title: Tools based on multivariate statistical analysis for classification of soil and groundwater in Apulian agricultural sites.
abstract: In this paper, the results obtained from multivariate statistical techniques such as PCA (Principal component analysis) and LDA (Linear discriminant analysis) applied to a wide soil data set are presented. The results have been compared with those obtained on a groundwater data set, whose samples were collected together with soil ones, within the project "Improvement of the Regional Agro-meteorological Monitoring Network (2004-2007)". LDA, applied to soil data, has allowed to distinguish the geographical origin of the sample from either one of the two macroaeras: Bari and Foggia provinces vs Brindisi, Lecce e Taranto provinces, with a percentage of correct prediction in cross validation of 87%. In the case of the groundwater data set, the best classification was obtained when the samples were grouped into three macroareas: Foggia province, Bari province and Brindisi, Lecce and Taranto provinces, by reaching a percentage of correct predictions in cross validation of 84%. The obtained information can be very useful in supporting soil and water resource management, such as the reduction of water consumption and the reduction of energy and chemical (nutrients and pesticides) inputs in agriculture.
authors: Water Research Institute, National Research Council, Viale de Blasio 5, 70132, Bari, Italy. piera.ielpo@ba.irsa.cnr.it.|Institute of Atmospheric Sciences and Climate, National Research Council, s.p. Lecce-Monteroni Km 1.2, 73100, Lecce, Italy. piera.ielpo@ba.irsa.cnr.it.
authors: Pierina
authors: http://orcid.org/0000-0002-5579-2872
authors: P
authors: Ielpo
authors: Department of Pharmacy, Genoa University, Viale Cembrano 4, 16147, Genoa, Italy.
authors: Riccardo
authors: R
authors: Leardi
authors: Water Research Institute, National Research Council, Viale de Blasio 5, 70132, Bari, Italy.
authors: Giuseppe
authors: G
authors: Pappagallo
authors: Water Research Institute, National Research Council, Viale de Blasio 5, 70132, Bari, Italy.
authors: Vito Felice
authors: VF
authors: Uricchio
mesh_terms: D000383:Agriculture; D004784:Environmental Monitoring; D060587:Groundwater; D015999:Multivariate Analysis; D010575:Pesticides; D012987:Soil; D014874:Water Pollutants, Chemical
chemical_list: D010575:Pesticides; D012987:Soil; D014874:Water Pollutants, Chemical
keywords: Agricultural soil; Classification; Groundwater; LDA; Multivariate analysis; PCA; Soil quality