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

青豆在温暖的天气下迅速成熟，因此必须在1-2天的时间内收获，以确保最佳的嫩度和高品质。一旦收获，它们必须在150分钟内运输和冷冻，以保持这种品质。这些限制往往导致低效的加工计划和浪费作物在快速成熟期间或意外的高产量。利用遥感多光谱冠层反射率测量和气象数据是一种新颖的方法，可以在收获前高精度地估计产量和质量。该项目旨在通过开发一个供英国种植豌豆行业使用的在线平台，进一步扩展PGRO和诺丁汉大学开发的收获日期和产量预测模型的原型。该平台将提供一个用户可以利用预测模型的界面，同时有助于自动化、持续的模型改进和改进。我们进一步的目标是使该平台成为常规收获活动的一个组成部分，以便PGRO能够更好地支持未来的种植豌豆产业，并有可能扩展到其他豆科和非豆科作物。

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.