Towards real-time precision crop management: automatic during-harvest assessment of apple yield

实现实时精准作物管理：苹果产量收获期间自动评估

• 批准号: 10080669
• 金额: $ 4.63万
• 依托单位: ADRIAN SCRIPPS LIMITED
• 依托单位国家: 英国
• 项目类别: Grant for R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10080669
• 关键词: Towards; real; time; precision; crop

After harvest, apples are stored prior to being graded, packed and shipped to retailers, but producers often have little reliable information on the stored crop, which makes it difficult to match customer requirements. This leads to wasted crop at a cost to the farmer, as well as wasted money from storing apples that do not match specifications in cooled stores. If we could produce a size profile of the crop at the time of harvest then this would substantially aid planning, save money and reduce food waste. Together, the project team will develop significant functionality into an existing crop sizing/counting system that is currently parameterised for potatoes. This will allow us to create an innovative machine-vision system to provide real-time, geo-located count, size, and marketable yield during apple harvesting. This system will involve no additional labour requirements, unlike other options (e.g. drones), and will increase productivity by ensuring apple specifications can be optimized to the crop, increasing our farms' and the sector's resilience. Less waste will reduce environmental impact and will help the drive to net zero emissions.

收获后，将苹果在分级，包装和运送到零售商之前存储，但是生产商通常对存储的农作物的可靠信息几乎没有可靠的信息，这使得很难符合客户需求。这导致浪费农作物，费用为农民，以及从冷却商店中不符合规格的苹果中浪费的钱。如果我们能在收获时产生农作物的尺寸概况，那么这将大大帮助计划，节省金钱并减少食物浪费。项目团队将共同发展为现有的作物规模/计数系统的重要功能，该系统目前已针对土豆进行参数。这将使我们能够创建一个创新的机器视觉系统，以在Apple收获期间提供实时，地理位置的计数，大小和可销售的收益率。与其他选择（例如无人机）不同，该系统将不涉及其他劳动要求，并通过确保可以优化农作物的苹果规格来提高生产率，从而提高我们的农场和该行业的韧性。减少废物将减少环境影响，并有助于驱动净零排放。