Food Supply Research Articles

Coupling effect of landscape patterns on the spatial and temporal distribution of ecosystem services: a case study in Harbin City, Northeast China

To secure the enduring the long-term growth of ecosystem services, the city of Harbin in northeastern China must prioritize the optimization of its landscape pattern. However, there is a dearth of studies pertaining to the geospatial repercussions of landscape patterns on ecosystem services. This study examined the properties of spatio-temporal evolution of Harbin’s landscape patterns from 2000 to 2020 and six essential ecosystem services: food supply, water yield, soil conservation, carbon storage, water purification, and habitat quality. It used the geographical detector (GD) to reveal the effects of landscape pattern changes on ecosystem services and the geographically weighted regression (GWR) model to map ecosystem services’ responses to changes in landscape pattern heterogeneity. The results showed that from 2000 to 2020, the landscape types in Harbin tended to become richer, the spatial heterogeneity increased, and the degree of fragmentation decreased significantly. Water yield continued to increase, habitat quality slightly improved, soil conservation and carbon storage initially decreased and then increased, and water purification and food supply first increased and then decreased. Landscape pattern evolution had a substantial impact on ecosystem services. Landscape composition had a greater influence on ecosystem services than did landscape configuration in Harbin City, with the proportion of agricultural land, the proportion of woodland, the largest patch index, and the aggregation index having a greater effect on ecosystem services. A significant challenge in territorial spatial planning is how to develop distinct ecosystem services in a balanced fashion, because in the majority of cases, the effects of landscape patterns on individual services are different or even opposing. To optimize local landscape patterns and develop total ecosystem services in a balanced manner, policymakers can use the study’s results, which emphasize the complex response of ecosystem services to changes in landscape patterns, to develop more accurate spatial planning strategies and plans.

Monosodium glutamate: A hidden risk factor for obesity?

Monosodium glutamate (MSG) has become one of the most widely used food additives in the global food supply. Although it has been classified for decades as a food ingredient that is generally recognized as safe, concerns about the health impacts of chronic MSG use, especially its potential effect on weight, are still ongoing. This comprehensive review summarizes the available human and animal evidence, highlighting potential mechanisms linking MSG use to weight gain or obesity, and discusses challenges and future research directions. Because of MSG intake worldwide as well as hidden MSG in food labeling, there is a pressing need for a mechanistic understanding of the health impacts of MSG use especially on weight. To generate robust scientific evidence and to clarify public concerns, rigorous mechanistic studies and randomized controlled clinical trials are warranted.

Rice yield predictions using remote sensing and machine learning algorithms: A review

Crop yield prediction is becoming increasingly crucial due to global food security concerns, as highlighted by recent reports from the World Health Organization. Accurate early predictions can mitigate famine risks by estimating food supply, which is essential for 820 million people facing hunger globally. Rice is the primary staple food consumed worldwide; therefore, global rice yield and rice area are monitored using emerging technologies such as remote sensing (RS) and machine learning (ML). These technologies provide valuable tools for enhancing rice yield predictions. RS includes critical information on crop health, soil conditions and weather patterns. In contrast, ML algorithms analyze these datasets to identify patterns and relationships that affect yield. Integrating these technologies offers promising improvements in yield forecasting accuracy, with applications showing successful yield predictions 1-3 months before harvest. Various ML techniques, including Random Forest, Support Vector Machines and deep learning models such as LSTM (Long-Short Term Memory), have been employed, often in combination with RS data. However, these models face challenges, such as data quality, managing high-dimensional RS data and accounting for spatial and temporal variability. Despite these challenges, integrating RS and ML has significant potential for advancing precision agriculture and achieving sustainable food production. This study explores the advancements, practical applications and challenges associated with using RS and ML for rice yield prediction, emphasizing the importance of these technologies in addressing global food security and promoting sustainable agricultural practices.

Estimating energy consumption and GHG emissions in the U.S. food supply chain for net-zero

This work provides a database of the U.S. food system’s energy consumption and GHG emissions at the national and state levels by food supply chain (FSC) stage, fuel type, and food commodity. We estimate that the U.S. FSC consumed a total 4660 TBTU (4900 PJ) of site energy, 7130 TBTU (7500 PJ) of primary energy, and generated 970 MMT of GHG emissions in 2016. Among all the stages, on-farm production is the largest energy consumer (31% primary energy) and GHG emissions contributor (70%), largely due to raising animals. Optimizing distribution can reduce the stage’s energy consumption and GHG emissions and increase products’ shelf-life. Reducing food loss and waste is another good option, as it decreases the amount of food necessary to grow, thus impacting the overall FSC. The database can help stakeholders identify stage- and region-specific strategies and measures to curtail the environmental footprint of the U.S. food system.

