Real‐time assurance of food safety and quality requires decisions at line speed, from farm to retail, using signals that span vision, spectroscopy, volatiles, biosensing, and process telemetry. This review investigates and summarizes evidence on multimodal artificial intelligence that fuses such heterogeneous data to detect hazards, verify authenticity, and predict freshness within seconds. We outline sensing coverage along the chain, typical response times, and reported limits of detection, then detail data engineering practices that make disparate streams analysis‐ready, including time synchronization, co‐registration to ground truth, and robust sampling for multisite and multiseason generalization. We appraise fusion strategies, from early and late schemes to attention‐based hybrids that learn joint embeddings across images, spectra, and gas sensor time series, and we summarize head‐to‐head studies where multimodality improves accuracy or reduces error against unimodal baselines. We discuss the maturation of foundation scale encoders and vision language systems for food tasks, together with efficient adaptation, knowledge infusion from HACCP, and bias control. Finally, we examine edge deployment and validation in industrial settings, including hardware constraints, latency budgets, repeatability and reproducibility, documentation for audits, and perspectives on regulatory alignment in EU and US contexts, extended to China's standards‐driven framework where the National Health Commission (NHC) and the State Administration for Market Regulation (SAMR) jointly issue and update National Food Safety Standards (GB) that govern key compliance requirements for labelling and contaminant limits. Evidence gaps persist, notably few multisite deployments over long durations, limited public benchmarks for hyperspectral and e‐nose fusion, and sparse cost–benefit analyses in the scholarly record. Addressing these gaps will enable trustworthy, auditable multimodal AI that complements existing controls and reduces waste while protecting consumers.

Nanotechnology is playing an important role to develop modern solutions in food safety and agriculture that make it highly efficient as well as safe. This paper is aimed at dissecting how nanotechnology can be used in smart packaging, delivery systems and food security in agriculture. Smart packaging instills such features like increased shelf life, food safety, and real-time monitoring of food quality when nanomaterials are incorporated into the packaging system. Hi-tech delivery systems made possible through nanotechnology improve the effectiveness of agrochemicals, minimize the adverse effects on the environment, and reclaim the principles of sustainable farming. In addition, nanotechnology helps to protect food from spoilage as well as enhance crop quality, yield, and pest resistance, and upgrade the nutritional value of foods. Combining the results of the current state of nanotechnology development and its future prospects, this paper recognizes nanotechnology as a powerful tool for the agricultural industry and a secure food supply chain.

Background: Effective management of postprandial glycemic control is critical for diabetic patients, as elevated postprandial glucose levels can lead to complications such as cardiovascular disease and neuropathy. This study evaluates isomaltulose, a low-glycemic-index carbohydrate, as an alternative to sucrose in mitigating postprandial glucose spikes. Objectives: To synthesize evidence from existing studies and assess the efficacy of isomaltulose in reducing postprandial glycemic levels compared to sucrose in diabetic populations. Methods: A systematic review and meta-analysis were conducted following PRISMA guidelines. Searches were performed across PubMed, Cochrane Library, and ClinicalTrials.gov for randomized controlled trials or crossover studies comparing isomaltulose and sucrose. Data were extracted, and the Cochrane Risk of Bias tool was used to assess study quality. Results: Ten studies were included, involving 367 participants. The meta-analysis showed that isomaltulose significantly reduced plasma glucose level at 60 min post-meal, though the actual effect could be modest in terms of clinical relevance compared to sucrose (MD: −7.99, 95% CI: −8.58, −7.39, p < 0.00001). Notable variability in the study results was observed, which may be attributed to multiple factors such as participant demographics and meal composition. Conclusions: The findings from the analysis are supportive for the use of isomaltulose as a beneficial dietary alternative to sucrose for managing postprandial glycemic levels in diabetic patients. Future research effort is suggested to focus on larger, diverse populations to enhance generalizability and explore the impact of dietary context on glycemic response.

This research examines the association between global oil prices and food prices, focusing on both symmetric and asymmetric perspectives, with a particular focus on the Hong Kong context. The context has a unique reliance on imports, and highly integrated global market exposure requires thorough analysis. Using linear Autoregressive Distributed Lag (ARDL) and nonlinear (NARDL) approaches, both short and long-run pass-through effects of oil price shocks on domestic food prices from 1990 to 2023 were examined. The results show that short-term oil pricing fluctuations do not significantly affect and decrease competitive pricing strategies and long-term contact. Conversely, in the long run, positive oil price shocks significantly increase food prices, whereas negative shocks yield a significant decrease. Importantly, the magnitudes of these effects are not equal, showing the asymmetric nature of the adjustment process. Additionally, global food prices and interest rates significantly influence local food prices. The findings highlight the need for diversified import strategies, efficient logistics, and price stabilization measures to protect against global market volatility and ensure Hong Kong’s food security and economic stability.

One of the key aspects of the modern farming that can be derived from technology is the computer vision, which is the part of the technology that involves the application to the processes of farming. This chapter discusses diverse applications of this technology in relation to agriculture: crops health check, efficient farming, identification of weeds/pests, and intelligent picking. Data acquisition is explained in detail along with how the various real life problems that arise in the implementation of such technologies like image processing in different settings, subsequent addition of more functionalities to the exisiting system and the integration of the system with other systems are addressed. In addition, the Chapter presents one's suggestions on new trends and creations in terms of new horizons and advancements, including innovative methods, algorithms, or paradigms, for example, new computation methods, improved methods and approaches to data acquisition, or principles like edge computing or multisite platforms.

Brazil couples the world’s second-largest ethanol industry with a floating exchange rate, and sugarcane mills in the Centre-South region can reallocate crushing capacity between sugar and ethanol each season. This paper asks whether the exchange rate remains a useful hedging instrument for downstream fuel price risk in such an economy. Using monthly data from January 2006 through March 2026 (243 observations), we combine the Federal Reserve Board’s daily BRL/USD series with Brazil’s National Petroleum Agency (ANP) retail pump-price survey and sector production statistics from UNICA and the Ministry of Agriculture. We estimate static OLS hedge ratios by regime, a bivariate DCC–GARCH(1,1) model on log returns, and annual sugar-share allocation regressions at the safra level. Three findings stand out. First, the full-sample OLS hedge ratio is β = −0.091 (t = −1.11, R² = 0.006), statistically indistinguishable from zero. Second, the DCC-implied conditional correlation fluctuates in a narrow band around zero (mean −0.047, range [−0.23, +0.16]), and the dynamic hedging-effectiveness gain is economically trivial (0.5 percent variance reduction). Third, the sugar-share of cane at the mill gate shows only weak, statistically insignificant responses to BRL/USD and retail ethanol prices once cane volume is controlled. The retail ethanol market thus behaves as if it is largely insulated from short-run currency shocks, a pattern consistent with the 2011–2016 Petrobras administered-pricing regime and with the pricing smoothing that pump stations apply to wholesale cost movements. The results imply that policy and firm-level risk management should not rely on FX instruments to stabilise consumer-facing biofuel prices, and that welfare-relevant volatility management requires upstream tools — inventory buffers, stabilisation funds, or tax-based smoothing. The evidence also qualifies a widespread assumption in the biofuel policy literature that flex-fuel demand is the dominant transmission channel from world commodity markets to the Brazilian pump.