Abstract Pecel is a traditional Javanese dish consisting of blanched, boiled, or steamed vegetables accompanied by Sambel Pecel , a sauce based on peanuts. Beyond its role as a daily staple, Pecel serves as a cultural emblem of identity, resilience, and ecological knowledge. Despite its centrality in Javanese culinary traditions, Pecel has received limited scholarly attention as an ethnic food that integrates biodiversity, symbolism, and health. This narrative review integrates interdisciplinary perspectives to examine Pecel’s preparation, symbolism, regional variations, and nutritional profile. Data were drawn from archival sources, ethno-gastronomic studies, and food composition databases. The peanut sauce contributes plant-based protein, unsaturated fats, and bioactive compounds such as resveratrol, flavonoids, and phytosterols, while additional ingredients, including tamarind, kaffir lime leaves, and aromatic ginger, enhance both sensory qualities and functional properties. Complementing this base, the diverse array of vegetables, herbs, and edible flowers provides essential vitamins, minerals, fibre, and phytochemicals associated with antioxidant, anti-inflammatory, cardioprotective, and other bioactivities. Together, these elements create synergistic health effects that support satiety, metabolic regulation, and long-term disease prevention. Moreover, the existence of multiple regional variants such as Pecel Ndeso , Pecel Madiun , Pecel Kecombrang , Pecel Gambringan , Pecel Semanggi , Pecel Gudeg , Pecel Pakis, Pecel Yogya , Pecel Tumpang , Pecel Punten , and Pecel Latoh demonstrates Pecel’s adaptability to local biodiversity and cultural practices. Beyond its gastronomic role, Pecel emerges as a holistic foodway that unites nutrition, ecology, and cultural heritage, underscoring its significance for both heritage preservation and promoting sustainable diets.
We present CERES (Calibrated Early-warning and Risk Estimation System), an automated probabilistic forecasting system for acute food insecurity. CERES generates 90-day ahead probability estimates of IPC Phase 3+ (Crisis), Phase 4+ (Emergency), and Phase 5 (Famine) conditions for 43 high-risk countries globally, updated weekly. The system fuses six data streams, precipitation anomalies (CHIRPS), vegetation indices (MODIS NDVI), conflict events (ACLED), IPC classifications, food consumption scores (WFP), and cereal price indices (FAO/WFP) - through a logistic scoring model with author-specified initial coefficients and parametric input-perturbation intervals (n=2,000 draws). In historical back-validation against four IPC Phase 4-5 events selected for data completeness, CERES assigned TIER-1 classification in all four cases; these are in-sample sanity checks only, not prospective performance claims. All prospective predictions are timestamped, cryptographically identified, and archived for public verification against IPC outcome data at the T+90 horizon. To the author's knowledge, CERES is the first famine early warning system that is simultaneously: (1) probabilistic, (2) open-access, (3) continuously running, (4) machine-readable at prediction level, and (5) committed to public prospective verification of every prediction made.
Reliance on images for dietary assessment is an important strategy to accurately and conveniently monitor an individual's health, making it a vital mechanism in the prevention and care of chronic diseases and obesity. However, image-based dietary assessment suffers from estimating the three dimensional size of food from 2D image inputs. Many strategies have been devised to overcome this critical limitation such as the use of auxiliary inputs like depth maps, multi-view inputs, or model-based approaches such as template matching. Deep learning also helps bridge the gap by either using monocular images or combinations of the image and the auxillary inputs to precisely predict the output portion from the image input. In this paper, we explore the different strategies employed for accurate portion estimation.
