Unlocking the secrets of apple harvests: Advanced stratification techniques in the Himalayan region

Abstract

This study focuses on standardizing sampling techniques and comparing various methods of sample allocation to effectively estimate apple area and production in the Himalayan region of India. We investigate different stratification tools,in formulating a sampling plan using information gathered from select orchardists in the locale during the 2016-17 period, it becomes essential to explore diverse methodologies to define the most suitable stratum boundaries, ascertain the requisite number of strata, and identify the optimal sample size. The stratification process, underpinned by the ''Area under Apple'' variable, which demonstrates a pronounced association with apple production, assumes a central role in this endeavor Several methods are utilized to construct strata, such as equalizing strata totals, cumulative equalization, equalization of ½{r(x) + f(x)} and equalization of f(x) . We assess their efficiencies in estimating total apple production in the study district. The combination of the ''Cum f(x)'' of Neyman allocation demonstrates the lowest variance and the highest efficiency within a range of 2–4 strata, coupled with an increase in sample size from 10 to 40. Consequently, it can be inferred that the ''Cum f(x)'' method, particularly with L > 2, is preferable for estimating apple production in the Himalayan region of India.

Keywords

• Apple production
• Stratified random sampling
• Optimum stratification
• Neyman allocation
• Relative efficiency