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http://krishi.icar.gov.in/jspui/handle/123456789/46640| Title: | Predicting pest population using weather variables an ARIMAX time series framework |
| Other Titles: | Not Available |
| Authors: | Prawin Arya Ranjit Kumar Paul Anil Kumar K. N. Singh N. Sivaramne Pradeep 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 Department of Statistics, C.C.S. University, Meerut - 250 004, India. |
| Published/ Complete Date: | 2015-09-01 |
| Project Code: | Not Available |
| Keywords: | ARIMAX Model Forecasting Pest Population Weather Variables |
| Publisher: | Not Available |
| Citation: | Prawin Arya, Ranjit Kumar Paul, Anil Kumar, K. N. Singh, N. Sivaramne and Pradeep Chaudhary (2015). Predicting Pest Population Using Weather Variables : An Arimax Time Series Framework Int. Journal 0f Agricultural Statistics and Science 11(2), 381-386. |
| Series/Report no.: | Not Available; |
| Abstract/Description: | Farmers are encountering several issues in endeavour to increase crop productivity. Despite several successful new agricultural technologies related with crop cultivation, India is unable to attain world average mark in productivity. One of the main reasons for this is climatic conditions and abundance of insects and pests. To mitigate the loss due to pest attacks and for better yield, forecasting of pest population based on historical data and pertinent external climatic information is considered. Autoregressive Integrated Moving Average with Exogenous variables (ARIMAX) time-series model is applied for modelling and forecasting the pest population after testing for stationarity. Primary weekly data (2008-2012) for three pests namely Jassids, Whitefly and Thrips in Guntur and Faridkot Districts along with weekly maximum temperature, minimum temperature, rainfall, maximum RH and minimum RH have been used for model development. Evaluation of forecasting is carried out with relative mean absolute prediction error (RMAPE). Diagnostic test were applied and results showed that maximum temperature and minimum temperature along with maximum relative humidity have a significant role for Whitefly and Thrips at Guntur district respectively. Rainfall was found to be significant at Faridkot district in case of Thrips. The fitted models along with the data points are also presented. A perusal of figures indicates that in both districts, the population of Whitefly 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: | 5.13 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/123456789/46640 |
| Appears in Collections: | AEdu-IASRI-Publication |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 381-386.pdf | 451.11 kB | Adobe PDF | View/Open |
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