ДИНАМИКА РАЗВИТИЯ ОТРАСЛИ СКОТОВОДСТВА В РЕСПУБЛИКЕ ХАКАСИЯ

The purpose of research is to study the dynamics of development and the current state of the cattle breeding industry in the Republic of Khakassia to provide the population with milk and meat of their own production. The results of monitoring the number of cattle, gross production of meat and milk, average milk yield per cow per year, meat and milk production per capita in the region are presented. Research was carried out in 2000–2021, the data studied is presented by categories of farms of various forms of ownership. It is noted that cattle breeding is one of the leading livestock sectors in the region. Over the past twenty years, the total number of cattle has increased by 37.1 thousand heads (27.6 %), including cows by 9.7 thousand (15.5 %), gross beef production by 0.8 thousand tons (8.4 %), milk by 6.4 thousand tons (5.2 %). Agricultural organizations currently account for only 11.7 % of beef and 19.7% of milk from their gross production. The average milk yield per cow increased by 1.8 times and amounted to 3637 kg of milk per year, including in agricultural organizations it increased by 3.3 times and amounted to 4431 kg. Milk production per capita in Khakassia in 2021 amounted to 246.3 kg, beef – 19.4 kg, the region's supply of own-produced milk was 75.8 %, beef – 97.0 %. The region has the necessary resources for the development of the industry: the presence of agricultural land of 1911.9 thousand hectares, including 826.4 thousand hectares of pastures, types of beef cattle have been created (Sonsky, Andrianovsky) adapted to local feeding and climatic conditions. An increase in milk and meat production must be achieved through an increase in the number of cattle in agricultural organizations and peasant (farm) farms, improvement of existing breeds and types, strengthening the food supply and a scientific approach to feeding and keeping animals.

Long-term Effect of Tillage, Residue and Biofertilizer on Soil Microbial Biomass Carbon and Dehydrogenase Activity under Rice-wheat Cropping System in Terai Agro-ecological Region of West Bengal

As a major supply of staple foods, the rice-wheat cropping system is crucial to global food security. However, continuous cultivation of these crops has led to several soil-related environmental problems, including the gradual decline in soil health and quality. In this context, maintaining soil health necessitates the adoption of conservation agriculture. This study assessed the effect of tillage, residue and biofertilizer management practices on soil dehydrogenase activity (SDHA) and soil microbial biomass carbon (SMBC) of post wheat soils at various soil depth (0-5 cm, 5-10 cm, 10-20 cm and 20-40 cm). The research was conducted as part of a long-term field experiment initiated in 2006 in rice-wheat cropping system under a factorial randomized block design with three replications in the Terai agro-ecological regions of West Bengal. The results revealed that the SDHA and SMBC were increased by the influence of long-term zero tillage, bio fertilizer & residue addition at the most of the soils depths under study except at 20-40 cm. The highest short-term change of SDHA (213.19%) in compared to the initial soil status was observed in conventionally tilled soil with biofertilizer addition treatment combination. Since SDHA and SMBC are critical indicators of soil health and quality, this study also explored their relationship. Positive good regression coefficient of 0.74, 0.65 and 0.67 at 0-5 cm, 5-10 cm and 10-20 cm soil depth were observed respectively. These findings highlight the strong association between the two parameters. With growing future demand of foods, conservation agriculture must be practiced to ensure the long-term sustainability of soil productivity. The study provides evidence that implementing zero tillage along with residue and biofertilizer addition significantly improves these key soil health parameters.

