Project Crystal Ball: Predict and Preserve Profitability of Orchards
水晶球项目:预测并保持果园的盈利能力
基本信息
- 批准号:10027459
- 负责人:
- 金额:$ 33.98万
- 依托单位:
- 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:
- 关键词:
项目摘要
A report released in June 2021 by WWF & Tesco found that globally 15% of food is wasted before it even leaves the farm gate. The majority of this waste occurs in middle- and high-income countries across Europe, North America and developed Asia, and one of the key reasons is human factors within the supply chain. Another report in March this year from WRAP estimated that food surplus and waste on-farms across the UK totals 3.6 million tonnes, worth £1.2 billion. In particular, WRAP reports that 9.4% of apples are wasted and 10.8% are surplus, with losses to farmers of £53.8m. The value of apples depends on the shape, colour and presence of blemishes, although size is arguably the most important metric. The relationship between fruit size and value is complex, changing every year and different for each variety. Regardless of the details, British farmers must aim for quite tight size band targets to achieve high value, and if their fruit ends up outside these bands, it can result in situations where the apples production costs outweigh the expected commercial value/returns. Using a drone that costs less than £2,500, it is possible to acquire high-resolution footage across an orchard automatically, avoiding any obstacles. This low capex automated solution for detailed crop analysis enables farmers to gather accurate up-to-date crop data across their farms quickly, simply and affordably. Drone surveys can generate insights into a crop's performance, with the goal of allowing growers and agronomists to streamline their operations to improve crop quality and maximise yields. High resolution cameras combined with the speed and precision of a drone means farmers can have detailed maps of an orchard on demand, showing tree size, blossom loading, fruit set and more. These data can be used by farmers to understand how their crops are developing, and inform their choice or interventions to optimise the value of their crops. Working with YAGRO on this project, we will integrate yield and quality estimates on the developing crops based on drone surveys, with detailed commercial intelligence. This will provide farmers with market-level information, enabling them to understand the commercial value of their changing forecasts. By linking data on production costs to date with quality requirements and end-market prices, they will be able to assess their current position, the need for action and the risk involved.
世界自然基金会和乐购在2021年6月发布的一份报告发现,在全球范围内,15%的食物甚至在离开农场大门之前就被浪费了。这些浪费大部分发生在欧洲、北美和亚洲发达地区的中高收入国家,其中一个关键原因是供应链中的人为因素。WRAP在今年3月发布的另一份报告估计,英国各地农场的食物盈余和垃圾总量为360万吨,价值12亿GB。特别是,WRAP报告称,9.4%的苹果被浪费,10.8%的苹果过剩,农民损失5380万GB。苹果的价值取决于形状、颜色和瑕疵的存在,尽管大小可以说是最重要的衡量标准。果实大小和价值之间的关系是复杂的,每年都在变化,每个品种都不同。无论细节如何,英国农民必须以相当严格的条带目标来实现高价值,如果他们的水果最终超出了这些条带,可能会导致苹果生产成本超过预期商业价值/回报的情况。使用成本低于2500 GB的无人机,可以自动获取跨越果园的高分辨率镜头,避免任何障碍。这一用于详细作物分析的低资本支出自动化解决方案使农民能够快速、简单且经济实惠地收集其农场的准确最新作物数据。无人机调查可以洞察作物的表现,目的是让种植者和农学家简化他们的操作,以提高作物质量并最大化产量。高分辨率摄像头与无人机的速度和精度相结合,意味着农民可以按需获得果园的详细地图,显示树的大小、开花情况、结果等。农民可以使用这些数据来了解他们的作物是如何发展的,并为他们的选择或干预措施提供信息,以优化他们的作物价值。在这个项目上,我们将与YAGRO合作,将基于无人机调查的发展中作物的产量和质量估计与详细的商业情报结合起来。这将为农民提供市场层面的信息,使他们能够理解不断变化的预测的商业价值。通过将迄今为止的生产成本数据与质量要求和终端市场价格联系起来,他们将能够评估自己目前的状况、采取行动的必要性和所涉及的风险。
项目成果
期刊论文数量(0)
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其他文献
吉治仁志 他: "トランスジェニックマウスによるTIMP-1の線維化促進機序"最新医学. 55. 1781-1787 (2000)
Hitoshi Yoshiji 等:“转基因小鼠中 TIMP-1 的促纤维化机制”现代医学 55. 1781-1787 (2000)。
- DOI:
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LiDAR Implementations for Autonomous Vehicle Applications
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
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吉治仁志 他: "イラスト医学&サイエンスシリーズ血管の分子医学"羊土社(渋谷正史編). 125 (2000)
Hitoshi Yoshiji 等人:“血管医学与科学系列分子医学图解”Yodosha(涉谷正志编辑)125(2000)。
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Effect of manidipine hydrochloride,a calcium antagonist,on isoproterenol-induced left ventricular hypertrophy: "Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,K.,Teragaki,M.,Iwao,H.and Yoshikawa,J." Jpn Circ J. 62(1). 47-52 (1998)
钙拮抗剂盐酸马尼地平对异丙肾上腺素引起的左心室肥厚的影响:“Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,
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