Minimizing Food Waste Research Articles

Sustainable Culinary Conservation: Pioneering Efforts to Minimize Food Waste in Ghana's Fast‐Food Industry

Sustainable Culinary Conservation: Pioneering Efforts to Minimize Food Waste in Ghana's Fast‐Food Industry

Preparation and characterization of polyphenol–chitosan conjugate–eugenol essential oil microcapsule and its effect on storage behavior of cherry tomato

AbstractGiven the high volatility, low water solubility, and oxidative sensitivity of essential oils, this study synthesized microcapsules of essential oil (EEO) (quercetin–chitosan–EEO [QE–CS–EEO]) using a QE–CS graft copolymer as the wall material and EEO as the core material. Research findings indicate that QE–CS exhibits superior in vitro antioxidant activity, with scavenging abilities for 2,2‐diphenyl‐1‐picrylhydrazyl and 2,2′‐azino‐bis(3‐ethylbenzothiazoline‐6‐sulfonic acid) ABTS+ radicals being 58.71% and 77.03% greater than those of CS, respectively, thereby providing more effective protection for the essential oil. In comparison to CS essential oil, microcapsules (CS–EEO), QE–CS–EEO demonstrated an 18.65% increase in EEO encapsulation efficiency, achieving a total encapsulation efficiency of 41.29%. Based on these results, various edible coating solutions were formulated, including Control, E1 (1% CS), E2 (0.5% CS + 0.5% CS–EEO), E3 (0.5% CS + 0.5% QE–CS–EEO), and E4 (1% EEO), to extend the shelf life of cherry tomatoes. Notably, cherry tomatoes treated with the E3 formulation maintained superior freshness indicators, exhibiting an extended shelf life of approximately 9–12 days compared to the control group. This study aims to explore a novel microcapsule wall material and provide a strategy for extending the shelf life of fruits and vegetables, thereby minimizing food waste.

Minimizing Waste, Maximizing Sustainability: Analyzing Collaborative Practices Implementation Barriers in the Agri-Fresh Produce Industry

The agri-fresh produce industry confronts problems in minimizing food waste and achieving supply chain sustainability due to its complicated structure and lack of stakeholder participation. Significant food waste at numerous supply chain stages undermines the triple bottom line (Society, economy and environment) and wastes resources. Stakeholder collaboration, research, and information exchange can all help to minimize waste and improve sustainability. This study identifies barriers to implementing collaborative practices through literature analysis and expert insights and categorizes them into seven dimensions: relationship management practice, contractual and economic practice, joint practice, technological and information sharing practice, relationships management practice, and supply chain design practice. Furthermore, the grey-Decision Making Trial and Evaluation Laboratory (grey-DEMATEL) and Analytic Network Process (ANP) were employed to develop an integrated framework that identifies interrelationships and prioritizes dimensions and attributes. The influence relationship diagraph helps decision-makers make policy recommendations by understanding the cause-effect interrelationships among the dimensions and their corresponding barriers. Finally, sensitivity analysis was performed to ensure that the results are robust and reduce decision-making biases.

From Root to Stem: Optimizing Produce Utilization and Reducing Waste through Sustainable Cooking Practices

Background: In modern society, food waste is a pressing issue contributing to environmental degradation and resource depletion. “From Root to Stem” proposes a solution by advocating for sustainable cooking practices that maximize the use of every part of produce. Objectives: The objectives of this study were twofold. Firstly, to assess the existing levels of awareness and implementation of root-to-stem cooking practices among hospitality students. Secondly, to identify the obstacles hindering widespread adoption of root-to-stem cooking and to pinpoint the factors that facilitate its uptake. Additionally, the study aimed to propose effective strategies for promoting the incorporation of root-to-stem cooking practices in both domestic and commercial environments. Methodology: To accomplish these goals, a quantitative research approach, specifically employing a descriptive research design, was utilized. Data collection involved the use of an online questionnaire distributed via Google Forms among a select group of hospitality students with expertise in the kitchen. Convenience sampling was employed to gather data, resulting in a sample size of 328 participants. Data analysis was conducted using SPSS version 23, based on a mixed questionnaire format. Results: The data reveals that 92.1% of respondents are familiar with root-to-stem cooking. However, only 4.3% always incorporate these techniques, with 58.6% doing so sometimes. 87.4% have received formal education or training on root-to-stem cooking, and 78.1% believe it can contribute to reducing food waste. Additionally, 56.3% are moderately likely to explore root-to-stem cooking further in the future. Conclusion: Root-to-stem cooking offers a sustainable solution to minimize food waste by utilizing entire plants. Despite obstacles like limited consumer awareness and logistical challenges, collaborative efforts among stakeholders can drive its adoption. Through education, digital platforms, and policy interventions, root-to-stem cooking can revolutionize culinary practices and promote a more sustainable food system.

A Mobile Application to Facilitate Meal Box Sharing in Corporate Environments Using Cloud Infrastructure

Food waste is a pressing global issue, particularly in urban settings, where substantial amounts of surplus food go unused. In corporate environments, this challenge is compounded by the lack of dedicated platforms to facilitate food sharing and reduce waste effectively. This paper examines the current landscape of food waste, existing solutions, and the need for a specialised platform aimed at corporate employees. The proposed solution is the creation of a user-friendly application that enables the sharing of untouched homemade meals. Suppliers can post their meal boxes with details such as location, type of food, and availability status, while consumers can search for and select meal boxes based on their preferences. This paper addresses the gap in solutions for reducing food waste within corporate environments. The meal-box-sharing app provides a practical and sustainable method for minimising food waste and promoting productivity, health, and safety in the workplace.

Fermentation for Revalorisation of Fruit and Vegetable By-Products: A Sustainable Approach Towards Minimising Food Loss and Waste.

In a world increasingly focused on sustainability and integrated resource use, the revalorisation of horticultural by-products is emerging as a key strategy to minimise food loss and waste while maximising value within the food supply chain. Fermentation, one of the earliest and most versatile food processing techniques, utilises microorganisms or enzymes to induce desirable biochemical transformations that enhance the nutritional value, digestibility, safety, and sensory properties of food products. This process has been identified as a promising method for producing novel, high-value food products from discarded or non-aesthetic fruits and vegetables that fail to meet commercial standards due to aesthetic factors such as size or appearance. Besides waste reduction, fermentation enables the production of functional beverages and foods enriched with probiotics, antioxidants, and other bioactive compounds, depending on the specific horticultural matrix and the types of microorganisms employed. This review explores the current bioprocesses used or under investigation, such as alcoholic, lactic, and acetic acid fermentation, for the revalorisation of fruit and vegetable by-products, with particular emphasis on how fermentation can transform these by-products into valuable foods and ingredients for human consumption, contributing to a more sustainable and circular food system.

The role of global waste management and circular economy towards carbon neutrality

Solid waste management is a cross-cutting issue that significantly influences multiple aspects of sustainable development globally. The waste sector is a major anthropogenic source of global greenhouse gas (GHG) emissions. Most global GHG assessments of waste management rely on generic data due to limitations in available data. This research used reflective inventory data for municipal solid waste (MSW) treatment systems related to the income levels of countries, resulting in more context-specific and comprehensive assessments of GHG emissions. This study aims to assess life cycle GHG emissions from the global MSW management sector for the years 2023, 2030, and 2050 and then analyses the global and regional waste management goals set by the United Nations Environment Programme (UNEP) and the European Union (EU) to identify hotspots in the MSW management systems and critical factors that influence GHG emissions from the waste sector. The study was conducted in accordance with the standards outlined in ISO 14067:2018. The results show that the average global GHG emissions from 1 tonne of MSW in 2023 based on the existing MSW management practices was approximately 89.7 kg CO2e. The major contributor was the open dumping of MSW, contributing almost 70 % of GHG emissions. The global MSW management sector emitted a total of 173.2 Mt CO2e GHG emissions in 2023. If no improvements are made to existing systems, GHG emissions from the waste sector are projected to increase to 203.4 Mt CO2e by 2030, and to 289.5 Mt CO2e by 2050. Achieving waste management goals can reduce GHG emissions by approximately 1 % to more than 160 %. The implementation of the circular economy in the waste sector has the potential to achieve net zero emissions from the global MSW management sector by 2030 and 2050. This study provides achievable MSW management targets for the world and highlights key factors to achieve carbon neutrality from the waste sector. Prioritising policies such as upgrading open dumps, standardising household-level waste separation procedures, minimising food waste, establishing national recycling targets, and promoting circular economy through a zero-waste approach could substantially reduce GHG emissions from the waste sector. These findings are important for the adoption of circular economy principles in MSW management systems to effectively support the pursuit of carbon neutrality goals.

Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food Waste

The cold chain logistics industry faces significant challenges in terms of transportation costs and carbon emissions. It is imperative to plan multimodal transportation routes efficiently to address these issues, minimize food waste, and reduce carbon emissions. This paper focuses on four key optimization objectives for multimodal cold chain transport: minimizing total transportation time, costs, carbon emissions, and food waste. To tackle these objectives, we propose a high-dimensional multiobjective route optimization model for multimodal cold chain networks. Our approach involves the development of a multiobjective evolutionary algorithm, utilizing Monte Carlo simulation and a one-by-one selection strategy. We evaluate the proposed algorithm’s performance by analyzing various convergence and distribution indicators. The average values for the minimum total transportation time, transportation cost, carbon emission cost, and cargo loss rate derived from the proposed algorithm ultimately converge to 6721.7, 5184.4, 301.5, and 0.21, respectively, demonstrating the effectiveness of the algorithmic solution. Additionally, we benchmark our algorithm against the existing literature to showcase its efficiency in solving high-dimensional multi-objective route optimization problems. Furthermore, we investigate the impact of different parameters, such as carbon tax rates, temperature, and cargo activation energy, on carbon emissions, and food waste. Moreover, we conduct a real-world case study to apply our approach to solving a practical business problem related to multimodal cold chain transportation. The insights gained from this research offer valuable decision-making support for multimodal carriers in developing low-carbon and environmentally friendly transportation strategies to efficiently transport perishable goods.

Investigating household food waste in Indonesia: An extended norm activation model

Consumers waste significant amounts of food. Food waste presents a substantial problem for the environment, society and economy. Addressing the food waste challenge is crucial for fostering sustainable behavior and achieving the Sustainability Development Goal 12.3 agenda. Norms are a significant determinant in motivating consumers to prevent food waste and could be activated by other factors. Religiosity has the potential to influence norms related to food waste behavior. This study investigated how religiosity affects the intentions of consumers to minimize food waste. The interplay of religiosity, personal norms, subjective norms, and intention to avoid food waste was examined by the extended norm activation model. Data were obtained from Muslim consumers in Indonesia. Structural equation modeling evaluation showed that religiosity positively affects the intention to prevent food waste. The intention to avoid food waste is more closely associated with personal norms compared to subjective norms. Personal norms mediate the religiosity and food waste reduction intention relationship. Consumer awareness activates personal norms by making them feel accountable for food waste’s negative impact. These findings provide insights to stakeholders in developing policies to mitigate the food waste issue.

Enhancing resource recovery in Indonesian upcycled food supply chains: collaborative innovation networks and their drivers

ABSTRACT This study provides theoretical and practical perspectives on resource recovery (RR) in upcycled food (UF) supply chains. The goal of RR in UF supply chains is to minimize food waste and maximize the value derived from food byproducts and surplus. However, since these supply chains are fragmented and recovering and utilizing food waste involve inherent uncertainties, implementation is challenging. This study employs the fuzzy Delphi method and a fuzzy decision-making trial and evaluation laboratory. The analysis validates 29 attributes of RR in UF supply chains, examines their causal relationships, and assesses hierarchical interdependencies. The findings reveal that financial resources, managerial strategies, and digital infrastructure causally drive collaborative innovation networks. This study provides managerial implications for the UF industry, highlighting the importance of engaging business stakeholders, supporting collaborative problem solving, allocating budgets strategically, developing lifecycle value strategies, and focusing on value creation. These insights can inform strategies and sustainable practices in the food sector.

