Designing and Implementing Advanced Machinery for the Agrocomplex to Boost Agricultural Output
Keywords:
Agricultural Machinery , Mechanization , Farm ProfitabilityAbstract
Purpose: This study investigates the impact of advanced machinery adoption on agricultural output, labor efficiency, and farm profitability.
Methods: Conducted using a quantitative approach, the research analyzes data collected from 100 farms that implemented various types of machinery, including automated harvesters, GPS-guided tractors, and precision irrigation systems.
Results: The findings indicate a significant increase in agricultural output, with crop yield rising by 26.67% post-machinery adoption. Additionally, the study revealed a 31.25% reduction in labor hours per crop, showcasing the labor-saving potential of advanced equipment. Most notably, farm profitability increased by 30%, suggesting that the initial investment in machinery is offset by long-term financial gains. Statistical analyses, including regression models, confirmed that machinery use, farm size, and crop type are key predictors of these positive outcomes. These results align with prior literature on the benefits of mechanization but offer new insights by examining the combined effects of multiple machinery types on farm performance. The study fills a gap in understanding the comprehensive economic impact of agricultural technology and offers valuable implications for policymakers aiming to promote sustainable farming practices. Support for machinery adoption, especially for smallholder farmers, is recommended to further enhance productivity and profitability in agriculture.
References
Akintayo, A. A. (2023). Impact of IFAD Value Chain Development Programs on the Livelihood Outcomes of Rice Value Chain Actors in Nigeria (Doctoral dissertation, Kwara State University (Nigeria)).
Antonelli, C., Orsatti, G., & Pialli, G. (2023). The knowledge-intensive direction of technological change. Eurasian Business Review, 13(1), 1-27.
Barrile, V., Simonetti, S., Citroni, R., Fotia, A., & Bilotta, G. (2022). Experimenting agriculture 4.0 with sensors: A data fusion approach between remote sensing, UAVs and self-driving tractors. Sensors, 22(20), 7910.
Cani, P. D., Depommier, C., Derrien, M., Everard, A., & de Vos, W. M. (2022). Akkermansia muciniphila: paradigm for next-generation beneficial microorganisms. Nature Reviews Gastroenterology & Hepatology, 19(10), 625-637.
Çelebi, E. (2023). The Efficacy of Interest Subsidies as an Investment Incentive Instrument. Industrial Policy, 3(2), 12-26.
Correa Castro, J. C. (2022). Concept study of a Digital Twin of a Precision Agricultural Robot (Master's thesis, uis).
Deng, J., & Chen, X. (2021). Research on Artificial Intelligence Interaction in Computer‐Aided Arts and Crafts. Mobile Information Systems, 2021(1), 5519257.
Gassner, A., & Dobie, P. (2022). Agroforestry: A primer. Design and management principles for people and the environment.
Javaid, M., Haleem, A., Singh, R. P., Suman, R., & Gonzalez, E. S. (2022). Understanding the adoption of Industry 4.0 technologies in improving environmental sustainability. Sustainable Operations and Computers, 3, 203-217.
Jensen, T. A., Antille, D. L., & Tullberg, J. N. (2024). Improving On-farm Energy Use Efficiency by Optimizing Machinery Operations and Management: A Review. Agricultural Research, 1-19.
Keskin, Ö. (2022). Analysis of the impact of agricultural credits on agricultural mechanization in Türkiye. Mustafa Kemal Üniversitesi Tarım Bilimleri Dergisi, 29(1), 158-167.
Kijo-Kleczkowska, A., Bruś, P., & Więciorkowski, G. (2022). Profitability analysis of a photovoltaic installation-A case study. Energy, 261, 125310.
Mahmud, M. S. A., Abidin, M. S. Z., Emmanuel, A. A., & Hasan, H. S. (2020). Robotics and automation in agriculture: present and future applications. Applications of Modelling and Simulation, 4, 130-140.
Monteiro, A., Santos, S., & Gonçalves, P. (2021). Precision agriculture for crop and livestock farming—Brief review. Animals, 11(8), 2345.
Qian, L., Lu, H., Gao, Q., & Lu, H. (2022). Household-owned farm machinery vs. outsourced machinery services: The impact of agricultural mechanization on the land leasing behavior of relatively large-scale farmers in China. Land Use Policy, 115, 106008.
Ren, X., Huang, B., & Yin, H. (2023). A review of the large-scale application of autonomous mobility of agricultural platform. Computers and Electronics in Agriculture, 206, 107628.
Tutal, O. (2022). Impact of Climate Change on Agricultural Production and Yield in Turkey (Doctoral dissertation, Marmara Universitesi (Turkey)).
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Journal of Agrocomplex and Engineering
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
