Automated vineyard yield estimation using computer vision
Automated vineyard yield estimation using computer vision
批准号:
452538-2013
负责人:
Najjaran, Homayoun
金额:
$1.82万
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2013
资助国家:
加拿大
项目状态:
已结题
起止时间:
2013-01-01 至 2014-12-31
中文摘要
鹌鹑门酒庄是奥肯那根领先的优质VQA葡萄酒生产商之一,并在参与葡萄栽培研究以提高葡萄园运营和葡萄质量方面有着悠久的历史。准确可靠的早期产量估算对于葡萄园管理者在收获前对他们的劳动进行必要的调整至关重要。有了这些信息,他们可以提高产量,降低成本。然而,获得可靠的产量估计并非易事,因为它受到几个潜在参数的影响,包括时间和气候变化、土壤条件和虫害。目前的行业实践主要依赖于在生长季节从选定的葡萄园进行人工随机抽样,并将样本测量结果外推到整个葡萄园。鹌鹑之门一直致力于利用技术来提高葡萄的质量和产量,同时减少每英亩土地的种植和收获所需的资源。现有的人工取样方法已不能满足行业需求,需要一种自动化、快速的替代方法
英文摘要
Quails' Gate Winery is one of Okanagan's leading producers of premium VQA wines and has a demonstrated history of participating in viticulture research to improve vineyard operations and grape quality. Accurate and reliable early yield estimation is crucial for vineyard managers to make the necessary adjustments to their labors before the harvest. With this information they can improve production and reduce cost. However, having reliable yield estimation is nontrivial as it is subject to several underlying parameters including temporal and climate variations, soil conditions, and pest infestation. Current industry practices rely mainly on manual random sampling from selected vineyards during the growing season and extrapolate the sample measurements to the entire vineyard. Quails' Gate has been interested in the use of technology to improve grape quality and production while reducing the resources required to farm and harvest each acre of land. The existing manual sampling practice cannot meet the industry demand, and the need for an automated and fast alternative
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