Machine learning-based optimal temperature management model for safety and quality control of perishable food supply chain

The management of a food supply chain is difficult and complex because of the product's short shelf-life, time-sensitivity, and perishable nature which must be carefully considered to minimize food waste. Temperature-controlled perishable food supply chain provides the highly crucial facilities necessary to maintain the quality and safety of the product. The storage temperature is the most vital factor in maintaining both the quality and shelf-life of a perishable food. Adequate storage temperature control ensures that perishable foods are transported to the end-users in good quality and safe to consume. This paper presents perishable food storage temperature control through mathematical optimal control model where the storage temperature is regarded as the control variable and the deterioration of the perishable food’s quality follows the first-order reaction. The optimal storage temperature for a single perishable food is determined by applying the Pontryagin's maximum principle to solve the optimal control model problem. For multi-temperature commodities supply chain, an unsupervised machine learning (ML) method, called k-means clustering technique is used to determine the temperature clusters for a range of perishables. Based on descriptive analysis, it is observed that the k-means clustering technique is effective in identifying the best suitable storage temperature clusters for quality control of multi-commodity supply chain.

Reducing food waste for environmental sustainability: study in Indonesia

Abstract Food waste is one of the problems that must be resolved immediately considering the difficulty of this type of waste to be reprocessed. Food waste has negative economic, social and environmental consequences and occurs most often during the consumption stage, especially in households. Thus, to assist Indonesian policies aimed at minimizing food waste, the purpose of this research is to comprehend consumer food waste behavior (FWB). This study explains this phenomenon using awareness, knowledge, and the Theory of Planned Behavior (TPB). The results of analysis from 205 Indonesian respondents using PLS-SEM found that attitude, subjective norms, and perceived behavioral control had a significant influence on food waste avoidance intention (FWAI) which ultimately could minimize FWB. However, it has been demonstrated that awareness has little impact on consumer understanding, which in turn has no impact on FWAI and FWB. These results can provide an idea for regulators in Indonesia regarding the variables that must be influenced so that consumer behavior can be changed, and food waste can be reduced. The results of this investigation also contribute to realizing Goal No. 12 of the Sustainable Development Agenda, which is responsible for production and consumption.

Innovative Solutions for Sustainable Logistics in Food Manufacturing Industries overcome Barriers and Challenges

This paper explores innovative solutions for sustainable logistics in the food manufacturing industry, focusing on how these strategies address key challenges. It examines how advancements in technology, logistics strategies, and eco-friendly practices contribute to sustainability while maintaining efficiency and profitability. The study analyzes data from companies that have adopted modern logistics solutions, such as AI-driven optimization, renewable energy, and circular supply chain models, supplemented by expert interviews to gain practical insights. The findings reveal that these solutions help reduce carbon emissions, minimize food waste, and optimize resource use. Companies that have implemented these strategies have successfully overcome common barriers such as high costs, infrastructure complexity, and regulatory challenges. While the research focuses on large-scale manufacturers, smaller companies remain under explored, suggesting the need for future studies on scalability and policy frameworks to support wider adoption. This paper offers a unique contribution by combining current innovations in sustainable logistics with practical industry challenges, providing actionable insights for food manufacturers and laying the foundation for further research into overcoming financial and technological barriers.

Using blockchain technology to achieve sustainability in the hospitality industry by reducing food waste

