Food Efficiency Research Articles

QTL mapping and whole-genome sequencing analysis for novel genetic resources associated with sucrose content in soybean [Glycine max (L.) Merr.]

Key messageA major QTL for sucrose content was mapped on chromosome 8 in PI 506593. The novel genetic variants and candidate genes were further identified within the major QTL.Sucrose in soybean [Glycine max (L.) Merr.] contribute to animal feed efficiency and natural sweetness of soy products. Thus, identifying novel genetic resources, such as quantitative trait loci (QTL), associated with sucrose content in soybean is essential for enhancing seed values. In this study, two recombinant inbred line populations derived from the same high sucrose donor parent, PI 506593, were used to identify significant QTLs. A total of 11 sucrose-related regions on chromosomes (Chrs.) 4, 5, 6, 8, 10, and 13 were identified using QTL analysis. Among them, four QTLs (qSUC_08.1, qSUC_08.2, qSUC_08.3, and qSUC_08.4) were clustered in the interval of 40,597,410–42,861,364 bp on Chr. 8, which was considered major QTL region. A desirable marker at 41,834,095 bp was tested in two populations, showing that two phenotypically extreme groups were efficiently differentiated. We further identified 44 and 54 candidate genes with non-synonymous mutations in the major QTL region based on the annotations of Wm82.a2.v1 and Wm82.a5.v1 assemblies, respectively. Among 54 candidate genes from Wm82.a5.v1, Protein Variation Effect Analyzer (PROVEAN) revealed that 18 genes contained 34 variants that had deleterious impacts on biological functions. RNA-seq analysis highlighted five candidate genes that were highly expressed in pod and seed tissues during reproductive stages and other plant parts. A gene, Gm_Wm82_23219 (Glyma.08G293800, Wm82.a2.v1) encoding proline-rich protein 4-like, was highlighted in both PROVEAN and RNA-seq analyses. Novel findings in this study will be valuable genetic resources in soybean breeding programs that aim to improve efficiency in animal feed and human food.

Therapeutic Potential of Suaeda japonica Makino Leaf Extract Against Obesity in 3T3-L1 Preadipocytes and HFD-Induced C57BL/6J Mice.

The worldwide obesity prevalence is increasing, affecting around 4 million individuals annually. This research critically evaluated the anti-obesity efficacy of the Korean mudflat halophyte herb Suaeda japonica (Suaeda japonica Makino). In the obese mice model, the administration of 200mg/kg b.w. of S. japonica extract (SJE) significantly mitigated obesity by modulating body and organ weight, food efficiency ratio, energy expenditure, multiple blood chemistry parameters, lipid accumulation, adipose tissue hypertrophy, and various gene expressions associated with lipogenesis and thermogenesis. The significant obesity control (80%) of the aforementioned concentration of SJE treatment in mice mimics the plant-derived commercial anti-obesity drug Garcinia cambogia (Garcinia gummi-gutta) (80%, 245mg/kg) b.w. Since SJE has not been extensively studied for obesity management, this study demonstrated that it might influence physiological, biochemical, and molecular pathways to combat obesity and related metabolic illnesses.

Fecal shedding level of Haemonchus contortus is associated with gastrointestinal bacterial microbial composition in naturally infected sheep.

A complex interaction of gastrointestinal parasites with sheep hosts may involve bacteria communities, parasite genera, parasitic genes, and biological pathways. Haemonchus contortus presents a global challenge for ruminants, and the bacterial community can influence sheep's resistance and susceptibility to these parasites. Thus, a better understanding of this complex interaction could contribute to the development of a new approach to parasite control. This study evaluated the bacterial community of Corriedale sheep naturally infected with H. contortus based on the fecal egg counts over ten months and then classified as having low (LC), intermediate (IC), or high (HC). Stool samples were collected monthly for egg counts (EPG), and 16S rRNA gene sequencing was performed on five animals from each group. The average EPG was 2,635 ± 105 for HC, 845 ± 129 for IC, and 110 ± 70 for LC, with a significant difference (p = 0.0001). Firmicutes, Proteobacteria, and Spirochaetes were more abundant in the HC group. 102 bacterial genera showed significant differences between the LC and HC groups. Beta diversity was statistically different (p<0.005) for HC compared with the other two groups; also, different communities were found between LC and HC. Sediminispirochaeta, Oribacterium, Alloprevotella, Prevotellaceae_UCG-001, Prevotellaceae_UCG-003, Ruminiclostridium_6 and Ruminococcus_1were significant more abundant in LC, and IC group. Acetobacter and Methanocorpusculum had a significant reduction in the LC group. Thus, bacterial genera related to low methane emission and food efficiency were significantly present in the LC group. Therefore, a better understanding of the role of host-bacterial community-parasite interaction could contribute to improving parasite control management.

