Valorisation of Agri-Food Waste for Bioactive Compounds: Recent Trends and Future Sustainable Challenges.

Worldwide, a massive amount of agriculture and food waste is a major threat to the environment, the economy and public health. However, these wastes are important sources of phytochemicals (bioactive), such as polyphenols, carotenoids, carnitine, coenzymes, essential oils and tocopherols, which have antioxidant, antimicrobial and anticarcinogenic properties. Hence, it represents a promising opportunity for the food, agriculture, cosmetics, textiles, energy and pharmaceutical industries to develop cost effective strategies. The value of agri-food wastes has been extracted from various valuable bioactive compounds such as polyphenols, dietary fibre, proteins, lipids, vitamins, carotenoids, organic acids, essential oils and minerals, some of which are found in greater quantities in the discarded parts than in the parts accepted by the market used for different industrial sectors. The value of agri-food wastes and by-products could assure food security, maintain sustainability, efficiently reduce environmental pollution and provide an opportunity to earn additional income for industries. Furthermore, sustainable extraction methodologies like ultrasound-assisted extraction, pressurized liquid extraction, supercritical fluid extraction, microwave-assisted extraction, pulse electric field-assisted extraction, ultrasound microwave-assisted extraction and high hydrostatic pressure extraction are extensively used for the isolation, purification and recovery of various bioactive compounds from agri-food waste, according to a circular economy and sustainable approach. This review also includes some of the critical and sustainable challenges in the valorisation of agri-food wastes and explores innovative eco-friendly methods for extracting bioactive compounds from agri-food wastes, particularly for food applications. The highlights of this review are providing information on the valorisation techniques used for the extraction and recovery of different bioactive compounds from agricultural food wastes, innovative and promising approaches. Additionally, the potential use of these products presents an affordable alternative towards a circular economy and, consequently, sustainability. In this context, the encapsulation process considers the integral and sustainable use of agricultural food waste for bioactive compounds that enhance the properties and quality of functional food.

Effects of sleep deprivation on food-related Pavlovian-instrumental transfer: a randomized crossover experiment.

Recent research suggests that insufficient sleep elevates the risk of obesity. Although the mechanisms underlying the relationship between insufficient sleep and obesity are not fully understood, preliminary evidence suggests that insufficient sleep may intensify habitual control of behavior, leading to greater cue-elicited food-seeking behavior that is insensitive to satiation. The present study tested this hypothesis using a within-individual, randomized, crossover experiment. Ninety-six adults underwent a one-night normal sleep duration (NSD) condition and a one-night total sleep deprivation (TSD) condition. They also completed the Pavlovian-instrumental transfer paradigm in which their instrumental responses for food in the presence and absence of conditioned cues were recorded. The sleep × cue × satiation interaction was significant, indicating that the enhancing effect of conditioned cues on food-seeking responses significantly differed across sleep × satiation conditions. However, this effect was observed in NSD but not TSD, and it disappeared after satiation. This finding contradicted the hypothesis but aligned with previous literature on the effect of sleep disruption on appetitive conditioning in animals-sleep disruption following learning impaired the expression of appetitive behavior. The present finding is the first evidence for the role of sleep in Pavlovian-instrumental transfer effects. Future research is needed to further disentangle how sleep influences motivational mechanisms underlying eating.

Wild capuchin monkeys use stones and sticks to access underground food.

Primates employ different tools and techniques to overcome the challenges of obtaining underground food resources. Humans and chimpanzees are known to tackle this problem with stick tools and one population of capuchin monkeys habitually uses stone tools. Although early hominids could have used stones as digging tools, we know little about when and how these could be useful. Here, we report a second primate population observed using stone tools and the first capuchin monkey population to habitually use the 'stick-probing' technique for obtaining underground resources. The bearded capuchin monkeys (Sapajus libidinosus) from Ubajara National Park, Brazil, use 'hands-only' and 'stone-digging' techniques for extracting underground storage organs and trapdoor spiders. Males also use 'stick-probing' and 'stone-stick' techniques for capturing trapdoor spiders. Tool use does not increase success in obtaining these resources. Stone-digging is less frequent in this population than in the only other known population that uses this technique. Females use stones in a lower proportion of their digging episodes than males in both populations. Ecological and cultural factors potentially influence technique choice and sex differences within and between populations. This population has a different pattern of underground food exploration using tools. Comparing this population with others and exploring the ecological and cultural factors under which capuchin monkeys employ different tools and techniques will allow us to better understand the pressures that may have shaped the evolution of those behaviors in primates.

