Search Results (55)

Peach fruit develops chilling injury (CI) during cold storage, yet the symptoms are milder at 0 °C than at 5 °C; however, the underlying mechanism remains unclear. This study demonstrated that peach fruit stored at 0 °C maintains higher levels of structural phospholipids and membrane lipid unsaturation, along with lower activities of lipase and lipoxygenase (LOX), thereby alleviating membrane damage. Using lipidomics, we identified phosphatidic acid (PA) as a lipid closely associated with CI characteristics and revealed that it plays a signaling role at the early stage of storage at 0 °C, while its reduced levels at the later stage alleviate membrane damage, thereby participating in the regulation of CI in peach fruit. Moreover, at 0 °C, Phospholipase D (PLD) activity exhibited an initial increase followed by a decrease, which was consistent with the overall changes in PA content. During storage, PLD activity and PA content at 0 °C were significantly lower than those at 5 °C and 15 °C. These findings highlight the critical role of PA in temperature-dependent regulation and provide potential molecular targets for precise management of CI in the postharvest cold chain of peach fruit. Full article

The white peach scale, Pseudaulacaspis pentagona (Targioni-Tozzetti) (Hemiptera: Diaspididae), is a highly polyphagous insect pest of global phytosanitary relevance affecting fruit trees, perennial crops, and ornamental plants in temperate and subtropical regions. Its invasive success is largely driven by high thermal tolerance, a wide host range, and strong survival capacity under postharvest handling and cold-chain storage, which greatly enhances its potential for long-distance dispersal through international trade of fresh fruit and plant material. A systematic review and meta-synthesis of 105 scientific studies published between 1958 and 2026 identified key research areas, including geographic distribution and invasion pathways, host plants and varietal susceptibility, temperature-dependent life history, agricultural impact and quarantine risk, chemical and biological control strategies, and the development of phenology-based monitoring and prediction tools using thermal models and pheromones. Although recent official reports do not confirm the presence of P. pentagona in Ecuador, climate suitability modeling and evidence of long-term survival during cold storage indicate a high risk of introduction and establishment, particularly in inter-Andean valleys. Consequently, preventive phytosanitary surveillance and integrated pest management strategies tailored to Ecuadorian Andean fruit production are proposed, emphasizing phenological monitoring, nursery and agro-urban inspections, and the conservation of natural enemies as a foundation for sustainable management of this emerging pest. Full article

Loquat is a highly perishable, non-climacteric fruit that is prone to chilling injury, decay, and eating quality deterioration during cold storage. This study evaluates the effectiveness of tragacanth gum (TG) as a plant-based edible coating to mitigate postharvest chilling injury (CI) and preserve the eating quality of loquat fruit. Two commercial cultivars, ‘Sufaid’ and ‘Surkh’, were coated with 1% TG and stored at 4 ± 1 °C with 90 ± 5% relative humidity for 20 days, followed by 2 days at 20 °C ± 1 °C (specific focus on retail handling). TG-coated fruits exhibited significantly reduced weight loss and lower decay compared to controls. TG application alleviated CI symptoms and reduced respiration rates. TG-treated fruits maintained higher levels of titratable acidity, total soluble solids, and ascorbic acid. TG application also elevated phytochemical levels and antioxidant potential, reinforcing the fruit’s biochemical defenses against postharvest stress. Furthermore, TG treatment suppressed oxidative stress by lowering malondialdehyde and hydrogen peroxide levels and enhanced the activities of key antioxidant enzymes (SOD, CAT and APX). TG-coated fruits also showed improved taste, flavor, and consumer acceptability at shelf after storage. In conclusion, results indicate that application of TG coating represents a sustainable, eco-friendly strategy to alleviate CI and improve postharvest eating quality of commercial loquat cultivars, offering potential for broader adoption in the fresh fruit supply chain. Full article

