Emerging Postharvest Technologies to Enhance the Shelf-Life of Fruit and Vegetables: An Overview

Effects of Moringa oleifera leaf-derived carbon dots treatment on ROS metabolism regulation for postharvest flowering Chinese cabbage preservation

Postharvest flowering Chinese cabbage is prone to rapid senescence and quality deterioration during storage at room temperature. The imbalance of reactive oxygen species (ROS) metabolism is one of the critical factors leading to this process. In this study, we synthesized Moringa oleifera leaf-derived carbon dots (MoCDs) and investigated the effects of MoCDs treatment on ROS metabolism regulation for postharvest flowering Chinese cabbage preservation. The results showed that MoCDs exhibited more efficient antioxidant activity than M. oleifera extract, attributed to their abundant surface functional groups, including hydroxyl, carboxyl, and amino groups, and an extensive sp2-hybridized carbon network. Moreover, MoCDs treatment could reduce the accumulation of hydrogen peroxide and superoxide anion radical in postharvest flowering Chinese cabbage by generally enhancing the activities of a series of key antioxidant enzymes and increasing the contents of non-enzymatic antioxidants, which significantly delayed leaf senescence and deterioration of appearance and nutritional quality of postharvest flowering Chinese cabbage during storage. In summary, as an effective antioxidant, MoCDs entered leaf cells to scavenge excessive ROS directly; as an elicitor, MoCDs enhanced the ROS scavenging ability of the endogenous antioxidant defense system in postharvest flowering Chinese cabbage. These dual protective mechanisms synergistically regulated ROS metabolism, thus benefiting the postharvest preservation of flowering Chinese cabbage.

Using a Region-Based Convolutional Neural Network (R-CNN) for Potato Segmentation in a Sorting Process

This study focuses on the segmentation part in the development of a potato-sorting system that utilizes camera input for the segmentation and classification of potatoes. The key challenge addressed is the need for efficient segmentation to allow the sorter to handle a higher volume of potatoes simultaneously. To achieve this, the study employs a region-based convolutional neural network (R-CNN) approach for the segmentation task, while trying to achieve more precise segmentation than with classic CNN-based object detectors. Specifically, Mask R-CNN is implemented and evaluated based on its performance with different parameters in order to achieve the best segmentation results. The implementation and methodologies used are thoroughly detailed in this work. The findings reveal that Mask R-CNN models can be utilized in the production process of potato sorting and can improve the process.

Multi-omics analysis of non-pungent (Capsicum annuum) and fiery hot ghost chili (C. chinense) provides insights into proteins involved in fruit development and metabolites biosynthesis

Global omics offer extensive insights into the diversity of essential biomolecules across various plant developmental stages. Despite advancements in high-throughput technologies, the integrated analysis of global omics such as proteomics, transcriptomics, and metabolomics, is yet to be fully explored in fruits of Capsicum species. In this study, we used an integrated omics approach to identify proteins involved in fruit development, and metabolite biosynthesis in the placenta and pericarp tissues of two contrasting genotypes belonging to ghost chili (Capsicum chinense) and C. annuum. The mass spectrometry analysis identified a total of 4,473 and 2,012 proteins from the pericarp and placenta tissues of Capsicum fruits. We observed expression of developmental stage-specific proteins, such as kinases, transferases, ion transporters, F-box proteins, and transcription factors that were enriched in the biosynthesis of primary and secondary metabolites. The abundance of these proteins corresponded with RNAseq data. Key proteins related to capsaicinoids biosynthesis, such as Acyltransferase 3, 3-oxoacyl-[acyl-carrier protein], 4-coumaroyl co-A ligase, and 3-ketoacyl-coA synthase 3, were identified in placenta of highly pungent ghost chili, along with J-domain proteins and transcription factors such as MYB101, MYB 14-like, bHLH112, NAC, and Cyt p450 CYP82D47, suggesting their role in capsaicinoids and secondary metabolites biosynthesis. Further, we observed a correlation of the expression of genes and proteins with the abundance of primary and secondary metabolites, such as carbohydrates, alcohols, fatty acids, phenolics, glycerides, polyamines, and amino acids. Our findings provide a novel multiomics resources for future functional studies, with potential applications in breeding programs.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-025-01581-7.

