%. Among these equations, M3(Pollock et al.) demonstrated the least total error. Total error of estimation by near-infrared(NIR) was less than that of available anthropometric measurement equations. The results of the cross-validation of 12 equations on females revealed that F3(Sloan et al.) was clearly superior in accuracy of prediction. 4) Correlational analyses showed that estimation of body fat by NIR measurement seemed to be more closely associated with body fat determined by underwater weighing in women than men, in older subjects than younger ones, and in fatter subjects than leaner ones.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1155-1155
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• 2001

The quality of agricultural products is very important factor for consumers. In Japan, quality is sometimes more important than cost. Usually, the quality of fresh food products is determined in terms of shape, color, size, etc. However, these indices are not always associated with taste, leaving consumers to complain. Recently, two types of the fruit quality meter (a tabletop type - K-FS200 and a portable type - K-BA100, Kubota Corp.) using NIR technology were introduced in Japan. A tabletop instrument is for post harvest use and a portable one is for precision agriculture use. The both meters use the NIR region from 600nm to 1000nm in the interactance mode to determine quality factors related to taste. The instruments can measure sugar content and acidity of such fruit as apples, tomatoes, tangerines and other fruits. The measurement is timely, nondestructive and precise. For example, the coefficient of variation (CV) is less than 6% for sugar in most fruits. The K-FS200 has been evaluated in supermarkets, grading facilities, and wholesalers in Japan. The introduction of the K-FS200) has drawn attention to taste quality and its use is becoming more popular. In addition, researchers or farmers are becoming interested in measuring product ingredient not only after harvest but also during growing in the field so that they can make intelligent judgements concerning soil amendments, such as fertilizers and water, employs the fiber probe for flexible measurement and is battery powered for field use. Design of the fruit quality meters will be discussed. Applications to fruit quality will be presented.