Predicted impact of banning nonessential, energy-dense food and beverages in schools in Mexico: A microsimulation study.

BACKGROUND: Childhood obesity is a growing concern worldwide. School-based interventions have been proposed as effective means to improve nutritional knowledge and prevent obesity. In 2023, Mexico approved a reform to the General Education Law to strengthen the ban of sales and advertising of nonessential energy-dense food and beverages (NEDFBs) in schools and surroundings. We aimed to predict the expected one-year change in total caloric intake and obesity prevalence by introducing the ban of NEDFBs sales in schools, among school-aged children and adolescents (6 to 17 years old) in Mexico. METHODS AND FINDINGS: We used age-specific equations to predict baseline fat-free mass (FFM) and fat mass (FM) and then estimated total energy intake (TEI) per day. The TEI after the intervention was estimated under 4 scenarios: (1) using national data to inform the intervention effect; (2) varying law compliance; (3) using meta-analytic data to inform the intervention effect size on calories; and (4) using national data to inform the intervention effect by sex and socioeconomic status (SES). We used Hall's microsimulation model to estimate the potential impact on body weight and obesity prevalence of children and adolescents 1 year after implementing the intervention in Mexican schools. We found that children could reduce their daily energy intake by 33 kcal/day/person (uncertainty interval, UI, [25, 42] kcal/day/person), reducing on average 0.8 kg/person (UI [0.6, 1.0] kg/person) and 1.5 percentage points (pp) in obesity (UI [1.1, 1.9] pp) 1 year after implementing the law. We showed that compliance will be key to the success of this intervention: considering a 50% compliance the intervention effect could reduce 0.4 kg/person (UI [0.3, 0.5] kg/person). Our sensitivity analysis showed that the ban could reduce body weight by 1.3 kg/person (UI [0.8, 1.8] kg/person) and up to 5.4 kg/person (UI [3.4, 7.5] kg/person) in the best-case scenario. Study limitations include assuming that obesity and the contribution of NEDFBs consumed at school remain constant over time, assuming full compliance, and not considering the potential effect of banning NEDFBs in stores near schools. CONCLUSIONS: Even in the most conservative scenario, banning sales of NEDFBs in schools is expected to significantly reduce obesity, but achieving high compliance will be key to its success. WHY WAS THIS STUDY DONE?: - School-based interventions have been recognized as effective means to improve nutritional knowledge and prevent obesity-related diseases.- In December 2023, the Chamber of Representatives of Mexico approved an amendment that strengthens and updates the General Education Law (Article 75) and nutritional guidelines to ban the sales and advertising of nonessential energy-dense food and beverages (NEDFBs) in schools. WHAT DID THE RESEARCHERS DO AND FIND?: - We used age-specific equations to predict baseline fat-free mass (FFM) and fat mass (FM) and total energy intake (TEI) per day.- We used microsimulation modeling to predict body weight and obesity prevalence of children and adolescents 1 year after implementing the intervention in Mexican schools.- Our modeling study suggests that an important impact on obesity prevalence can be expected if the law is implemented and enforced as intended. WHAT DO THESE FINDINGS MEAN?: - If successful, this law could serve as an example beyond Mexico on how to achieve changes in body weight through school food regulation.- An important limitation of our main scenario is that we assumed full compliance of schools with the law, yet lower compliance will reduce its impact. We also did not consider historical trends on obesity or NEDFBs consumed in schools during our 1 year simulation, and we considered only the ban impact inside schools, excluding effects near and outside schools.

Comparison of Sales From Vending Machines With 4 Different Food and Beverage Messages: A Randomized Trial.

