University of Hertfordshire

By the same authors

Final Report of Ceres Funding Project 1C1P1

Research output: Book/ReportCommissioned report

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Original languageEnglish
PublisherUniversity of Hertfordshire
Number of pages67
DOIs
Publication statusPublished - 23 Jul 2021

Abstract

In 2019 the final on-farm validation of the UH prediction system (funded by Ceres, in collaboration with Agri-tech Services) took place on eight participating sites (from six farms) in England and Scotland. The aim of the project was to conduct an on-farm validation of the prediction system, in order to provide a simple, user friendly decision support system to growers to control the disease with fewer fungicide applications. A wide range of criteria were covered during the validation process: disease control, a range of geographical locations, manufacturers of temperature and humidity sensors, strawberry cultivars, growing media and methods. Pesticide application data for both prediction and control plots, costings and disease assessment results were received from all participating sites at the end of the season. The results of the validation and cost-benefits analysis were presented in this report. The prediction system was used on sites in both England and Scotland and a variety of cultivars were grown including Sweet Eve, Prize, Murano, Katrina and Amesti (everbearers) and Malling™ Centenary (June bearer). Two different types of sensors were used, Davis and SMS. Most growers used coir on tabletops, however on two sites, crops were grown on raised beds in soil. All growers who used the prediction system had commercially satisfactory disease control with fewer fungicide applications (by at least one spray) than the routine spray programme. They also benefited from financial savings due to reduced fungicide applications and labour costs. Positive feedback on using the prediction system in the 2019 validation was received from participating growers, as well as wide interest from other growers on adopting the prediction system in the coming season. The validation of the prediction system in 2019 has met the milestones of the project and has proven that the system, under all criteria, provided improved assistance to growers during their decision-making processes, achieving satisfactory disease control with fewer applications. The licence for the prediction system has now been agreed and will be signed in the Spring of 2020 which enables the system to be commercially available in 2020.

Notes

© 2021 The Author(s). This is an open access work distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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