Determining the geographical origin of Sechium edule fruits by multielement analysis and advanced chemometric techniques

Hidalgo, Melisa J.; Fechner, Diana C.; Marchevsky, Eduardo Jorge; Pellerano, Roberto Gerardo

doi:10.1016/j.foodchem.2016.04.120

Cited by 34 publications

(15 citation statements)

References 24 publications

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“…33 On the other hand, exploratory analysis and principal component analysis (PCA) have been widely used to evaluate samples from different geographical origin or submitted to different treatments. [34][35][36][37] This type of chemometric analysis facilitates the visualization and interpretation of complex data. 38,39 Although PCA is widely used in analytical chemistry, its use as a tool to evaluate the mineral composition of foods, mainly for vegetable samples from biofortification studies, is still scarce in the literature.…”

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confidence: 99%

Effect of Selenite and Selenate Application on Mineral Composition of Lettuce Plants Cultivated Under Hydroponic Conditions: Nutritional Balance Overview Using a Multifaceted Study

Silva¹,

Cidade²,

Heerdt³

et al. 2017

J. Braz. Chem. Soc.

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The effect of selenate and selenite enrichment on mineral composition of a red type of lettuce cv. "Veneza roxa" was evaluated using inductively coupled plasma-optical emission spectroscopy (ICP OES), molecular modeling and principal component analysis (PCA). Both Se species did not show toxicity, while selenate promoted the greatest Se accumulation by the plant. There was an increase of 886 µg of Se per 100 g of fresh sample at different concentrations of selenate, but for selenite the maximum variation was only of 114 µg per 100 g. Selenate promoted the absorption of Mo and S and the reduction of K, Mn and P, meanwhile selenite increased Mn and decreased Mo accumulation. Copper and Fe absorption was negatively affected, Ca and Mg showed a slight increase, and Na and Zn were not affected by Se species. Despite the changes in the nutritional balance, Se-enriched lettuce can still be considered a potential dietary source of this essential element.

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confidence: 99%

Effect of Selenite and Selenate Application on Mineral Composition of Lettuce Plants Cultivated Under Hydroponic Conditions: Nutritional Balance Overview Using a Multifaceted Study

Silva¹,

Cidade²,

Heerdt³

et al. 2017

J. Braz. Chem. Soc.

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“…A study was conducted to investigate how mineral composition of the fruit could be used as a discriminating factor to determine geographical origin of S. edule in Argentina. After microwave digestion, major and trace element composition was determined using ICP-OES [61]. LDA, KNN, PLS-DA, and SVM were applied for classification of a 92-sample data set.…”

Section: Vegetablesmentioning

confidence: 99%

Comparison of Chemometric Problems in Food Analysis using Non-Linear Methods

2020

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Food analysis is a challenging analytical problem, often addressed using sophisticated laboratory methods that produce large data sets. Linear and non-linear multivariate methods can be used to process these types of datasets and to answer questions such as whether product origin is accurately labeled or whether a product is safe to eat. In this review, we present the application of non-linear methods such as artificial neural networks, support vector machines, self-organizing maps, and multi-layer artificial neural networks in the field of chemometrics related to food analysis. We discuss criteria to determine when non-linear methods are better suited for use instead of traditional methods. The principles of algorithms are described, and examples are presented for solving the problems of exploratory analysis, classification, and prediction.

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“…PLS-DA is a linear classification method that combines the properties of partial least squares regression with the discrimination power of a classification technique [39]. PLS regression was applied to NIR data in order to develop prediction models for calcium, magnesium and strontium content in bone samples.…”

Section: Chemometric Data Treatmentmentioning

confidence: 99%