基于计算机视觉数据对大棚作物生长趋势的挖掘

设施农业具有可控的环境条件,可以通过工程技术手段实现作物的高效生产。大棚是设施农业的重要形式,能够显著提高作物的抗灾减灾和反季节生产能力。大棚作物的生长状况反映出大棚生产管理的效果,并作为农艺操作和产量预测的依据。为此,开发了通过计算机视觉分析大棚作物的植株颜色和发育阶段等生长信息的方法,利用专家系统挖掘视觉分析数据,评判作物的生长状况,预测后续生长趋势和最终产量。大棚黄瓜的试验结果表明:基于计算机视觉的数据挖掘可以准确评判黄瓜的生长状况,较为准确地预测成熟时期和最终产量,提高了大棚生产的智能化水平。

Excavation of Crop Growth Trend Based on Computer Vision Data in Greenhouse

Facility agriculture has controlled environmental conditions and can realize efficient crop production through engineering and technical means. Greenhouses are an important form of facility agriculture and can significantly increase crop resilience and mitigation and off-season production capacity. The growth status of greenhouse crops reflects the effect of greenhouse production management and serves as a basis for agricultural operation and yield forecast. In this paper, we developed a method to analyze growth information such as plant color and growth stage in greenhouse crops by using computer vision. The expert system was used to mine the visual analysis data to judge the growth status of crops and predict the subsequent growth trend and final yield. The test results on greenhouse cucumber show that data mining based on computer vision can accurately judge the growth status of cucumber, predict the mature period and the final yield more accurately, and increase the intelligence level of greenhouse production.