Background: Artificial intelligence (AI) is increasingly being proposed for postharvest food-safety control of animal-source foods, but its practical value depends on whether models can support real decisions rather than only report high accuracy. Methods: This narrative review used a structured literature mapping of peer-reviewed work, mainly from 2020 to 2025, identified through database searches and citation tracking using combined terms for artificial intelligence, machine learning, animal-source foods, postharvest food safety, slaughterhouse inspection, cold-chain monitoring, traceability, authenticity, HACCP, validation, and regulatory applicability. Results: The most implementation-proximate applications are computer vision prescreening in slaughterhouses and processing plants, sensor- and IoT-based cold-chain surveillance, freshness and adulteration screening, and digital traceability systems. Across these areas, stronger evidence is associated with clearly defined control points, transparent reference methods, external or temporal validation, auditable data flows, and documented human oversight. The main weaknesses are single-site datasets, retrospective designs, incomplete reporting of reference methods, limited workflow testing, and insufficient attention to false alerts, fallback procedures, and governance. Conclusions: AI should be viewed as targeted decision support, not as a replacement for established food-safety control. Future studies should prioritize prospective, multi-site, workflow-embedded validation and show how alerts lead to documented corrective or verification actions. Full article

Coriandrum sativum L. is a widely cultivated aromatic herb exhibiting substantial variation in essential oil quality and yield among different accessions. This study assessed germination performance, essential oil composition, yield, chemotype distribution, and fragrance characteristics in 48 C. sativum accessions collected from 19 countries spanning four Köppen–Geiger climate zones: Tropical/Subtropical, Arid/Semi-arid, Temperate, and Continental/Cold. All accessions were grown under standardized field conditions, and essential oils were extracted from aerial parts using steam distillation followed by direct-GC/MS analysis. Seed germination rates were consistently high (mean: 92.25 ± 5.85%; range: 71–100%) and did not differ significantly by climate zone (Kruskal–Wallis H = 5.500, p = 0.139) or country of origin (H = 21.833, p = 0.240), indicating that post-harvest management, rather than climatic provenance, primarily determines seed viability. Essential oil profiles were dominated by (E)-2-decenal (mean: 44.56%), decanal (11.75%), and 2-dodecenal (13.47%). Principal component analysis (PCA) of 18 compounds detected in at least 19 accessions accounted for 70.16% of total variance across five components, with PC1 reflecting a gradient from long-chain saturated aldehyde accumulation to linalool enrichment. Permutational multivariate analysis of variance (PERMANOVA) demonstrated significant compositional differentiation among climate zones (Pseudo-F = 1.662, p = 0.028), whereas country-level grouping was not significant (p = 0.256). Tropical/subtropical accessions exhibited the highest linalool content (mean: 15.39 ± 8.71%) and essential oil yield (mean: 0.269 ± 0.120% v/w), significantly surpassing arid/semi-arid and temperate zones (p < 0.05). Two chemotypes were identified, (E)-2-decenal (91.7%) and linalool (8.3%), each associated with distinct fragrance profiles (earthy/aldehydic/woody versus herbal/sweet, respectively). These findings demonstrate that climate zone of origin is significantly associated with C. sativum essential oil composition and productivity, with tropical/subtropical accessions providing superior yield and linalool content. Chemotype characterization offers an additional criterion for germplasm selection in targeted industrial applications. Full article

Ethyl formate (EF) is a promising alternative to methyl bromide for postharvest disinfestation, but berry export chains require efficacy under refrigerated handling without loss of marketable quality. Using spotted-wing drosophila (Drosophila suzukii) in blueberries as a cold-chain model, we compared stage-specific tolerance at 5 to 15 °C and identified 1-day-old eggs as the most tolerant stage, with mortality strongly temperature dependent. Egg-stage concentration to mortality relationships were quantified under 4 h exposures at 5, 10, and 15 °C to nominate temperature-specific intensities within EF flammability safety limits. Candidate schedules (69, 83, and 94 mg·L⁻¹ for 4 h at 5, 10, and 15 °C) were confirmed by verification-scale zero-survivor tests under simulated cold-chain conditions, achieving complete control of the most tolerant egg stage. Post-treatment quality was assessed after 1, 7, and 14 days of cold storage. Weight loss, firmness, total soluble solids, titratable acidity, sucrose, and proanthocyanidins were driven mainly by storage time and temperature. EF effects were limited to transiently elevated respiration early in storage, with no detectable injury, decay, or adverse changes in appearance or other physicochemical attributes. Overall, EF provides a cold-chain compatible processing window integrating efficacy, operational safety, and quality preservation for refrigerated blueberry export logistics. Full article

