Differences between conventional and glyphosate tolerant soybeans and moisture effect in their discrimination by near infrared spectroscopy

Agelet, Lidia Esteve; Armstrong, Paul R.; Tallada, Jasper G.; Hurburgh, Charles R.

doi:10.1016/j.foodchem.2013.04.087

Cited by 13 publications

(2 citation statements)

References 17 publications

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“…As a promising alternative approach to the traditional analytical techniques, near-infrared (NIR) spectrometry, when combined with chemometrics, has demonstrated great potential for rapid analysis of food products [ 15 – 19 ]. NIR has some advantages over traditional chemical analysis, including less sample pretreatments, being fast and economical, simultaneous multicomponent characterization or analysis, and the feasibility for online analysis.…”

Section: Introductionmentioning

confidence: 99%

Quality Degradation of Chinese White Lotus Seeds Caused by Dampening during Processing and Storage: Rapid and Nondestructive Discrimination Using Near-Infrared Spectroscopy

Cai

et al. 2015

Journal of Analytical Methods in Chemistry

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Dampening during processing or storage can largely influence the quality of white lotus seeds (WLS). This paper investigated the feasibility of using near-infrared (NIR) spectroscopy and chemometrics for rapid and nondestructive discrimination of the dampened WLS. Regular (n = 167) and dampened (n = 118) WLS objects were collected from five main producing areas and NIR reflectance spectra (4000–12000 cm−1) were measured for bare kernels. The influence of spectral preprocessing methods, including smoothing, taking second-order derivatives (D2), and standard normal variate (SNV), on partial least squares discrimination analysis (PLSDA) was compared to select the optimal data preprocessing method. A moving-window strategy was combined with PLSDA (MWPLSDA) to select the most informative wavelength intervals for classification. Based on the selected spectral ranges, the sensitivity, specificity, and accuracy were 0.927, 0.950, and 0.937 for SNV-MWPLSDA, respectively.

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Section: Introductionmentioning

confidence: 99%

Quality Degradation of Chinese White Lotus Seeds Caused by Dampening during Processing and Storage: Rapid and Nondestructive Discrimination Using Near-Infrared Spectroscopy

Cai

et al. 2015

Journal of Analytical Methods in Chemistry

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“…La soja ha estat per la seva importància a nivell mundial la lleguminosa on s'han centrat més esforços, havent-se utilitzat per a la determinació de proteïna, aminoàcids essencials, àcids grassos, carbohidrats i fòsfor inorgànic (Jiang 2009;Fontaine 2001;Sun 2008;Delwiche 2006). Actualment els esforços en el camp de la soja se centren en la discriminació de varietats transgèniques de les convencionals mitjançant l'espectre NIR (Esteve 2013;Wu 2013). La tecnologia NIR també s'ha aplicat per a l'anàlisi de proteïna, humitat, grasses totals, àcids grassos, cendres, mido, sòlids solubles, fibra dietètica total i propietats funcionals en cigrons i pèsols (Flinn 1998;Font 2006;Urban 1999;Chalucova 2000).…”

Section: Estat De La Tecnologia Ir I Aplicació En L'agriculturaunclassified

Utilització de l'espectroscòpia d'infraroig com a eina per a la selecció i millora de la mongeta seca (Phaseolus vulgaris L.)

