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Research Article Open access CC BY 4.0

Monitoring of Wheat and Rice Nitrogen Status by Remote Sensing

M. Irfan, Z. I. Ahmed, T. A. Khan, Waqas Ahmad, Muhammad Tanveer Akhtar, Khawar Iqbal, Muhammad Naveed Malik

Journal of Experimental Agriculture International · pp. 1–13 · Published 30 Nov 2018

10.9734/JEAI/2018/16566

Abstract

Crop growth and production are dependent on the amount of total nitrogen (N) absorbed by plants, but as well as also on the N distribution within plant canopies. Nitrogen (N) is the major agricultural input in all over the world and applying the optimum amount of N at the right time, place and at the critical physiological stage is a major challenge for wheat and rice growers. Assessment of canopy nitrogen content (CNC) at the right timing in crops is important for growth diagnosis and precision management of crops to gain maximum yield and better quality while also reducing adverse environmental impacts. Hence, to minimize the losses of nitrogen fertilizer, environmental pollution from cropping activities, a reliable, real time and non -destructive techniques of remote sensing are needed to monitor crop N status and site-specific N management in agricultural fields. Remote sensing has been widely used for determination of crop N status. In this review paper the results of previous studies that investigated the monitoring of crop nitrogen content (CNC) and the remote sensing methods that have been proposed to monitor this phenomenon for wheat and rice crops has been discussed. When a complete understanding of monitoring of N status in the crop is achieved, researchers will be able to improve related quantitative modeling. Regarding monitoring of crop nitrogen content (CNC) by using remote sensing, the few existing methods can be mentioned according to the hyper spectral data used. This paper has reviewed the results of different technological methods of remote sensing to monitor the nitrogen content of wheat and rice. All these methods and techniques for the monitoring of (CNC) are presented here and it is hoped that this work can provide helpful information for future work.

Nitrogen remote sensing vegetation indices green scanning laser wheat and rice remote sensing techniques

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