Recognition of osmotolerant yeast spoilage in kiwi juices by near-infrared spectroscopy coupled with chemometrics and wavelength selection

Niu, Chen; Yuan, Yahong; Guo, Hong; Wang, Xin; Wang, Xuan; Yue, Tianli

doi:10.1039/c7ra12266g

Cited by 7 publications

(3 citation statements)

References 30 publications

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“…The statistical model can be almost completely described by means of the first two PCs, which accounted for 99% of the total variance. The PCA clearly shows that YCH can be classified based on genus, which is consistent with previous studies showing that FTIR spectra of yeast cells can be used to discriminate yeasts strains and species (Kümmerle et al ., 1998; Oelofse et al ., 2010; Niu et al ., 2018).…”

Section: Resultsmentioning

confidence: 99%

Use of FT‐NIR and XPS techniques to distinguish cell hull fractions prepared by autolysis or HPH from Saccharomyces cerevisiae and Brettanomyces bruxellensis strains

Bakhos

Skaff

Esvan

et al. 2021

Int J of Food Sci Tech

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Yeast hulls can be used to adsorb undesirable compounds such as volatile phenols that may be present in wine. To understand this adsorption process, the properties of the cell walls and their chemical composition need to be better understood. A study was conducted using four different yeast fractions of either autolysed or high-pressure homogeniser (HPH)-crushed yeast biomasses of Saccharomyces cerevisiae and Brettanomyces bruxellensis. Near-infrared spectroscopy (FT-NIR) coupled with X-ray photoelectron spectroscopy (XPS) was used and analysed by principal component analysis (PCA). The FT-NIR spectral region of Saccharomyces and Brettanomyces statistically analysed by PCA showed a clear discrimination accounting for 76% of the variation in the data for PC1; moreover, yeast hulls prepared from the same strain and subjected to two different treatments were also separated. These methods classify yeast cell hulls (YCH) according to strain, composition and treatment applied. Our results indicate that yeast hulls obtained by autolysis are less rich in proteins than those resulting from HPH treatment due to the high pressure that releases more proteins and exposes them on the surface of the cell wall. The composition of YCH at the extreme surface is similar to that found deeper in the wall.

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Section: Resultsmentioning

confidence: 99%

Use of FT‐NIR and XPS techniques to distinguish cell hull fractions prepared by autolysis or HPH from Saccharomyces cerevisiae and Brettanomyces bruxellensis strains

Bakhos

Skaff

Esvan

et al. 2021

Int J of Food Sci Tech

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show abstract

“…Furthermore, CARS was a wavelength selection method based on “survival of the fittest” from Darwin's Evolution Theory aiming at reducing redundant information in the full wavelengths models (Niu et al, ), and it may effectively remove unused variables and reduce the co‐linear effects of modeling variables (Wang et al, ). Therefore, CARS method was used to select variables in this article.…”

Section: Methodsmentioning

confidence: 99%

Study on pesticide residues classification of lettuce leaves based on polarization spectroscopy

Zhou

Sun

et al. 2018

J Food Process Engineering

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In order to effectively implement the rapid and nondestructive testing of pesticide residues in lettuce leaves, polarization spectral detection technology was used in this article. There were 90 pieces of lettuce leaves from five different groups, as well as a total of 450 samples of lettuce were used to collect polarization spectral information. CARS, IRIV, and SPA were used to obtain optimal wavelengths. BP neural network, KNN, and SVM were used to establish classification models. The results showed that the significance of these parameters from primary factor to secondary factor were incident zenith angle A, detector polarization angle D, detecting zenith angle B, and sample stage azimuth E, respectively. Besides, optimal level of A, B, D, and E were 60°, 45°, 30°, and 270°, respectively. Furthermore, the best classification model different kinds of pesticide residues in lettuce leaves was CARS‐SVM model, with calibration identification rate of 100%, prediction identification rate of 97.78%. It confirms that polarization spectral detection technology is a feasible and effective method for classifying different pesticide residues in lettuce leaves. Practical applications It is of great significance to understand the effects of pesticide residues on the biological structure and to reveal new biological functions and mechanisms of action. In order to effectively implement the rapid and nondestructive testing of pesticide residues in lettuce leaves, polarization spectral detection technology was used in this article. In addition, the order and superior level of polarization spectral factor were obtained through the calculation of the range using orthogonal test. It confirms that the polarization spectra is a feasible and effective method for discriminating different pesticide residues in lettuce leaves.

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“…Detection and identification of spoilage yeast in beverages was demonstrated using SERS (78). A near-infrared approach was also utilized for the example of kiwifruit juices, with particular focus on osmotolerant yeast, which are frequent contaminants of high-sugar foods (90). In fact, examples of the safety surveillance application of vibrational spectroscopy can be found not only in the food industry but in environmental studies, e.g., to monitor water contamination (68).…”

Section: Yeastsmentioning

confidence: 99%

Whole-Organism Analysis by Vibrational Spectroscopy

Christensen

Rüther

Kochan

et al. 2019

Annual Rev. Anal. Chem.

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Vibrational spectroscopy has contributed to the understanding of biological materials for many years. As the technology has advanced, the technique has been brought to bear on the analysis of whole organisms. Here, we discuss advanced and recently developed infrared and Raman spectroscopic instrumentation to whole-organism analysis. We highlight many of the recent contributions made in this relatively new area of spectroscopy, particularly addressing organisms associated with disease with emphasis on diagnosis and treatment. The application of vibrational spectroscopic techniques to entire organisms is still in its infancy, but new developments in imaging and chemometric processing will likely expand in the field in the near future.

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Recognition of osmotolerant yeast spoilage in kiwi juices by near-infrared spectroscopy coupled with chemometrics and wavelength selection

Abstract: The study developed a NIR-SVM model for accurate recognition of osmotolerant yeasts in kiwi juice for the first time.

Cited by 7 publications

References 30 publications

Use of FT‐NIR and XPS techniques to distinguish cell hull fractions prepared by autolysis or HPH from Saccharomyces cerevisiae and Brettanomyces bruxellensis strains

Use of FT‐NIR and XPS techniques to distinguish cell hull fractions prepared by autolysis or HPH from Saccharomyces cerevisiae and Brettanomyces bruxellensis strains

Study on pesticide residues classification of lettuce leaves based on polarization spectroscopy

Whole-Organism Analysis by Vibrational Spectroscopy

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