• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.51 no.spc1
• /
• pp.304-309
• /
• 2006

Near infrared reflectance spectroscopy (NIRS) was used to develop a rapid and nondestructive method for the determination of fatty acid composition in sesame (Sesamum indicum L.) seed oil. A total of ninety-three samples of intact seeds were scanned in the reflectance mode of a scanning monochromator, and reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations were developed using modified partial least square regression with internal cross validation (n=63). The equations obtained had low standard errors of cross-validation and moderate $R^2$ (coefficient of determination in calibration). Prediction of an external validation set (n=30) showed significant correlation between reference values and NIRS estimated values based on the SEP (standard error of prediction), $r^2$ (coefficient of determination in prediction) and the ratio of standard deviation (SD) of reference data to SEP. The models developed in this study had relatively higher values (more than 2.0) of SD/SEP(C) for oleic and linoleic acid, having good correlation between reference and NIRS estimate. The results indicated that NIRS, a nondestructive screening method could be used to rapidly determine fatty acid composition in sesame seeds in the breeding programs for high quality sesame oil.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1623-1623
• /
• 2001

Composting is a biological method used to transform the organic waste into stable, humified organic amendments. Humification is indicated as the key factor in improving the quality of compost, because of the importance of humic substances to soil ecology, fertility and structure, and their beneficial effects on plant growth The compost constituents vary widely, however, the degree of maturity is very important factor in compost quality. So this experiment carried out to determine the rapid estimation of the quality in cattle, pig, chicken and waste composts using near infrared reflectance spectroscopy(NIRS). Near infrared reflectance spectra of composts was obtained by Infra Alyzer 500 scanning spectrophotometer at 2-nm intervals from 1100 to 2500nm. Multiple linear regression(MLR) or partial least square regression (PLSR) was used to evaluate a NIRS method for the rapid and nondestructive determination of humic acid contents in composts. The results summarized that NIR spectroscopy can be used as a routine testing method to determine quantitatively the humic acid content in the compost samples ondestructively. Especially, we supposed that absorbance around 2300nm is related to humic acid as a factor of compost maturity. However the NIR absorption approach is empirical, it actually requires many combinations of samples and data manipulations to obtain optimal prediction.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.35 no.1
• /
• pp.1-11
• /
• 2015

In this study, an online seed potato sorting system using a visible and near infrared (40 1100 nm) transmittance spectral technique and statistical model was evaluated for the nondestructive determination of infected and sound seed potatoes. Seed potatoes that had been artificially infected with Pectobacterium atrosepticum, which is known to cause a soil borne disease infection, were prepared for the experiments. After acquiring transmittance spectra from sound and infected seed potatoes, a determination algorithm for detecting infected seed potatoes was developed using the partial least square discriminant analysis method. The coefficient of determination($R^2_p$) of the prediction model was 0.943, and the classification accuracy was above 99% (n = 80) for discriminating diseased seed potatoes from sound ones. This online sorting system has good potential for developing a technique to detect agricultural products that are infected and contaminated by pathogens.

• Journal of Biosystems Engineering
• /
• v.37 no.5
• /
• pp.319-326
• /
• 2012

Purpose: Cheese texture is an important sensory attribute mainly considered for consumers' acceptance. The feasibility of nondestructive measurements of cheese texture was explored using non-contact ultrasonic sensors. Methods: A novel non-contact air instability compensation ultrasonic technique was used for five varieties of hard cheeses to measure ultrasonic parameters, such as velocity and attenuation coefficient. Five texture properties, such as fracturability, hardness, springiness, cohesiveness, and chewiness were assessed by a texture profile analysis (TPA) and correlated with the ultrasonic parameters. Results: Texture properties of five varieties of hard cheese were estimated using ultrasonic parameters with regression analysis models. The most effective model predicted the fracturability, hardness, springiness, and chewiness, with the determination coefficients of 0.946 (RMSE = 21.82 N), 0.944 (RMSE = 63.46 N), 0.797 (RMSE = 0.06 ratio), and 0.833 (RMSE = 17.49 N), respectively. Conclusions: This study demonstrated that the non-contact air instability compensation ultrasonic sensing technique can be an effective tool for rapid and non-destructive determination of cheese texture.

• Journal of Biosystems Engineering
• /
• v.32 no.3
• /
• pp.166-172
• /
• 2007

Egg quality indices are related with freshness, size of air chamber, loss of weight, and viscosity of the yolk and the protein. However, since the described quality parameters require measured in a destructive way, it is not suitable to inspect the egg quality with complete enumeration. Therefore, this study was performed to investigate the potential of image analysis method for evaluation of internal egg quality. Samples of 90 fresh eggs were collected immediately after laying and stored up to 24 days. Five eggs were randomly drawn from each storage condition (packing vs unpacking) at a regular interval and loss of weight, specific gravity and size of air chamber were measured. The image analysis for nondestructive measurement of size of air chamber was also studied. Results showed that the egg weight and gravity gradually decreased with increasing of storage days, while the size of air chamber linear increased caused by evaporation of water through the shell. A relationship a between conventional method and the image analysis method for measuring the size of air chamber was developed with the correlation coefficient of 0.928. The new finding implied that image analysis might provide a useful nondestructive tool to assess internal egg quality.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.18 no.2
• /
• pp.103-111
• /
• 1998

