## 4 Discussion
Regarding the goodness of the model, the selected vegetation indices showed absence of collinearity, as a VIF of 2.16, obtained for both cases, was lower than the collinearity threshold value of 10 ([PERSON] and [PERSON], 2018). Moreover, the normality of the residuals was assumed, as the Shapiro-Wilk test p value was over 0.05 (0.297) and the null hypotheses, which assumes that the data is normal, was accepted. The plot of residuals also suggested it as shown in Figure A1 of Appendix A. The fact that maximum and minimum pixel value averages were the most suitable statistical summary combination shows that, for studying grain yield, exploring crop canopy evolution through time may provide an improved output in comparison with single date image data. However, it shows that focusing on the phenological period of heading can provide relatively higher correlations with grain yield, explaining 83% of variability in this case. Namely, segregating phenological periods is a a useful approach in order to calculate empirical grain yield estimations in contrast with following whole season pixel values without explicitly considering phenological periods itself. Estimating the phenological stage with the GDD and focusing on the specific period, heading in this case, eases processing demands and yields accurate results, while clearly diminishing costs. Sentinel-2 spatial resolution allows for the fine evaluation of the statistical summaries and consequently more precise estimations. Using late-season imagery in order to take advantage of barley's earlier senescence proved to be efficient for wheat crop land classification, again, taking maximal advantage of the S2 return interval temporal frequency to identify the optimal date for the separation of like cereal crops. Our results are congruent with the Navarre regional government's official statistics, as Table 9 demonstrates. The average grain yield obtained after applying the grain yield stepwise equation from Table 7, for all of the classified wheat fields, showed similar results with official (i.e., after harvest) grain yield averages. Sentinel-2 spatial resolution allowed accurate mapping and estimation of grain yield, while other satellites would not have yielded such precise results regarding field delimitations, for instance. The grain yield estimation model was applied to the wheat classified parcels without considering genotypic differences within the region (both concerning classification and grain yield modelling issues) due to the fact that for the 2017-2018 season 80% of the fields across the whole of Navarre used either Camargo or Marcopolo (2018). Therefore, a general wheat genotypic homogeneity was supposed in the whole region. In order to be able to use the yield estimation based on spectral data from Sentinel-2 to estimate the yield across the entire study area, it is necessary to also develop a pixel or better field-level image classification. The slightly lower Fscore of wheat classification accuracy in the Ribera Alta southern sub-region might be due to the limited surface area devoted to this crop type in comparison with the other two sites--a higher difficulty in accurately classifying wheat fields was observed with 13 misclassifications with a proportionally smaller number of ground data points for wheat at this site (Table 8). Moreover, it could be a consequence of the smaller size of the fields in this southern zone. Bare soil did present substantial misclassification with \"other crops\" in this southern zone; this likely occurred due to the major presence of barley in zone VI and the earlier senescence it features, especially considering that this zone is substantially drier. Relevant misclassifications happened with wheat and bare soil in all of the three zones. Unfortunately, ground reference points in which the cultivar was specified were only obtained for wheat, the other available ground points could not be specified among the other cultivated crops, namely barley and other minor crops such as oats were not well differentiated.