Multielement determination in orange juice by ICP-MS associated with data mining for the classification of organic samples
| Autor: | Márcio Arruda Bacchi, Elisabete A. De Nadai Fernandes, Rommel Melgaço Barbosa, Christian Turra, Fernando Barbosa, Márcio Dias de Lima |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Rangpur lime
02 engineering and technology Orange (colour) Aquatic Science computer.software_genre 01 natural sciences Inductively coupled plasma mass spectrometry (ICP-MS) 0202 electrical engineering electronic engineering information engineering Multilayer perceptron Orange juice lcsh:Agriculture (General) Data mining Inductively coupled plasma mass spectrometry Trace elements Support vector machines Chromatography lcsh:T58.5-58.64 lcsh:Information technology Chemistry 010401 analytical chemistry Forestry lcsh:S1-972 Citrus limonia 0104 chemical sciences Computer Science Applications 020201 artificial intelligence & image processing Animal Science and Zoology Agronomy and Crop Science computer Citrus × sinensis |
| Zdroj: | Information Processing in Agriculture, Vol 4, Iss 3, Pp 199-205 (2017) |
| ISSN: | 2214-3173 |
| Popis: | The aim of this study was to discriminate organic from conventional orange juice based on chemical elements and data mining applications. A comprehensive sampling of organic and conventional oranges was carried out in Borborema, state of Sao Paulo, Brazil. The fruits of the variety Valencia (Citrus sinensis (L.) Osbeck) budded on Rangpur lime (Citrus limonia Osbeck) were analyzed. Eleven chemical elements were determined in 57 orange samples grown in organic and conventional systems. In order to classify these samples, data mining techniques (Support Vector Machine (SVM) and Multilayer Perceptron (MLP)) were combined with feature selection (F-score and chi-squared). SVM with chi-squared had a better performance compared with the other techniques because it reached 93.00% accuracy using only seven chemical components (Cu, Cs, Zn, Al, Mn, Rb and Sr), and correctly classified 96.73% of the samples grown in an organic system. |
| Databáze: | OpenAIRE |
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