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Developing a decision support system to improve crop management, yield forecasting and resource use efficiency in UK soft fruit production

Developing a decision support system to improve crop management, yield forecasting and resource use efficiency in UK soft fruit production
开发决策支持系统,以改善英国软果生产的作物管理、产量预测和资源利用效率
批准号:
BB/M027317/2
负责人:
Mark Else
金额:
$46.5万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --

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中文摘要
翻译
英国软果产业是英国农村经济的重要组成部分,草莓和树莓的年销售额为111K,零售额为4.52亿英镑。在过去的15年里,软果行业在新技术和高产品种的开发上投入了大量资金,草莓1级产量/公顷已从8吨提高到21吨(Defra)。然而,如果优化作物农艺,38t/ha的商业产量是可能的。产量差距的部分原因是综合隧道内多变的环境因素,以及种植者为应对这些变量而做出的经营决策。在多变的天气中过度灌溉和高化肥投入会增加疾病易感性,降低适销对路的产量,并降低感官品质。因此,每年收获的软水果中有33%被浪费,原因是腐烂、瘀伤和质地质量差等疾病。减少30%的软果垃圾将阻止英国的进口,并为BGG种植者带来额外的收入,每年约为500万GB。此外,BGG种植者对一级产量的不准确预测导致2013年仅两周时间内就损失了100万GB的收入,提高产量预测的准确性有望每年增加300万至400万GB的收入。为了实现这一目标,该联盟将开发一个决策支持系统(DSS),使种植者能够改进运营决策,并减少多变天气对作物产量、质量和浪费的影响。种植者、零售商和消费者将受益于更准确的产量预测,从而实现更好的定价,更高的资源利用效率,从而节省成本和改善环境性能,在生产过程中减少浪费,增加销售吨位,改善高质量新鲜水果的供应一致性,并确保保质期,从而减少仓库浪费。财团在软果农艺和畜牧业、作物生理和营养、底物科学、食品质量科学、工程、建模、信息技术和气象学方面拥有专业知识,并在提供和利用公款资助的研发方面拥有良好的记录。财团将:1)开发、测试和部署创新的技术、科学、和气象解决方案,以减少多变天气对产量和质量的影响;2)提高优质植物营养水果供应的一致性和保质期;3)减少收获前后的浪费,从而带来更大的盈利能力和资源利用效率;4)提高作物产量和时机预测的准确性,以确保更高的产品定价和种植者利润;5)开发和部署决策支持系统,以帮助种植者改善其业务的经济和环境可持续性;6)提高英国软果生产对天气和气候变化影响的弹性。这些新技术的原型概念将在East Mling Research(EMR)使用专有草莓和树莓品种进行科学实验。然后,将在BGG种植者现场部署和进一步开发DSS,以量化提高资源使用效率、通过减少废物提高生产率以及通过更准确的产量预测提高种植者利润率的潜力。我们预计,采用这些产出将带来每年15-1700万GB的收入增长。进入市场的途径将首先通过商业推广到BGG在英国的60家软果种植者和海外合作伙伴。DSS将可转移给BGG的核果种植者、英国其他树果行业以及英国和海外其他受保护和不受保护的高价值园艺生产系统,在这些系统中,需要提高耕作精度以推进可持续集约化并产生经济影响。
英文摘要
The UK soft fruit industry is a vital part of the UK's rural economy with annual sales of strawberries and raspberries of 111 Kt, worth c. £452M at retail sales value. The soft fruit sector has invested heavily in the development of new technology and higher-yielding varieties over the last 15 years and strawberry Class 1 yield/ha has risen from 8 t to 21 t (Defra). However, commercial yields of 38 t/ha are possible if crop agronomy is optimised. The yield gap is due in part to changeable environmental factors within the polytunnels, and the operational decisions made by growers in response to these variables. Over-irrigation and high fertiliser inputs during changeable weather can increase disease susceptibility, lower marketable yields and reduce organoleptic quality. Consequently, 33% of all harvested soft fruit is wasted each year, due to disorders such as rots, bruising and poor textural quality. A 30% reduction in soft fruit waste would stem UK imports and generate extra income for BGG growers of c. £5M p.a. Furthermore, inaccurate predictions of Class 1 yields by BGG growers resulted in lost revenue of £1M in just one two-week period in 2013 and improving the accuracy of yield forecasts could be expected to increase revenue by £3-4M p.a.To achieve this, the consortium will develop a Decision Support System (DSS) that will enable growers to improve operational decision making and reduce the impact of changeable weather on crop yield, quality and wastage. Growers, retailers and consumers will benefit from more accurate yield forecasts leading to better pricing, greater resource use efficiency leading to cost savings and improved environmental performance, lower waste during production leading to increased tonnage to sell, improved consistency of supply of high quality fresh fruit with an assured shelf-life leading to reduced wastage in store.The consortium has expertise in soft fruit agronomy and husbandry, crop physiology and nutrition, substrate science, food quality science, engineering, modelling, IT and meteorology, and has a strong track record of delivering and exploiting publicly-funded R&D. The consortium will: 1) develop, test and deploy innovative technological, scientific, and meteorological solutions to reduce the impact of changeable weather on yield and quality; 2) improve consistency of the supply of high quality, phytonutritious fruit with an assured shelf-life; 3) reduce pre- and post-harvest waste leading to greater profitability and resource use efficiency; 4) improve accuracy of crop yield and timing forecasts to assure higher product pricing and improved grower margins; 5) develop and deploy a DSS to help growers improve the economic and environmental sustainability of their businesses; 6) increase resilience of UK soft fruit production to the impacts of weather and climate variability.Proof-of-concept of these novel technologies will be tested in scientific experiments using proprietary varieties of strawberry and raspberry at East Malling Research (EMR). The DSS will then be deployed and developed further on BGG grower sites to quantify the potential to deliver a greater efficiency in the use of resources, improved productivity from waste reduction, and improved grower margins from more accurate yield forecasts. We anticipate revenue gains of £15-17M p. a. arising from the adoption of the outputs. The route to market will be via commercial roll-out to BGG's 60 UK soft fruit growers and overseas partners in the first instance. The DSS will be transferable to BGG's stone fruit growers, to other UK tree fruit sectors and to other protected and unprotected high-value horticultural production systems in the UK and overseas where improved farming precision is needed to advance sustainable intensification and deliver economic impact.
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国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
补偿性还是非补偿性规则:探析风险决策的行为与神经机制
  • 批准号:
    31170976
  • 项目类别:
    面上项目
  • 资助金额:
    64.0万元
  • 批准年份:
    2011
  • 负责人:
    李纾
  • 依托单位:
基于神经营销学方法的品牌延伸认知与决策研究
  • 批准号:
    70772048
  • 项目类别:
    面上项目
  • 资助金额:
    20.0万元
  • 批准年份:
    2007
  • 负责人:
    马庆国
  • 依托单位: