Logistic Regression Modeling of Cropping Systems To Predict Fumonisin Contamination in Maize

• DOI: 10.1021/jf801809d
• Publication Date: 2008-10-09T11:59:13Z
• Authors: Paola Battilani; Amedeo Pietri; Carlo Barbano; Andrea Scandolara; Terenzio Bertuzzi; Adriano Marocco
• Keywords: Fumonisin; Cropping system

The aims of this research were to monitor the presence fumonisins in maize crops northern Italy over a 6 year period, study role cropping system on fumonisin levels, and contribute development predictive for contamination. In period from 2002 2007, 438 samples collected five regions, supported by agronomic data, analyzed content. Fumonisin was detected almost all grain samples, but 2007 less 2005 more contaminated compared other years. Preceding crop, maturity class hybrids, nitrogen fertilization, sowing harvest week, moisture significantly affected level logistic regression developed explained around 60% variability with major roles longitude, class, growing weeks. function can be used quantify effect these factors system.