To develop a grain storage energy pile-based quasi-low-temperature storage system that utilizes clean and green geothermal energy to provide low-temperature cooling for grain storage facilities, numerical simulation methods were employed to investigate the effects of heat exchange pipe flow velocity and system operation time on the thermal performance and energy efficiency of the grain storage energy pile system. An optimized operational strategy was proposed to enhance the technical and economic performance of the system, as well as its energy-saving and carbon-reduction capabilities. Taking a grain storage facility in Zhengzhou as a case study, the analysis conducted under summer cooling conditions demonstrated that the flow velocity of the energy pile system significantly influences the heat exchange capacity and energy consumption of the pile. Reasonable control of operation and intermittent periods can not only ensure energy-saving effects but also meet the quasi-low-temperature storage requirements for grain. Compared to the unoptimized scheme, the optimized energy pile regulation scheme reduced energy consumption by 18.7%. Furthermore, when compared to other cooling solutions such as grain cooling machines, air conditioning, and ground-source heat pumps, the energy consumption of the energy pile system was reduced by 65.6%, 45.9%, and 25.0%, respectively.
Food processing and manufacture, Nutrition. Foods and food supply
Kyriakos Kalpakoglou, Lorena Calderón-Pérez, Noemi Boqué
et al.
IntroductionModern lifestyle trends such as sedentary behaviors and unhealthy diets pose a major health challenge, as they have been related to multiple pathologies. Following a healthy diet has become increasingly difficult in today’s fast-paced world. Given this context, artificial intelligence can play a pivotal role in addressing the challenge.MethodsWe present an AI-based nutrition recommendation system that generates balanced, personalized weekly meal plans tailored to the nutritional needs and preferences of healthy adults. The proposed method retrieves dishes and meals from an expert-validated database featuring Mediterranean foods, following a structured four-step process to recommend a weekly Nutrition Plan (NP).ResultsThe system’s performance is evaluated across 4,000 generated user profiles in three key areas: (a) dish/meal filtering accuracy based on user-specific parameters (e.g., allergies), (b) diversity of meals and food group balance, and (c) accuracy in caloric and macronutrient recommendations. The system achieves high accuracy in terms of suggested caloric and nutrient content while ensuring seasonality, diversity, and food group variety.DiscussionWith solid accuracy in filtering, diversity, and caloric/macronutrient suggestions, the proposed system offers a promising solution to modern dietary challenges.
Michelle Canning, Michael Bazaco, Brett Weed
et al.
The Centers for Disease Control and Prevention (CDC), working closely with public health and regulatory partners, investigate outbreaks of foodborne illness. Outbreak investigations continue to identify melons as an important source of outbreak-associated illness. We characterized the epidemiology of outbreaks linked to melons from 2012 to 2021, summarized public health responses to these outbreaks, and identified potential opportunities for prevention efforts and interventions. We queried CDC’s Foodborne Disease Outbreak Surveillance System (FDOSS) for all Salmonella, Escherichia coli (E. coli), and Listeria monocytogenes outbreaks linked to melons and collected data from the U.S. Food and Drug Administration’s (FDA) Coordinated Outbreak Response & Evaluation (CORE) Network internal databases for information regarding outbreak investigations that involved FDA’s evaluation and response activities. Descriptive statistics were calculated for outbreaks overall, by melon type, and by etiology, including the number of outbreaks, illnesses, hospitalizations, deaths, patient demographics including sex and age, outbreak duration, investigation duration, seasonality, serotypes, and food preparation and consumption settings. During 2012–2021, 18 outbreaks were linked to melons. The median number of outbreaks per year was 2 (range: 0–3); there were no melon-associated outbreaks reported in 2015. These 18 outbreaks resulted in 821 illnesses, 251 hospitalizations, and 10 deaths. More than half of the melon-associated Salmonella outbreaks in this reporting timeframe were linked to cantaloupe. Outbreak illnesses clustered in the U.S. Midwest and in outbreaks where the growing area was known, most were produced domestically (4/7, 57%), frequently grown in Indiana. Traceback and epidemiologic investigations demonstrated that contamination can occur at all points along the farm-to-fork continuum, requiring the need for pathogen control at every step.
