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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.
Agrahari et al. (Thu,) studied this question.
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