10127969CauliGrowth: Forecasting Cauliflower Growth to Optimise Harvest-Time Prediction and Reduce WasteActiveCollaborative R&DInnovate UKCauliflower is a staple of the British diet, playing a key role in a Sunday roast, Christmas dinner and cauliflower-cheese. In 2019 pre-covid, 82,000 tonnes were produced in the UK, but we typically need to import between 10-30% of the crop to satisfy demand. At the same time, there is a large amount of waste in cauliflower production worldwide, including in the UK. A key problem is that it can be difficult accurately to forecast growth of the cauliflower heads at a whole field level, and more particularly for individual plants. Different plants grow at different rates depending on local soil conditions, moisture and nutrient levels, and the growing curds are covered by a layer of leaves, making it impossible to see how big each head of cauliflower is. The problems translate to harvesting: for brassicas, harvest remains an extremely manual and high-skilled job, with teams of pickers deployed several times to each field selecting cauliflowers that are ready by parting the leaves to visualise the heads and then feeling them with their hands to assess size. Cauliflowers that fit the target size are cut with a knife and trimmed, but mistakes can be made, quality problems generate significant waste, and there can be over-production at inopportune times of year. Our concept is to introduce a step change in the way that cauliflower growth can be forecast. We aim to use state-of-the-art camera systems, coupled with artificial intelligence, to provide a method of predicting head size and growth rate for individual plants. Combined with bespoke growth models, this will provide the industry with substantially improved forecasting of the crop's readiness levels, thereby allowing pickers to be deployed fewer times and to target their harvesting operations to specific fields, specific regions of a field or even specific plants where the crop best fits a retailers' specifications.