Mid-infrared spectroscopy and support vector machines applied to control the hydrogenation process of soybean oil

Sánchez, Jorge; Pereira, Sérgio Benedito Gonçalves; Lima, Patrícia Casarin de; Possebon, Gabriela; Tanamati, Augusto; Poppi, Ronei J.; Tanamati, Ailey Aparecida Coelho; Bona, Evandro

doi:10.1007/s00217-017-2855-9

Cited by 15 publications

(8 citation statements)

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“…However, an undesirable upshot of the hydrogenation of vegetable oils is the formation of trans isomers whose regular consumption in diets is associated with the risk of cardiovascular disease (Liu, Inbaraj, & Chen, 2007;Martin, de Oliveira, Visentainer, Matsushita, & de Souza, 2008). The iodine value (IV) is one of the parameters mostly used for monitoring the progress of the vegetable oils hydrogenation reaction (Dijkstra, 2012;Sanchez et al, 2017). IV represents the relative degrees of unsaturation of the fatty acids and its first introduction in 1884 by German chemist Arthur von Hübl was a breakthrough in the analysis of oils and fats (Li, van de Voort, Sedman, & Ismail, 1999).…”

Section: Introductionmentioning

confidence: 99%

Monitoring industrial hydrogenation of soybean oil using self-organizing maps

et al. 2019

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Monitoring the hydrogenation reaction is crucial to guarantee a product with desired properties. The combination of gas chromatography (GC) with self-organizing maps (SOM) may be an alternative to extract relevant information during the hydrogenation. We analyzed two partially hydrogenated fats produced in an industrial reactor. The quantification of the fatty acids methyl esters and the iodine value (IV) calculation was performed by GC. The SOM was able to cluster the samples according to the IV and reaction time. The weight maps depicted the variation of monounsaturated fatty acids associated with the increase of 18:1 and the variation of poly-unsaturated are mainly correlated with 18:2. An increase was observed in saturated fatty acids and trans-fatty acids associated respectively with 18:0 and 18:1(trans). Besides, it was confirmed that trans-isomers are more stable than the cis-isomers. Therefore, the SOM with GC was an efficient tool for monitoring the hydrogenation process.

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Section: Introductionmentioning

confidence: 99%

Monitoring industrial hydrogenation of soybean oil using self-organizing maps

et al. 2019

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“…The highest R v 2 value obtained for iodine value prediction was 0.98. Similarly, other authors have made very good models for iodine value prediction [ 25 , 34 ]. Dyminska et al analyzed 13 different oils (sunflower, avocado, hemp, high-linolenic flax, low-linolenic flax, safflower, walnut, roasted sesame, rice, corn, rapeseed, pumpkin seed, hazel) and obtained a model based on IR spectral data with R v 2 = 0.988.…”

Section: Discussionmentioning

confidence: 85%

“…However, the purpose of this study was very different to ours. Only one type of oil was used, and the aim was to monitor changes in the iodine value during a very specific process: hydrogenation [ 25 ]. In our study, the aim was to control the quality of different types of specific oils not subjected to any deterioration process.…”

Section: Discussionmentioning

confidence: 99%

“…The use of infrared spectroscopy for vegetable oil analysis is not new [ 19 ]. Many successful studies for the detection of geographical origin and adulteration as well as quantification of oxidation parameters have been conducted [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 ]. Most studies are performed on olive oil and edible oils used for frying [ 23 , 27 , 28 , 29 , 30 , 31 , 32 ].…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, the number of samples is usually low, or only one type of oil is used. Samples are usually prepared by heating or oxidizing the oils to different degrees [ 22 , 24 , 25 , 33 ]. However, only a few studies have been conducted for a larger set of different oils [ 34 ] and for many different parameters [ 27 ] and never for the types of oils used in this study.…”

Section: Introductionmentioning

confidence: 99%

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Statistical FT-IR Spectroscopy for the Characterization of 17 Vegetable Oils

Ladan

Glavač

2022

Molecules

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Vegetable oils have been utilized for centuries in the food, cosmetic, and pharmaceutical industries, and they contribute beneficially to overall human health, to active skincare, and to effective treatments. Monitoring of the vegetable oils is carried out by the methods described in the European Pharmacopeia, which is time-consuming, has poor repeatability, and involves the use of toxic organic chemicals and expensive laboratory equipment. Many successful studies using IR spectroscopy have been carried out for the detection of geographical origin and adulteration as well as quantification of oxidation parameters. The aim of our research was to explore FT-IR spectroscopy for assessing the quality parameters and fatty acid composition of cranberry, elderberry, borage, blackcurrant, raspberry, black mustard, walnut, sea buckthorn, evening primrose, rosehip, chia, perilla, black cumin, sacha inchi, kiwi, hemp, and linseed oil. Very good models were obtained for the α-linolenic acid and linoleic acid contents, with R2 = 1.00; Rv2 values of 0.98, 0.92, 0.89, and 0.84 were obtained for iodine value prediction, stearic acid content, palmitic acid content, and unsaponifiable matter content, respectively. However, we were not able to obtain good models for all parameters, and the use of the same process for variable selection was found to be not suitable for all cases.

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