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Vol. 11, Special Issue 4 (2022)

Forecasting area, production and productivity of mango in Gujarat by using an artificial neural network model

Author(s):
Prity Kumari, DJ Parmar, Sathish Kumar M, YA Lad and AB Mahera
Abstract:
The present study conducted to forecasting area, production and productivity of mango in Gujarat by using different models. The secondary data on area, production and productivity of mango in Gujarat (1991-92 to 2017-18) were collected from Directorate of Horticulture, Gujarat. Time series secondary data on area, production and productivity of mango were collected for the period 1958-59 to 2017-18. The collected data were analyzed in R Studio (version 3.5.2) software. Different Artificial Neural Network models employed to forecast area, production and productivity of fruits crops and also find out best models through comparison of all models. 4:1s:1l, 2:2s:1l & 2:2s:1l ANN architectures, were the most appropriate model for predicting its area, production and productivity with forecasted value for 2018-19 144.95 thousand hectares, 809.91 thousand metric tonnes and 7.17 metric tonnes per hectare respectively, where area, production and productivity are likely to go down for upcoming year.
Pages: 822-826  |  360 Views  176 Downloads
How to cite this article:
Prity Kumari, DJ Parmar, Sathish Kumar M, YA Lad and AB Mahera. Forecasting area, production and productivity of mango in Gujarat by using an artificial neural network model. The Pharma Innovation Journal. 2022; 11(4S): 822-826.

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