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，苹果在分级、包装和运输给零售商之前被储存起来，但生产商往往对储存的作物没有什么可靠的信息，这使得很难满足客户的要求。这导致了农作物的浪费，同时也浪费了储存不符合冷藏库规格的苹果的钱。如果我们能在收获时制作出作物的大小轮廓，那么这将大大有助于规划，节省资金并减少食物浪费。项目团队将共同开发现有作物尺寸/计数系统的重要功能，该系统目前已为马铃薯参数化。这将使我们能够创建一个创新的机器视觉系统，以在苹果收获期间提供实时、地理定位的数量、大小和可销售的产量。与其他选择（例如无人机）不同，该系统将不需要额外的劳动力，并将通过确保苹果规格可以根据作物进行优化来提高生产力，从而提高我们农场和该行业的弹性。减少浪费将减少对环境的影响，并有助于实现净零排放。