Food processing and manufacture, Nutrition. Foods and food supply
Aim: This study aimed to assess the viability of Lacticaseibacillus rhamnosus GR-1 in four yogurt formulations with or without flax, chia, and hemp seeds during multiple time points across fermentation and cold storage. Additionally, the study evaluated consumer acceptance of the seed-fortified yogurts based on ratings of appearance, flavour, texture, and overall acceptability. Methods: Four yogurt samples were inoculated with the probiotic strain L. rhamnosus GR-1 and fermented for up to 6 h at 38°C, followed by refrigerated storage at 4°C for up to 30 days, respectively. Microbial enumeration was performed throughout fermentation and storage to assess the viability of L. rhamnosus GR-1. 84 participants engaged in a sensory evaluation where the consumer acceptability of the yogurt samples was evaluated. Results: Microbial analysis showed consistent viable counts of L. rhamnosus GR-1 across all fermentation and storage time points, where the sample containing chia seeds maintained the highest levels of probiotic viability. pH significantly decreased (p < 0.05) during fermentation in all treatments, with further reductions during storage only in the flax, hemp, and chia samples. Sensory evaluation revealed that the control scored highest in appearance, flavour, texture, and overall acceptability (p < 0.001). While participants showed the highest preference for the control sample, 77% indicated they would consider purchasing probiotic yogurt. Conclusions: Overall, adding flax, hemp, and chia seeds supports the viability of L. rhamnosus GR-1 in probiotic yogurt. Seed mucilage may play a vital role in the growth and viability of probiotics in yogurt products. The findings from this research provide a valuable foundation for the development of more nutrient-dense and consumer-friendly probiotic yogurt products.
Food processing and manufacture, Nutrition. Foods and food supply
The Best-Worst Method (BWM) has emerged as a prominent multi-criteria decision-making method for determining the weights of the decision criteria. Among various BWM models, this research focuses on the linear model of the BWM. This model calculates weights by solving an optimization problem, necessitating optimization software. In this article, we present a novel framework that solves this optimization model mathematically, yielding an analytical expression for the resultant weights, thus eliminating the requirement for an optimization software. The proposed approach enhances both the conceptual clarity of the underlying optimization process and the computational efficiency of the model. Based of this framework, we demonstrate the model's limited response to data variations, i.e., its lower data sensitivity. We also compute the values of consistency index for the linear BWM, which are required to calculate the consistency ratio - a consistency indicator used for assessing inconsistency in input data. Finally, we illustrate the validity and applicability of the proposed approach through five numerical examples and a real-world case study that ranks eighteen drivers across three categories - Industry 4.0, sustainability, and circular economy - in relation to sustainable development goals-driven agri-food supply chains.
The knowledge transfer from 3D printing technology paved the way for unlocking the innovative potential of 3D Food Printing (3DFP) technology. However, this technology-oriented approach neglects userderived issues that could be addressed with advancements in 3DFP technology. To explore potential new features and application areas for 3DFP technology, we created the Mobile Food Printer (MFP) prototype. We collected insights from novice chefs for MFP in the restaurant context through four online focus group sessions (N=12). Our results revealed how MFP can be applied in the current kitchen routines (preparation, serving, and eating) and introduce novel dining experiences. We discuss our learnings under two themes: 1) dealing with the kitchen rush and 2) streamlining workflows in the kitchen. The opportunities we present in this study act as a starting point for HCI and HFI researchers and encourage them to implement mobility in 3DFP with a useroriented lens. We further provide a ground for future research to uncover potentials for advancing 3DFP technology.
This paper presents a novel approach to optimizing pricing and replenishment strategies in fresh food supermarkets by combining Long Short-Term Memory (LSTM) networks with Particle Swarm Optimization (PSO). The LSTM model, enhanced with an attention mechanism, is used to predict sales volumes, pricing trends, and spoilage rates over a seven-day period. The predictions generated by the LSTM model serve as inputs for the PSO algorithm, which iteratively optimizes pricing and replenishment strategies to maximize profitability while adhering to inventory constraints. The integration of cost-plus pricing allows for dynamic adjustments based on fixed and variable costs, ensuring real-time adaptability to market fluctuations. The framework not only maximizes profits but also reduces food waste, contributing to more sustainable supermarket operations. The attention mechanism enhances the interpretability of the LSTM model by identifying key time points and factors influencing sales, improving decision-making accuracy. This methodology bridges the gap between predictive modeling and optimization, offering a scalable solution for dynamic pricing and inventory management in fresh food retail and other industries dealing with perishable goods.