Effect of Processing Methods on the Micronutrient Profile, Colour, and Anti-nutritive Components of Justicia heterocarpa (mwidu)

Justicia heterocarpa (mwidu) is a popular indigenous leafy vegetable picked wild in rural regions of Morogoro, Tanzania, during the wet seasons. This research examined the impact of processing on micronutrients, total phenols, and anti-nutrient content. The fresh leaves (FL) underwent direct shade drying (UBLDDR), blanched shade drying (BLDR), blanched oven drying (BLDO), fermentation (FFL), and gas and microwave cooking (FLCO5, FLCO10, and FLMCO2). Vitamins, chlorophyll, minerals, phenolic compounds, and anti-nutrients were analyzed. All laboratory experiments adhered to procedures and guidelines. The pH dropped more significantly to <3.5 in a 3% salt-3% sugar brine solution with 1.328 ± 0.006 mg/100 g of lactic acid compared to its counterpart. Blanched leaves dried in 5 days, but unblanched leaves took 15 days. Fermented samples demonstrated a notable reduction in total chlorophyll concentration (0.0964 ± 0.075 mg/g) compared to other processing techniques. The nutritional and anti-nutritional composition of Justicia heterocarpa showed significant change (P < 0.05) depending on processing methods. The results indicated a significant loss of vitamin C in the fermented and ten-minute cooked samples, at 74.57% and 61.64%, respectively.Cooked FLMCO2 (107.4%, 11.29 ± 0.03 mg/100g) and FLCO5 (86.26%, 10.51 ± 0.02 mg/100g) exhibited more than a two-fold increase in beta-carotene compared to fresh leaves (3.67 mg/100g). In comparison to alternative processing procedures, samples cooked for 10 minutes exhibited significant mineral leaching, whereas unblanched direct shade drying preserved the highest mineral concentration. Fermented samples (532.83 ± 14.91 GAE/100 g) exhibited a 64.19% increase in total Phenolic compounds compared to fresh leaves (190.83 ± 14.91 GAE/100 g). Nonetheless, tannins increased by 68.1% (254.44 ± 7.45 GAE/100g) in the fermented samples. Samples exposed to extended cooking (17.8 ± 3.17 mg/100 g) and fermentation (40.28 ± 3.34 mg/100 g) exhibited the lowest levels of phytates. The oxalate concentration was significantly decreased in the cooked samples. Justicia heterocarpa may serve as a sustainable food supply in areas of Tanzania experiencing nutritional deficits.

Climate-based measures of supply chain resilience

PurposeSupply chains are a complex but integral part of the food distribution system with unique vulnerabilities, as agricultural production is a function of biological processes and food goods are perishable necessities. Various shocks, including pandemics, geopolitical conflicts and extreme weather events, can cause disruptions to the food supply chain. International trade often plays an adaptive role in mitigating the effects of these shocks as it allows for a market-oriented redistribution of resources that can mitigate the impacts of localized shortages and surpluses.Design/methodology/approachWith this in mind, our goal is to combine information on weather shocks and trade flows to propose novel supply chain resilience metrics focusing on key weather drivers in over 50 countries. We focus on the role of extreme heat (degree days above 29°C) for maize, soybeans and rice, but the approach is general enough to be widely applied to any combination of crops, trade partners and weather/climate variables.FindingsWe focus on the role of extreme heat (degree days above 29°C) for maize, soybeans and rice, but the approach is general enough to be widely applied to any combination of crops and weather/climate variables. Leveraging globally gridded temperature data, we estimate the metrics for the United States and find a heterogeneous range of resilience across crops and risk dimensions. In addition, we provide a detailed look at the spatial correlations with the US and its historical trade partners and find evidence that these metrics could (potentially) be enhanced via strategic trade relationships.Research limitations/implicationsLeveraging globally gridded temperature data, we estimate the metrics for the United States of America and China to demonstrate differences that might arise from a net-exporter versus net-importer perspective. Our results suggest that these metrics can be useful for disentangling the resilience a country faces between its own internal supply chain versus its participation in other countries’ supply chains.Practical implicationsSince these metrics are a combination of exogenous spatial correlations of weather shocks and endogenous trade patterns, we also discuss how they can be adjusted via strategic trade relationships to enhance resiliency.Originality/valueOur results provide pertinent insights to US policymakers promoting export expansion under climate change (USDA FAS, 2024). Moreover, the metrics provided here are focused on climate resiliency and thus could be an important component of strategic trade decisions given the recent concerns between the US and Mexico centered around GM maize (Beckman et al., 2024) and the seemingly improving US–India agricultural trade relationship.

Food supply chain disruptions and its resilience: a framework and review for resilience strategies in the digital era

Food supply chain disruptions and its resilience: a framework and review for resilience strategies in the digital era

Rational Redomestication for Future Agriculture.

