Discrimination of Nitrogen Concentration of Fertilized Corn with Extracted Algae and Polymer Based on Its Leaf Color Images

Djawad, Yasser A (2020) Discrimination of Nitrogen Concentration of Fertilized Corn with Extracted Algae and Polymer Based on Its Leaf Color Images. International Information and Engineering technology Association, 25 (7). pp. 303-309.

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Abstract

Determination of nitrogen levels in plants is essential for variable rate fertilizer application in precision agriculture. In the past, several techniques have been developed for nitrogen concentration estimation in plants and crops employing vision system, however, they are computationally expensive and hence requires a considerable amount of time to produce accurate results. The technique developed in this work the determination of nitrogen levels in plants could be achieved effectively in real-time time by advance image processing techniques, machine visions and support vector machine (SVM) with MATLAB. The developed technique processes leaf’s colored image via examining it Red, Green and Blue (RGB) values and compares them with standard intensity levels. The experimental results show effectiveness of the developed technique and accurately detect low or high concentration levels in corn. In addition, this method depends on two techniques for a final result, i.e. color intensity and SVM. If the answer is not similar between the two techniques the process will be repeated until the detection is similar. This study could be applied to a variety of crops, since this technique does not require large collection of data for training and special expertise for its on-field application.

Item Type:	Article
Subjects:	KARYA ILMIAH DOSEN Universitas Negeri Makassar > KARYA ILMIAH DOSEN
Divisions:	KOLEKSI KARYA ILMIAH UPT PERPUSTAKAAN UNM MENURUT FAKULTAS > KARYA ILMIAH DOSEN KARYA ILMIAH DOSEN
Depositing User:	Pustakawan Amaluddin Zaihal
Date Deposited:	25 Mar 2021 03:54
Last Modified:	25 Mar 2021 03:54
URI:	http://eprints.unm.ac.id/id/eprint/19708

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