Modeling and optimization of energy efficiency and product quality in staple food roasting using machine learning: A case study on cassava processing

Modeling and optimization of energy efficiency and product quality in staple food roasting using machine learning: A case study on cassava processing

Implementing Advanced Analytics for Optimizing Food Supply Chain Logistics and Efficiency

The global food supply chain faces significant challenges in ensuring efficiency and minimizing disruptions, especially in the face of unexpected events, fluctuating demand, and logistical complexities. Implementing advanced analytics within food supply chains can transform operational dynamics, enabling precise prediction of potential disruptions and enhancing logistics efficiency. This study proposes a robust framework that leverages machine learning algorithms to forecast disruptions—such as delays in transport, shifts in consumer demand, or adverse weather conditions—and to optimize the logistics flow accordingly. By incorporating predictive modeling and real-time data analysis, this framework aims to enhance decision-making capabilities across various stages of the supply chain, from production and warehousing to transportation and delivery. The proposed framework utilizes a combination of supervised learning for demand forecasting and unsupervised learning for anomaly detection, enabling early identification of potential logistical challenges. Furthermore, integrating these analytics with real-time data sources, such as IoT sensors and satellite imagery, facilitates a comprehensive view of supply chain status, thereby increasing responsiveness and adaptability to unforeseen events. The potential future integration of this framework with autonomous delivery systems, such as drones or autonomous vehicles, could further streamline last-mile logistics, reducing both cost and delivery time while maintaining the quality and safety of perishable goods. This study not only demonstrates the immediate benefits of machine learning-driven predictive analytics but also discusses the scalability and flexibility of this approach for broader applications within global food systems. Future research can explore enhancements in algorithmic accuracy and integration with blockchain for traceability, supporting transparent, resilient, and highly efficient food supply chains. The integration of autonomous delivery systems will additionally be a key focus for ensuring seamless, reliable, and sustainable logistics operations in a rapidly evolving food industry landscape.

Intake of S-Methylmethionine Alters Glucose Metabolism and Hepatic Gene Expression in C57BL/6J High-Fat-Fed Mice.

A diet containing foods that are sources of S-methylmethionine (SMM), and its use as a dietary supplement, have demonstrated beneficial health effects. Thus, the objective of this work was to evaluate the inclusion of SMM as a dietary supplement in C57BL/6J high-fat-fed mice to verify whether this compound alone would be responsible for these positive effects. Mice were divided into three groups: LF (low-fat diet), HF (high-fat diet), and HF+SMM (high-fat diet plus SMM), and maintained for 10 weeks with water and food provided ad libitum. Body weight and food intake were measured weekly, and food efficiency was calculated. In addition, at week 9, fasting glucose was measured and, after necropsy, at week 10, liver, inguinal adipose, and kidney weights were measured; triglycerides, histology, liver gene expression, serum insulin, and MCP-1 levels were also determined. Final body weight, average weight gain, and the liver/body weight of the SMM group showed a significant difference with the LF group. HF+SMM-fed mice show improved regulation in glucose metabolism, demonstrated by the assessment of fasting glucose, insulin concentration, and HOMA-IR, compared with the HF-fed group. Liver triglycerides and MCP-1 levels showed no significant differences between fed groups. By the positive gene regulation of Sult1e1, Phlda1, and Ciart, we hypothesized that SMM administration to mice may have regulated xenobiotic, glucose, and circadian rhythm pathways.

Different effects of low- and high-density lipoproteins in egg yolk on lipid metabolism of mouse: Role of phospholipids-to-cholesterol intake ratio.