Importance: Point-of-sale food messaging can encourage healthier purchases, but no studies have directly compared multiple interventions in the field. Objective: To examine which of 4 food and beverage messages would increase healthier vending machine purchases. Design, Setting, and Participants: This randomized trial assessed 13 months (February 1, 2019, to February 29, 2020) of vending sales data from 267 machines and 1065 customer purchase assessments from vending machines on government property in Philadelphia, Pennsylvania. Data analysis was performed from March 5, 2020, to November 8, 2022. Interventions: Study interventions were 4 food and beverage messaging systems: (1) beverage tax posters encouraging healthy choices because of the Philadelphia tax on sweetened drinks; (2) green labels for healthy products; (3) traffic light labels: green (healthy), yellow (moderately healthy), or red (unhealthy); or (4) physical activity equivalent labels (minutes of activity to metabolize product calories). Main Outcomes and Measures: Sales data were analyzed separately for beverages and snacks. The main outcomes analyzed at the transaction level were calories sold and the health status (using traffic light criteria) of each item sold. Additional outcomes were analyzed at the monthly machine level: total units sold, calories sold, and units of each health status sold. The customer purchase assessment outcome was calories purchased per vending trip. Results: Monthly sales data came from 150 beverage and 117 snack vending machines, whereas 1065 customers (558 [52%] male) contributed purchase assessment data. Traffic light labels led to a 30% decrease in the mean monthly number of unhealthy beverages sold (mean ratio [MR], 0.70; 95% CI, 0.55-0.88) compared with beverage tax posters. Physical activity labels led to a 34% (MR, 0.66; 95% CI, 0.51-0.87) reduction in the number of unhealthy beverages sold at the machine level and 35% (MR, 0.65; 95% CI, 0.50-0.86) reduction in mean calories sold. Traffic light labels also led to a 30-calorie reduction (b = -30.46; 95% CI, -49.36 to -11.56) per customer trip in the customer purchase analyses compared to physical activity labels. There were very few significant differences for snack machines. Conclusions and Relevance: In this 13-month randomized trial of 267 vending machines, the traffic light and physical activity labels encouraged healthier beverage purchases, but no change in snack sales, compared with a beverage tax poster. Corporations and governments should consider such labeling approaches to promote healthier beverage choices. Trial Registration: ClinicalTrials.gov Identifier: NCT06260176.

Food price trends during the COVID-19 pandemic in Brazil.

The present study aims to analyze the trends in food price in Brazil with emphasis on the period of the Covid-19 pandemic (from March 2020 to March 2022). Data from the Brazilian Household Budget Survey and the National System of Consumer Price Indexes were used as input to create a novel data set containing monthly prices (R$/Kg) for the foods and beverages most consumed in the country between January 2018 and March 2022. All food items were divided according to the Nova food classification system. We estimated the mean price of each food group for each year of study and the entire period. The monthly price of each group was plotted to analyze changes from January 2018 to March 2022. Fractional polynomial models were used to synthesize price changes up to 2025. Results of the present study showed that in Brazil unprocessed or minimally processed foods and processed culinary ingredients were more affordable than processed and ultra-processed foods. However, trend analyses suggested the reversal of the pricing pattern. The anticipated changes in the prices of minimally processed food relative to ultra-processed food, initially forecasted for Brazil, seem to reflect the impact of the Covid-19 pandemic on the global economy. These results are concerning as the increase in the price of healthy foods aggravates food and nutrition insecurity in Brazil. Additionally, this trend encourages the replacement of traditional meals for the consumption of unhealthy foods, increasing a health risk to the population.

Share of food group expenditure in Mexican households according to the gender of the head of household and size of the locality.

OBJECTIVE: To evaluate differences in the percentage of expenditure on food groups in Mexican households according to the gender of the household head and the size of the locality. DESIGN: Analysis of secondary data from the National Household Income and Expenditure Survey (ENIGH) 2018. We estimated the percentage of expenditure on fifteen food groups according to the gender of the head of household and locality size and evaluated the differences using a two-part model approach. SETTING: Mexico, 2018. PARTICIPANTS: A nationally representative sample of 74 647 Mexican households. RESULTS: Female-headed households allocated a lower share of expenditure to the purchase of sweetened beverages and alcoholic beverages and higher percentages to milk and dairy, fruits and water. In comparison with metropolitan households, households in rural and urban localities spent more on cereals and tubers, sugar and honey, oil and fat and less on food away from home. CONCLUSIONS: Households allocate different percentages of expenditure to diverse food groups according to the gender of the head of the household and the size of the locality where they are located. Future research should focus on understanding the economic and social disparities related to differences in food expenditure, including the gender perspective.