Modern agricultural practices rely on high-input, intensive cultivation of a few crop varieties with limited diversity, increasing the vulnerability of our agricultural systems to biotic and abiotic stresses and the effects of climate changes. This necessitates a paradigm shift toward a more sustainable agricultural model to ensure a stable and dependable food supply for the burgeoning global population. Leveraging knowledge from crop biology, genetics, and genomics, alongside state-of-the-art biotechnologies, rational redomestication has emerged as a targeted and knowledge-driven approach to crop innovation. This strategy aims to broaden the range of species available for agriculture, restore lost genetic diversity, and further improve existing domesticated crops. We summarize how diverse plants can be exploited in rational redomestication endeavors, including wild species, underutilized plants, and domesticated crops. Equipped with rational redomestication approaches, we propose different strategies to empower the fast and slow breeding systems distinguished by plant reproduction systems.

Beyond Compliance: Leveraging Regulatory Compliance to Drive Innovation in Food Supply Chain Traceability

Purpose: The Food Safety Modernization Act (FSMA) 204, effective January 2026, represents a transformative shift in global food supply chain management, emphasizing proactive over reactive traceability. This research investigates FSMA 204's regulatory framework, associated challenges, and its potential to drive innovation. Methodology: Through qualitative analysis and case studies of Trustwell and Campbell Soup Company, the study identifies the dual role of FSMA 204 as both a compliance mandate and a catalyst for operational advancements. Key challenges include high compliance costs, technological integration barriers, and limited timelines. However, the regulation incentivizes the adoption of advanced technologies such as blockchain for secure record-keeping, IoT for real-time monitoring, and AI/ML for predictive analytics, which collectively enhance transparency, efficiency, and competitive differentiation. These innovations turn regulatory obligations into opportunities for businesses to optimize supply chain processes, improve consumer trust, and achieve sustainability. Case studies demonstrate how strategic planning and the use of traceability technologies enable compliance while promoting ESG goals. Findings: The findings underscore the importance of proactive strategies and technological investments to navigate FSMA 204's requirements effectively. Unique Contribution to Theory, Policy and Practice: This research contributes to the discourse by framing FSMA 204 compliance as a strategic enabler for businesses to foster growth and sustainability, positioning it as a global benchmark for traceability standards. By leveraging these insights, food industry stakeholders can transform compliance challenges into pathways for innovation and resilience.

Ranking of Autonomous Technologies for Sustainable Logistics Activities in the Confectionery Industry

The food supply chain (FSC) faces significant challenges, including the short shelf life of products, stringent food safety standards, and the growing demand for online ordering. These challenges underscore the need for a resilient and sustainable FSC, particularly in the confectionery industry, which is further burdened by the demand for innovative and healthier products. The aim of this paper is to optimize material handling activities in warehouse operations within the confectionery industry by ranking and selecting adequate material handling equipment (MHE). This paper proposes a novel hybrid multi-criteria decision-making model that integrates the Simple Aggregation of Preferences Expressed by Ordinal Vectors Group Decision Making (SAPEVO-M), Fuzzy Analytic Hierarchy Process (FAHP), and Fuzzy COmprehensive distance-Based Ranking (FCOBRA) methods. The model was applied to a real-world case study involving four alternative solutions and twelve defined evaluation criteria. The application of the model identified the implementation of an Automated Guided Vehicle system (AGVs) as the optimal alternative, offering substantial automation of logistics activities and addressing identified company challenges. The engagement of AGVs is estimated to reduce operational costs by 20%, improve warehouse operation efficiency by 30%, and decrease CO2 emissions by 25%. The contribution of this paper lies in the development of a methodological framework for evaluating and selecting MHE, as well as in highlighting the importance of optimizing material handling processes in the confectionery industry.

Food loss and waste reduction by using industry 4.0 technologies: examples of promising strategies

Abstract Food loss and waste represent a significant global issue, posing a threat to food sustainability on a worldwide scale. Approximately one-third of the food produced for human consumption is wasted, resulting in substantial environmental impact and economic loss. However, the growing awareness among consumers and the development of emerging technologies driven by the 4th Industrial Revolution (Industry 4.0) present numerous opportunities to reduce food loss and waste. This article provides a comprehensive examination of recently developed strategies for reducing food loss and waste. The role of Industry 4.0 technologies, such as the Internet of Things, artificial intelligence, cloud computing, blockchain, and big data, is highlighted through examples of various promising initiatives. The results of this analysis show that the application of digital technologies to address the issue of food loss and waste is on the rise globally, with Industry 4.0 technologies revolutionizing many sectors, including the food sector. This article could assist scholars and industry leaders in comprehending the urgency and significance of implementing Industry 4.0 in the food sector. Further research is necessary, and closer collaboration between producers, distributors, consumers, and other actors involved in the food supply chain is still required to reduce food loss and waste further.

