Supervised pattern recognition applied to the discrimination of the floral origin of six types of Italian honey samples

Marini, Federico; Magrı̀, Antonio; Balestrieri, F.; Fabretti, F.; Marini, D.

doi:10.1016/j.aca.2004.01.013

Cited by 72 publications

(53 citation statements)

References 17 publications

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“…Supervised pattern recognition was applied in this study to those 86 samples, considering several chemical parameters as variables. Discriminant analysis was used for hard classification purposes, trying to establish possible connections among groups of samples and variables (Marini et al 2004;García-Giménez et al 2006;Petit-Domínguez et al, 2008). This procedure is useful for classifying the dataset into groups according to the plant species, the sample points or the contamination grade.…”

Section: Statistical Treatmentmentioning

confidence: 99%

Biomonitoring of chemical elements in an urban environment using arboreal and bush plant species

Rucandio

Petit‐Domínguez

Fidalgo-Hijano

et al. 2010

Environ Sci Pollut Res

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The leaves and needles collected from bush and arboreal plants common in this city have demonstrated to be useful to evaluate the level of pollution not only through the chemical analysis but also through the recognition of the visual injury symptoms. The application of multivariate statistical techniques combined with determining of element concentration and correlation analysis has been proved to be an effective tool for reach the objectives of the present work. This allows visualising quickly the damages and leading the sampling through the points of high-level pollution, saving analysis, time and money.

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Section: Statistical Treatmentmentioning

confidence: 99%

Biomonitoring of chemical elements in an urban environment using arboreal and bush plant species

Rucandio

Petit‐Domínguez

Fidalgo-Hijano

et al. 2010

Environ Sci Pollut Res

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“…Therefore, there is a tendency to replace pollen analysis by finding analytical and/or physicochemical markers for honey discrimination. Minerals and trace elements (Fernández-Torres et al, 2005;Hernández, Fraga, Jiménez, Jiménez, & Arias, 2005;Latorre et al, 1999), volatile compounds (Guyot, Scheirman, & Collin, 1999;Radovic et al, 2001;Soria et al, 2004), the protein pattern, flavonoids, physicochemical parameters like electrical conductivity, pH, total acidity and water activity (Acquarone, Buera, & Elizalde, 2007;Corbella & Cozzolino, 2006;Devillers, Morlot, Pham-Delegue, & Dore, 2004;Marini, Magrì, Balestieri, Fabretti, & Marini, 2004) are some of the parameters that have been extensively examined for the recognition of the floral and geographical origin of honeys.…”

Section: Introductionmentioning

confidence: 99%

Tracing the geographical origin of honeys based on volatile compounds profiles assessment using pattern recognition techniques

et al. 2010

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“…[8,24,25] For this purpose, for each categorical variable (geographical or botanical origin), the full set of wheat samples was divided into a training and a validation set (2/3 and 1/3 of randomly selected samples, respectively). The validation sets were composed of 33 samples for the assessment of geographic origin and 30 samples for the assessment of botanical origin.…”

Section: Nuclear Magnetic Resonancementioning

confidence: 99%

Geographical origin of durum wheat studied by ¹H‐NMR profiling

Lamanna

Cattivelli

Miglietta

et al. 2010

Magnetic Reson in Chemistry

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(1)H-Nuclear magnetic resonance (NMR) spectroscopy was used to detect metabolic profiles of wheat flour samples of different geographical and botanical origin. The NMR profiles were analyzed by multivariate statistical techniques in order to establish the origin of the samples. A linear model, able to discriminate among three different locations, was built achieving a prediction level of about 80% of correctly assigned samples. The principal classes of compounds responsible for the geographic origin discrimination were individuated in aromatic compounds and amino acids. The statistical modeling also indicated that botanical origin information is very poor in the NMR profiles of the analyzed wheat samples.

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Supervised pattern recognition applied to the discrimination of the floral origin of six types of Italian honey samples

Cited by 72 publications

References 17 publications

Biomonitoring of chemical elements in an urban environment using arboreal and bush plant species

Biomonitoring of chemical elements in an urban environment using arboreal and bush plant species

Tracing the geographical origin of honeys based on volatile compounds profiles assessment using pattern recognition techniques

Geographical origin of durum wheat studied by ¹H‐NMR profiling

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Supervised pattern recognition applied to the discrimination of the floral origin of six types of Italian honey samples

Cited by 72 publications

References 17 publications

Biomonitoring of chemical elements in an urban environment using arboreal and bush plant species

Biomonitoring of chemical elements in an urban environment using arboreal and bush plant species

Tracing the geographical origin of honeys based on volatile compounds profiles assessment using pattern recognition techniques

Geographical origin of durum wheat studied by 1H‐NMR profiling

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Product

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Geographical origin of durum wheat studied by ¹H‐NMR profiling