Imaging technologies and implementation of plant biomarker in agriculture using smart fertilizer management norms

There is a rapid increase in the agriculture field due to the fertilizer use, the fertilizer has increased the growth of crop production and negative effect over the fertilization is also reduced. The fertilizer is considered as the crucial point in the world of agriculture. In precision agriculture correct amount of fertilizer is given based on the smart fertilization this includes the information or data set, sensor or smart tools. This could provide smart fertilization and integrated nutrient management. The recent research in prediction method like machine learning based hyperspectral imaging support the N fertilization accuracy. By using image processing method, the damage caused by the various nutrients such as iron, potassium and nitrogen can be predicted by using Red, Green and Blue (RGB) color image. The present imaging technology cannot predict the exact nutrients present in the soil. Hence, a biomarker method has been proposed to overcome the challenges. This could be able to predict the exacts quantity of nutrients present in the soil and the prediction rate of the particular nutrients is with high specificity. This paper presents an overview of the present approach to plant phenotyping by imaging and plant biomarker-technology and to soil estimation by using image technologies for smart fertilization management.