A Statistical Approach for Analysis of Trend Pattern of Pigeon Pea in India

Singh, Gulshan and Kumar, Manish (2025) A Statistical Approach for Analysis of Trend Pattern of Pigeon Pea in India. Journal of Agriculture and Ecology Research International, 26 (1). pp. 1-12. ISSN 2394-1073

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Abstract

Aims: This paper deals with the analysis of trend pattern in area, production, and yield of pigeon pea in India.

Study design: Firstly, some well-known statistical models have been fitted to the concerned time series data on pigeon pea, and the trend values have been obtained. Then the accuracy of the concerned fitted models has been tested using various statistical measures. Finally, inferences are made regarding the trend pattern of pigeon pea in India.

Place and Duration of Study: The analysis is carried out using secondary time series data on area, production, and yield of pigeon pea in India pertaining to the period 2001-2023. The time series data have been collected from the records of the Directorate of Economics & Statistics, Department of Agriculture, Cooperation, and Farmers Welfare (DAC&FW), Govt. of India.

Methodology: The trend values have been computed on fitting well-known statistical models viz., linear model, exponential model, quadratic model, and cubic model. Moreover, the accuracy of the concerned fitted models has been evaluated using various statistical measures viz., coefficient of determination (R²), root mean square error (RMSE), and relative mean absolute percentage error (RMAPE).

Results: The results of the investigation reveal that the concerned models fitted well for exploring the trend in area, production, and yield of pigeon pea. Moreover, the cubic model is slightly more precise as compared to the other fitted models, and hence it could be utilized for forecasting the scenario of pigeon pea in India.

Conclusion: The findings of the study provide useful insights towards policy formulation regarding enhancement of pigeon pea production for meeting global food demand and nutritional security.

Item Type: Article
Subjects: STM Digital > Agricultural and Food Science
Depositing User: Unnamed user with email support@stmdigital.org
Date Deposited: 05 Mar 2025 04:07
Last Modified: 05 Mar 2025 04:07
URI: http://elibrary.ths100.in/id/eprint/1916

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