Recent evidence increasingly indicates that moderate egg consumption (up to one egg per day) poses no significant risk of cardiovascular diseases in healthy individuals, leading researchers to speculate whether other lipids in eggs affect lipid metabolism. In this research, C57BL/6J mice were given chow diets containing egg yolk low-density lipoprotein (LDL) and high-density lipoprotein (HDL), two natural components with different proportions of phospholipids and cholesterol, to explore the effects of the phospholipids-to-cholesterol intake ratio on lipid metabolism. Increases in liver weight and liver index were observed following LDL intake, while body weight and epididymal fat decreased after HDL intake in a dose-dependent manner. The food efficiency of chow diets decreased with increasing phospholipids content. Lipid biomarkers indicated that LDL intake significantly increased plasma LDL cholesterol and liver cholesterol levels. At equivalent cholesterol doses, the cholesterol-raising effects of HDL were weaker than those of LDL. Higher protein expression of cytochrome P450 family 7 subfamily A member 1 in the HDL groups suggested increased bile acid excretion at higher phospholipids-to-cholesterol intake ratios. Fecal metabolite analysis revealed significant changes in lipid composition, primarily involving glycerophospholipids, sphingolipids, and sterol lipids, consistent with the lipid profiles of LDL and HDL. The upregulation of cholic acid and deoxycholic acid in feces further confirmed increased bile acid excretion. This study highlights the differences in lipid metabolism in mice under varying phospholipids-to-cholesterol intake ratios, which may be associated with changes in dietary energy supply and bile excretion following phospholipids involvement.

Assessing nutritional efficiency of hospital food by the estimation of plate waste in a public hospital

Assessing nutritional efficiency of hospital food by the estimation of plate waste in a public hospital

Nutritional Composition and Effect of Loquat Fruit (Eriobotrya japonica L. var. Navela) on Lipid Metabolism and Liver Steatosis in High-Fat High-Sucrose Diet-Fed Mice.

Loquat (Eriobotrya japonica L.) is a popular fruit known for its sweet and slightly tangy flavor, which is widely consumed both fresh and in various processed forms. This study aimed to analyze the biochemical composition of loquat juice and investigate its metabolic benefits in mice fed a high-fat/high-sucrose diet (HFSD). Mice were fed either a standard diet or an HFSD and received or not the loquat juice at 4 or 8 mL/kg body weight for 8 weeks. Body weight, food efficiency ratio, plasma lipoprotein profile, plasma glucose, and lipid indices were monitored throughout the experiment. At the end of the experiment, additional assessments were performed, including lipid content measurements in liver, adipose tissue, bile, and feces; hepatic antioxidant enzyme activities (superoxide dismutase and catalase); hepatic malondialdehyde content; plasma biomarkers of liver injury; liver histology; and organ relative weight. Feeding mice with the HFSD resulted in a significant perturbation in lipid and glucose metabolism, obesity, liver steatosis, and oxidative stress-related enzymes. However, the concomitant administration of loquat juice significantly corrected this imbalance. Fresh loquat juice is low in fat and protein, moderately sugary, and energetically light; however, it is rich in minerals, vitamin C, and various phytochemicals compounds, such as phenolic acids, flavonoids, and carotenoids. The loquat juice could be considered a functional food and could be valorized through the extraction of active substances and their use as food supplements to prevent lipid metabolism disorders and the resulting health complications.

Liraglutide prevents body and fat mass gain in ovariectomized Wistar rats

Estrogens exert beneficial metabolic effects by reducing food intake and enhancing energy expenditure through both central and peripheral mechanisms. The decrease of estrogen, as occurs in ovariectomy (OVX), leads to metabolic disturbances, such as increased body weight, adipose tissue mass, basal blood glucose, and impaired glucose tolerance. These effects can be reversed by reintroducing estrogen. GLP-1 and its receptor agonists, known for their antihyperglycemic properties, also exhibit anorexigenic effects. Besides that, research indicates that GLP-1 analogs can induce metabolic changes peripherally, such as increased fatty acid oxidation and inhibited lipogenesis. Given the shared metabolic actions of GLP-1 and estrogens, we explored whether liraglutide, a GLP-1 agonist, could mitigate the metabolic effects of estrogen deficiency. We tested this hypothesis using ovariectomized rats, a model that simulates menopausal estrogen deficiency, and treated them with either liraglutide or 17β-Estradiol benzoate for 21 days. Ovariectomy resulted in elevated DPP-IV activity in both plasma and inguinal white adipose tissue (iWAT). While estrogen replacement effectively countered the DPP-IV increase in both plasma and iWAT, liraglutide only prevented the rise in iWAT DPP-IV activity. Liraglutide prevented body weight and fat mass gain after ovariectomy to the same extent as estradiol treatment. This can be explained by the lower food intake and food efficiency caused by estradiol and liraglutide. However, liraglutide was associated with increased pro-inflammatory cytokines and inflammatory cells in white adipose tissue. Further research is crucial to fully understand the potential benefits and risks of using GLP-1 receptor agonists in the context of menopause.