Paleoenvironmental and sea level changes across the Paleocene-lower Eocene interval at the central and southwestern Sinai, Egypt

Detailed stratigraphic studies of the Paleocene-lower Eocene interval were conducted on four stratigraphic successions (Sudr-Alhitan, Thamad, Abu-Qada, and Nukhul) in central and southwestern Sinai. These sections are arranged along a North-South direction as: Sudr-Alhitan, Thamad, Abu-Qada, and Nukhul. The biostratigraphic framework was achieved by integrating data of calcareous nannofossils and planktonic foraminifera. The studied area experienced two major tectonic events, most likely related to the Syrian Arc System (SAS), which led to two distinct hiatuses of significant magnitude, evidenced from integrated biostratigraphic analysis and thorough field observations. Benthic foraminifera assemblages suggest a deposition in outer neritic to upper bathyal setting for investigated sites, except for the Tarawan and Thebes formations in Abu-Qada and Sudr-Alhitan sections, which were deposited in middle-outer neritic and outer neritic settings, respectively. Benthic foraminiferal indices indicate an oligo-mesotrophic environment associated with oxic/suboxic conditions at the bottom of the seawater for the studied interval. Low oxygen levels and mesotrophic conditions were seen to mark the Paleocene Eocene Thermal Maximum event, as evidenced by the organic-rich laminated sediment, low benthic foraminiferal indices, and the occurrence of agglutinated taxa Repmanina charoides and Ammobaculites spp., which reflects a major change in food supply. The obtained sequence stratigraphic framework shows that the depositional record of the studied area is significantly influenced by both the regional tectonics and eustatic sea level.

Food Availability, Accessibility, and Affordability through the Scope of Food Security Level and Food Environment Perception in Mexico City’s Marginated Area

Background: Food availability, accessibility, utilization, and stability, the four pillars of food security, have sound impact on food environment activities, regarding households’ food availability, accessibility, and affordability. Food availability implies the adequate supply of healthy food and food accessibility complements and builds on food availability by ensuring that households are able to obtain that food, and that food affordability is limited by incomes and food prices. Methods: In this research, socioeconomic characteristics, food security status and food environment (food availability, accessibility, and affordability) perception of households in Ecatepec, México, a marginal Mexico City conurbation area, were determined with the adequate survey. The collected data were analyzed by logistic regression to stablish the significant relationship among the independent variables (household food security status) with the socioeconomic features, in addition to food environment perception, in order to determinate which facts were significant with food security in this marginal area. Results: Educational level (P<0.001), household income (P<0.001), and belonging to a social assistance program (P<0.001) have a significant effect on food security status. Households with lower income, with food insecurity status, presented lower purchasing power. In contrast, households with food security and mild food insecurity were less likely to agree with the food that they can purchase. A better income, and therefore, a higher purchasing power was reflected in the need to access to more healthy food within their neighborhood. Conclusion: Results indicate that the food environment in this marginal area is benevolent, and households find a way to remain resilient in order to provide enough food for their families. Public policies must be focused on reducing poverty and giving more opportunities to promote social mobility

Highly sensitive smart chitosan/zein film cross-linked with Fe2+ chelated red radish anthocyanins nanoparticles for mushroom freshness monitoring.

Fe2+-loaded red radish anthocyanin (RRA) and zein composite nanoparticles (FZNPs) were firstly prepared to enhance the color and stability of RRA. The addition of Fe2+ caused anthocyanin to form color chelates, enhancing its pH color sensitivity. The prepared FZNPs showed good stability and anthocyanin retention during long-term storage. The obtained FZNPs are further loaded onto chitosan/zein (C/Z) film, resulting in a highly sensitive smart film capable of detecting changes in pH. When these FZNPs were incorporated into C/Z films, the mechanical properties of the films were improved (12.1 to 16.1MPa) and the swelling degree of the films was reduced (422% to 67%). The addition of FZNPs also enhanced the hydrophobicity and thermal stability of smart films. The smart film showed visible color changes in response to pH variations and acetic acid gas. As the mushroom deteriorated, the color change of smart films provided a clear indicator of quality loss. Smartphone-based color identification and a WeChat mini program were further successfully utilized for rapid freshness analysis. This system provided a rapid, reliable method for evaluating food quality, with potential applications in food monitoring and supply chain management.