Development and testing of two tools to assess point-of-sale food and beverage marketing to children in restaurants.

OBJECTIVE: To describe the development and testing of two assessment tools designed to assess exterior (including drive-thru) and interior food and beverage marketing in restaurants with a focus on marketing to children and teens. DESIGN: A scoping review on restaurant marketing to children was undertaken, followed by expert and government consultations to produce a draft assessment tool. The draft tool was mounted online and further refined into two separate tools: the Canadian Marketing Assessment Tool for Restaurants (CMAT-R) and the CMAT-Photo Coding Tool (CMAT-PCT). The tools were tested to assess inter-rater reliability using Cohen's Kappa and per cent agreement for dichotomous variables, and intra-class correlation coefficients (ICCs) for continuous or rank-order variables. SETTING: Waterloo, Ontario, Canada. PARTICIPANTS: Restaurants of all types were assessed using the CMAT-R (n 57), and thirty randomly selected photos were coded using the CMAT-PCT. RESULTS: The CMAT-R collected data on general promotions and restaurant features, drive-thru features, the children's menu and the dollar/value menu. The CMAT-PCT collected data on advertisement features, features considered appealing to children and teens, and characters. The inter-rater reliability of the CMAT-R tool was strong (mean per cent agreement was 92·4 %, mean Cohen's κ = 0·82 for all dichotomous variables and mean ICC = 0·961 for continuous/count variables). The mean per cent agreement for the CMAT-PCT across items was 97·3 %, and mean Cohen's κ across items was 0·91, indicating very strong inter-rater reliability. CONCLUSIONS: The tools assess restaurant food and beverage marketing. Both showed high inter-rater reliability and can be adapted to better suit other contexts.

The relationship between the price and demand of alcohol, tobacco, unhealthy food, sugar-sweetened beverages, and gambling: an umbrella review of systematic reviews.

BACKGROUND: The WHO highlight alcohol, tobacco, unhealthy food, and sugar-sweetened beverage (SSB) taxes as one of the most effective policies for preventing and reducing the burden of non-communicable diseases. This umbrella review aimed to identify and summarise evidence from systematic reviews that report the relationship between price and demand or price and disease/death for alcohol, tobacco, unhealthy food, and SSBs. Given the recent recognition as gambling as a public health problem, we also included gambling. METHODS: The protocol for this umbrella review was pre-registered (PROSPERO CRD42023447429). Seven electronic databases were searched between 2000-2023. Eligible systematic reviews were those published in any country, including adults or children, and which quantitatively examined the relationship between alcohol, tobacco, gambling, unhealthy food, or SSB price/tax and demand (sales/consumption) or disease/death. Two researchers undertook screening, eligibility, data extraction, and risk of bias assessment using the ROBIS tool. RESULTS: We identified 50 reviews from 5,185 records, of which 31 reported on unhealthy food or SSBs, nine reported on tobacco, nine on alcohol, and one on multiple outcomes (alcohol, tobacco, unhealthy food, and SSBs). We did not identify any reviews on gambling. Higher prices were consistently associated with lower demand, notwithstanding variation in the size of effect across commodities or populations. Reductions in demand were large enough to be considered meaningful for policy. CONCLUSIONS: Increases in the price of alcohol, tobacco, unhealthy food, and SSBs are consistently associated with decreases in demand. Moreover, increasing taxes can be expected to increase tax revenue. There may be potential in joining up approaches to taxation across the harm-causing commodities.

Fine-grained food image classification and recipe extraction using a customized deep neural network and NLP.

