The impact of fungicide treatment and Integrated Pest Management on barley yields: Analysis of a long term field trials database

Abstract

This paper assesses potential for Integrated Pest Management (IPM) techniques to reduce the need for fungicide use without negatively impacting yields. The impacts of three disease management practices of relevance to broad acre crops –disease resistance, forecasting disease pressure, and fungicide use – were analysed to determine impact on yield using a long-term field trials database of Scottish spring barley, with information from experiments across the country regarding yield, disease levels, and fungicide treatment. Due to changes in data collection practices, data from 1996 to 2010 were only available at trial level, while data from 2011 to 2014 were available at plot level. For this reason, data from 1996 to 2014 were analysed using regression models, while a subset of farmer relevant varieties was taken from the 2011–2014 data, and analysed using ANOVA, to provide additional information of particular relevance to current farm practice. While fungicide use reduced disease severity in 51.4%of a farmer-relevant subset of trials run 2011–2014, and yields were decreased by 0.62 t/ha on average, this was not statistically significant in 65% of trials. Fungicide use had only a minor impact on profit in these trials, with an average increase of 4.4% for malting and 4.7% for feed varieties, based on fungicide cost and yield difference; potential savings such as reduced machinery costs were not considered, as these may vary widely. Likewise, the1996–2014 database showed an average yield increase of 0.74 t/ha due to fungicide use, across a wide range of years, sites, varieties, and climatic conditions. A regression model was developed to assess key IPM and site factors which influenced the difference between treated and untreated yields across this 18-year period. Disease resistance, season rainfall, and combined disease severity of the three fungal diseases were found to be significant factors in the model. Sowing only highly resistant varieties and, as technology improves, forecasting disease pressure based on anticipated weather would help to reduce and optimise fungicide use.