A nondestructive ultrasonic technique is presented for estimating the reinforcement volume fractions of particulate composites. The proposed technique employs a theoretical model which accounts for composite microstructures, together with a measurement of ultrasonic velocity to determine the reinforcement volume fractions. The approach is used for a wide range of SiC particulate reinforced Al matrix ($SiC_p/Al$) composites. The method is considered to be reliable in determining the reinforcement volume fractions. The technique could be adopted in a production unit for the quality assessment of the metal matrix particulate composite extrusions.

• Proceedings of the Korean Reliability Society Conference
• /
• 2001.06a
• /
• pp.235-238
• /
• 2001

It is well known that the reliability of materials of mechanical products is becoming more and more important not only for assurance of quality, but for international competition of products. In order to assure the reliability of materials or mechanical products nondestructive evaluation (NDE) techniques are playing more important roles. The existence of Internal defects in materials or mechanical parts is served as crack initiation site during the various loading condition. Historically, nondestructive evaluation (NDE) technique has been used almost exclusively for detecting microscopic discontinuities In materials or mechanical parts after they have been in service to expand the role of the NDE to include all aspects of materials production and application. Research efforts are being directed at developing and perfecting NDE techniques capable of monitoring (1) materials production processes (2) material integrity following transport, storage and fabrication and (3) the amount and rate of degradation during service. In addition, efforts are underway to develop technique capable of quantitative discontinuity sizing, permitting determination of response using fracture mechanics analysis, as well as techniques for quantitative materials characterization to replace the qualitative techniques used in the past. In this paper, the important role of NDE technology for reliability assurance of materials/mechanical parts is introduced.

• Bulletin of the Korean Chemical Society
• /
• v.29 no.7
• /
• pp.1391-1394
• /
• 2008

Polymer materials are very difficult to decompose for the purpose of chemical analysis. Nondestructive analysis without pretreatment provides a suitable solution that will overcome this obstacle. In this study, CRM candidate samples that contained toxic elements such as As, Cd, Cr and Zn in a polypropylene (PP) were analyzed using instrumental neutron activation analysis (INAA). The analytical results were obtained from ten samples selected by random sampling at two different concentration levels (low and high). Particular attention was paid to reducing analytical errors and evaluating the associated uncertainty.

• Journal of Biosystems Engineering
• /
• v.43 no.4
• /
• pp.369-378
• /
• 2018

Purpose: The aim of this study was to construct a saponin content-predicting model using shortwave infrared imaging spectroscopy. Methods: The experiment used a shortwave imaging spectrometer and ENVI spectral acquisition software sampling a spectrum of 910 nm-2500 nm. The corresponding preprocessing and mathematical modeling analysis was performed by Unscrambler 9.7 software to establish a ginsenoside nondestructive spectral testing prediction model. Results: The optimal preprocessing method was determined to be a standard normal variable transformation combined with the second-order differential method. The coefficient of determination, $R^2$, of the mathematical model established by the partial least squares method was found to be 0.9999, while the root mean squared error of prediction, RMSEP, was found to be 0.0043, and root mean squared error of calibration, RMSEC, was 0.0041. The residuals of the majority of the samples used for the prediction were between ${\pm}1$. Conclusion: The experiment showed that the predicted model featured a high correlation with real values and a good prediction result, such that this technique can be appropriately applied for the nondestructive testing of ginseng quality.

• Korean Journal of Agricultural Science
• /
• v.43 no.5
• /
• pp.715-722
• /
• 2016

Rapid determination of food quality is important in food distribution. In this study, the chemical properties of oats were analyzed using visible-near infrared (VIS-NIR) spectroscopy. The objective of this study was to develop and validate a predictive model of oat quality by VIS-NIR spectroscopy. A total of 200 oat samples were collected from domestic and import markets. Reflectance spectra, moisture, protein, fat, Fe, and K of oat samples were measured. Reflectance spectra were measured in the wavelength range of 400 - 2,500 nm at 2 nm intervals. The reflectance spectrum of an oat sample was measured after sample cell and reflectance plate spectrum measurement. Preprocessing methods such as normalization and $1^{st}$ and $2^{nd}$ derivations were used to minimize the spectroscopic noise. The partial-least-square (PLS) models were developed to predict chemical properties of oats using a commercial software package, Unscrambler. The PLS models showed the possibility to predict moisture, protein, and fat content of oat samples. The coefficient of determination ($R^2$) of moisture, protein, and fat was greater than 0.89. However, it was hard to predict Fe and K concentrations due to their low concentrations in the oat samples. The coefficient of determinations of Fe and K were 0.57 and 0.77, respectively. In future studies, the stability and practicability of these models should be improved by using a high accuracy spectrophotometer and by performing calibrations with a wider range of oat chemicals.