A predictive model of wheat grain yield based on canopy reflectance indices and the theoretical definition of yield potential

Predicting crop yields through simple methods would greatly aid crop breeding programs and could also be deployed at farm level to inform best crop management practices. This research proposes a new method for predicting wheat grain yields, along the crop growth cycle, based on canopy cover and reflectance indices, the Yieldp Model. The model was evaluated by comparing grain yields measured at harvest with the outputs of the proposed model using phenotypic data collected for a wheat population grown under UK field conditions for the 2015 and 2016 seasons. Accumulated radiation (RAD), Normalized Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI), Water Index (WI), Harvest Index (HI) and canopy cover indices were the components of the model. Results suggested that the biomass accumulation predicted by the model was responsive along the crop cycle and the grain yield predicted was correlated to measured grain yield (r = 0.59; p < 0.001 for 2015; r = 0.64, p < 0.001 for 2016). The model allowed early prediction of grain yield based on biomass accumulated at anthesis (r = 0.54; p < 0.001 for 2015; r = 0.48, p < 0.001 for 2016). Evaluation of the model components enabled an improved understanding of the main factors limiting yield formation along the crop cycle. The proposed Yieldp Model explores a new concept of yield modelling and can be the starting point for the development of cheap and robust, on-farm, yield prediction during the crop cycle