Global eating habits cause health issues leading people to mindful eating. This has directed attention to applying deep learning to food-related data. The proposed work develops a new framework integrating neural network and natural language processing for classification of food images and automated recipe extraction. It address the challenges of intra-class variability and inter-class similarity in food images that have received shallow attention in the literature. Firstly, a customized lightweight deep convolution neural network model, MResNet-50 for classifying food images is proposed. Secondly, automated ingredient processing and recipe extraction is done using natural language processing algorithms: Word2Vec and Transformers in conjunction. Thirdly, a representational semi-structured domain ontology is built to store the relationship between cuisine, food item, and ingredients. The accuracy of the proposed framework on the Food-101 and UECFOOD256 datasets is increased by 2.4% and 7.5%, respectively, outperforming existing models in literature such as DeepFood, CNN-Food, Wiser, and other pre-trained neural networks.

Predicting the short and long term effects of food price inflation, armed conflicts, and climate variability on global acute malnutrition in Somalia.

BACKGROUND: Malnutrition poses a substantial challenge in Somalia, impacting approximately 1.8 million children. This critical issue is exacerbated by a multifaceted interplay of factors. Consequently, this study seeks to examine the long-term and short-term effects of armed conflicts, food price inflation, and climate variability on global acute malnutrition in Somalia. METHODS: The study utilized secondary data spanning from January 2015 to December 2022, sourced from relevant databases. Two distinct analytical approaches were employed to comprehensively investigate the dynamics of global acute malnutrition in Somalia. Firstly, dynamic autoregressive distributed lag (ARDL) simulations were applied, allowing for a nuanced understanding of the short and long-term effects of armed conflicts, food price inflation, and climate variability on malnutrition. Additionally, the study employed kernel-based regularized least squares, a sophisticated statistical technique, to further enhance the robustness of the findings. The analysis was conducted using STATA version 17. RESULTS: In the short run, armed conflicts and food price inflation exhibit positive associations with global acute malnutrition, particularly in conflict-prone areas and during inflationary periods. Moreover, climatic variables, specifically temperature and rainfall, demonstrate positive associations. It is important to note that temperature lacks a statistically significant relationship with global acute malnutrition in the short run. In the long run, armed conflicts and food price inflation maintain persistent impacts on global acute malnutrition, as confirmed by the dynamic ARDL simulations model. Furthermore, both temperature and rainfall continue to show positive associations with global acute malnutrition, but it is worth noting that temperature still exhibits a non-significant relationship. The results from kernel-based regularized least squares were consistent, further enhancing the robustness of the findings. CONCLUSIONS: Increased armed conflicts, food price inflation, temperature, and rainfall were associated with increased global acute malnutrition. Strategies such as stabilizing conflict-prone regions, diplomatic interventions, and peace-building initiatives are crucial, along with measures to control food price inflation. Implementing climate adaptation strategies is vital to counter temperature changes and fluctuating rainfall patterns, emphasizing the need for resilience-building. Policymakers and humanitarian organizations can leverage these insights to design targeted interventions, focusing on conflict resolution, food security, and climate resilience to enhance Somalia's overall nutritional well-being.

Trends in the contribution of greenhouse gas emissions from food and beverage purchases in Mexico: 1989-2020.

BACKGROUND: Assessing the trends in dietary GHGE considering the social patterning is critical for understanding the role that food systems have played and will play in global emissions in countries of the global south. Our aim is to describe dietary greenhouse gas emissions (GHGE) trends (overall and by food group) using data from household food purchase surveys from 1989 to 2020 in Mexico, overall and by education levels and urbanicity. METHODS: We used cross-sectional data from 16 rounds of Mexico's National Income and Expenditure Survey, a nationally representative survey. The sample size ranged from 11,051 in 1989 to 88,398 in 2020. We estimated the mean total GHGE per adult-equivalent per day (kg CO2-eq/ad-eq/d) for every survey year. Then, we estimated the relative GHGE contribution by food group for each household. These same analyses were conducted stratifying by education and urbanicity. RESULTS: The mean total GHGE increased from 3.70 (95%CI: 3.57, 3.82) to 4.90 (95% CI 4.62, 5.18) kg CO2-eq/ad-eq/d between 1989 and 2014 and stayed stable between 4.63 (95% CI: 4.53, 4.72) and 4.89 (95% CI: 4.81, 4.96) kg CO2-eq/ad-eq/d from 2016 onwards. In 1989, beef (19.89%, 95% CI: 19.18, 20.59), dairy (16.87%, 95% CI: 16.30, 17.42)), corn (9.61%, 95% CI: 9.00, 10.22), legumes (7.03%, 95% CI: 6.59, 7.46), and beverages (6.99%, 95% CI: 6.66, 7.32) had the highest relative contribution to food GHGE; by 2020, beef was the top contributor (17.68%, 95%CI: 17.46, 17.89) followed by fast food (14.17%, 95% CI: 13.90, 14.43), dairy (11.21%, 95%CI: 11.06, 11.36), beverages (10.09%, 95%CI: 9.94, 10.23), and chicken (10.04%, 95%CI: 9.90, 10.17). Households with higher education levels and those in more urbanized areas contributed more to dietary GHGE across the full period. However, households with lower education levels and those in rural areas had the highest increase in these emissions from 1989 to 2020. CONCLUSIONS: Our results provide insights into the food groups in which the 2023 Mexican Dietary Guidelines may require to focus on improving human and planetary health.

