Food Loss and Waste Prevention Strategies from Farm to Fork

New insights in food security and environmental sustainability through waste food management

Food waste has been identified as one of the major factors that constitute numerous anthropogenic activities, especially in developing countries. There is a growing problem with food waste that affects every part of the waste management system, from collection to disposal; finding long-term solutions necessitates involving all participants in the food supply chain, from farmers and manufacturers to distributors and consumers. In addition to food waste management, maintaining food sustainability and security globally is crucial so that every individual, household, and nation can always get food. "End hunger, achieve food security and enhanced nutrition, and promote sustainable agriculture" are among the main challenges of global sustainable development (SDG) goal 2. Therefore, sustainable food waste management technology is needed. Recent attention has been focused on global food loss and waste. One-third of food produced for human use is wasted every year. Source reduction (i.e., limiting food losses and waste) and contemporary treatment technologies appear to be the most promising strategy for converting food waste into safe, nutritious, value-added feed products and achieving sustainability. Food waste is also employed in industrial processes for the production of biofuels or biopolymers. Biofuels mitigate the detrimental effects of fossil fuels. Identifying crop-producing zones, bioenergy cultivars, and management practices will enhance the natural environment and sustainable biochemical process. Traditional food waste reduction strategies are ineffective in lowering GHG emissions and food waste treatment. The main contribution of this study is an inventory of the theoretical and practical methods of prevention and minimization of food waste and losses. It identifies the trade-offs for food safety, sustainability, and security. Moreover, it investigates the impact of COVID-19 on food waste behavior.

Willingness to Pay a Higher Price for Pork Obtained Using Animal-Friendly Raising Techniques: A Consumers' Opinion Survey

In Italy, the consumption of pork meat is increasing, despite consumers' attitudes being addressed toward a greater sensitivity about animal welfare and its link with safe food. Considering the relatively high animal welfare standards and the divergence in public interest in farm animal welfare and ethical issues, the objective of this study-in continuation of our previous paper relating to consumer behavior and preferences in welfare-friendly pork breeding-was to investigate habits of pork consumers regarding pig welfare, principally evaluating their willingness to pay (WTP) a higher price for pork obtained using raising techniques with an approach based on animal welfare. An ad hoc questionnaire-based survey was submitted to consumers (n = 404) in Messina province, Italy. Results suggest that 47% of consumers were willing to pay an additional price for pork from farms that apply specific animal welfare standards. Positive correlations were between WTP and farming techniques (p = 0.001), organic farming methods (p = 0.001), and farms in which animal welfare is taken care of and guaranteed (p < 0.001). These findings suggest that consumers intend to pay a higher price for pork, like other animal products obtained using animal-friendly raising techniques. The sensitivity to the animal welfare of a single human being may influence consumers' attitudes toward pork consumption.

The status of the global food waste mitigation policies: experience and inspiration for China

Food waste has become a significant challenge faced by the community with a shared future for mankind, and it has also caused a considerable impact on China's food security. Scholars across disciplines, international organizations, and especially policymakers are increasingly interested in food waste. Policies are seen as a powerful factor in reducing food waste, but current research on related policies is more scattered. This paper summarizes and analyzes the experiences of food waste policy development and implementation by systematically reviewing the studies on food waste reduction policies. The results of this paper's analysis show that current global food waste policies are focused at the national strategic level, with approaches such as legislation, food donation, waste recycling, awareness and education, and data collection. At the same time, we find that the current experience of developed countries in policy formulation and implementation is beneficial for policy formulation in developing countries. And taking China as an example, we believe that developing countries can improve food waste policies in the future by improving legislation, guiding the development of food banks, promoting social governance, and strengthening scientific research projects. These policies will all contribute strongly to global environmental friendliness. In addition, we discuss some of the factors that influence the development of food waste policies and argue that in the future, more consideration needs to be given to the effects of policy implementation and that case studies should focus more on developing countries. This will contribute to the global sustainable development process.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10668-023-03132-0.

Effect of Moisture Content on Frictional Properties of Some Selected Grains in Indonesia

The frictional property of grains is one of the most important engineering parameters in developing solid bulk handling of grains. It is necessary for designing agricultural facilities and production process activities. These properties are expressed as internal friction angle (φ) and wall friction angle (θ), which are known to be affected by the moisture content of the grains. This research investigates the effect of moisture content on the values of φ and θ of some selected grains. In the research, some indigenous Indonesian grain types, including rough rice, white rice, corn, soybean, and coffee, each in three varieties and three level of moisture contents, were used as the research samples. Those angles were measured using a self-constructed direct shear cell apparatus. Three different normal loads for each grain type were used with three replications. It is concluded that φ and θ of the tested grains increase with moisture contents with different trends of increments. The relationship of those angles with moisture contents can be expressed as linear regression equations. The slope of the regression lines for both φ and θ is significantly affected by grain type (p<0.05). For φ, coffee (Excelsa) is the most susceptible to the change in moisture content, while dent corn (Hibrida) is the least affected one. For θ, soybean (Galunggung) is the most susceptible to the change in moisture content, while rough rice (Mapan 5) is the least affected one.