The hospitality industry generates significant food waste, leading to adverse environmental and economic impacts, social and ethical concerns, legal and regulatory issues, and operational challenges. The lack of traceability and trust among stakeholders in the hospitality industry exacerbates the expensive and difficult nature of food waste management. This work proposes a blockchain-based solution that aims to minimize food waste generated in hospitality outlets, thereby fostering a sustainable food ecosystem. Within this context, the term ’sustainable food ecosystem’ refers to the interconnected network of stakeholders involved in the responsible management of food resources within the hospitality industry. In this context, we categorize these stakeholders under the umbrella of ’food resource management entities,’ encompassing both food donation organizations and recycling companies, recognizing their distinct roles in the effective management of surplus food resources. With our proposed solution, businesses can track and verify the origin, movement, and disposal of food items in real-time, facilitating streamlined inventory planning, waste reduction, and heightened operational efficiency. Additionally, the proposed system ensures transparency and accountability, guaranteeing the proper and efficient disposal of food waste. Using a permissioned Ethereum network, our solution establishes seamless connectivity between food and beverage outlets and various food resource management entities. We present a generalized system for secure information sharing, integrating advanced algorithms tailored to capture and enhance trust among participating stakeholders. Furthermore, our thorough security analysis underscores the robustness of our proposed solution, effectively addressing various security vulnerabilities. Lastly, the proposed blockchain-based solution is commercially viable, enabling the hospitality industry to operate with enhanced efficiency while providing improved information connectivity for various stakeholders in the food supply chain.

A Hierarchical RF-XGBoost Model for Short-Cycle Agricultural Product Sales Forecasting.

Short-cycle agricultural product sales forecasting significantly reduces food waste by accurately predicting demand, ensuring producers match supply with consumer needs. However, the forecasting is often subject to uncertain factors, resulting in highly volatile and discontinuous data. To address this, a hierarchical prediction model that combines RF-XGBoost is proposed in this work. It adopts the Random Forest (RF) in the first layer to extract residuals and achieve initial prediction results based on correlation features from Grey Relation Analysis (GRA). Then, a new feature set based on residual clustering features is generated after the hierarchical clustering is applied to classify the characteristics of the residuals. Subsequently, Extreme Gradient Boosting (XGBoost) acts as the second layer that utilizes those residual clustering features to yield the prediction results. The final prediction is by incorporating the results from the first layer and second layer correspondingly. As for the performance evaluation, using agricultural product sales data from a supermarket in China from 1 July 2020 to 30 June 2023, the results demonstrate superiority over standalone RF and XGBoost, with a Mean Absolute Percentage Error (MAPE) reduction of 10% and 12%, respectively, and a coefficient of determination (R2) increase of 22% and 24%, respectively. Additionally, its generalization is validated across 42 types of agricultural products from six vegetable categories, showing its extensive practical ability. Such performances reveal that the proposed model beneficially enhances the precision of short-term agricultural product sales forecasting, with the advantages of optimizing the supply chain from producers to consumers and minimizing food waste accordingly.

Leftover love: Exploring the behavioural heterogeneity of household meal wasters

Meal leftovers are a major component of household food waste. However, there is a limited understanding of leftover food management behaviours, which can assist in reducing food waste in household settings. This study segments households with distinctive behaviours associated with meal leftover management. Principal component analysis and cluster analysis were used for consumer segmentation. Data on meal leftovers and food management behaviours were collected using a national-level survey of 1728 Australian households. We identified two heterogenous groups of households regarding leftover meal management, ‘Self-sufficient savers’ (59% of the sample) and ‘Naïve discarders’ (41% of the sample). The findings indicate that inefficient cooking and storing behaviours lead to cooked meals being discarded. ‘Naïve discarders’ dispose of leftover meals either immediately or after storing them because they do not have sufficient cooking skills to repurpose leftovers or judge the safety of the food after storing them. They also lack meal-planning skills. In contrast, the ‘Self-sufficient savers’ demonstrated efficient cooking skills and storing behaviours. They read and followed the storage and meal portioning instructions. Results highlight the need for customised interventions targeting consumers with low cooking and storing knowledge to contribute towards overall food waste minimisation.