Disaster-induced power outages create cascading disruptions across urban lifelines, yet the timed coupling between grid failure and essential service access remains poorly quantified. Focusing on Hurricane Beryl in Houston (2024), this study integrates approximately 173000 15-minute outage records with over 1.25 million visits to 3187 food facilities to quantify how infrastructure performance and human access co-evolve. We construct daily indices for outage characteristics (intensity, duration) and food access metrics (redundancy, frequency, proximity), estimate cross-system lags through lagged correlations over zero to seven days, and identify recovery patterns using DTW k-means clustering. Overlaying these clusters yields compound power-access typologies and enables facility-level criticality screening. The analysis reveals a consistent two-day lag: food access reaches its nadir on July 8 at landfall while outage severity peaks around July 10, with negative correlations strongest at a two-day lag and losing significance by day four. We identify four compound typologies from high/low outage crossed with high/low access disruption levels. Road network sparsity, more than income, determines the depth and persistence of access loss. Through this analysis, we enumerate 294 critical food facilities in the study area requiring targeted continuity measures including backup power, microgrids, and feeder prioritization. The novelty lies in measuring interdependency at daily operational resolution while bridging scales from communities to individual facilities, converting dynamic coupling patterns into actionable interventions for phase-sensitive restoration and equity-aware preparedness. The framework is transferable to other lifelines and hazards, offering a generalizable template for diagnosing and mitigating cascading effects on community access during disaster recovery.
Tibebu Kassawmar, Tibebu Kassawmar, Ermias Teferi
et al.
Analysis of grain production performance can provide reference information to explore multiple cropping options and further improve the resource use efficiency of farming methods. This study investigated the spatiotemporal dynamics of grain production performance and efficiency of major crop production systems (CPS) in the Ethiopia’s Blue Nile Basin. The results show that only 39% of the basin is currently cultivated, although a significant cropland expansion (10%) was recorded between 1985 and 2020. The study identified 11 major CPS, mostly practiced in the basin. Of these, single cropping based on the main rainy season (Meher-Only) covers the largest area (26%), followed by Meher-Residual-Intermittent (12%) and Meher-Belg-Dependable (11%). Extended-Meher, Meher-Residual-Dependable, Meher-Residual-Intermittent, and Meher-Belg-Dependable are the four more powerful CPS with higher efficiency. Comparatively, CPS practiced in Wet-Woyna-Dega and Wet-Dega have better overall performance. Findings confirm that agricultural space management (land) and green-water (rainfall) utilization are the most influential factors, followed by land use planning and land use systems (CPS) invention. As landscape suitability for grain production governs future performance, in the low elevation and flood plains parts of the basin, the possibility of creating additional space into the food system is very high. In mountainous and high-altitude regions, the efficiency of grain production will decrease because incorporating additional arable land into the food system is trivial. In the last three decades, in BNB, only 10% of arable land (equivalent to 30 million quintals of food) has been added to the good system, which can support approximately 6 million people. Compared to the population growth of the basin (12 million 1985–2020), its contribution to the food system was less than 50%. This confirms that multiple cropping systems, such as Residual moisture-based CPS, have played a significant role in boosting the food system in the basin. Therefore, improving grain production performance/efficiency requires targeted investments, including the invention of more adaptable crop varieties, efficient cropping practices, and the introduction of advanced agricultural space and water management technologies. The results of the study will help identify important policy gaps and suggest possible options to enhance residual farming and other multiple cropping systems.
Nutrition. Foods and food supply, Food processing and manufacture
Conor M. Artman, Aditya Mate, Ezinne Nwankwo
et al.
We developed a common algorithmic solution addressing the problem of resource-constrained outreach encountered by social change organizations with different missions and operations: Breaking Ground -- an organization that helps individuals experiencing homelessness in New York transition to permanent housing and Leket -- the national food bank of Israel that rescues food from farms and elsewhere to feed the hungry. Specifically, we developed an estimation and optimization approach for partially-observed episodic restless bandits under $k$-step transitions. The results show that our Thompson sampling with Markov chain recovery (via Stein variational gradient descent) algorithm significantly outperforms baselines for the problems of both organizations. We carried out this work in a prospective manner with the express goal of devising a flexible-enough but also useful-enough solution that can help overcome a lack of sustainable impact in data science for social good.
