Artificial intelligence (AI) refers to computer systems doing tasks that usually need human intelligence. AI is constantly changing and is revolutionizing the healthcare field, including nutrition. This review’s purpose is four-fold: (i) to investigate AI’s role in nutrition research; (ii) to identify areas in nutrition using AI; (iii) to understand AI’s future potential impact; (iv) to investigate possible concerns about AI’s use in nutrition research. Eight databases were searched: PubMed, Web of Science, EBSCO, Agricola, Scopus, IEEE Explore, Google Scholar and Cochrane. A total of 1737 articles were retrieved, of which 22 were included in the review. Article screening phases included duplicates elimination, title-abstract selection, full-text review, and quality assessment. The key findings indicated AI’s role in nutrition is at a developmental stage, focusing mainly on dietary assessment and less on malnutrition prediction, lifestyle interventions, and diet-related diseases comprehension. Clinical research is needed to determine AI’s intervention efficacy. The ethics of AI use, a main concern, remains unresolved and needs to be considered for collateral damage prevention to certain populations. The studies’ heterogeneity in this review limited the focus on specific nutritional areas. Future research should prioritize specialized reviews in nutrition and dieting for a deeper understanding of AI’s potential in human nutrition.

Background: Malnutrition remains a significant public health issue in Kenya. Multisectoral Nutrition Governance (MNG) is increasingly being acknowledged as a catalyst for enhancing nutrition programming and outcomes. Effective MNG establishes policies, systems, and mechanisms that enable coordinated, adequately funded, and sustainable nutrition actions across sectors; however, its understanding and progress assessment remain inadequate. Objective: This study aimed to qualitatively assess the status of MNG and propose strategies to strengthen MNG mechanisms for improved nutrition actions and outcomes in Kenya. We hypothesized that effective performance across the MNG domains is associated with effective multisectoral nutrition actions and improved nutrition outcomes. Design: This study used a qualitative design to assess the MNG status over the past 10 years (2012–2023). Nineteen program managers and officers from government and non-governmental institutions implementing nutrition at the national level were included. Data collection was conducted between January and March 2024 through key informant interviews (KIIs). Thematic analysis, guided by both inductive and deductive coding, was carried out using MAXQDA (Maximizing Qualitative Data Analysis) software. Results: The findings indicate progress in strengthening MNG in the previous decade, though gaps persist. The progress was driven by improved political awareness and commitment, the adoption of nutrition policy and planning frameworks, and improved coordination. Constraints that impede MNG progress include inadequate financing and over-reliance on donor funding, limited translation of commitments to actions, lack of unified monitoring and evaluation (M&E) systems and fragmented policies. Conclusions: Strengthening multisectoral M&E systems that allow timely collection and utilization of data, ensuring sustainable financing for nutrition, enhancing accountability mechanisms and improving coherence across sectors are important for further improvement of MNG.

Sorghum is a nutritious, healthy, gluten-free whole grain, with the United States (U.S.) leading its production globally. While sorghum is consumed worldwide, it is mainly used for animal feed and biofuel in the U.S. Organoleptic characteristics and consumers’ perceptions determine food acceptance and eating behavior. Therefore, this study aimed to investigate the acceptance of and eating and purchase intentions toward sorghum-based foods among college students in a southern university in the U.S. Eighty-three students participated in a series of sensory evaluations using two sets of four sorghum samples each and a 15 min break. Seven sensory attributes were evaluated with a nine-point hedonic scale, and a five-point scale was used for eating and purchase intentions. To assess the panelists’ acceptance, the overall acceptance scale score (range: 1–9) was normalized (range: 0–100) and used for analyses. Spiced sorghum cookies (77.95 ± 14.23) had the highest acceptance, followed by sorghum shrimp grits (74.51 ± 19.42). Overall acceptance, eating intention, and purchase intention were strongly associated across all food items, although the strength differed by food type. Sorghum-based foods were accepted despite the participants’ lack of exposure to sorghum and its null consumption. These outcomes will help to develop innovative sorghum-based foods to facilitate sorghum consumption and benefit consumer health in the U.S.