Sheng Xiaohan, Liu Guangmin
School of Social Sciences, Rice University, Houston, TX77005, USA.
Department of Accounting, School of Economics and Management, Harbin University, Harbin, 150086, China.
Sci Rep. 2024 Sep 27;14(1):22365. doi: 10.1038/s41598-024-72117-4.
This research focuses on the importance of management strategies, green innovation, and sustainable practices in the agricultural sector. These factors are crucial for job creation, food security, and environmental conservation. Particularly in water-scarce regions, effective management is necessary to overcome natural resource constraints and encourage a shift towards digital agriculture (AGRI). The study aims to identify and analyze the challenges and issues related to agricultural research and technology in Asian countries. The collected data were analyzed using exploratory factor analysis in the SPSS software. The analysis revealed a range of issues and challenges for agricultural development, including those related to the structure and policy framework, the availability and quality of resources and infrastructures, and the provision of effective support services, all of which encompassed factors such as research and technology investment, research management, productivity, research culture, networking, and the integration of higher education and agricultural research. To estimate the efficiency of technology development, agricultural development, and support services for AGRI, an artificial neural network (ANN) was utilized. The ANN was trained by incorporating changes in management strategies, green innovation, and sustainability across a broader range of experimental scenarios. The evaluation of the ANN's predictions showed that improvements in management strategies and the adoption of green innovation and sustainability significantly impacted the productivity of technology development, agricultural development, and support services for AGRI. The accuracy of the ANN's predictions was further assessed using linear regression. The results indicated an acceptable level of error when compared to the target results obtained from experimental tests. Overall, this study emphasizes the importance of effective management, green innovation, and sustainable practices in driving advancements in technology and agricultural development.
本研究聚焦于农业领域管理策略、绿色创新和可持续实践的重要性。这些因素对于创造就业、粮食安全和环境保护至关重要。特别是在水资源稀缺地区，有效管理对于克服自然资源限制并鼓励向数字农业（AGRI）转型是必要的。该研究旨在识别和分析亚洲国家与农业研究和技术相关的挑战和问题。使用SPSS软件中的探索性因素分析对收集到的数据进行分析。分析揭示了农业发展面临的一系列问题和挑战，包括与结构和政策框架、资源和基础设施的可用性及质量，以及有效支持服务的提供相关的问题，所有这些都涵盖了诸如研究和技术投资、研究管理、生产力、研究文化、网络以及高等教育与农业研究的整合等因素。为了评估AGRI的技术开发、农业发展和支持服务的效率，使用了人工神经网络（ANN）。通过纳入更广泛实验场景中管理策略、绿色创新和可持续性的变化来训练ANN。对ANN预测的评估表明，管理策略的改进以及绿色创新和可持续性的采用对AGRI的技术开发、农业发展和支持服务的生产力产生了重大影响。使用线性回归进一步评估了ANN预测的准确性。与从实验测试获得的目标结果相比，结果表明误差水平可接受。总体而言，本研究强调了有效管理、绿色创新和可持续实践在推动技术进步和农业发展方面的重要性。
