Title of article
Differentiation of mangoes (Magnifera indica L.) conventional and organically cultivated according to their mineral content by using support vector machines
Author/Authors
Hernلndez-Sلnchez، نويسنده , , M. C. Martin-Luis، نويسنده , , G. and Moreno، نويسنده , , I. and Cameلn، نويسنده , , A. and Gonzلlez، نويسنده , , A.G. and Gonzلlez-Weller، نويسنده , , D. and Castilla، نويسنده , , A. and Gutiérrez، نويسنده , , A. and Rubio، نويسنده , , Marيa del C. and Hardisson de la Torre، نويسنده , , A.، نويسنده ,
Issue Information
ماهنامه با شماره پیاپی سال 2012
Pages
6
From page
325
To page
330
Abstract
Mangoes of uniform genetics (Lippens variety) cultivated in the Gomera Island (Canary Islands) by conventional and organic farming were used to analyze the mineral content in order to differentiate crops cultivated in the same geographic area by the cultivation practices. Farming differences as well as soil differences may be reflected in the mineral content of the mangoes cultivated in these extensions. Concentration metal profiles consisting of the content of Ca, Co, Cu, Fe, K, Mg, Mn, Na, Ni and Zn in mangoes were obtained by using atomic absorption spectrometry (AAS). Pattern recognition classification procedures were applied for discriminating purposes. Linear discriminant analysis (LDA) allows to a classification performance of about 73% and support vector machines (SVM) found up to a 93% of prediction ability. The classification success when applying support vector machines techniques is due to their ability for modeling non-linear class boundaries.
Keywords
Metal content , Pattern recognition , Support Vector Machines , cultivars , Mangoes
Journal title
Talanta
Serial Year
2012
Journal title
Talanta
Record number
1665719
Link To Document