Quantum of trust: Overview of blockchain technology for product authentication in food and pharmaceutical supply chains

Quantum of trust: Overview of blockchain technology for product authentication in food and pharmaceutical supply chains

Sustainable Solutions for Ukrainian Grain Transit Through Poland: Enhancing Terminal Infrastructure

The ongoing conflict in Ukraine has significantly disrupted global food supply chains, exacerbating existing food security challenges. To mitigate these disruptions, this study proposes a comprehensive approach to establishing sustainable intermodal terminals and technology parks along the Ukrainian–Polish border. To address this research issue, we analyzed the Ukrainian and global grain markets using publicly available statistical data. This analysis revealed the need to enhance grain transit through Poland, with terminal development identified as a crucial factor. Furthermore, a thorough analysis of the Polish freight rail transport market provided forecasts of potential demand for rail transit. Utilizing Petri nets as a modeling tool, we simulated the transit system at the macro level. Based on this simulation, we identified potential locations for freight terminals at the Ukrainian border near EU countries. Employing the AHP methodology, we evaluated these potential locations and selected Kovel in the Volyn region of Ukraine as the most promising alternative. For this location, we proposed the development of a new technological park. The implementation of this project, with the capacity to process and clear up to 600 wagons per day, would facilitate the transshipment of up to 3000 tons of grain per day from Ukraine to EU countries.

An Optimized Hybrid Model for Perishable Product Quality Inference in the Food Supply Chain

The supply chain for perishable products faces significant challenges in monitoring and maintaining product quality. These products are particularly vulnerable to environmental dynamic conditions and variations in distribution and transportation. To address these challenges, leveraging the Internet of Things (IoT) and quality inference techniques during transportation can provide valuable insights for both consumers and producers. The objective of the research is to develop a model for inferring the quality of perishable products using an IoT sensor dataset to monitor perishable product quality continuously. This research applied a hybrid approach combining a Fuzzy Inference System (FIS), clustering models, and genetic algorithms to infer the product quality during supply chain distribution with IoT sensors. The result shows that the hybrid FIS model, which employs Gaussian membership functions and fuzzy c-means clustering for rule generation, achieves a high accuracy with an R²: 0.873. This research contributes to improving the model by employing genetic algorithms in optimizing the inference model by activating only five out of seven rules. The model optimization achieves optimal computation time while aiming to preserve model accuracy. However, test results indicate that the combination of rules has not yet significantly enhanced the model's accuracy, though it holds potential for future development. Doi: 10.28991/ESJ-2025-09-01-027 Full Text: PDF

Low energy density, high nutrient adequacy and high nutrient density are each associated with higher diet costs in Chinese adults from Henan Province

ObjectivesFood price is a determining factor in food choice which affect diet quality accordingly. However, the association between food price and diet quality has not been thoroughly discussed among Chinese adults. This study aimed to analyze the association of daily energy-adjusted dietary costs (CNY/2000 kcal) and diet quality among Chinese adults.MethodsA total of 680 Chinese adults aged above 25 years from Henan province were investigated in 2020. Three indices were adopted for evaluating diet quality: the nutrient-rich foods 9.2 (NRF 9.2) index for evaluating nutrient density, the mean adequacy ratio (MAR) for evaluating nutrient adequacy, energy density (ED) based on solid foods only for evaluating energy density. The daily energy-adjusted diet cost was calculated by dividing the estimated daily diet costs (CNY/day) by the energy intake per day (kcal/day) and multiplying the result by 2000.ResultsSubjects who closely adhered to the NRF9.2, MAR, and ED paid ¥8.92, ¥13.17, and ¥14.34 more for daily food consumption, respectively, than those who weakly adhered to these dietary patterns did. Furthermore, multiple linear regression analysis adjusted covariance revealed that an increase in ¥1 of the energy-adjusted diet cost per day was associated with changes of 0.494 units (P < 0.001), 0.003 units (P < 0.001), and − 0.018 units (P < 0.001) in the NRF9.2, MAR, and ED, respectively.ConclusionHigher energy-adjusted diet cost was associated with higher quality diets. This might be important for public health policies to develop strategies to promote healthy diets by regulating food supply and its costs.