Colombian avocado feasibility study

哥伦比亚鳄梨可行性研究

• 批准号: 10020378
• 金额: $ 2.66万
• 依托单位: CKX GROUP LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10020378
• 关键词: Colombian; avocado; feasibility; study

For some farmers, pesticides represent one-third of their costs, and pesticide overuse through blanket spraying of fields has significant biodiversity implications. While pesticides treat diseases and pests, they also kill helpful bugs (an essential source of nutrients), requiring nitrogen-based fertiliser to boost crop yields. Artificial pesticide use is increasing every year, and this pesticide-fertiliser combination has the potential to contaminate groundwater sources.Agribot is developing precision farming technologies to reduce pesticide use. Agribot uses AI to detect crop stress (under/over-fed, under/over-watered, mites, disease) from satellite data, and diagnose disease with 99.98% accuracy. This creates an invaluable early detection system, enabling the use of less aggressive (often organic) treatments that only work if administered early.As part of this feasibility study, research will be carried out to explore the process of adding additional crops to the Agribot models specifically avocados, coffee and cacao so that farmers on an international level can benefit from accurate and accessible precision farming technology.

对于一些农民来说，农药占他们成本的三分之一，通过地毯式喷洒农药过度使用对生物多样性有重大影响。虽然杀虫剂可以治疗疾病和害虫，但它们也会杀死有益的虫子(一种基本的营养来源)，这需要氮基化肥来提高作物产量。人工农药的使用每年都在增加，这种农药和化肥的组合有可能污染地下水来源。农业机器人正在开发精准农业技术，以减少农药的使用。Agribot使用人工智能从卫星数据中检测作物胁迫(不足/过量，水分不足/过量，蠕虫，疾病)，并以99.98%的准确率诊断疾病。这创造了一个无价的早期检测系统，使得只有在早期实施才有效的不那么激进的(通常是有机的)处理方法得以使用。作为这项可行性研究的一部分，将开展研究，探索在Agribot模型中添加更多作物的过程，特别是鳄梨、咖啡和可可，以便国际上的农民能够从准确和可获得的精准农业技术中受益。