Comparison of different methods of grapevine yield prediction in the time window between fruitset and veraison

Abstract

<p style="text-align: justify;"><strong>Aim</strong>: To compare grape yield prediction methods to determine which provide the best results in terms of earliness of prediction in the growing season, accuracy and precision.</p><p style="text-align: justify;"><strong>Methods and results</strong>: The grape yields predicted by six models – one for use at fruitset (FS), two for use at <em>veraison</em> (V1 and V2), and three for use during the lag phase (LP40, LP50 and LP60) – were compared to field-measured yields. Regressions for the yield predicted by each model were constructed. The V1 and V2 models had the highest R<sup>2</sup> (0.75) and efficiency index (EF; 0.67-0.71) and the lowest RMSE values (±16-17%, or <0.5 kg per m of row). The FS model had the same or similar R<sup>2</sup> (0.58), EF (0.06) and RMSE (±30%, or <0.83 kg per m of row) values as the LP models, but allowed yield predictions to be made one month earlier.</p><p style="text-align: justify;"><strong>Conclusion</strong>: The validated FS, V1 and V2 models are all useful in predicting grape yields and could be used to accurately forecast (with different errors) grape yields at either early or later time points according to winery needs. These models could be improved as further data become available in following seasons.</p><p style="text-align: justify;"><strong>Significance and impact of the study</strong>: Few validated models are available for predicting grapevine yields at fruitset and <em>veraison</em>. This study provides predictive models that can be used at these different times of the growth cycle.<strong></strong></p>