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Hyperspectral Analysis of Wheat Leaf Rust (WLR) Disease: A Review

M.K. Maid1 , R.R. Deshmukh2

  1. Department of CS ans IT, Dr. B. A. M. U, Aurangabad, India.
  2. Department of CS ans IT, Dr. B. A. M. U, Aurangabad, India.

Correspondence should be addressed to: mm915monali@gmail.com .

Section:Review Paper, Product Type: Journal Paper
Volume-6 , Issue-1 , Page no. 215-219, Jan-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i1.215219

Online published on Jan 31, 2018

Copyright © M.K. Maid, R.R. Deshmukh . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: M.K. Maid, R.R. Deshmukh, “Hyperspectral Analysis of Wheat Leaf Rust (WLR) Disease: A Review,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.1, pp.215-219, 2018.

MLA Style Citation: M.K. Maid, R.R. Deshmukh "Hyperspectral Analysis of Wheat Leaf Rust (WLR) Disease: A Review." International Journal of Computer Sciences and Engineering 6.1 (2018): 215-219.

APA Style Citation: M.K. Maid, R.R. Deshmukh, (2018). Hyperspectral Analysis of Wheat Leaf Rust (WLR) Disease: A Review. International Journal of Computer Sciences and Engineering, 6(1), 215-219.

BibTex Style Citation:
@article{Maid_2018,
author = {M.K. Maid, R.R. Deshmukh},
title = {Hyperspectral Analysis of Wheat Leaf Rust (WLR) Disease: A Review},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2018},
volume = {6},
Issue = {1},
month = {1},
year = {2018},
issn = {2347-2693},
pages = {215-219},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1661},
doi = {https://doi.org/10.26438/ijcse/v6i1.215219}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i1.215219}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1661
TI - Hyperspectral Analysis of Wheat Leaf Rust (WLR) Disease: A Review
T2 - International Journal of Computer Sciences and Engineering
AU - M.K. Maid, R.R. Deshmukh
PY - 2018
DA - 2018/01/31
PB - IJCSE, Indore, INDIA
SP - 215-219
IS - 1
VL - 6
SN - 2347-2693
ER -

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Abstract

Remote Sensing has wide range of applications in many different fields. Remote Sensing has been found to be a valuable tool in evaluation, monitoring, and management of land, water and crop resources. The applications of remote sensing techniques in the field of agriculture are wide and varied ranging from crop identification, detection of disease on different crops & predicting grain yield of crops. Many remote sensing applications are devoted to the agricultural sector. The selected applications are put in the context of the global challenges the agricultural sector is facing: minimizing the environmental impact, while increasing production and productivity. The application of remote sensing in agriculture typically involves measuring reflectance of electromagnetic radiation in the visible (390 to 770 nm), near-infrared (NIR, 770 to 1,300 nm), or middle-infrared (1,300 to 2,500 nm) ranges using spectrometers. This paper reviews the concept of hyperspectral remote sensing, use of remote sensing in terms of agriculture field, study of diseased wheat leaves using hyperspectral remote sensing.

Key-Words / Index Term

Remote Sensing, Wheat Leaf Rust, Vegetation Indices, ASD Fieldspec4 Spectroradiometer

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