Impact of high pressure impregnation and air drying on the quality of Dosidicus gigas slices

Humboldt squid (Dosidicus gigas) is the most abundant cephalopod in the fishing industry, and its high nutritional and organoleptic properties make it a go-to food product for consumers. Therefore, developing new processing techniques seems imperative to minimize quality deterioration and provide products with appropriate characteristics. The study aimed to determine the effect of high-pressure impregnation (HPI) pretreatment on hot air-drying kinetics and the quality of Humboldt squid slices. Various pressures, times, and concentrations of osmotic solution during HPI were evaluated, followed by drying at 40 and 60 °C. The HPI pretreatment reduced the drying time by around 26% when dried at 40 °C, and only 18% when dried at⋅ 60 °C compared with unpretreated samples. The Weibull, Page, and Logarithmic models were considered for experimental drying curve modeling. Diffusion coefficient values varied from 3.82 to 6.59 × 10-9 m2/s for all drying conditions. Moreover, the color, texture, and water-holding capacity were determined. Rehydration capacity values increased due to less damage to cellular tissue than the control (HPI-untreated dried samples). Also, scanning electron microscope (SEM) images showed a compacted structure of HPI-dried squid samples. Overall, HPI proved to be a beneficial pretreatment as it reduced drying time and improved the quality characteristics of Humboldt squid.

Combination transcriptomic and metabolomic reveal deterioration of the blue honeysuckle (Lonicera caerulea L.) fruit and candidate genes regulating metabolism in the post-harvest stage

Blue honeysuckle, a new berry with high nutritional value, possesses typical berry postharvest properties, including extreme perishability, rapid quality loss, and high sensitivity to microbial infections. At present, the underlying mechanisms of postharvest quality deterioration, senescence, and low-temperature regulation remain largely unknown. This study aimed to elucidate the metabolic shifts and genetic regulation underlying the preservation or deterioration of blue honeysuckle during storage at room temperature (25 °C) and low temperature (4 °C). Storage at 4 °C inhibited fruit decay and preserved better visual quality, weight, firmness, and total soluble solid and acid contents. We identified 24 key differentially accumulated metabolites that specifically changed during the qualitative shift at room temperature and were effectively regulated by 4 °C. Commonly associated metabolites, sorbitol, succinic acid, malic acid, naringenin, pinobanksin, and taxifolin, characterize the deterioration of blue honeysuckle. These metabolites were integrated with transcriptomic data for weighted correlation network analysis (WGCNA). Regulatory networks were used for the identification of key genes and transcription factors (TFs) influencing sugar, organic acid, flavonoid, and phenolic acid metabolism during storage. The findings provide insight into metabolic regulation and the improvement of flavor in postharvest blue honeysuckle fruit.

Recent Advances in Postharvest Application of Exogenous Phytohormones for Quality Preservation of Fruits and Vegetables

The increasing global population has heightened the demand for food, leading to escalated food production and, consequently, the generation of significant food waste. Factors such as rapid ripening, susceptibility to physiological disorders, and vulnerability to microbial attacks have been implicated as contributing to the accelerated senescence associated with food waste generation. Fruits and vegetables, characterized by their high perishability, account for approximately half of all food waste produced, rendering them a major area of concern. Various postharvest technologies have thus been employed, including the application of phytohormone treatments, to safeguard and extend the storability of highly perishable food products. This review, therefore, explores the physicochemical properties and biological aspects of phytohormones that render them suitable for food preservation. Furthermore, this review examines the effects of externally applied phytohormones on the postharvest physiology and quality attributes of fresh produce. Finally, the review investigates the mechanisms by which exogenous phytohormones preserve food quality and discusses the associated limitations and safety considerations related to the use of these compounds in food applications.

Tracing pistachio nuts' origin and irrigation practices through hyperspectral imaging

Pistachio trees have become a significant global agricultural commodity because their nuts are renowned for their unique flavour and numerous health benefits, contributing to their high demand worldwide. This study explores the application of Hyperspectral Imaging (HSI) and Machine Learning (ML) to determine pistachio nuts' geographic origin and irrigation practices, alongside predicting essential commercial quality and yield parameters. The study was conducted in two Spanish orchards and employed HSI technology to capture spectral data. It used ML models like Partial Least Squares (PLS), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) for analysis. The results demonstrated high accuracy in classifying pistachios based on origin, with accuracies exceeding 94%, and in assessing water content and colour pigments, where both PLS and SVM models achieved 99% accuracy. The research highlighted distinct spectral signatures associated with different irrigation treatments, particularly in the Near-Infrared (NIR) region, with PLS showing an accuracy of 92%. However, challenges were noted in predicting fruit orientation, while predicting height location within the tree was more successful, reflecting clearer spectral distinctions. Regression models also showed promise, particularly in predicting yield (R2 = 0.89 with PLS) and percentage of blank nuts (R2 = 0.71 with PLS). The correlation analysis revealed key insights, such as an inverse relationship between blank nuts and yield, and a strong correlation between yield and split nuts. Despite challenges in predicting fruit orientation, the research showed promising results in forecasting yield and commercial quality factors, indicating the effectiveness of spectral analysis in optimising pistachio production and sustainability.