This field study examined extant aquatic food production and marketing in the three coastal states of Lagos, Ogun, and Ondo before IMTA across 15 Local Government Areas (LGAs)/Local Council Development Areas (LCDAs). Marketing mix practices in coastal aquatic food systems were explored through a structured, qualitative assessment using a multi-value chain perspective. Monthly sales volumes most frequently fell within the range of 1–5 tonnes. The local market was dominant, with some sales in the international markets. Respondents asserted that post-harvest processing was diverse, and some were satisfied with the technology available to preserve their products. Cold storage practices across coastal states were hindered by unreliable power supply. Zero-level channel distribution dominated among traders, with over 90% relying on word-of-mouth (WOM) to promote their products. Consumers showed a strong preference for the quality of local products and expressed openness to incorporating seaweed into their purchases. Health benefits, taste, and other reasons for purchase decisions varied significantly across the state χ² (df = 8, n = 300) = 92.39, p < 0.001. These findings provide a baseline for IMTA in Nigeria, highlighting existing strengths, market dynamics, and infrastructure gaps that must be addressed to support sustainable integration. Full article

Reliable potato quality monitoring during postharvest handling requires compact sensing systems that can acquire chemically relevant information while operating on irregular tuber surfaces. In this study, a Flexible Spectral Sensing Gripper (FSSG) was developed by integrating a low-cost 12-channel visible/near-infrared (Vis/NIR) spectral sensor array, electronic components, and an ESP32-S microcontroller onto a flexible printed circuit (FPC) substrate encapsulated with PDMS. By embedding the sensing units into the grasping interface, the FSSG enables conformal, multi-point spectral acquisition during potato handling, reducing optical-coupling uncertainty associated with unstable contact. Spectral reflectance data were collected from potato tubers, and dry matter content (DMC) and starch content (SC) were determined by standard chemical analysis as reference values. Multiple linear regression (MLR) and partial least squares regression (PLSR) models were compared under Norm, SNV, MSC, SNV-Norm, and MSC-Norm preprocessing conditions, and support vector machine (SVM) classification was used to distinguish healthy and artificially induced deteriorated samples. Normalization combined with MLR provided the best performance among the evaluated regression approaches, achieving cross-validation coefficients of determination ($R_{CV}^2$) of 0.847 and 0.817 and RPD values of 2.557 and 2.345 for DMC and SC, respectively. The SVM model achieved 98.67% accuracy for healthy versus artificially induced deteriorated potato samples. Overall, the FSSG demonstrates the value of combining gripper-integrated spectral sensing with interpretable chemometric modeling for potato quality screening. The FSSG enables real-time non-destructive quality prediction and disease-detected classification of potatoes, improves sorting accuracy and production efficiency, and provides general sensing solutions for controlled-environment agriculture, cold-chain logistics, and value-added processing of agricultural products. Full article

As representatives of early-flowering herbaceous peony types, certain cultivars known as the ‘Coral’ series are highly prized in the global cut flowers market for their unique dynamic color transitions from orange-red (amber) to creamy yellow during the florescence and senescence periods. Despite their strong growth vigor and high commercial value, these cultivars face critical postharvest preservation challenges, most notably rapid petal abscission and short vase life. Previous studies have confirmed that postharvest quality deterioration of these peony cut flowers, including undesired color fading and accelerated senescence of petals, is closely associated with ethylene and ROS accumulation. To address these development impediments, systematic optimization of the entire industrial chain is essential. Proposed countermeasures include preharvest regulation of environmental conditions and cultivation practices to establish a foundation for quality formation, as well as postharvest strategies such as precise harvest timing, anti-ethylene treatments, and full cold-chain logistics. Meanwhile, simplifying the distribution system and optimizing terminal vase preservation techniques are also crucial to maintain postharvest quality. In the long term, promoting sustainable development of the global cut-flower industry will require breeding new germplasm with low ethylene sensitivity from a global perspective, continuously optimizing agronomic practices to overcome year-round supply constraints, and accelerating the application of intelligent technologies such as the Internet of Things (IoT) in full chain quality management. Full article

