ABSTRACT

Precise use of fertilizers has been a focal point in world agriculture for years because it increases crop production and reduces the negative impact of over-fertilization. Smart fertilizer management using information/data, sensors, and smart tools allows correct fertilization in precision agriculture, smart agriculture, and integrated nutrient management. Recent progress in prediction methods, such as hyperspectral imaging with machine learning, supports accurate N fertilization. In contrast, damage caused by the deficiency of several nutrients, such as Fe, K, and N, can be accurately identified by red, green, and blue (RGB) images. Current imaging technologies cannot cover all nutrients, but it has been proposed that nutrient biomarkers could be able to quantitatively predict the status of a particular nutrient with high specificity. This review presents an overview of the current approaches to plant phenotyping by imaging/sensor- and plant biomarker-technologies, and to soil analysis by imaging/sensor technologies for smart fertilizer management.

摘要

多年来，精确使用化肥一直是世界农业的焦点，因为它可以提高作物产量并减少过度施肥的负面影响。使用信息/数据、传感器和智能工具的智能肥料管理允许在精准农业、智能农业和综合养分管理中正确施肥。预测方法的最新进展，例如使用机器学习的高光谱成像，支持准确施氮。相比之下，由于缺乏 Fe、K 和 N 等几种营养素造成的损害，可以通过红、绿、蓝 (RGB) 图像准确识别。当前的成像技术无法涵盖所有​​营养素，但有人提出，营养素生物标志物可以高特异性地定量预测特定营养素的状态。