Issue |
BIO Web Conf.
Volume 65, 2023
EBWFF 2023 - International Scientific Conference Ecological and Biological Well-Being of Flora and Fauna (Part 2)
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|
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Article Number | 01014 | |
Number of page(s) | 8 | |
Section | Advances in Crop and Plant Cultivation | |
DOI | https://doi.org/10.1051/bioconf/20236501014 | |
Published online | 04 September 2023 |
Statistical analysis of vegetable productivity dynamics of Uzbekistan
Tashkent State Agrarian University, 2, University street, Tashkent, 100140, Uzbekistan
* Corresponding author: fayziev47@mail.ru
In all fields, there are a lot of random events at a given time. In particular, the process of growing agricultural crops, which is repeated over a certain period, that is, seasonally, is the basis for our analysis as a discrete {Yt,t ∈ T} random dynamic series. This research contributes to the existing literature on agricultural productivity by focusing on the unique context of Uzbekistan. By utilizing a rigorous statistical approach and considering multiple influencing factors, we aim to provide evidence-based recommendations to policymakers and stakeholders for enhancing vegetable productivity and ensuring sustainable agricultural development. In the article, the average yield of {Yt,t ∈ T} vegetables grown in open and closed lands of the Republic of Uzbekistan in 2006-2020 was statistically analyzed using modern methods of mathematical statistics suitable for stable dynamic series, and point and interval statistical estimates were made for vegetable yield with a 95% guarantee. The trend part, which characterizes the main direction of vegetable cultivation, is determined, and the yield obtained from vegetables in the coming years is predicted. The fact that this process has an autocorrelation relationship was determined with the help of statistical criteria, and its important characteristics and laws were studied.
Key words: Discrete / dynamic / statistical / trend / autocorrelation
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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