Sumaporn Kasemsumran

Bio: Sumaporn Kasemsumran is an academic researcher from Kasetsart University. The author has contributed to research in topics: Partial least squares regression & Fermentation. The author has an hindex of 16, co-authored 43 publications receiving 973 citations. Previous affiliations of Sumaporn Kasemsumran include Kwansei Gakuin University.

The detection and quantification of adulteration in olive oil by near-infrared spectroscopy and chemometrics.

Abstract: A new procedure has been developed for the classification and quantification of the adulteration of pure olive oil by soya oil, sun flower oil, corn oil, walnut oil and hazelnut oil. The study was based on a chemometric analysis of the near-infrared (NIR) spectra of olive-oil mixtures containing different adulterants. The adulteration of olive oil was carefully carried out gravimetrically in a 4 mm quartz cuvette, starting with pure olive oil in the cuvette first. NIR spectra of the 525 adulterated mixtures were measured in the region of 12,000-4000 cm(-1). The spectra were subjected batch wise to multiplicative signal correction (MSC) before calculating the principal component (PCA) models. The MSC-corrected data were subjected to Savitzky-Golay smoothing and a mean normalization procedure before developing partial least-squares calibration (PLS) models. The results revealed that the models predicted the adulterants, corn oil, sun flower oil, soya oil, walnut oil and hazelnut oil involved in olive oil with error limits +/-0.57, +/-1.32, +/-0.96, +/-0.56 and +/-0.57% weight/weight, respectively. Furthermore, the PCA developed models were able to classify unknown adulterated olive oil mixtures with almost 100% certainty. Quantification of the adulterants was carried out using their respective PLS models within the same error limits as mentioned above.

Feasibility of Near-Infrared Spectroscopy to Detect and to Quantify Adulterants in Cow Milk

Abstract: Cow milk adulteration involves the dilution of milk with a less-expensive component, such as water or whey. Near-infrared spectroscopy (NIRS) was employed to detect the adulterations of milk, non-destructively. Two adulteration types of cow milk with water and whey were prepared, respectively. NIR spectra of milk adulterations and natural milk samples in the region of 1100 - 2500 nm were collected. The classification of milk adulterations and natural milk were conducted by using discriminant partial least squares (DPLS) and soft independent modelling of class analogy (SIMCA) methods. PLS calibration models for the determination of water and whey contents in milk adulteration were also developed, individually. Comparisons of the classification methods, wavelength regions and data pretreatments were investigated, and are reported in this study. This study showed that NIR spectroscopy can be used to detect water or whey adulterants and their contents in milk samples.

Simultaneous determination of human serum albumin, γ-globulin, and glucose in a phosphate buffer solution by near-infrared spectroscopy with moving window partial least-squares regression

Abstract: Near-infrared (NIR) spectra in the 12000–4000 cm−1 region were measured for phosphate buffer solutions containing human serum albumin (HSA), γ-globulin, and glucose with various concentrations at 37 °C. Five levels of full factorial design were used to prepare a sample set consisting of 125 samples of three component mixtures. The concentration ranges of HSA, γ-globulin and glucose were 0.00–6.00 g dl−1, 0.00–4.00 g dl−1 and 0.00–2.00 g dl−1, respectively. The 125 sample data were split into two sets, the calibration set with 95 data and the prediction set with 30 data. The most informative spectral ranges of 4648–4323, 4647–4255 and 4912–4304 cm−1 were selected by moving window partial least-squares regression (MWPLSR) for HSA, γ-globulin, and glucose in the mixtures, respectively. For HSA, the correlation coefficient (R) of 0.9998 and the root mean square error of prediction (RMSEP) of 0.0289 g dl−1 were obtained. For γ-globulin, R of 0.9997 and RMSEP of 0.0252 g dl−1 were obtained. The corresponding statistic values of glucose were 0.9997 and 0.0156 g dl−1, respectively. These statistical values obtained by MWPLSR are highly significant and better than those calculated by using the regions reported in the literature. The results presented here show that MWPLSR can select the informative regions with a simple procedure and increase the power of NIR spectroscopy for simultaneous determination of the concentrations of HSA, γ-globulin and glucose in the mixture systems.

Theory and application of near infrared reflectance spectroscopy in determination of food quality

Abstract: Near infrared reflectance spectroscopy (NIRS) is a non-destructive and rapid technique applied increasingly for food quality evaluation in recent years. It provides us more information to research the quality of food products. This review intends to give an overview of the type of information that can be obtained based on some developed theory and food research of NIRS. It includes the principle of NIRS technique, the specific techniques with chemometrics for data pre-processing methods, qualitative and quantitative analysis and model transfer, and the wide applications of NIRS in food science. In addition, the promise of NIRS technique for food quality evaluation is demonstrated, and some problems which need to be solved or investigated further are also discussed.

Recent technological advances for the determination of food authenticity

Abstract: The relative potential of various technologies for the confirmation of food authenticity and quality are discussed. Techniques that have found new applications in the field of quality assurance since 2001 are discussed in terms of their potential ease of application in an industrial setting. The use of specific techniques with chemometric analysis for the classification of food samples based on quality attributes is also included in this review. The techniques discussed are spectroscopy (UV, NIR, MIR, visible, Raman), isotopic analysis, chromatography, electronic nose, polymerase chain reaction, enzyme-linked immunosorbent assay and thermal analysis.