Migration patterns of organophosphate esters from plastic food packaging simulants to foods: Donors, behaviours, and influencing factors

In recent years, organophosphate esters (OPEs) have been widely produced and used as flame retardants and plasticizer additives, posing significant ecological and health risks. Dietary intake is considered to be the primary route of human exposure to OPEs. Plastic food packaging materials are considered a crucial source for contamination of OPEs in food. However, the migration behaviour of OPEs from plastic food packaging materials into foods has received limited attention. In this study, we employed a novel method to prepare migration donors containing 13 kinds of OPEs. The migration behaviours of OPEs from food packaging simulants (polypropylene) to foods (full-fat milk powder) were simulated, and factors influencing the migration of OPEs were examined, including the properties of the target compounds, migration temperature, fat content of the migration receptors, and mass transfer mode. The results indicated that OPEs exhibited a significant migration tendency. Low molecular weight OPEs (< 300 Da) had faster migration efficiency compared to high molecular weight OPEs. The mean migration efficiencies of various OPEs showed a significant negative correlation with their molecular weights (p < 0.01) and a significant positive correlation with temperature (p < 0.01). Except for resorcinol bis(diphenyl phosphate) (RDP), which showed almost no migration, the mean migration efficiencies of other OPEs at 25 °C, 40 °C, and 60 °C were 3.1–37.5 %, 9.0–60.0 %, and 23.9–80.4 %, respectively. Most of the OPEs demonstrated higher migration efficiency in high-fat content food than low-fat content food. The migration of OPEs from food packaging simulants to foods primarily occurred through contact rather than gas-phase mass transfer. Overall, this study uncovers the migration behaviours of OPEs from food packaging simulants to foods and scrutinized the relevant factors influencing the migration. It is expected that the research in terms of the contamination control of OPEs in food will benefit from this work.

System Design, Modelling, Energy Analysis, and Industrial Applications of Ohmic Heating Technology

AbstractThe food and drink industry is gradually gaining sustainability pressure due to the high carbon emissions rate and limited availability of traditional energy supplies. Thus, it is essential to consider energy efficiency and decarbonisation of the ever-expanding food and drink industry. Ohmic heating technology is a highly energy-efficient and quick method of electrically heating food products. It uses the resistance of the food material to convert electrical energy into heat. However, the heating rate of ohmic heating depends on several process variables, such as electrical conductivity, voltage gradient, and voltage frequency. Therefore, it is important to study and understand the effects of these process variables to optimise the modelling and control of ohmic heating systems to obtain desirable output from food products. Hence, this study presents a review of the effects of process parameters on nutritional and organoleptic qualities, product yields, and energy efficiency of ohmic heating, along with its various industrial applications. The technology shows promising advancements in colour and nutritional quality, increasing energy efficiency, shorter processing times, and higher product yields compared to conventional heating processes.

Supplementation with Fish Oil and Selenium Protects Lipolytic and Thermogenic Depletion of Adipose in Cachectic Mice Treated with an EGFR Inhibitor.

Lung cancer and cachexia are the leading causes of cancer-related deaths worldwide. Cachexia is manifested by weight loss and white adipose tissue (WAT) atrophy. Limited nutritional supplements are conducive to lung cancer patients, whereas the underlying mechanisms are poorly understood. In this study, we used a murine cancer cachexia model to investigate the effects of a nutritional formula (NuF) rich in fish oil and selenium yeast as an adjuvant to enhance the drug efficacy of an EGFR inhibitor (Tarceva). In contrast to the healthy control, tumor-bearing mice exhibited severe cachexia symptoms, including tissue wasting, hypoalbuminemia, and a lower food efficiency ratio. Experimentally, Tarceva reduced pEGFR and HIF-1α expression. NuF decreased the expression of pEGFR and HIF-2α, suggesting that Tarceva and NuF act differently in prohibiting tumor growth and subsequent metastasis. NuF blocked LLC tumor-induced PTHrP and expression of thermogenic factor UCP1 and lipolytic enzymes (ATGL and HSL) in WAT. NuF attenuated tumor progression, inhibited PTHrP-induced adipose tissue browning, and maintained adipose tissue integrity by modulating heat shock protein (HSP) 72. Added together, Tarceva in synergy with NuF favorably improves cancer cachexia as well as drug efficacy.

