Edible oil

Ahmed, Syed Riaz; Shafique, Aimen; Azeem, Farrukh; Nadeem, Habib Ullah; Siddique, Muhammad Hussnain; Zubair, Muhammad; Rasool, Danish; Rasul, Ijaz

doi:10.1016/b978-0-12-821886-0.00002-6

Cited by 3 publications

(1 citation statement)

References 109 publications

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“…Edible oils are rich in essential nutrients for human beings and thus are some of the most common cooking ingredients in our daily lives [ 1 ]. However, different kinds of oils have different compositions and contents of substances that are beneficial to human health.…”

Section: Introductionmentioning

confidence: 99%

Reflectance Spectroscopy with Multivariate Methods for Non-Destructive Discrimination of Edible Oil Adulteration

Weng

Wang

et al. 2021

Biosensors

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The visible and near-infrared (Vis-NIR) reflectance spectroscopy was utilized for the rapid and nondestructive discrimination of edible oil adulteration. In total, 110 samples of sesame oil and rapeseed oil adulterated with soybean oil in different levels were produced to obtain the reflectance spectra of 350–2500 nm. A set of multivariant methods was applied to identify adulteration types and adulteration rates. In the qualitative analysis of adulteration type, the support vector machine (SVM) method yielded high overall accuracy with multiple spectra pretreatments. In the quantitative analysis of adulteration rate, the random forest (RF) combined with multivariate scattering correction (MSC) achieved the highest identification accuracy of adulteration rate with the full wavelengths of Vis-NIR spectra. The effective wavelengths of the Vis-NIR spectra were screened to improve the robustness of the multivariant methods. The analysis results suggested that the competitive adaptive reweighted sampling (CARS) was helpful for removing the redundant information from the spectral data and improving the prediction accuracy. The PLSR + MSC + CARS model achieved the best prediction performance in the two adulteration cases of sesame oil and rapeseed oil. The coefficient of determination (RPcv2) and the root mean square error (RMSEPcv) of the prediction set were 0.99656 and 0.01832 in sesame oil adulterated with soybean oil, and the RPcv2 and RMSEPcv were 0.99675 and 0.01685 in rapeseed oil adulterated with soybean oil, respectively. The Vis-NIR reflectance spectroscopy with the assistance of multivariant analysis can effectively discriminate the different adulteration rates of edible oils.

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Section: Introductionmentioning

confidence: 99%

Reflectance Spectroscopy with Multivariate Methods for Non-Destructive Discrimination of Edible Oil Adulteration

Weng

Wang

et al. 2021

Biosensors

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Importance and Applications of Biodegradable Materials and Bioplastics From Renewable Resources

Ahmed¹,

Rasul²,

Ijaz³

et al. 2022

Biodegradable Materials and Their Applications

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Comprehensive Analysis of the Components of Walnut Kernel (Juglans regia L.) in China

Geng

Ning

et al. 2021

Journal of Food Quality

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The contents of main components in 45 walnut kernels from 5 walnut-planting provinces in China (Yunnan, Shaanxi, Shandong, Hebei, and Sichuan) were determined using colorimetry, high-performance liquid chromatography, and gas chromatography, including flavonoids, vitamin E, trace elements, fatty acids, and amino acids. The levels of flavonoids and vitamin E were higher in walnuts from Yunnan than in walnuts from the other four provinces. The levels of zinc and iron were relatively higher in walnuts from Shandong, and the calcium content in walnuts from Yunnan was much lower. No obvious difference was found in crude fat concentration for nuts from the five provinces, but differences were observed in the crude protein content. Oleic acid was the predominant unsaturated fatty acids in all walnut species; the monounsaturated fatty acid content was the highest in walnuts from Yunnan. The data obtained here provided insight into differences in walnuts resulting from different growing environments and germplasm genetic traits.

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Edible oil

Cited by 3 publications

References 109 publications

Reflectance Spectroscopy with Multivariate Methods for Non-Destructive Discrimination of Edible Oil Adulteration

Reflectance Spectroscopy with Multivariate Methods for Non-Destructive Discrimination of Edible Oil Adulteration

Importance and Applications of Biodegradable Materials and Bioplastics From Renewable Resources

Comprehensive Analysis of the Components of Walnut Kernel (Juglans regia L.) in China

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