Development of a precise thermal time model for grain filling in barley: A critical assessment of base temperature estimation methods from field-collected data

Abstract

Precise phenology modelling of grain filling is essential to understand how the environment explored by barley crops in the field affects malting quality. Grain-filling duration is controlled by temperature; hence thermal time models are widely used for describing grain development. Although a precise base temperature is essential for the accuracy of thermal time models, estimations of this parameter for barley grain filling are scarce in the literature; moreover, the methods employed for its determination seldom establish clearly whether grain filling is being treated as a development or as a growth phenomenon. Even worse, the base temperature during grain filling is usually arbitrarily set to zero. In this work we tested five different methods to estimate the thermal time requirement for completing grain filling in four commercial barley cultivars and the base temperature above which temperature must be accumulated for its calculation, using field-collected data. The crops were sown in a wide range of different dates during three consecutive years and grown under two contrasting nitrogen availabilities. All the estimation methods performed relatively well. Developmental base temperature was close to 8 °C for all cultivars, although genotypic differences were noted. Optimum temperatures for grain filling are reported for three of the four cultivars; however, including this parameter in the models only slightly improved the predictions in one out of three cultivars. The effect of nitrogen availability was negligible and inconsistent across cultivars and environments thus indicating that the models developed can be applied in a wide range of nutritional situations. A broad application model, with a base temperature of 8.4 °C and a thermal time requirement for completing grain filling of 352 °Cd, is reported for barley grain development. All the models were validated against independent data. These models can be used by researchers aiming to unscramble the effects of environment explored by the mother plant on grain malting quality. Further applications include predicting the timing of physiological maturity, and with it, harvest time.