Blunted food conditioned place preference-like behavior in adolescent-stressed male hamsters

Social stress during adolescence results in long lasting weight gain, obesity, and enhanced food hoarding behavior in hamsters. We wanted to determine whether stress also enhanced conditioned place preference-like behavior (CPP-like) for food reward, as would be expected from studies with substances like cocaine. Our experimental animals were exposed daily to aggressive adults for two weeks in early puberty, while also trained to explore a V-shaped maze containing a food reward at one end. They were tested for CPP-like behavior on the last day of social stress. Our results showed that while stress enhanced weight gain, food intake, food efficiency, and body fat, it caused a reduction of Place Preference as compared to controls. In fact, the correlated relationship between Place Preference and body fat was inverted by stress exposure: while it was positively correlated in controls, it was mildly negatively correlated in stressed hamsters. These unexpected data illustrate the extent of adaptive behavior in foraging animals once a resource has become untrustworthy.

The paradoxes of the protein transition maintain existing animal production and consumption systems.

The shift towards reduced consumption of animal-based products, referred to as the protein transition, is increasingly viewed as an opportunity to drive sustainable food systems transformations. Here we explore three central paradoxes of the protein transition. The first underscores the focus on substituting animal proteins with alternative sources, rather than reducing overall protein consumption. The second focuses on the search for new protein sources, rather than tackling overconsumption and overproduction. The third involves the continued export of animal proteins from Europe, a practice defended under the guise of food security, efficiency and comparative advantage. These narratives dominate public discourse, justifying existing production and consumption patterns, shaping perceptions and influencing decisions and policies that impact the future direction of our food systems. Given the influence of stakeholders' narratives in the transition, we advocate for a holistic and systemic perspective that transcends isolated and quick-fix solutions to foster coherent strategies to advance the protein transition.

Optimizing Food &amp; Baverage Company Performance Through Governance and Social Responsibility: Random Effect Model Approach

The purpose of this study is to improve the efficiency of food and beverage companies listed on the Indonesia Stock Exchange by implementing GCG &amp; CSR principles. Using panel data from 95 companies covering the period 2018-2022 and using the Random Effects model, the regression analysis shows that the Board of Commissioners has no statistically significant effect on company performance. In contrast, the Audit Committee shows a significant and beneficial impact. The novelty of this study emphasizes the complex nature of the interaction between GCG parameters, CSR, and business success in the food and beverage industry. Practical suggestions include increasing the authority of the Audit Committee to improve performance and applying CSR more contextually to reduce the impact of the Board of Commissioners. The contribution of this research is a valuable understanding of the interaction between governance dynamics and CSR in the context of strategic decision-making.

Maternal genetics and diet modulate vitamin A homeostasis of the offspring and affect the susceptibility to obesity in adulthood in mice.

Perinatal nutrition exerts a profound influence on adult metabolic health. This study aimed to investigate whether increased maternal vitamin A (VA) supply can lead to beneficial metabolic phenotypes in the offspring. The researchers utilized mice deficient in the intestine-specific homeobox (ISX) transcription factor, which exhibits increased intestinal VA retinoid production from dietary β-carotene (BC). ISX-deficient dams were fed a VA-sufficient or a BC-enriched diet during the last week of gestation and the whole lactation period. Total retinol levels in milk and weanling livers were 2- to 2.5-fold higher in the offspring of BC-fed dams (BC offspring), indicating increased VA supplies during late gestation and lactation. The corresponding VA-sufficient and BC offspring (males and females) were compared at weaning and adulthood after being fed either a standard or high-fat diet (HFD) with regular VA content for 13 weeks from weaning. HFD-induced increases in adiposity metrics, such as fat depot mass and adipocyte diameter, were more pronounced in males than females and were attenuated or suppressed in the BC offspring. Notably, the BC offspring were protected from HFD-induced increases in circulating triacylglycerol levels and hepatic steatosis. These protective effects were associated with reduced food efficiency, enhanced capacity for thermogenesis and mitochondrial oxidative metabolism in adipose tissues, and increased adipocyte hyperplasia rather than hypertrophy in the BC offspring. In conclusion, maternal VA nutrition influenced by genetics may confer metabolic benefits to the offspring, with mild increases in late gestation and lactation protecting against obesity and metabolic dysregulation in adulthood.NEW & NOTEWORTHY A genetic mouse model, deficient in intestine-specific homeobox (ISX) transcription factor, is used to show that a mildly increased maternal vitamin A supply from β-carotene feeding during late gestation and lactation programs energy and lipid metabolism in tissues and protects the offspring from diet-induced hypertrophic obesity and hepatic steatosis. This knowledge may have implications for human populations where polymorphisms in ISX and ISX target genes involved in vitamin A homeostasis are prevalent.

