Chemometric interpretation of pesticide occurence in soil samples from an intensive horticulture area in north Portugal

An extensive monitoring programme of pesticides was carried out in soil samples from an intensive horticulture area in north of Portugal, putting into practice the needs for increased control of soil quality as far as organic pollution is concerned. The area under investigation was additionally defined as vulnerable to nitrates due to local soil and aquifer characteristics, which might be extended to pesticides contamination. Five sampling sites were selected and soils analysed at three depths in eight sampling campaigns, for the period of 2 years. A stepwise multivariate statistical approach was selected to uncover most relevant patterns inside a complex environmental data matrix. Cluster analysis was applied both to group pesticides and samples, giving a primary and unsupervised overlook of privileged relationships. Clusters of persistent pesticides and selected herbicides were identified, whereas sample classes were also formed and disposed geographically. Thirty eight percent of analysed soils samples fell into one class characterized by low contamination (class 1 in cluster analysis), which is entirely representative of the sampling site no. 1. Afterwards, linear discriminant analysis was applied to identify those pesticides, which had a higher impact in the definition of classes. Finally, factor analysis using a five component model was implemented in order to bring to light the constitution and data variance explained by each of the five main principal components, as well as, their relation to pest management practices. A factor was identified (PC1 – 22% variance) composed of chlorinated pesticides, which was representative of one of the investigated sites indicating its high contamination status. Qualitative main findings and class average concentration values were obtained through this multivariate statistical approach.