Pollen-based predictive modelling of wine production: application to an arid region

• Improved pollen-based wine forecasting model were tested for an arid wine region.
• The model integrates hierarchically the major derived grapevine-yield components.
• The regional pollen index explains 71% of the wine production annual variability.
• The model is about 81% accurate in predicting the wine volume production.

A wine forecast model for one of the most arid wine regions of the Europe—Alentejo was improved and tested for the period 1998–2014. During this period, Alentejo region had strong upward trends in wine production associated to the increase of vineyard area. The forecast model was supported on a hierarchical analysis, including the determination of the potential production at flowering by quantifying airborne pollen concentration, followed by a climate based evaluation of the possible impact of fruit-set conditions in the limitation of production. Through the monitoring of airborne pollen flows it is possible to define an accurate main pollen season and determine the regional pollen index that will be used as independent variable in the regional forecast model. The time trend, which was initially removed from data, was then added back to obtain the forecast. Stepwise regression and cross-validation were employed during the period 1998–2014 for calibration of the model used for predicting annual wine production. The developed model explained about 86% of wine variance over the years with absolute average error of 6% for the cross validation and 87% of cases had differences between actual and forecasted wine production below 10%. The reliability and early-indication ability of the proposed forecast model justify their use to respond to a number of government agencies and wine industry concerns and activities.

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