A Comprehensive Overview of Tomato Processing By-Product Valorization by Conventional Methods versus Emerging Technologies

The tomato processing industry can be considered one of the most widespread food manufacturing industries all over the world, annually generating considerable quantities of residue and determining disposal issues associated not only with the wasting of invaluable resources but also with the rise of significant environmental burdens. In this regard, previous studies have widely ascertained that tomato by-products are still rich in valuable compounds, which, once recovered, could be utilized in different industrial sectors. Currently, conventional solvent extraction is the most widely used method for the recovery of these compounds from tomato pomace. Nevertheless, several well-known drawbacks derive from this process, including the use of large quantities of solvents and the difficulties of utilizing the residual biomass. To overcome these limitations, the recent advances in extraction techniques, including the modification of the process configuration and the use of complementary novel methods to modify or destroy vegetable cells, have greatly and effectively influenced the recovery of different compounds from plant matrices. This review contributes a comprehensive overview on the valorization of tomato processing by-products with a specific focus on the use of "green technologies", including high-pressure homogenization (HPH), pulsed electric fields (PEF), supercritical fluid (SFE-CO₂), ultrasounds (UAE), and microwaves (MAE), suitable to enhancing the extractability of target compounds while reducing the solvent requirement and shortening the extraction time. The effects of conventional processes and the application of green technologies are critically analyzed, and their effectiveness on the recovery of lycopene, polyphenols, cutin, pectin, oil, and proteins from tomato residues is discussed, focusing on their strengths, drawbacks, and critical factors that contribute to maximizing the extraction yields of the target compounds. Moreover, to follow the "near zero discharge concept", the utilization of a cascade approach to recover different valuable compounds and the exploitation of the residual biomass for biogas generation are also pointed out.

Chitosan and other edible coatings to extend shelf life, manage postharvest decay, and reduce loss and waste of fresh fruits and vegetables

Fresh fruits and vegetables contain high percentage of water and continue metabolic activity after being harvested, resulting in ripening, increased sensitivity to decay-causing fungi, and consequent loss and waste. Edible coatings are prepared from naturally occurring renewable sources and can contribute to reducing waste, respecting environment, and consumer health. Chitosan and other edible coatings form a thin layer surrounding fresh produce that acts as a protective agent, extending shelf life, and have the potential to control their ripening process and maintain nutritional properties of the coated product. This review discusses recent research on the application of chitosan and other edible coatings to prevent fungal decay, keep the quality, and reduce fresh product waste.

Application of the IoT in the Food Supply Chain─From the Perspective of Carbon Mitigation

With the rising demands on supply chain transparency and food security, the rapid outspread of the Internet of Things (IoT) to improve logistical efficiency, and the rising penetration of sensor technology into daily life, the extensive integration of the IoT in the food sector is well anticipated. A perspective on potential life cycle trade-offs in regard to the type of integration is necessary. We conduct life cycle assessment (LCA) integrated with shelf life-food loss (SL-FL) models, showing an overall 5-fold leverage on carbon reduction, which is diet dependent and a function of income. Meat presents the highest leverage, 35 ± 11-times, owing to its high carbon footprint. Two-thirds (65%) of global sensors (1 billion) engaged in monitoring fruits and vegetables can mitigate less than 7% of the total reduced carbon emissions. Despite the expected carbon emission reductions, widespread adoption of the IoT faces multiple challenges such as high costs, difficulties in social acceptance, and regional variability in technological development. Furthermore, changes in the distribution of transportation resources and dealer service models, requirements regarding the accuracy of sensor data analysis, efficient and persistent operation of devices, development of agricultural infrastructure, and farmer education and training have all increased uncertainty. Nonetheless, the research trend in smart sensors toward smaller chips and the potential integration of machine learning or blockchain as further steps make it possible to leverage these advantages to facilitate market penetration. These insights facilitate the future optimization of the application of IoT sensors for sustainability.

