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.

The current examines the influence of Islamic values on smoking behaviors among undergraduate students at Yarmouk University in Irbid, Jordan (N: 334). Tobacco use, in religious and cultural terms, is viewed as abhorrent; it is a significant concern for this population group. The study intends to identify how Islamic values affect the perception of students on smoking and, consequently, their smoking behavior. A self-administered questionnaire assessed sociodemographic data and the past 30 days of cigarette use. Descriptive statistics, such as frequencies and percentages, midpoint and standard deviation, and inferential statistics, such as chi-square tests, t-tests, ANOVA, Pearson correlation, and hierarchical regression, were used to analyze smoking behaviors, Islamic values, and demographic attributes. The study shows that Islamic values have a strong negative attitude towards smoking; students attributed smoking to religion, family and social expectations and perceptions, health and economic implications. Further, the hierarchical regression analysis revealed that cigarette use, hookah and e-cigarette, gender, and attitude towards Islamic values were suitable predictors for cigarette use. This study advances knowledge regarding smoking behaviors from the cultural-religious perspective. It highlights the importance of historically and culturally informed gender-sensitive prevention programs that address smoking-related beliefs, attitudes, and practices. Collaboration with the Ministry of Health and media outlets to integrate Islamic values into public health campaigns can reduce smoking among university students by aligning cultural and religious beliefs with health messaging.