This research builds upon the Latvian Twitter Eater Corpus (LTEC), which is focused on the narrow domain of tweets related to food, drinks, eating and drinking. LTEC has been collected for more than 12 years and reaching almost 3 million tweets with the basic information as well as extended automatically and manually annotated metadata. In this paper we supplement the LTEC with manually annotated subsets of evaluation data for machine translation, named entity recognition, timeline-balanced sentiment analysis, and text-image relation classification. We experiment with each of the data sets using baseline models and highlight future challenges for various modelling approaches.
Houda Elfane, Khadija Sahel, Sanaa El-Jamal
et al.
Background: Low birth weight (LBW) is a major health problem responsible for neonatal mortality and morbidity such as diabetes, obesity and cardiovascular disease in adulthood.
Objective. This case-control study aims to compare data on the intake of energy, macro and micronutrient in two groups of pregnant women, who gave birth to low birth weight (LBW) babies named cases and those who gave birth to babies of normal weight (NW) called controls.
Material and methods: The collection of information was done using an established questionnaire for 400 pregnant women, allowing the collection of data on socio-demographic and obstetrical factors. Nutritional intake was obtained by recording food consumption using the 24-hour recall method. Anthropometric measurements of parturient and fundal height (FH) were measured before delivery.
Results: The mean FH of the cases was 25.69±0.13 and that of the controls was 31.83±0.06. The gestational age of the cases was on average 31.65±0.21 week of amenorrhea (WA) against 38.04±0.08 WA for the controls. 37% of LBW newborns had an Apgar score < 7 (p< 0.001) and 71% were hospitalized in neonatal intensive care (p<0.001). Micronutrient deficiency was raised and concerned calcium 34.02% vs 60.65%, folates 48.32% vs 68.01% and iron 50.85% vs 66% in cases and controls respectively. Newborns from NW had a weight of 3395.5±15.99 against 1957.25±30.72 for those from LBW.
Conclusion: This study shows that the nutritional intake did not cover all the nutrient needs of the pregnant women studied and that newborns with LBW are associated with an altered anthropometric status. Improving the living conditions of mothers, good monitoring of pregnancy, and good nutritional education can significantly improve the nutritional status with the same food intake and should be integrated into the nutritional intervention strategies.
Nutrition. Foods and food supply, Industrial medicine. Industrial hygiene
Manal, A. Sorour, Ashraf, A. Anwar, Omnia, E Salama
The most crucial factors to consider when creating soybean milk, a device for transferring heat between two fluids, are the heating conditions. The field of thermal engineering is particularly active when it comes to heat exchanger design optimization. Using performance data on the use of cooling soybean milk with chilled water, an optimum channel flow velocity and an ideal number of plates were determined. To determine the optimum channel flow velocity and plate count, performance data on the use of cooling soybean milk with cold water were used. Using a Brookfield rheometer, the apparent viscosity of soybean milk was determined on both the hot and cold sides. Additionally, the annual cost, purchase cost, and fixed cost were calculated. Pressure drops and Reynolds numbers for fluids were computed. For an annual production rate of 43797.65 m3/year, it was discovered that the minimum flow velocity is 2.25 m/s, the ideal number of plates is 17, and the minimal total yearly cost is 35000 L.E./year.
Food processing and manufacture, Nutrition. Foods and food supply
High-performance, environmentally-friendly biodegradable packaging as substitutes for conventional plastics becomes severe demand to nowadays economy and society. As an aliphatic aromatic copolyester PBAT is recognized as the preferred alternative to traditional plastics. However, the relatively high cost and weak properties obstacles the widespread adoption of PBAT. Modification pertaining to improve the properties, lower the cost, and include the functional additives of PBAT is a continuous effort to meet the needs of food accessibility, antibacterial properties, oxygen resistance, high mechanical strength, stable size, low moisture absorption, and various gas permeability for commercial competitiveness.