Impact of food waste addition in energy efficient municipal wastewater treatment by aerobic granular sludge process.

Recently, one of the main purposes of wastewater treatment plants is to achieve a neutral or positive energy balance while meeting the discharge criteria. Aerobic granular sludge (AGS) technology is a promising technology that has low energy and footprint requirements as well as high treatment performance. The effect of co-treatment of municipal wastewater and food waste (FW) on the treatment performance, granule morphology, and settling behavior of the granules was investigated in the study. A biochemical methane potential (BMP) test was also performed to assess the methane potential of mono- and co-digestion of the excess sludge from the AGS process. The addition of FW into wastewater enhanced the nutrient treatment efficiency in the AGS process. BMP of the excess sludge from the AGS process fed with the mixture of wastewater and FW (195 ± 17 mL CH4/g VS) was slightly higher than BMP of excess sludge from the AGS process fed with solely wastewater (173 ± 16 mL CH4/g VS). The highest methane yield was observed for co-digestion of excess sludge from the AGS process and FW, which was 312 ± 8 mL CH4/g VS. Integration of FW as a co-substrate in the AGS process would potentially enhance energy recovery and the quality of effluent in municipal wastewater treatment.

Analyzing spatio-temporal changes and trade-offs/synergies of gross ecosystem product based on water-energy-food nexus.

The value of the ecosystem's ultimate goods and services for human welfare and long-term economic and social development is known as the gross ecosystem product (GEP). For the study of GEP accounting, the suggested water-energy-food (WEF) nexus offers a fresh viewpoint. This work aims to build a GEP accounting index system based on WEF, investigate its spatio-temporal evolution characteristics, and assess trade-offs and synergies between and within the water, energy, and food subsystems. Using the Three Gorges Reservoir area (TGRA) as an illustration, the findings revealed that, firstly, the comprehensive benefit of GEP based on WEF showed an upward trend in TGRA. Still, it was worth noting that the total production of the food ecosystem decreased. Secondly, the GEP based on WEF in five periods showed a spatial pattern of "high east and west, low middle." Thirdly, the Pearson correlation coefficient indicated that the GEP trade-off relationships based on WEF were dominant in TGRA, with the strongest trade-offs between AQV, SCV, APV, and LEV. In addition, in bivariate local spatial autocorrelation, the value of the six ecosystem service function relationships was dominated by the trade-off relationship, and the distribution of trade-offs and synergies showed significant heterogeneity at the county scale in the TGRA. Finally, hot spot analysis showed that the hot spots of the gross water and energy ecosystem products were scattered in the tail area of the study area. In contrast, the hot spots of the gross food ecosystem product were concentrated in the belly region. The findings of this study provided a basis for the scientific formulation of territorial spatial pattern optimization for water, energy, and agricultural resources in the TGRA and can more accurately reflect the status of the ecological environment and changes of WEF over time. Moreover, this paper also gives full play to the growth advantages of shipping and aquatic products, implements effective soil erosion prevention and control measures, and establishes water-saving mechanisms and other measures in terms of water resources. Subregional plans for industrial structure and strengthening of waste gas and wastewater treatment facilities regarding energy resources are developed. Implement the cultivated land protection system and promote the superiority of crop varieties and other measures in terms of food resources.

