Field-testing of a decision support system (DSS) to optimize irrigation management of kiwifruit in Italy: a comparison with current farm management

Kiwifruit is sensitive to water deficit throughout the growing season and possible restrictions in summer easily affect fruit size and yield. On the opposite, excessive water supply in poor draining soils is often associated with severe problems of plant decay. Moreover, 'regulated deficit irrigation' during specific fruit growing stages can be used to control fruit quality. Therefore, 'precise' irrigation management is required under conditions of increasingly limited water availability promoted by climate change. In the context of precision farming, decision support systems (DSS) are promising tools to support irrigation management, and advances in digital technologies enable for an 'easy' data access by means of mobile devices. In Italy, the Bluleaf™ DSS has been developed to support irrigation scheduling based on the modeling approaches suggested by FAO Irrigation & Drainage Papers n. 56 and 66. The computation of daily crop water balances requires local weather data and setting of site-specific parameters; the integration of different types of soil and/or plant sensors enables to 'calibrate' model parameters thanks to the 'real-time' feedbacks received from the cropping system. In recent years, several farmers adopted the Bluleaf™ DSS for the irrigation management of kiwifruit under different pedoclimatic conditions in Italy. This paper briefly analyses field data collected at farm scale during 2016-18 for relevant case-studies, with specific reference to: i) the estimated crop evapotranspiration for different types of orchards; ii) the comparison between farm and DSS-based irrigation strategies; iii) results in terms of yield and fruit quality that could be related to possible differences in water regimes. The analysis highlights that in kiwifruit significant water savings could be achieved with respect to current farm management (20-25%, on average) by means of an appropriate irrigation scheduling supported by DSS, without affecting final yield and quality.