科学家最近利用以色列Plantarray植物生理表型设备发表了题为Detection of Potassium Deficiency and Momentary Transpiration Rate Estimation at Early Growth Stages Using Proximal Hyperspectral Imaging and Extreme Gradient Boosting的文章。

摘要:

钾是一种在生长季需供应充足以避免因缺乏导致作物产量降低的大量元素。蒸腾速率是即时生理特征，指示土壤水分含量、植物水需求、非生物胁迫。本研究中，组合2种系统来生成高光谱-生理植物数据库用以鉴别分类钾处理(低、中、高) 以及通过高光谱图像估计即时蒸腾速率。研究使用了PlantArray 3.0 来控制施肥、记录环境条件并计算蒸腾速率。另外，安装了携带高光谱相机的半自动平台，每半小时拍摄数列辣椒植物图像。每小时采集的集成特征和光谱信息用于鉴别给定钾处理（平均精度= 80%）的植物，并用来估算蒸腾速率 (RMSE = 0.025 g/min）。

Detection of Potassium Deficiency and Momentary Transpiration Rate Estimation at Early Growth Stages Using Proximal Hyperspectral Imaging and Extreme Gradient Boosting

Abstract:

Potassium is a macro element in plants that is typically supplied to crops in excess throughout the season to avoid a deficit leading to reduced crop yield. Transpiration rate is a momentary physiological attribute that is indicative of soil water content, the plant’s water requirements, and abiotic stress factors. In this study, two systems were combined to create a hyperspectral–physiological plant database for classification of potassium treatments (low, medium, and high) and estimation of momentary transpiration rate from hyperspectral images. PlantArray 3.0 was used to control fertigation, log ambient conditions, and calculate transpiration rates. In addition, a semi-automated platform carrying a hyperspectral camera was triggered every hour to capture images of a large array of pepper plants. The combined attributes and spectral information on an hourly basis were used to classify plants into their given potassium treatments (average accuracy = 80%) and to estimate transpiration rate (RMSE = 0.025 g/min

Citation:

Weksler, S. ; Rozenstein, O. ; Haish, N. ; Moshelion, M. ; Wallach, R. ; Ben-Dor, E. Detection of Potassium Deficiency and Momentary Transpiration Rate Estimation at Early Growth Stages Using Proximal Hyperspectral Imaging and Extreme Gradient Boosting. Sensors 2021, 21.