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Detection of disease from Chilly Plant Using Vegetation Indices

Akshay V. Kshirsagar1 , Ratnadeep R. Deshmukh2 , Pooja V. Janse3 , Rohit Gupta4 , Jaypalsing N. Kayte5

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-1 , Page no. 333-337, Jan-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i1.333337

Online published on Jan 31, 2019

Copyright © Akshay V. Kshirsagar, Ratnadeep R. Deshmukh, Pooja V. Janse, Rohit Gupta, Jaypalsing N. Kayte . 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: Akshay V. Kshirsagar, Ratnadeep R. Deshmukh, Pooja V. Janse, Rohit Gupta, Jaypalsing N. Kayte, “Detection of disease from Chilly Plant Using Vegetation Indices,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.333-337, 2019.

MLA Style Citation: Akshay V. Kshirsagar, Ratnadeep R. Deshmukh, Pooja V. Janse, Rohit Gupta, Jaypalsing N. Kayte "Detection of disease from Chilly Plant Using Vegetation Indices." International Journal of Computer Sciences and Engineering 7.1 (2019): 333-337.

APA Style Citation: Akshay V. Kshirsagar, Ratnadeep R. Deshmukh, Pooja V. Janse, Rohit Gupta, Jaypalsing N. Kayte, (2019). Detection of disease from Chilly Plant Using Vegetation Indices. International Journal of Computer Sciences and Engineering, 7(1), 333-337.

BibTex Style Citation:
@article{Kshirsagar_2019,
author = {Akshay V. Kshirsagar, Ratnadeep R. Deshmukh, Pooja V. Janse, Rohit Gupta, Jaypalsing N. Kayte},
title = {Detection of disease from Chilly Plant Using Vegetation Indices},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2019},
volume = {7},
Issue = {1},
month = {1},
year = {2019},
issn = {2347-2693},
pages = {333-337},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3507},
doi = {https://doi.org/10.26438/ijcse/v7i1.333337}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i1.333337}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3507
TI - Detection of disease from Chilly Plant Using Vegetation Indices
T2 - International Journal of Computer Sciences and Engineering
AU - Akshay V. Kshirsagar, Ratnadeep R. Deshmukh, Pooja V. Janse, Rohit Gupta, Jaypalsing N. Kayte
PY - 2019
DA - 2019/01/31
PB - IJCSE, Indore, INDIA
SP - 333-337
IS - 1
VL - 7
SN - 2347-2693
ER -

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Abstract

Yield of chilly is very important aspect for farmer, it is depend on the supplied water to plant and use of pesticide. The chilly plant is mostly infected by white fly, bacterial leaf spot, pepper mosaic virus. In this paper we use peeper mosaic virus infected leaves of chilly plant. We also use four different vegetation Indices and Support Vector Machine classification to classify between diseased and non-diseased leaf. Among four vegetation indices, we found NPCI is better indices in this study work.

Key-Words / Index Term

NPCI, MCARI, NDVI, TCARI, SVM

References

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