The aims of this study were to: (i) evaluate the relationships between vegetation indices (VIs) derived from Sentinel-2 imagery and grain yield (GY) and the number of spikes per square meter (SN) of winter wheat and triticale; (ii) determine the dates and plant growth stages when the above relationships were the strongest at individual field scale, thus allowing for accurate yield prediction. Observations of GY and SN were performed at harvest on six fields (three locations in two seasons: 2017 and 2018) in three regions of Poland, i.e., northeastern (A—Brożówka), central (B—Zdziechów) and southeastern Poland (C—Kryłów). Vegetation indices (Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), modified SAVI (mSAVI), modified SAVI 2 (mSAVI2), Infrared Percentage Vegetation Index (IPVI), Global Environmental Monitoring Index (GEMI), and Ratio Vegetation Index (RVI)) calculated for sampling points from mid-March until mid-July, covering within-field soil and topographical variability, were included in the analysis. Depending on the location, the highest correlation coefficients (of about 0.6–0.9) for most of VIs with GY and SN were obtained about 4–6 weeks before harvest (from the beginning of shooting to milk maturity). Therefore, satellite-derived VIs are useful for the prediction of within-field cereal GY as well as SN variability. Information on GY, predicted together with the results for soil nutrient availability, is the basis for the formulation of variable fertilize rates in precision agriculture. All examined VIs were similarly correlated with GY and SN via the commonly used NDVI. The increase in NDVI by 0.1 unit was related to an average increase in GY by about 2 t ha⁻¹.

A proper understanding of cultivar adaptation to different environments is of great relevance in agronomy and plant breeding. As wheat is the most important crop in Poland, with a total of about 22% of the total sown area, the study of its performance in environments with different productivity levels for consequent cultivar recommendation is of major importance. In this paper, we assess the relative performance of winter wheat cultivars in environments with different productivity and propose a method for cultivar recommendation, by considering the information of environmental conditions and drought stress. This is performed in the following steps: (1) calculation of expected wheat productivity, depending on environmental factors, (2) calculation of relative productivity of cultivars in the environments, and (3) recommendation of cultivars of a specific type and range of adaptation. Soil and weather conditions were confirmed as the most important factors affecting winter wheat yield. The weather factors should be considered rather in shorter (e.g., 10 day) than longer (e.g., 60 day) time periods and in relation to growth stages. The ANCOVA model with genotype and management intensity as fixed factors, and soil and weather parameters as covariates was proposed to assess the expected wheat productivity in particular environments and the expected performance of each genotype (cultivar). The recommendation of cultivars for locations of specified productivity was proposed based on the difference between the expected cultivar yield and the mean wheat productivity, and compared with the Polish official cultivar recommendation list.