From waste to wellness: a review on the harness of food industry by‐products for sustainable functional food production

SummaryThe production of functional foods has been on a consistent rise in the past few years. The increasing demand for these foods could play a pivotal role in addressing the escalating issue of food waste and in the creation of innovative food formulations. Utilising by‐products from the food industry has become commonplace due to their advantageous nutritional composition and functional properties. These by‐products retain richness in colour compounds, proteins, amino acids, lipids, fatty acids, sugars, fibres, minerals, vitamins, antioxidants and antimicrobial compounds. This abundance of elements can be harnessed to develop innovative food products. This review examines the potential of utilising food industry wastes for producing functional foods, focusing on residues from animal and vegetable origins; such residues find application in creating snacks, beverages, fermented foods, bakery items, dairy products, pasta, charcuterie, chocolate, flavouring agents, additives and culinary innovations. This study seeks to establish a sustainable strategy for minimising food waste disposal, fostering a bio‐based food production industry and enhancing overall sustainability by uncovering alternatives for novel, nutritious and value‐added food products.

From Screen to Scraps: Online Food Waste Behavioural Intention Among Young Adults Shoppers in Malaysia

Food waste has become a worldwide problem for many years, and Malaysia's high levels of waste are making climate change worse and putting food security at risk. The study explores the factors influencing food waste intention during online ordering among young adults in the Klang Valley using a purposive sampling method. Data were collected through an online questionnaire, resulting in 312 valid responses from young adults who have utilised at least one online delivery app. The data were analysed using the Statistical Package for the Social Sciences (SPSS). The findings reveal that attitude, subjective norm, perceived behavioural control, and price consciousness significantly influence the behavioural intention to reduce food waste, with attitude having the highest mean score. These insights offer policy recommendations for governments, restaurants, meal-ordering platforms, and consumers to efficiently minimise food waste.

Sistem pangan dalam pertanian berkelanjutan

Background: Food systems have issues such as the governance and economics of food production, sustainability, how food is disposed of, how food production affects the environment, and the impacts on the health of individuals and populations from the food. Findings: Agriculture currently faces major challenges worldwide, including feeding a growing world population, managing ecosystem goods and services in response to a changing global environment, and reducing poverty. The food systems approach has been widely used to identify, analyze and assess the impacts of system activities and outcomes to help identify intervention points to improve food security. Methods: This study uses a case study with data sources through primary and secondary data supported by the interview technique used. Conclusions: Recommendations for a sustainable food system are made through the formation of a more detailed sustainable food system policy that looks at environmental, social and economic aspects; optimizing the use of local food by ensuring the availability of land and water; inclusive access as food; applying the concept of sustainability to the food system cycle from upstream to downstream; expanding the diversity of staple food types and ensuring quality and nutrition; developing food barns with local wisdom and involving the community; maintaining food prices in each value chain; forming a lifestyle of consuming food responsibly; and minimize food waste.

Culinary Home Empowerment for Food Waste Prevention and Minimization: Feasibility and Efficacy Protocol.

The purpose of this research is to evaluate the feasibility, acceptability, and preliminary efficacy of a household food-waste prevention and minimization intervention, titled the Culinary Home Empowerment for Food Waste Prevention and Minimization (CHEF-WPM), which consists of a culinary education video series for home cooks. The specific aims are to (1) assess the effects of the intervention at a population level across process (feasibility, usage, acceptability, satisfaction) and preliminary efficacy (motivation, opportunity, ability) metrics and (2) assess the effects of the intervention at a community level across process (feasibility, usage, acceptability, satisfaction) and preliminary efficacy (motivation, opportunity, ability, household food waste, sustainable dietary practices) metrics. The intervention includes eight modules, each containing three to five brief videos, as well as downloadable recipes and worksheets. The evaluation will explore the effects of the program through two distinct investigations, namely (1) voluntary access to the intervention content in a population-based setting and (2) intensive delivery of the intervention content as part of a remote class in a community setting. Evaluation of the intervention in the population-based setting will use a single-arm, quasi-experimental post-test only study design. All home cooks who access the videos will be invited to answer a five-question post-video survey about acceptability, satisfaction, and potential implementation of the learning. A separate sample of individuals will be recruited to participate in a more in-depth evaluation (pre- and multiple post-test survey). Evaluation of the community-based intervention will use a mixed methods study design. Findings from the two distinct evaluation studies will be jointly discussed and triangulated to support larger conclusions about the intervention's desirability, impact on motivation, opportunity, ability, and food waste, and the potential directions for further improvement.