The purpose of this study is to analyze issues related to the use of green technology and to provide a theoretical basis for how the application of green technology in agriculture can reduce inequality. Additionally, the study aims to explore policy alternatives based on the analysis of inequality reduction issues through farmer surveys. For this purpose, this study used survey data to analyze farmers’ perceptions, acceptance status, willingness to accept green technology, and perceptions of inequality. The quantitative analysis was performed to analyze the relationship between the acceptance of green technology and perceptions of inequality. The results confirmed that access to information, perception of climate change, and awareness of the need to reduce greenhouse gas emissions are major factors. In particular, the higher the satisfaction with policies regarding the introduction of green technology, the lower the perception of inequality. Specifically, the acceptance of green technology showed a significant positive correlation with access to information, perception of climate change, and awareness of the need to reduce greenhouse gas emissions, while perceptions of inequality showed a significant negative correlation with policy satisfaction. In conclusion, green technology in agriculture is vital for reducing climate change damage and inequality. However, targeted policy support for small-scale farmers is essential for successful adoption. This study provides policy implications related to the application of green technology in the agricultural sector, which can promote sustainable agricultural development.
A decent income is an important part of overcoming economic disparities in agricultural development, especially in developing countries where most of the population are small farmers. As a developing country, Indonesia has also established a decent standard of living by setting a minimum wage as a reference for a decent income at the national and regional levels. However, this benchmark is not relevant to be applied uniformly at all levels of workers. This research determines the national coffee development area as the study center. We developed the Anker living wage methodology as a simple concept for determining living income for certain worker communities, especially for small farmers in rural areas who dominate the type of work in Indonesia. a socio-spatial approach is used to visualize the distribution of the dynamics of a decent life in various conditions of farming households. We found that 96.6% of coffee farming households in the national coffee development area had an inadequate living income, and only 3.4% were at an adequate level. We conclude that the current state of agricultural land management does not guarantee a decent income, even though efforts have been made to maximize agricultural crop productivity. The spatial description also shows that this condition is evenly distributed throughout residential areas. It is hoped that this approach can become an essential reference in implementing agricultural development programs that focus on welfare and equitable development as benchmarks for sustainable development goals in the future.
The transition to sustainable agricultural practices is critical in the face of escalating climate challenges. Despite significant advances, the integration of green technologies within agribusiness remains underexplored. This study undertakes a comprehensive bibliometric analysis, utilizing data from the Web of Science Core Collection (1990–2023), to elucidate the integration of green technologies within agribusiness strategies. The research highlights key trends, influential authors, prominent journals, and significant thematic clusters, including biogas, biochar, biotech remediation, sustainable agriculture transition, low-carbon agriculture, and green strategies. By employing R, Bibliometrix, and VOSviewer, the study provides a nuanced understanding of the research landscape, emphasizing the critical role of strategic planning, policy frameworks, technological innovation, and interdisciplinary approaches in promoting sustainable agricultural development. The findings underscore the growing scholarly interest in sustainable practices, driven by global initiatives such as the UN’s 2030 Agenda and the Paris Agreement. This study contributes to the literature by offering qualitative insights and policy implications, highlighting the necessity for a holistic integration of green technologies to enhance the environmental and economic viability of agribusinesses.
The economy, unemployment, and job creation of South Africa heavily depend on the growth of the agricultural sector. With a growing population of 60 million, there are approximately 4 million small-scale farmers (SSF) number, and about 36,000 commercial farmers which serve South Africa. The agricultural sector in South Africa faces challenges such as climate change, lack of access to infrastructure and training, high labour costs, limited access to modern technology, and resource constraints. Precision agriculture (PA) using AI can address many of these issues for small-scale farmers by improving access to technology, reducing production costs, enhancing skills and training, improving data management, and providing better irrigation infrastructure and transport access. However, there is a dearth of research on the application of precision agriculture using artificial intelligence (AI) by small scale farmers (SSF) in South Africa and Africa at large. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) and Bibliometric analysis guidelines were used to investigate the adoption of precision agriculture and its socio-economic implications for small-scale farmers in South Africa or the systematic literature review (SLR) compared various challenges and the use of PA and AI for small-scale farmers. The incorporation of AI-driven PA offers a significant increase in productivity and efficiency. Through a detailed systematic review of existing literature from inception to date, this study examines 182 articles synthesized from two major databases (Scopus and Web of Science). The systematic review was conducted using the machine learning tool R Studio. The study analyzed the literature review articled identified, challenges, and potential societal impact of AI-driven precision agriculture.
This study systemically examines the numerous impacts of climate change on agriculture in Tunisia. In this study, we establish an empirical and comprehensive methodology to assess the effects of climate changes on Tunisian agriculture by investigating current climatic patterns using crop yields and socioeconomic variables. The study also assesses the types of adaptation strategies agriculture uses in Tunisia and explores their effectiveness in coping with climate-related adversities. We also consider some resilience factors, namely the ecological aspect and economic and social camouflage pursued by the (very) men in Tunisian agriculture. We also extensively discuss the complex interconnected relationship between policy interventions and community-based adaptations, a crucial part of the ongoing debate on climate change adaptation and resilience in agriculture. The findings of this study contribute to this important conversation, particularly for areas facing similar challenges.
This study investigates the impacts of converting agricultural land into agrotourism areas on environmental, socio-cultural, and economic perspectives within Batukliang District, Central Lombok Regency, Indonesia. With a case study approach, this qualitative descriptive research employed interviews with three target groups: local farmers, residents, and tourism actors. The findings revealed seven key points identified as influences affecting the socio-cultural aspects of land change, including community impact, cultural preservation, cultural identity loss, community dynamics change, local cultural commercialization, cultural heritage loss, and traditional livelihoods. The results also unveiled nine financial impacts, 8 of which were associated with economic implications such as economic challenges, risk management, brand building, costs and investments, market access, increased revenue, and income diversity, which contribute positively to local economic development. The study concluded that integrating community involvement empowerment strategies, income diversification, sustainable farming promotion, and land-use regulation is crucial for developing a successful sustainable agrotourism destination.
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