Technological advancements are transforming agriculture, yet adoption rates among agricultural extension officers, especially in regions like West Java, remain modest due to several challenges. This study applies the Technology Acceptance Model (TAM) to investigate factors influencing the adoption of agricultural technologies by agricultural extension officers in West Java. Specifically, we explore the role of socialization, training, access to technology, cost, perceived ease of use, and perceived usefulness in shaping behavioral intention and actual adoption. Data were collected from 295 agricultural extension officers via structured surveys and analyzed using SmartPLS 4 software. The findings indicate that socialization and training collectively enhance both perceived ease of use and perceived usefulness, while Technology Investment Worth specifically enhances perceived usefulness by emphasizing the value of the investment. Access to technology also plays a critical role in increasing ease of use perceptions. Both perceived ease of use and usefulness positively influence behavioral intention, which in turn is a strong predictor of actual adoption. The results provide valuable insights for policymakers aiming to increase technology uptake among agricultural extension officers, promoting sustainable agricultural practices through improved access, support, and cost reduction initiatives.

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 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.

The technology of vermicomposting containing their leachates, teas and other extracts such as vermiwash as a result of earthworm action is widely applied for safe management of agricultural, industrial, domestic and hospital wastes. Remediation of polluted soils, improving crop productivity and inducing the resistance against biotic and abiotic stresses are other advantages of vermicompost derived liquids when used in agriculture. Contrary to the fact that chemical fertilizers are still widely used in agriculture, societies gradually become aware of the negative effects of these fertilizers on their health. Therefore, vermicompost derived liquids contain high amount of valuable plant nutrients which has the potential to be used as liquid fertilizer. This paper reviews the potential of vermicompost derived liquids as as an efficient combination of nutrient source of vermicompost derived liquids contributing to plant growth and acting as a deterrent to biotic and abiotic stresses.

The rising trend of tourists selecting agrotourism as a tourist destination has become an intriguing study issue. Seremban is a well-known tourist attraction that is popular among visitors. As a result, Seremban has been selected as the study site. However, river pollution may have an influence on Seremban’s natural environment and agrotourism potential. Furthermore, inadequate infrastructure, such as unauthorized parking, exacerbated the inhabitants’ problems. A growing number of young people leave Seremban to pursue employment or further education in other cities, with no desire to work as farmers. The labor scarcity has also made it difficult for farmers to grow their farms. Consequently, the study aims to examine how factors such as the natural environment, tourist infrastructure, perceived social advantages, and perceived barriers influence the attitudes of Seremban residents towards agrotourism, with a focus on its potential for driving economic growth. This study adopts quantitative research methods, employing descriptive and causal research designs. Primary data collection is conducted through questionnaires, supplemented by secondary data. Non-probability quota sampling is utilized due to the absence of a specific sampling frame, with a sample size of 385 respondents determined using G*Power software. Constructs are developed based on previous research, and the questionnaire comprises Likert-scale items to gauge attitudes and perceptions. A pilot study assesses the instrument’s reliability. Data analysis is performed using SPSS software, encompassing multiple linear regression and Pearson correlation analyses in addition to descriptive statistics. The findings provide valuable insights into the factors driving residents’ perceptions of agrotourism in Seremban, emphasizing the importance of the natural environment, tourism infrastructure, perceived social benefits, and perceived barriers in shaping attitudes. Additionally, the study highlights the resilience of residents’ positive attitudes toward agrotourism, despite potential challenges and barriers identified. Overall, these results offer implications for policymakers and stakeholders involved in tourism development in the region.