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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
IJCMAS is now DOI (CrossRef) registered Research Journal. The DOIs are assigned to all published IJCMAS Articles.
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2020)
[Effective from January 1, 2020]
For more details click here

ICV 2018: 95.39
Index Copernicus ICI Journals Master List 2018 - IJCMAS--ICV 2018: 95.39
For more details click here

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Original Research Articles

PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com / submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2018.7(3): 2680-2689
DOI: https://doi.org/10.20546/ijcmas.2018.703.310


Remote Sensing as Pest Forecasting Model in Agriculture
D. Sudha Rani1, M.N. Venkatesh2, Ch. Naga Satya Sri2 and K. Anand Kumar2
1Scientist (Entomology), Agricultural Research Station, Garikapadu, Krishna dt, India
2Agricultural Polytechnic, Garikapadu, Krishna dt, India
*Corresponding author
Abstract:

Agriculture plays a dominant role in the growth of Indian economy contributing nearly 28 per cent towards Gross Domestic Product (GDP). Insect pests (14 per cent), diseases and weeds inflict enormous losses to the potential agricultural production. The yield losses due to pest population can be suppressed to be greater extent if their incidence is known well in advance so that timely adoption of remedial measures is possible. This led to a concept of ‘forecasting’ which is an important component of the IPM strategy. Forecasting methods are based on the models that utilize data on weather parameters, farmer’s eye estimates, agrometerological conditions, remote sense crop reflectance observations etc. either separately or in an integrated manner. The visual detection of plant responses to biotic stresses with acceptable levels of accuracy, precision and speed is difficult. These responses affect the amount and quality of electromagnetic radiation reflected from crop canopies. Hence, remote sensing is the technique involving instruments that measure and record the changes in electromagnetic radiation and provides better means of objectively quantifying biotic stresses in comparison to visual assessment methods. In this review article, briefed the concept, principles and types of remote sensing with some case studies to augment the acquaintance on the concept of “Remote Sensing” as pest forecasting model.


Keywords: Remote sensing, Forecasting model, Pests
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How to cite this article:

Sudha Rani, D., M.N. Venkatesh, Ch. Naga Satya Sri and Anand Kumar, K. 2018. Remote Sensing as Pest Forecasting Model in Agriculture.Int.J.Curr.Microbiol.App.Sci. 7(3): 2680-2689. doi: https://doi.org/10.20546/ijcmas.2018.703.310