Econometric analysis of grain yields (using the example of the Republic of Azerbaijan)
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.2.01Keywords:
Productivity, Crops, Econometric analysis, Agriculture, Statistical modeling.Dimensions Badge
Issue
Section
License
Copyright (c) 2025 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This article is an econometric analysis of the influence of factors affecting the yield of grain crops in the Republic of Azerbaijan. In the course of the work, the dependence of yield on climatic, economic and agrotechnical factors was assessed based on correlation and regression analysis. The results of statistical modeling were formed, which allows identifying the most important determinants, such as the number of meteorological workers, the level of mechanization of production at the enterprise, the average annual number of crops, the use of mineral fertilizers, and government funding. The data obtained can be used to develop detailed recommendations for increasing the efficiency of grain crop production, as well as developing forecast models to improve planning in agriculture.Abstract
How to Cite
Downloads
Similar Articles
- Sawitri Devi, Raj Kumar, Unveiling scholarly insights: A bibliometric analysis of literature on gender bias at the workplace , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Ramesh Babu Durai C, D. Madhivadhani, A. Sumathi, Lily Saron Grace, Graph neural networks for modeling ecological networks and food webs , The Scientific Temper: Vol. 16 No. 02 (2025): The Scientific Temper
- Neha Chitale, Lajwanti Lalwani, A Bibliometric Analysis of Global Research From 1928 To 2019 On Mobilization with Movement on Functional Disability in Low Back Pain , The Scientific Temper: Vol. 16 No. 10 (2025): The Scientific Temper
- V. Parimala, D. Ganeshkumar, Solar energy-driven water distillation with nanoparticle integration for enhanced efficiency, sustainability, and potable water production in arid regions , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Dimpal Khambhati, Chirag Patel, Analyzing cardiac physiology: ECG ensemble averaging and morphological features under treadmill-induced stress in LabVIEW , The Scientific Temper: Vol. 16 No. 07 (2025): The Scientific Temper
- Reena Lawrence, Kapil Lawence, Manisha Prasad, Ritika Singh, ANTIOXIDANT ACTIVITY OF METHANOL EXTRACT OF ZINGIBER OFFICINALE GROWN IN NORT INDIAN PLAINS , The Scientific Temper: Vol. 1 No. 01 (2010): The Scientific Temper
- Muhammed Jouhar K. K., Dr. K. Aravinthan, An improved social media behavioral analysis using deep learning techniques , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Rashmi Chandra, Afroz Alam, Phytochemical Analysis Using X-ray Diffraction Spectroscopy (XRD) and GC-MS Analysis of Bioactive Compounds in Cucumis sativus L. (Angiosperms; Cucurbitaceae) , The Scientific Temper: Vol. 13 No. 01 (2022): The Scientific Temper
- Gomathi P, Deena Rose D, Sampath Kumar R, Sathya Priya M, Dinesh S, Ramarao M, Computer vision for unmanned aerial vehicles in agriculture: applications, challenges, and opportunities , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Selva Kumar D, Revisiting the challenges of disinvestment practices and central public sector enterprises (CPSEs): Indian empirical evidence , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.

