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http://krishi.icar.gov.in/jspui/handle/123456789/42852
Title: | Predicting pest population using weather variables: an ARIMAX time series framework |
Other Titles: | Not Available |
Authors: | P. Arya R. K Paul A. Kumar K. N. Singh N. Sivaramne P. Chaudhary |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | ICAR::Indian Agricultural Statistics Research Institute ICAR::National Academy of Agricultural Research and Management C.C.S. University, Meerut, India |
Published/ Complete Date: | 2015-02-01 |
Project Code: | Not Available |
Keywords: | ARIMAX Model Forecasting Pest Population Weather Variables |
Publisher: | Not Available |
Citation: | Arya, Prawin, Paul, Ranjit Kumar, Kumar, Anil, Singh, K. N., Sivaramne, N. and Chaudhary, Pradeep (2015). Predicting pest population using weather variables: an ARIMAX time series framework, 11(2) 381-386. |
Series/Report no.: | Not Available; |
Abstract/Description: | Farmers are encountering several issues in endeavour to increase crop productivity. Despite several successfulnew agricultural technologies related with crop cultivation, India is unable to attain world average mark in productivity. Oneof the main reasons for this is climatic conditions and abundance of insects and pests. To mitigate the loss due to pest attacksand for better yield, forecasting of pest population based on historical data and pertinent external climatic information isconsidered. Autoregressive Integrated Moving Average with Exogenous variables (ARIMAX) time-series model is appliedfor modelling and forecasting the pest population after testing for stationarity. Primary weekly data (2008-2012) for three pestsnamely Jassids, Whitefly and Thrips in Guntur and Faridkot Districts along with weekly maximum temperature, minimumtemperature, rainfall, maximum RH and minimum RH have been used for model development. Evaluation of forecasting iscarried out with relative mean absolute prediction error (RMAPE). Diagnostic test were applied and results showed thatmaximum temperature and minimum temperature along with maximum relative humidity have a significant role for Whitefly andThrips at Guntur district respectively. Rainfall was found to be significant at Faridkot district in case of Thrips. The fittedmodels along with the data points are also presented. A perusal of figures indicates that in both districts, the population ofWhitefly is best predicted followed by Jassids and Thrips. |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Research Paper |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | International Journal of Agricultural and Statistical Sciences |
NAAS Rating: | 4.92 |
Volume No.: | 11(2) |
Page Number: | 381-386 |
Name of the Division/Regional Station: | Not Available |
Source, DOI or any other URL: | Not Available |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/42852 |
Appears in Collections: | AEdu-IASRI-Publication |
Files in This Item:
File | Description | Size | Format | |
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381-386.pdf | 451.27 kB | Adobe PDF | View/Open |
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