Deep Learning Based Dual Channel Banana Grading System Using Convolution Neural Network

Deep learning has recently been hailed as the most advanced computer vision technology for image classification. The invention of convolutional neural network (CNN) simplified the effort of feature engineering. Classification of various stages of fruit maturity using machine learning algorithms is a difficult task since it is difficult to distinguish the visual features of the fruits at different maturity stages. Fruit ripeness is critical in agriculture since it impacts the quality of the fruit. Manually determining the maturity of the fruit has various flaws, including the fact that it takes a long time, needs a lot of labor, and can lead to inconsistencies. In developing countries, agriculture is one of the most important economic sectors. Created system can be employed in the food processing business, in real-life applications where the intelligent system’s accuracy, cost, and speed will improve the production rate and allow satisfying consumer demand. With small number of image samples, the system is capable of automating assembly line related work for classifying bananas along with sufficient overall accuracy. The noninvasive method will also be used to classify other clustered fruits or horticultural crops in the future. The system can either replace or aid human operators who can focus their efforts on fruit selection. The combined merits of RGB and HSI (hyperspectral imaging) for classification of bananas were highlighted in the present study; they have possible application as a model for classification of several types of horticultural produce. The multi-input model’s quick processing time can be a useful and handy technique in the farm field during postharvest procedures. Via a combination of CNN and MLP applied to data collected using RGB and hyperspectral imaging, the multi-input model reliably recognizes bananas with an accuracy level of 98.4 percent as well as an F1-score of 0.97. The AI algorithm predicted the size (large, medium, and microscopic) and perspective (front or rear half) of banana classes with 99 percent accuracy. In comparison to previous studies that simply employed RGB imaging, the presented model revealed the value of integrating RGB imaging and HSI approaches.

Effects of Corruption Control on the Number of Undernourished People in Developing Countries

Developing countries will be home to 85% of the world's population by 2030. Hence, it is important to ensure food security for them. This effort is not easy, as the number of undernourished people (NUP) in the world has increased. We investigated the impact of food and non-production factors on the NUP in developing countries. This study employed secondary data from 57 developing countries between 2002 and 2018. These countries come from three regions, namely Africa, Asia, and Latin America and the Caribbean. One-step and two-step generalized method of moments (sys-GMM) models were used to analyze the data. The findings showed that the food production index, cereal import dependency ratio, economic globalization index, and human capital index had different effects on the NUP in each region. The excellent news is that corruption control can help developing countries minimize their NUP. Based on the findings, we propose efforts to improve physical and economical food access and control corruption, and developing country governments and the international community must demonstrate a strong commitment to reducing the prevalence of undernourishment.

The Contribution of Data-Driven Technologies in Achieving the Sustainable Development Goals

The United Nations’ Sustainable Development Goals (SDGs) set out to improve the quality of life of people in developed, emerging, and developing countries by covering social and economic aspects, with a focus on environmental sustainability. At the same time, data-driven technologies influence our lives in all areas and have caused fundamental economical and societal changes. This study presents a comprehensive literature review on how data-driven approaches have enabled or inhibited the successful achievement of the 17 SDGs to date. Our findings show that data-driven analytics and tools contribute to achieving the 17 SDGs, e.g., by making information more reliable, supporting better-informed decision-making, implementing data-based policies, prioritizing actions, and optimizing the allocation of resources. Based on a qualitative content analysis, results were aggregated into a conceptual framework, including the following categories: (1) uses of data-driven methods (e.g., monitoring, measurement, mapping or modeling, forecasting, risk assessment, and planning purposes), (2) resulting positive effects, (3) arising challenges, and (4) recommendations for action to overcome these challenges. Despite positive effects and versatile applications, problems such as data gaps, data biases, high energy consumption of computational resources, ethical concerns, privacy, ownership, and security issues stand in the way of achieving the 17 SDGs.

Metal-based nanoparticles, sensors, and their multifaceted application in food packaging

Due to the global rise of the human population, one of the top-most challenges for poor and developing nations is to use the food produces safely and sustainably. In this regard, the storage of surplus food (and derived products) without loss of freshness, nutrient stability, shelf life, and their parallel efficient utilization will surely boost the food production sector. One of the best technologies that have emerged within the last twenty years with applications in the packaging of food and industrial materials is the use of green mode-based synthesized nanoparticles (NPs). These NPs are stable, advantageous as well as eco-friendly. Over the several years, numerous publications have confirmed that these NPs exert antibacterial, antioxidant, and antifungal activity against a plethora of pathogens. The storage in metal-based NPs (M-NPs) does not hamper the food properties and packaging efficiency. Additionally, these M-NPs help in the improvement of properties including freshness indicators, mechanical properties, antibacterial and water vapor permeability during food packaging. As a result, the nano-technological application facilitates a simple, alternate, interactive as well as reliable technology. It even provides positive feedback to food industries and packaging markets. Taken together, the current review paper is an attempt to highlight the M-NPs for prominent applications of antimicrobial properties, nanosensors, and food packaging of food items. Additionally, some comparative reports associated with M-NPs mechanism of action, risks, toxicity, and overall future perspectives have also been made.