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Predicting Avena spp. control with clodinafop
Author(s) -
ANDREWS T S,
MEDD R W,
VAN DE VEN R J
Publication year - 2008
Publication title -
weed research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.693
H-Index - 74
eISSN - 1365-3180
pISSN - 0043-1737
DOI - 10.1111/j.1365-3180.2008.00632.x
Subject(s) - avena , environmental science , air temperature , volume (thermodynamics) , water content , covariate , moisture , mathematics , agronomy , agricultural engineering , statistics , biology , atmospheric sciences , geography , engineering , physics , meteorology , geotechnical engineering , quantum mechanics
Summary Previous analyses of two independent data sets, one generated by industry and the other involving purpose‐designed field experiments, showed that the factors relating to Avena spp. control with clodinafop in Australia are fairly consistent. This article details the combination of those, together with additional new industry data, into an overall set that was subject to linear mixed model and covariate analyses for the purpose of developing a predictive model. Cross‐validation methods were used to assess the potential for agronomic and environmental variables at the time of spraying clodinafop to predict Avena spp. mortality. The analyses showed that clodinafop dose, available soil moisture, cumulative minimum temperatures, maximum temperature on the day of spraying, spray water volume and the spray water volume by maximum temperature interaction at spraying were useful predictors and these were subsequently incorporated into a model. This model allows growers and agronomists to use knowledge of weather conditions on the day of application to tailor clodinafop dose and water volume accordingly, or to avoid spraying if they are adverse. The model’s potential to improve herbicide efficiency and be used as part of a long‐term Avena spp. management programme are briefly discussed.