Year: 2024
Type: article
Abstract: The study aimed to estimate the number of farmers growing cotton and cotton production for Amreli district. Employing a multi-stage sampling approach, we targeted a total of 100 farmers. Two talukas were selected from each district, followed by four villages from each taluka. At last, farmers from each village were chosen using Simple Random Sampling Without Replacement (SRSWOR) to ensure representativeness. Data collection involved direct interaction with each farmer through questionnaires, gathering information on landholding, fertilizer use, cropping patterns, and cotton yield specifically for the 2023 season. The district level data on crop production and related auxiliary variables were exploited through multiple linear regression model to estimate of crop production at block level. A scaled estimator of block level estimate also proposed. The percentage of cotton growing farmers ranged from 72% to 88%. BARE estimate of cotton production was found 19329.10 tonnes/ha over estimates the actual production. BARE estimates cotton yield of Rajula (55.57%) had lower standard errors. The correlation analysis showed a significant and positive association with factors such as total area under cotton cultivation, fertilizer consumption and rainfall. MLR revealed a positive and significant relationship between rainfall and cotton production. An empirical study for cotton production suggested that among scaled estimator, was more stable.
Institution: Junagadh Agricultural University
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: bronze
OpenAlex ID: W4402543338