Rapid characterization of transgenic and non-transgenic soybean oils by chemometric methods using NIR spectroscopy

Luna, Aderval S.; Silva, Arnaldo P. da; Pinho, Jéssica S. A.; Ferré, Joan; Boqué, Ricard

doi:10.1016/j.saa.2012.02.085

Cited by 99 publications

(67 citation statements)

References 21 publications

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“…Genetic engineering deals with ADN manipulation and creates new features for the original living being, i.e., changing the original genes display or introducing a new gene to the ADN. The modified gene is called transgene, from which the terms transgenic and genetically modified are derived (LUNA et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

<b>Hydration kinetics of transgenic soybeans

et al. 2015

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ABSTRACT. The kinetic and experimental analyses of the hydration process of transgenic soybeans (BRS 225 RR) are provided. The importance of the hydration process consists of the grain texture modifications which favor grinding and extraction of soybeans. The soaking isotherms were obtained for four different temperatures. Results showed that temperature affected transgenic soybeans´ hydration rate and time. )), the equilibrium concentration remained practically unchanged.Keywords: hydration, kinetics, transgenic soybean, mass transfer. Cinética de hidratação de soja transgênicaRESUMO. Este trabalho apresenta o estudo experimental e cinético do processo de hidratação de grãos de soja transgênica (BRS 225 RR). A importância da hidratação de grãos consiste na modificação da textura característica dos grãos, o que favorece a moagem e a subsequente etapa de extração. Foram obtidas curvas cinéticas de hidratação de soja para quatro níveis de temperatura. A análise destas curvas indicou que a temperatura exerce grande influência sobre a velocidade e o tempo de hidratação da soja transgênica. Durante 270 min. de processo, a umidade em base seca dos grãos aumentou de 0.12 ± 0.01 kg kg )), a concentração de equilíbrio praticamente não variou.Palavras-chave: hidratação, grãos, soja transgênica, transferência de massa.

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Section: Introductionmentioning

confidence: 99%

<b>Hydration kinetics of transgenic soybeans

et al. 2015

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“…These new variables are called Principal Component or PC (Arvanitoyannis, 2006;Luna, Silva, Pinho, Ferré, & Boqué, 2013;Pirouette, 2003).…”

Section: Exploratory Analysis Techniquesmentioning

confidence: 99%

“…The analysis was based on spectral data in the NIR region, in the spectral range of 1200-2500 nm with first derivative of the spectra (Grasel & Ferrão, 2016). Luna et al (2013) applied chemometric tools in NIR spectroscopic data and demonstrated that NIR spectroscopy can provide a rapid, nondestructive and reliable method to distinguish non-transgenic and transgenic soybean oils. Munck et al (2004) reported the use of PCA in NIR spectral data as screening method to characterize barley endosperm mutants and concluded that genetic diversity such as from gene regulated polysaccharide and storage protein pathways in the endosperm tissue can be discovered directly from the phenotype by chemometric classification of a spectral library, where the spectra were subjected to multiplicative signal correction (MSC).…”

Section: Exploratory Analysis Techniquesmentioning

confidence: 99%

Separation of Cultivars of Soybeans by Chemometric Methods Using Near Infrared Spectroscopy

Panero¹,

Silva²,

Panero³

et al. 2018

JAS

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Near Infrared (NIR) Spectroscopy technique combined with chemometrics methods were used to group and identify samples of different soy cultivars. Spectral data, collected in the range of 714 to 2500 nm (14000 to 4000 cm -1 ), were obtained from whole grains of four different soybean cultivars and were submitted to different types of pre-treatments. Chemometrics algorithms were applied to extract relevant information from the spectral data, to remove the anomalous samples and to group the samples. The best results were obtained considering the spectral range from 1900.6 to 2187.7 nm (5261.4 cm -1 to 4570.9 cm -1) and with spectral treatment using Multiplicative Signal Correction (MSC) + Baseline Correct (linear fit), what made it possible to the exploratory techniques Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) to separate the cultivars. Thus, the results demonstrate that NIR spectroscopy allied with de chemometrics techniques can provide a rapid, nondestructive and reliable method to distinguish different cultivars of soybeans.

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“…García-Molina et al (2016) used spectral sensing in the region of 400-2500 nm to discriminate transgenic wheat grain with excellent accuracy. Moreover, NIR combined with chemometrics has proved effective in identification of transgenic soybean oils (Luna et al, 2013), rice mutant seeds (Liu et al, 2014) and transgenic tomato (Xie et al, 2007). That is to say, a discriminant analysis model based on NIR spectra obtained enough information to discriminate the transgenic from parental samples because of their differences in chemical components.…”

Section: Classification Performance Based On Entire Spectral Bandsmentioning

confidence: 99%

Screening of transgenic maize using near infrared spectroscopy and chemometric techniques

Feng

Yin²,

Zhang

et al. 2018

Span. j. agric. res.

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The applicability of near infrared (NIR) spectroscopy combined with chemometrics was examined to develop fast, low-cost and non-destructive spectroscopic methods for classification of transgenic maize plants. The transgenic maize plants containing both cry1Ab/cry2Aj-G10evo proteins and their non-transgenic parent were measured in the NIR diffuse reflectance mode with the spectral range of 700-1900 nm. Three variable selection algorithms, including weighted regression coefficients, principal component analysis -loadings and second derivatives were used to extract sensitive wavelengths that contributed the most discrimination information for these genotypes. Five classification methods, including K-nearest neighbor, Soft Independent Modeling of Class Analogy, Naive Bayes Classifier, Extreme Learning Machine (ELM) and Radial Basis Function Neural Network were used to build discrimination models based on the preprocessed full spectra and sensitive wavelengths. The results demonstrated that ELM had the best performance of all methods, even though the model's recognition ability decreased as the variables in the training of neural networks were reduced by using only the sensitive wavelengths. The ELM model calculated on the calibration set showed classification rates of 100% based on the full spectrum and 90.83% based on sensitive wavelengths. The NIR spectroscopy combined with chemometrics offers a powerful tool for evaluating large number of samples from maize hybrid performance trials and breeding programs.

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Rapid characterization of transgenic and non-transgenic soybean oils by chemometric methods using NIR spectroscopy

Cited by 99 publications

References 21 publications

<b>Hydration kinetics of transgenic soybeans

<b>Hydration kinetics of transgenic soybeans

Separation of Cultivars of Soybeans by Chemometric Methods Using Near Infrared Spectroscopy

Screening of transgenic maize using near infrared spectroscopy and chemometric techniques

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