Validation and Application of a Predictive Model for Thrips-Induced Injury to Cotton Based on Abiotic Inputs

Previous work demonstrates that cotton seedling growth and tobacco thrips dispersal are both driven by weather, and that knowledge of these relationships can be used to predict thrips-induced injury to cotton.  Cotton seedlings are vulnerable to thrips injury until they reach the 5 true-leaf stage.  The degree of alignment of this period of vulnerability with the timing of dispersing thrips populations is a major determinant of the potential for thrips damage during a given season.  This alignment depends on weather and the date on which cotton is planted.  The work presented here aims to provide near-term forecasts of this alignment, based on weather data and information about cotton planting date, variety, and insecticide treatment.  These forecasts support decisions concerning deployment and timing of treatments targeting thrips.  The nature of this predictive tool's inputs and outputs using data from cotton cultivation throughout the southeast USA, as well as a demonstration of how the outputs support decisions, will be presented.