Post-harvest losses of fruits and vegetables are an important bottleneck in food systems of countries around the world, with 30–50% of perishable food items lost between farm and consumer, smallholder farmers in low-and-middle income countries (LMICs) with poor cold chain infrastructures facing a disproportionate burden. Evaporative cooling (EC) is a low-cost and energy-efficient alternative to mechanical refrigeration; however, traditional systems are operated in one position and are dependent on climate, which restricts its performance. The combination of Internet of Things (IoT) sensing, machine learning (ML), and the advanced control theory has made intelligent evaporative cooling systems (IECS) adaptive, data-driven platforms that can regulate the environment in real-time and optimise autonomously. This is a systematic literature review that was carried out according to PRISMA 2020, summarising 94 peer-reviewed articles published in 2018–2025 to map the technological landscape, performance indicators, and research directions of the field of post-harvest fruit and vegetable preservation using IECS. Findings indicate that IECS can considerably lower the storage temperatures, increase the shelf life by 50–200%, and reduce energy consumption by 75–90% compared to traditional refrigeration, and the payback period is as short as 1.2 years. In arid conditions, ML models are accurate in prediction with an R² of 0.98. The gaps in the research identified are a lack of validation in wet climatic conditions, non-existent standardised Ag-IoT protocols, inadequate Food–Energy–Water (FEW) nexus calculation, and no explainable AI (XAI) interfaces. An example of a conceptual framework of four layers synthesised is proposed to direct next-generation research and implementation of the IECS. Full article

Cold thermal energy storage (CTES) has emerged as a critical clean-energy technology for enhancing postharvest management in rural agricultural supply chains, where losses often exceed 20–40% due to inadequate cooling infrastructure and unreliable electricity. This review synthesizes the recent literature on CTES systems, including ice-, chilled-water-, and phase-change material (PCM)-based storage, with a focus on smart-farm integration, IoT-based monitoring, predictive control, and solar photovoltaic (PV) energy coupling. Trends in village-level cold rooms, micro-dairy milk cooling, and fruit–vegetable storage are critically examined, highlighting efficiency, resilience, and scalability relative to battery-dominant and conventional refrigeration systems. Current research gaps are identified in multi-scale modeling, PCM stability, state-of-charge estimation, techno-economic optimization, and AI-based operational strategies. Addressing these gaps is essential to realizing sustainable, low-carbon, and energy-efficient rural cold chains. Full article

In the postharvest supply chain, directly moving Korla fragrant pears from ice temperature storage to ambient display readily induces quality deterioration, shortens shelf life, and causes substantial economic losses. Using Korla fragrant pears as the study system, we propose a gradual rewarming protocol. We optimised temperature and time parameters with response surface methodology and validated the protocol by comparing changes in shelf-life quality and microstructure under gradual versus direct rewarming. Results indicate that rewarming at 6 °C for 12 h is the optimal condition for maintaining overall postharvest quality. Under these conditions, gradient rewarming significantly improved physical and chemical quality. Compared with direct rewarming, weight loss decreased by 2.6 percent, firmness increased to 4.23 kg/cm², the peak soluble solids content reached 12.5%, the respiratory peak was delayed and the rate slowed, and shelf life was extended by about 80%. Microstructural verification showed a more compact cellular arrangement, reduced intercellular spaces, and the mildest degree of cell collapse in pears subjected to gradient rewarming. The proposed gradient rewarming protocol provides theoretical and practical guidance for optimising temperature control strategies across the postharvest cold chain and retail stages for Korla fragrant pears. Full article

Global citrus exports rely heavily on temperature-controlled logistics to safeguard fruit quality and minimise postharvest losses. Temperature management remains a critical factor governing citrus quality throughout export logistics. Yet the extent to which historical shipment temperature data can meaningfully predict fruit condition at arrival has never been systematically assessed. This study presents a comprehensive review of how historical temperature records have been used to assess citrus quality within export supply chains, highlighting the lack of longitudinal temperature–quality correlations in existing research. Using PRISMA 2020 guidelines and Kitchenham’s three-phase review framework, 35 relevant peer-reviewed articles published between 2013 and 2025 were analysed. Bibliometric mapping identified dominant research concentrations in experimental cold chain studies and simulation-based approaches, with emerging themes around digital twins and virtual cold chain technologies. The review shows that current research predominantly employs controlled experimental designs and computational simulations to quantify temperature-driven deterioration, including chilling injury, decay rate, and weight loss. Although real-time temperature monitoring in commercial shipments is emerging, temperature deviations are rarely assessed alongside direct quality metrics. Although several studies have examined shipment temperatures alongside arrival-quality outcomes, these analyses are generally limited in duration, scope, or sensor resolution. Consequently, rigorous, multi-year, longitudinal datasets that pair detailed shipment temperature histories with standardised fruit-quality assessments remain largely unavailable, constraining the empirical validation of temperature–quality relationships in real export conditions. This gap significantly limits predictive capability in real-world export contexts. The review highlights the urgent need for a coordinated, long-term data infrastructure that integrates temperature and quality measurements across global citrus supply chains. Establishing such datasets, particularly in major exporting regions such as South Africa, would enable more robust modelling of temperature impacts, support the optimisation of cold chain practices, and contribute to international food loss-reduction goals. Full article

