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http://krishi.icar.gov.in/jspui/handle/123456789/76862
Title: | Forecasting of Pea Prices of Varanasi Market Uttar Pradesh, India through ARIMA Model |
Other Titles: | Not Available |
Authors: | Goyal, A., Badal, P.S., Kamalvanshi, V., Kumar, P. and Mondal, B. |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | BHU |
Published/ Complete Date: | 2022-03-01 |
Project Code: | Not Available |
Keywords: | ARIMA, SARIMA, RMSE, MAE, forecasting, peas |
Publisher: | Renu Publishers |
Citation: | Not Available |
Series/Report no.: | Not Available; |
Abstract/Description: | Pea (Pisum sativum) is the most common green pod-shaped vegetable widely grown as a cool-season crop. Green peas are used either- fresh or frozen and canned. India is one of the largest producers of peas in the world and ranks 5th on the of major pea producers. However, fluctuation in the prices of pea are common and lead to often reduced profit to farmers. A prior information about this price could help them in decision making regarding bringing the same for market or opting for processing. For this purpose ARIMA and SARIMA models were used to forecast the prices of pea for Varanasi in Uttar Pradesh using daily time series data of five years from 2017 to 2021. The best model was selected on the basis of R-squared, AIC, BIC, RMSE and MAE. The study revealed that out of ARIMA (3,1,5), SARIMA (1,0,1) (1,0,1) and SARIMA (0,0,1)(0,0,1), the 2nd were best fitted model for forecasting of pea prices for Varanasi. The forecasted values showed that the prices of pea were high in the month of November and February and low in December and January for the forecast year 2022. |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Review Paper |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | Agro Economist - An International Journal |
NAAS Rating: | 4.58 |
Volume No.: | 9 |
Page Number: | 49-54 |
Name of the Division/Regional Station: | Not Available |
Source, DOI or any other URL: | https://renupublishers.com/images/article/AEv9n1g.pdf |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/76862 |
Appears in Collections: | CS-NRRI-Publication |
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