Plans¹

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Common beans (Phaseolus vulagaris L.) are one of the most consumed and produced legumes in the world. Its high protein content makes it a high nutritional value product. As a result of its wide diversity, there are thousands of them conserved in seed banks and plant breeding centers. Chemical and sensory evaluations are necessary for their characterization and inclusion in plants breeding programs. Chemical analysis and sensory panels are time-consuming protocols and often require regents, which make them unsuitable for analysis of large amount of sample. Spectroscopy techniques are well-established nondestructible methods with a minimum sample preparation for determining the chemical components and sensory traits of foods. These techniques are suitable for managing a large volume of samples, because spectrum collection takes less than a minute. The main objective of this thesis is to develop regression models to correlate IR spectra with chemical composition and sensory traits. This thesis is composed of three publications in indexed journals, in which the main results are: i) For proper prediction of the chemical composition in common beans seed-coat, this seed-coat has to be removed from the cotyledon and ground to obtain a homogenous IR spectra; ii) Calcium, ash, dietary fiber values of the seed-coat can be predicted using NIR models; iii) It is possible to predict protein, starch, and total amylose using IR technology, moreover, the best models are obtained by the benchtop FT-NIR; iv) Nowadays, portable IR technology is almost at the same level as the benchtop instruments in terms of goodness of fit in prediction models; v) IR spectrum of the sample has a big impact in the developed models, so, it is necessary to cook , dry and ground the beans before registering the spectra; vi) It is not possible to predict aroma and seed-coat perception using NIR; vii) Finally, it is possible to integrate IR technology in common beans plants breeding and selection programs to analyze chemical composition and sensory trait. La mongeta seca (Phaseolus vulgaris L.) és una de les lleguminoses de gra més consumides i produïdes arreu del món i amb un alt valor nutricional degut al seu elevat contingut proteic. La seva gran diversitat fa que existeixen milers d’entrades conservades en els bancs de llavors i centres de millora vegetal. L’avaluació química i sensorial d’aquestes entrades donaria informació molt valuosa per a programes de millora vegetal, però requereixen processos llargs i laboriosos que els fan poc apropiats quan cal caracteritzar un gran nombre de mostres. L’espectroscòpia d’infraroig pot ser una alternativa ja que, l’espectre de la mostra, que es reagistra en pocs segons i que necessita un mínim pretractament de la mostra, podria donar una estimació dels caràcters químics i sensorials. L’objectiu principal d’aquesta tesi és, doncs, obtenir models que permetin correlacionar l’espectre en l’infraroig amb els atributs sensorial de la mongeta i amb el contingut d'aquells components químics que semblen influir en aquests atributs. La tesi s’articula en tres treballs: l'anàlisi química de la pell de la mongeta (fibra dietètica, àcids urònics, cendres, calci i magnesi), l'anàlisi química del cotiledó (proteïna, midó, amilosa) i els atributs sensorials de la mongeta (aroma, gust, farinositat, percepció, rugositat i brillantor de la pell). Els principals resultats són: i) Per a la correcte predicció de la composició química de la pell, aquesta ha de ser separada de cotiledó i molturada a fi d’obtenir una mostra suficientment homogènia; ii) El contingut en calci, cendres i fibra diatètica de la pell de la mongeta es pot predir utilitzant l’espectre NIR; iii) Es possible obtenir models per a la predicció de proteïna, midó i amilosa utilitzant varies tecnologies IR, essent els millors models el obtinguts amb FT-NIR; iv) Els resultats obtinguts amb equips d'IR portàtils i els seus homòlegs de sobretaula tenen bondats similars ; v) Per a la correcta predicció dels atributs sensorial és necessari coure, deshidratar i molturar la mongeta abans d’obtenir l’espectre; vi) els espectres NIR van permetre estimar el gust, farinositat, brillantor de la pell i rugositat de la pell de la mongeta valorats per un panel de tastador però no l’aroma i la percepció de la pell; vii) Finalment, es possible utilitzar la tecnologia IR, sent una eina molt valuosa per a la caracterització de col·leccions molt nombroses de mostres, per la selecció i la millora.

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Sensors for Non‐Destructive Quality Evaluation of Food

et al. 2021

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Differences between conventional and glyphosate tolerant soybeans and moisture effect in their discrimination by near infrared spectroscopy

Cited by 13 publications

References 17 publications

Quality Degradation of Chinese White Lotus Seeds Caused by Dampening during Processing and Storage: Rapid and Nondestructive Discrimination Using Near-Infrared Spectroscopy

Quality Degradation of Chinese White Lotus Seeds Caused by Dampening during Processing and Storage: Rapid and Nondestructive Discrimination Using Near-Infrared Spectroscopy

Utilització de l'espectroscòpia d'infraroig com a eina per a la selecció i millora de la mongeta seca (Phaseolus vulgaris L.)

Sensors for Non‐Destructive Quality Evaluation of Food

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