Analysing the influence of crop management on pesticide use intensity while controlling for external sources of variability with Linear Mixed Effects Models

作者：Buerger Jana; Guenther Astrid; de Mol Friederike; Gerowitt Baerbel

来源：Agricultural Systems, 2012, 111: 13-22.

DOI：10.1016/j.agsy.2012.05.002

• Standardised Treatment Index
• Linear Mixed Effects Models
• Integrated Pest Management
• On-farm data
• Pesticide monitoring
• Eastern Germany

We present an approach of Linear Mixed Effects Modelling to analyse the influence of crop management factors like rotation, tillage, seeding time and cultivar on pesticide use intensity from on-farm data. We use data from 761 winter wheat crops in eight commercial farms and six different regions of Eastern Germany. By defining cropping year, farm and region as random effects, the variability caused by these external factors can be accounted for before estimating effects of crop management factors. %26lt;br%26gt;The objective of the research we present was to develop and test a method to analyse pesticide use monitoring data appropriately in order to (1) gain insight into the relationship between crop management and pesticide use, (2) integrate external sources of variability into the analysis and quantify their effect, and thereby (3) make a large data pool accessible for further interpretation which will develop further because this kind of monitoring has recently been made mandatory throughout Europe. The benefit of such an analysis is to utilise the practical experience generated by farmers with their daily work that is mirrored in these data for research purposes. This could be valuable in, for example, assessing the effect of Integrated Pest Management (IPM) measures on the pesticide use intensity in arable agriculture, for which evidence is still scarce. %26lt;br%26gt;We quantified pesticide use intensity using the Standardised Treatment Index (STI). For fungicides, herbicides and growth regulators, we modelled the STI as response of 11 management variables using Linear Mixed Effects Modelling. Insecticide use intensity was not modelled since most fields were not treated with insecticides. %26lt;br%26gt;Our results confirmed that pesticide use variability is mainly caused by external sources, but pesticide use intensity is significantly connected to crop management, mainly to preceding crop, seeding time and cultivar characteristics. Pesticide use was smaller when preventive measures typical for IPM were applied. %26lt;br%26gt;We show that the Linear Mixed Effects Modelling approach with multiple predictor variables is well suited for analysing the connection between crop management and pesticide use. We discuss how the random variables influence pesticide use and treatment decisions. Our findings imply that future pesticide use analysis must take regional and farm specific factors into account more strongly, especially when deriving statistical means from on-farm samples. We conclude that the pesticide use monitoring could serve as a valuable data base for scientific research on IPM when data acquisition and analysis are well exploited. Results may be useful for convincing farmers to adopt cropping systems which are less dependent on pesticide use.

• 出版日期2012-9