The application of systematic accident analysis tools to investigate food safety incidents.

Effective food safety (FS) management relies on the understanding of the factors that contribute to FS incidents (FSIs) and the means for their mitigation and control. This review aims to explore the application of systematic accident analysis tools to both design FS management systems (FSMSs) as well as to investigate FSI to identify contributive and causative factors associated with FSI and the means for their elimination or control. The study has compared and contrasted the diverse characteristics of linear, epidemiological, and systematic accident analysis tools and hazard analysis critical control point (HACCP) and the types and depth of qualitative and quantitative analysis they promote. Systematic accident analysis tools, such as the Accident Map Model, the Functional Resonance Accident Model, or the Systems Theoretical Accident Model and Processes, are flexible systematic approaches to analyzing FSI within a socio-technical food system which is complex and continually evolving. They can be applied at organizational, supply chain, or wider food system levels. As with the application of HACCP principles, the process is time-consuming and requires skilled users to achieve the level of systematic analysis required to ensure effective validation and verification of FSMS and revalidation and reverification following an FSI. Effective revalidation and reverification are essential to prevent recurrent FSI and to inform new practices and processes for emergent FS concerns and the means for their control.

Recent advances on enhancing 3D printing quality of protein-based inks: A review.

3D printing is an additive manufacturing technology that locates constructed models with computer-controlled printing equipment. To achieve high-quality printing, the requirements on rheological properties of raw materials are extremely restrictive. Given the special structure and high modifiability under external physicochemical factors, the rheological properties of proteins can be easily adjusted to suitable properties for 3D printing. Although protein has great potential as a printing material, there are many challenges in the actual printing process. This review summarizes the technical considerations for protein-based ink 3D printing. The physicochemical factors used to enhance the printing adaptability of protein inks are discussed. The post-processing methods for improving the quality of 3D structures are described, and the application and problems of fourth dimension (4D) printing are illustrated. The prospects of 3D printing in protein manufacturing are presented to support its application in food and cultured meat. The native structure and physicochemical factors of proteins are closely related to their rheological properties, which directly link with their adaptability for 3D printing. Printing parameters include extrusion pressure, printing speed, printing temperature, nozzle diameter, filling mode, and density, which significantly affect the precision and stability of the 3D structure. Post-processing can improve the stability and quality of 3D structures. 4D design can enrich the sensory quality of the structure. 3D-printed protein products can meet consumer needs for nutritional or cultured meat alternatives.

Low-intensity alternating ventilation achieves effective humification during food waste composting by enhancing the intensity of microbial interaction and carbon metabolism.

Vertical static composting is an efficient and convenient technology for the treatment of food waste. Exploring the impact of oxygen concentration levels on microbial community structure and functional stability is crucial for optimizing ventilation technology. This study set three experimental groups with varying ventilation intensities based on self-made alternating ventilation composting reactor (AL2: 0.2 L kg-1 DM·min-1; AL4: 0.4 L kg-1 DM·min-1; AL6: 0.6 L kg-1 DM·min-1) to explore the optimal alternating ventilation rate. The results showed that the cumulative ammonia emission of AL2 group reduced by 25.13% and 12.59% compared to the AL4 and AL6 groups. The humification degree of the product was 1.18 times and 1.25 times higher than the other two groups. AL2 increased the relative abundance of the core species Saccharomonospora, thereby strengthening microbial interaction. Low-intensity alternating ventilation increased the carbon metabolism levels, especially aerobic_chemoheterotrophy, carbohydrate and lipid metabolism. However, it simultaneously reduced nitrogen metabolism. Structural equation model analysis demonstrated that alternating low-intensity ventilation effectively regulated both microbial diversity (0.81, p < 0.001) and metabolism (0.81, p < 0.001) by shaping the composting environment. This study optimized the intensity of alternating ventilation and revealed the regulatory mechanism of community structure and metabolism. This study provides guidance for achieving efficient and low-consumption composting.