Bases for pesticide dose expression and adjustment in 3D crops and comparison of decision support systems

Abstract

Authorities around the world have committed to limiting the use of chemical pesticides by reducing doses, among other strategies. Nevertheless, different dose expression models and decision support systems (DSSs) for dose adjustment coexist for high growing crops (3D crops). Among them, leaf wall area (LWA) and tree row volume (TRV) models have recently been proposed by the European and Mediterranean Plant Protection Organization (EPPO) for pre-registration trials. In this paper, the background and technical bases of six dose adjustment DSSs in fruit crops (PACE, AGMET, DOSA3D, OMAX and PULVARBO) and four in grape orchards (AGMET, OPTIDOSE, DOSAVIÑA and DOSA3D) are described and compared. The discussion leads to the conclusion that LWA and TRV represents a substantial improvement compared to the former crop ground area-based dose expression model. However, total leaf area is the most important parameter for dose adjustment, while sprayer efficiency is also a key factor. Additionally, it is suggested that deposition on leaves (mean values and variability) should be reported in pesticide efficacy evaluations in order to establish the required doses independently from the dose expression mode. The DOSA3D system, based on leaf area index estimation, was found to be the most conservative DSS regarding the spraying volume ratio to TRV because low spraying efficiencies are considered. Instead, AGMET was found to be the most effective for dose adjustment. However, despite the differences between the recommendations, all the analysed DSSs are useful tools for rational decision making about spraying volume rate and pesticide doses at national level. Their use should be promoted by the competent authorities.

This study wasfinanced by the EU Horizon 2020 project EUCLID[grant number 633999], the Spanish Ministry of Economy and Compet-itiveness project AgVance [AGL2013-48297-C2-2-R] and the SpanishMinistry of Agriculture, Fisheries and Food project GOPHYTOVID [con-tract 2018002001192]. We are also grateful for funding by theSecretaria d'Universitats i Recerca del Departament d'Empresa iConeixement de la Generalitat de Catalunya under Grant 2017 SGR 646