Differentiating Rice Varieties by Inductively Coupled Plasma Mass Spectrometry Chemical Profiling with Singular Value Decomposition Background Correction

Wang, Xinyi; Harrington, Peter de B.

doi:10.1007/s41664-018-0055-7

Cited by 2 publications

(2 citation statements)

References 36 publications

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“…Rice is one of the world's top three staple foods, 1–3 and feeds nearly half of the world's population 4 . Fresh rice has a special fragrance, glossy grain surface and good taste 5,6 . As a seasonal crop, however, rice needs to be stored to meet year‐round demand.…”

Section: Introductionmentioning

confidence: 99%

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Determination of trace chelating carboxylic acids in rice by green extraction combined with liquid chromatography–mass spectrometry analysis and its application in the evaluation of old and new rice

Kang,

Wang,

Feng

et al. 2024

Rapid Comm Mass Spectrometry

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RationaleAccurate identification of old rice samples from new ones benefits their market circulation and consumers. However, the current detection methods are still not satisfactory because of their insufficient accuracy or (and) time‐consuming process.MethodsChelating carboxylic acids (CCAs) were selectively extracted from rice, by stirring with chelating resin and a dilute Na2CO3 solution. The green analytical chemistry guidelines for sample preparation were investigated by using the green chemistry calculator AGREE prep. The extractant was determined by liquid chromatography–mass spectrometry (LC/MS), and statistical analysis of the analytical data was carried out to evaluate the significance of the difference by ChiPlot.ResultsThe limit of quantitation for the CCAs is in the range of 1 to 50 ng/mL, with a reasonable reproducibility. The CCAs in 23 rice samples were determined within a wide concentration range from 0.03 to 1174 μg/g. Intriguingly, the content of citric acid, malonic acid, α‐ketoglutaric acid and cis‐aconite acid in new rice was each found to be distinctively higher than that in old rice by several times. Even mixtures of old and new rice were found to show much difference in the concentration of citric acid and malic acid.ConclusionA green analytical method has been developed for the simultaneous determination of CCAs by LC/MS analysis, and the identification of old rice samples from new ones was easily carried out according to their CCA content for the first time. The results indicated that the described method has powerful potential for the accurate identification of old rice samples from new ones.

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Section: Introductionmentioning

confidence: 99%

“…4 Fresh rice has a special fragrance, glossy grain surface and good taste. 5,6 As a seasonal crop, however, rice needs to be stored to meet year-round demand. During storage, the nutritional composition of rice will change under the influence of environmental factors.…”

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confidence: 99%

Determination of trace chelating carboxylic acids in rice by green extraction combined with liquid chromatography–mass spectrometry analysis and its application in the evaluation of old and new rice

Kang,

Wang,

Feng

et al. 2024

Rapid Comm Mass Spectrometry

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Characterizing Variances of Adulterated Extra Virgin Olive Oils by UV-Vis Spectroscopy Combined with Analysis of Variance-Projected Difference Resolution (ANOVA-PDR) and Multivariate Classification

Gao

Zhang

2023

Applied Sciences

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The analysis of variance-projected difference resolution (ANOVA-PDR) was proposed and compared with multivariate classification for its potential in detecting possible food adulteration in extra virgin olive oils (EVOOs) by UV-Vis spectra. Three factors including origin, adulteration level, and adulteration type were systematically examined by the ANOVA-derived methods. The ANOVA-PDR quantitatively presented the separation of the internal classes according to the three main factors. Specifically, the average ANOVA-derived PDRs of the EVOO origination and adulteration level, respectively, is 4.01 and 1.78, while the conventional PDRs of the three factors are all less than 1.5. Furthermore, the partial least-squares-discriminant analysis (PLS-DA) and the PLS regression (PLSR) modeling with the selected sub-datasets from different origins were used to verify the results. The resulting models suggested that the three main factors and their interactions were all important sources of spectral variations.

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Differentiating Rice Varieties by Inductively Coupled Plasma Mass Spectrometry Chemical Profiling with Singular Value Decomposition Background Correction

Cited by 2 publications

References 36 publications

Determination of trace chelating carboxylic acids in rice by green extraction combined with liquid chromatography–mass spectrometry analysis and its application in the evaluation of old and new rice

Determination of trace chelating carboxylic acids in rice by green extraction combined with liquid chromatography–mass spectrometry analysis and its application in the evaluation of old and new rice

Characterizing Variances of Adulterated Extra Virgin Olive Oils by UV-Vis Spectroscopy Combined with Analysis of Variance-Projected Difference Resolution (ANOVA-PDR) and Multivariate Classification

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