• Food Science and Industry
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• v.55 no.1
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• pp.2-22
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• 2022

Near-infrared spectroscopy (NIRS) is one of the representative non-destructive and eco-friendly analysis methods used for rapid analysis of various ingredients in the food industry. To develop analysis model with NIRS, Chemometrics are applied after pre-treatment of spectrum. Many studies have been reviewed on the analysis of general and functional components for agricultural and livestock products. In the case of livestock products, some studies have been conducted for on-line analysis. This study investigated results on various samples and component applying near-infrared spectroscopy. Furthermore, the results according to sample condition were compared. It was confirmed that NIRS is applied to various fields in the food industry.

• Applied Chemistry for Engineering
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• v.23 no.1
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• pp.35-41
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• 2012

This paper proposes a new methodology for the real-time on-line quality monitoring of biofuel processes through the integration of infrared spectroscopy and chemometrics. A method of Partial Least Squares (PLS) in Chemometrics is employed for quantitative analysis of key components in bioethanol products. After a number of preprocessing methods and variable importance in projection (VIP) are used, Savitzky-Golay method showed the best performance in terms of spectrum correction, noise reduction, and model maintenance. The proposed method allows us to economically forecast the concentration of multiple impurities encountered with the production of bioethanol. The proposed system is also accurate enough ($R^2$ > 0.99) to replace the laboratory analysis.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.345-355
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• 2007

PLS methods are suited for regressing q-variate Y variables on p-variate X variables even in the presence of multicollinearity problem among X variables. Consequently, they are useful for analyzing datasets with smaller number of observations compared to the number of variables, such as NIR(near-infrared) spectroscopy data in chemometrics. In this study, we propose two visualizing methods of p-variate X variables and q-variate Y variable that can be used in connection with PLS analysis.

• The Korean Journal of Pesticide Science
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• v.10 no.2
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• pp.84-90
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• 2006

In the field of agriculture, FT-NIR mainly has been used in qualitative management of produces without sample preparation with a data set built from a quantitative value of sample components confirmed by another analytical instrument. On the other hand, inert materials of crop protection products nearly haven't examined instrumental analysis because of analytical problems of high-molecular inert materials and a variety of formulation type. This study, results make it possible to solve an analytical problems of crop protection products using FT-NIR chemometrics technique from spectrum calculator module.

• Food Science of Animal Resources
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• v.44 no.4
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• pp.934-950
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• 2024

This study addresses the prevalent issue of meat species authentication and adulteration through a chemometrics-based approach, crucial for upholding public health and ensuring a fair marketplace. Volatile compounds were extracted and analyzed using headspace-solid-phase-microextraction-gas chromatography-mass spectrometry. Adulterated meat samples were effectively identified through principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA). Through variable importance in projection scores and a Random Forest test, 11 key compounds, including nonanal, octanal, hexadecanal, benzaldehyde, 1-octanol, hexanoic acid, heptanoic acid, octanoic acid, and 2-acetylpyrrole for beef, and hexanal and 1-octen-3-ol for pork, were robustly identified as biomarkers. These compounds exhibited a discernible trend in adulterated samples based on adulteration ratios, evident in a heatmap. Notably, lipid degradation compounds strongly influenced meat discrimination. PCA and PLS-DA yielded significant sample separation, with the first two components capturing 80% and 72.1% of total variance, respectively. This technique could be a reliable method for detecting meat adulteration in cooked meat.

• Korean Chemical Engineering Research
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• v.45 no.6
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• pp.596-603
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• 2007

Rapid or on-line coal analysis is of great interest in coal industry as it would allow efficient plant operation. Multivariate analysis has been applied to near-infrared(NIR) spectra coal for investigating the relationship between coal properties(%) (moisture, ash, volatile matter, fixed carbon, carbon, hydrogen, nitrogen, oxygen, sulfur), heating value(kcal/kg) and corresponding near-infrared spectral data. The quantitative analysis was carried out by applying PLS(partial least squares regression) to determine a methodology able to establish a relationship between coal properties and NIR spectral data being applied mathematical pre-treatments for minimizing the physical features of the samples. As a results of the analysis, this technique is able to classify the species of coals and to predict the all coal properties except ash, nitrogen and sulfur. The efficient operation of coal fired power plant is expected owing to real time on-line coal analysis of moisture and heating value.

• Journal of Ginseng Research
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• v.41 no.1
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• pp.85-95
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• 2017

Background: American ginseng (Panax quinquefolius L.) and Asian ginseng (Panax ginseng Meyer) products, such as slices, have a similar appearance, but they have significantly different prices, leading to widespread adulteration in the commercial market. Their aroma characteristics are attracting increasing attention and are supposed to be effective and nondestructive markers to determine adulteration. Methods: The aroma characteristics of American and Asian ginseng were investigated using gas chromatography-mass spectrometry(GC-MS) and an electronic nose (E-nose). Their volatile organic compounds were separated, classified, compared, and analyzed with different pattern recognition. Results: The E-nose showed a good performance in grouping with a principle component analysis explaining 94.45% of variance. A total of 69 aroma components were identified by GC-MS, with 35.6% common components and 64.6% special ingredients between the two ginsengs. It was observed that the components and the number of terpenes and alcohols were markedly different, indicating possible reasons for their difference. The results of pattern recognition confirmed that the E-nose processing result is similar to that of GC-MS. The interrelation between aroma constituents and sensors indicated that special sensors were highly related to some terpenes and alcohols. Accordingly, the contents of selected constituents were accurately predicted by corresponding sensors with most $R^2$ reaching 90%. Conclusion: Combined with advanced chemometrics, the E-nose is capable of discriminating between American and Asian ginseng in both qualitative and quantitative angles, presenting an accurate, rapid, and nondestructive reference approach.

• Analytical Science and Technology
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• v.21 no.5
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• pp.345-363
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• 2008

Process analytics has been already widely utilized in a large-scale continuous production line such as petroleum industries for several decades. Although the process analytics has a long history, a concept of "Process Analytical Technology (PAT)" has been rapidly adopted as a new paradigm for the process monitoring in the production process of various industries. In this review, current status and recent developments of PAT in various research bodies have been introduced, including the introduction of various types of analytical instruments, chemometrics tools, and perspectives and future applications of PAT as well as the fundamentals on PAT such as terminology and its historical background.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.48 no.1
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• pp.34-42
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• 2016

In this study, we classified three copying papers and Korean, Chinese, and Japanese traditional papers using IR and/or NIR spectra and principal component analysis. Various chemicals are used when producing fine papers. In this case, the IR method to analyze functional groups is suitable for the classification of paper. On the other hand, NIR analysis is more suitable for the classification of traditional papers, as it uses nearly raw materials (pulp). Therefore, principal component analysis using IR and NIR depending on the paper production process will be the classification tool of paper.

• YAKHAK HOEJI
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• v.48 no.3
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• pp.177-181
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• 2004

Non-invasive blood glucose measurement from mouse tail was performed by near-infrared (NIR) spectroscopy. Three groups; normal, type I diabetes (insulin dependent diabetes mellitus, IDDM), type II diabetes (non-insulin dependent diabetes mellitus, NIDDM) group, were studied over a 10 weeks period with the collection of near-infrared (NIR) spectra. Spectral variations from long-term measurement (10 weeks) from dramatic and nonlinear changes in the optical properties of the live tissue sample were compensated by chemometrics techniques such as principle component analysis (PCA) and partial least squares (PLS) regression. The effect from mouse body temperature changes on NIR spectral data was also considered. This study showed that the compensation of variations from long-term measurement and temperature changes improved calibration accuracy of non-invasive blood glucose measurement.