Thermal time models for estimating wheat phenological development and weather-based relationships to wheat quality

Abstract

Accurate prediction of crop phenology is a key requirement for crop development models. The prediction of spring wheat yield and quality from meteorological data can be improved by quantifying heat and moisture conditions during specified phenological phases; therefore, accurate prediction of phenological development is important for estimating weather impacts on wheat quality. The objective of this study was to test the accuracy of biometeorological time (BMT), growing degree days (GDD), and physiological days (Pdays) for prediction of wheat phenological stages and impacts of growing season weather during those stages on wheat bread-making quality. Observed crop phenological stages and detailed weather data across 17 site-years in western Canada for six hard spring wheat varieties were collected to assess BMT, GDD and Pdays. Biometeorological time was most consistent for predicting the length of the seeding to jointing and seeding to anthesis growth stages and second most consistent behind GDD for predicting seeding to soft dough and seeding to maturity. The ability of the BMT and GDD models to predict calendar days to anthesis and maturity were further tested using field data from 166 farms across western Canada. Both GDD and BMT models were effective for predicting time from seeding to anthesis (R2 = 0.84 and 0.90, respectively) and seeding to maturity (R2 = 0.62 and 0.66, respectively). BMT- and GDD-predicted wheat growth phases were used to calculate modeled crop water use by growth period for producer fields. Crop water use is significantly correlated to key bread-making quality parameters of flour protein, farinograph dough development time and farinograph stability. Biometeorological time predicted water use was more highly correlated to these quality parameters than GDD predictions. Accordingly, the BMT scale is recommended for estimation of wheat phenological development especially for modeling weather impacts on wheat end-use quality.Key words: Spring wheat, phenological development, biometeorological time, growing degree day, physiological day, wheat quality