Development and provision of a digital platform enabling industry to predict harvest date and yield of vining pea

Vining peas mature rapidly in warm weather and must therefore be harvested within a 1-2-day window to ensure optimal tenderness and high quality. Once harvested, they must be transported and frozen within 150 minutes to maintain this quality. These limitations often lead to inefficient processing schedules and wasteful crop bypassing during periods of rapid maturation or unexpectedly high yields. The utilisation of remotely-sensed multispectral canopy reflectance measurements and meteorological data is a novel approach that allows yield and quality to be estimated with high accuracy prior to harvest.

This project aims to further expand on prototype harvest date and yield prediction models developed by PGRO and the University of Nottingham, through the development of an online platform for use by the UK vining pea industry. The platform will provide an interface through which users can exploit the prediction models, whilst contributing to automated, sustained model improvement and refinement. We further aim for the platform to become an integrated part of regular harvest activities so that PGRO can better support the vining pea industry into the future, with the potential for expansion into other legume and non-legume crops.