A considerable proportion of perishable goods, including fruits and vegetables, deteriorate prior to reaching customers. Inadequate refrigeration infrastructure, particularly in developing nations with arid climates and markets distant from agricultural sources, accounts for most of these losses. A food cold chain has three primary phases: pre-cooling, cold storage, and refrigerated transportation. All phases of the cold chain rely fundamentally on refrigeration to preserve perishable products at designated temperatures, relative humidity, and CO₂ concentrations, thus prolonging their shelf life. Solar-driven or aided refrigeration systems use solar energy to power cooling systems and preserve the food in the cold chain. These systems are especially beneficial in off-grid or developing areas for preserving perishable goods such as fruits, vegetables, and other food items, mitigating postharvest losses that can exceed 30–50% in areas with inconsistent energy supplies. Despite progress in efficiency and scalability, numerous research gaps remain across technological, economic, social, policy, and regional dimensions, including technical aspects, optimization, and integration. There is a need to enhance energy-efficient designs, particularly by managing solar intermittency to address non-uniform cooling, which leads to inconsistent ripening and spoilage, and by integrating sustainable refrigerants to mitigate environmental impact. Further development is necessary for micro-scale, transportable, or decentralized systems designed for small farms, while economic and financing obstacles include high upfront costs and limited financial accessibility. Substantial deficiencies exist in creating affordable models and funding channels for small-scale agriculturalists. Addressing these deficiencies could expedite adoption, thereby reducing global food loss and waste (accounting for 8–10% of GHG emissions) while improving food security. Future research must emphasize multidisciplinary methodologies that amalgamate engineering, economics, and social sciences to provide comprehensive solutions. Full article

The problem of the post-harvest loss of perishable products has been a loss facing food security, especially in areas that lack adequate cold chain facilities. This issue is directly connected with sustainability objectives because post-harvest losses are the major source of food wastage, unneeded energy use, and related greenhouse gas emissions. Cold storage with phase-change material (PCM) is a promising alternative, as it aims at stabilizing temperatures and enhancing energy consumption, but current analyses of performance have been conducted through experimental testing and computational fluid dynamic (CFD) simulations, which are precise but computationally expensive. To handle this drawback, the current work constructs a machine learning predictive model to predict the dynamics of charging and discharging temperature of PCM cold storage systems. Four regression models, namely Random Forest, Extreme Gradient Boosting (XGBoost), Support Vector Regression (SVR), and K-Nearest Neighbors (KNNs), were trained and tested on experimental datasets that were obtained for varying storage layouts. The various error and accuracy measures used to determine model performance comprised MSE, MAE, R², MAPE, and percentage accuracy. The findings suggest that Random Forest provides the best accuracy during both the charging and the discharging process, with the highest R² values of over 0.98 and with minimal mean absolute errors. The KNN model was competitive in the discharge process, especially in cases of consistent thermal recovery patterns, and XGBoost was consistent in layout accuracy. However, SVR had relatively lower robustness, particularly when using nonlinear charged dynamics. Among the evaluated models, the Random Forest algorithm demonstrated the highest predictive accuracy, achieving coefficients of determination (R²) exceeding 0.98 for both charging and discharging processes, with mean absolute errors below 0.6 °C during charging and 0.3 °C during discharging. This paper has proven that machine learning is an efficient surrogate to CFD and experimental-only methods and can be used to predict the thermal behavior of PCM quickly and precisely. The proposed framework will allow for developing cold storage systems based on energy efficiency, low costs, and sustainability, especially in the context of decentralized and resource-limited agricultural supply chains, with the help of quick and data-focused forecasting of PCM thermal behavior. Full article