Enhancing efficiency and Personalization in Food and Beverage Service through AI: Future Trends and Challenges

Artificial Intelligence (AI) is increasingly revolutionizing the food and beverage service industry by offering innovative solutions to enhance operational efficiency and personalize customer experiences. This abstract explores the transformative impact of AI technologies such as machine learning, predictive analytics, and robotics on various aspects of hospitality operations. AI-driven automation streamlines kitchen processes, optimizes inventory management, and reduces operational costs, thereby improving service consistency and profitability (Alsmadi et al., 2020; Li et al., 2021).AI facilitates personalized client interactions by analyzing vast datasets to understand individual preferences, dietary restrictions, and purchasing behaviors. This capability empowers establishments to offer tailored menu recommendations, personalized promotions, and interactive dining experiences that cater to diverse consumer needs (Chen et al., 2019; Huang et al., 2020). AI's integration into the food and beverage service industry significantly enhances customer satisfaction and loyalty while concurrently boosting revenue through targeted marketing and operational efficiencies. By leveraging AI technologies such as machine learning and predictive analytics, establishments can tailor offerings to meet individual preferences and anticipate consumer behavior, thereby fostering stronger customer relationships. Moreover, the future trajectory of AI in this sector foresees advancements in IoT integration, AR applications, and blockchain technology. These innovations are set to further transform operations by optimizing efficiency, enriching customer interactions, and ensuring robust supply chain transparency. IoT devices, for instance, will facilitate real-time data collection and analysis, thereby enhancing inventory management precision and optimizing resource allocation to meet demand fluctuations effectively. AR applications will offer immersive dining experiences, allowing customers to interact with digital menus or view culinary presentations. Blockchain technology will enhance transparency and traceability, ensuring food safety and compliance with regulatory standards. Together, these innovations will enable food and beverage establishments to innovate and differentiate themselves in a competitive market landscape, ultimately shaping the future of dining experiences worldwide to further optimize operations and enhance transparency in supply chain management (Jiang et al., 2023; Wang et al., 2023).

Two-year carcinogenicity study of a novel plasticizer, bis(2-ethylhexyl) cyclohexane-1,4-dicarboxylate (Eco-DEHCH), by oral diet in Han Wistar rats

Plasticizers are necessary for the usability of various products, including food contact materials. Exposure to plasticizers is most commonly made through the oral route. Several plasticizers have been reported to have adverse effects on humans and the environment. Thus, the present study aimed to determine the long-term toxicity and carcinogenicity of a novel plasticizer called bis(2-ethylhexyl) cyclohexane-1,4-dicarboxylate (Eco-DEHCH), which is an ecofriendly and biologically less harmful replacer. Groups of 50 male and 50 female Han Wistar rats were fed Eco-DEHCH at daily doses of 1,600, 5,000, or 16,000 ppm in their diet for at least 104 weeks. The rats were regularly monitored for mortality, clinical signs, body weight, food consumption, food efficiency, and perceivable mass. All animals were subjected to complete necropsy and histopathological examination. The results indicate that the rats well tolerated chronic exposure to Eco-DEHCH at highest daily doses of 16,000 ppm, with was equivalent to 805.1 mg/kg/day in males and 1060.6 mg/kg/day in females and did not show signs of toxicity or carcinogenicity. In conclusion, Eco-DEHCH could be a safe and promising alternative plasticizer.

BLOCKCHAIN IN AGRICULTURE: TRANSFORMING THE FOOD SUPPLY CHAIN FOR TRANSPARENCY AND EFFICIENCY IN THE EUROPEAN UNION

This paper explores the transformative role of blockchain technology in the European Union’s agriculture sector, focusing on the “Farm to Fork” concept. Employing a literature review, the paper examines the applications of blockchain within EU agriculture and its alignment with the EU’s emphasis on food supply chain transparency and efficiency. Several illustrative cases of blockchain implementation in the EU, such as the IBM Food Trust platform, are highlighted. The research underscores how blockchain enhances traceability, trust, and sustainability, thereby strengthening food safety and quality. The paper concludes that blockchain is catalysing a revolution in the EU’s food supply chain, fostering transparency and efficiency while aligning with the overarching objectives of the “Farm to Fork” concept.