Use of Integral Forage Palm Flour as an Innovative Ingredient in New Fettuccine-Type Pasta: Thermomechanical and Technological Properties, and Sensory Acceptance

Dehydrated integral forage palm cladode flour (FPF) presents a promising nutritional and functional approach to enriching fettuccine-type pasta. This study investigated the use of microwave-dehydrated FPF (at 810 W) as a partial wheat flour substitute (0, 5, 10, 15, and 20% w/w) in fresh and dry fettuccine-type pasta. The thermomechanical properties of flour blends and the technological and sensory attributes of the resulting pasta were evaluated. FPF displayed a high protein (15.80%), mineral (15.13%), dietary fiber (67.35%), and total soluble phenolic compound (251 mg EAG·100 g-1) content. While water absorption (~58%) and dough stability remained consistent across formulations, a decrease in maximum torque during heating was observed (p < 0.05). Fettuccine-type pasta containing 10% FPF exhibited an acceptable optimal cooking time, solid loss, weight gain, and textural properties for both fresh and dry pasta. Sensory evaluation revealed acceptability above 63% for pasta with 10% FPF, with a slight preference for the fresh version. Fresh pasta flavored with garlic and extra virgin olive oil (garlic and oil pasta) achieved a sensory acceptance rate of 79.67%. These findings demonstrate the potential of FPF for fettuccine-type pasta production, contributing desirable technological characteristics and achieving acceptable sensory profiles.

Unveiling the molecular dynamics of low temperature preservation in postharvest lotus seeds: a transcriptomic perspective

BACKGROUND

Postharvest quality deterioration poses a significant challenge to the commercial value of fresh lotus seeds. Low temperature storage is widely employed as the primary method for preserving postharvest lotus seeds during storage and transportation.

RESULTS

This approach effectively extends the storage life of lotus seeds, resulting in distinct physiological changes compared to room temperature storage, including a notable reduction in starch, protein, H2O2, and MDA content. Here, we conducted RNA-sequencing to generate global transcriptome profiles of postharvest lotus seeds stored under room or low temperature conditions. Principal component analysis (PCA) revealed that gene expression in postharvest lotus seeds demonstrated less variability during low temperature storage in comparison to room temperature storage. A total of 14,547 differentially expressed genes (DEGs) associated with various biological processes such as starch and sucrose metabolism, energy metabolism, and plant hormone signaling response were identified. Notably, the expression levels of DEGs involved in ABA signaling were significantly suppressed in contrast to room temperature storage. Additionally, nine weighted gene co-expression network analysis (WGCNA)-based gene molecular modules were identified, providing insights into the co-expression relationship of genes during postharvest storage.

CONCLUSION

Our findings illuminate transcriptional differences in postharvest lotus seeds between room and low temperature storage, offering crucial insights into the molecular mechanisms of low temperature preservation in lotus seeds.

Preparation of Cellulose Fiber Loaded with CuO Nanoparticles for Enhanced Shelf Life and Quality of Tomato Fruit

The present study reports on the preparation of a cellulose fiber (CF) composite from D. lutescens, combined with copper oxide nanoparticles (DL@CF/CuO), to prolong the shelf life of tomatoes after harvest. The isolated cellulose fiber material was comprehensively characterized using XRD, FTIR, and FE-SEM analyses. The DLCF and DL@CF/CuO nanoparticles exhibited crystalline cellulose, as indicated by the XRD investigation. Both DLCF and DL@CF/CuO showed O-H and C-H FTIR spectra with identifiable vibrational peaks. The FE-SEM images depicted the dispersion of DL@CF/CuO-based fibers in a cellulose fiber matrix containing CuO nanoparticles. A 0.3% (wt/wt), a solution of DL@CF/CuO was coated onto the surface of early ripening tomato fruits. After a 25-day storage period at 25-29 °C and 85% RH, the results showed a significant extension in the shelf life of the tomato fruits, in line with changes in physiological properties and fruit quality. The extension of shelf life in tomato fruit epidermis treated with DL@CF/CuO was confirmed through FE-SEM analysis. L929 fibroblast cells were treated with the developed DL@CF/CuO nanocomposite, and no signs of toxicity were detected up to 75 µg/mL. Additionally, the DL@CF/CuO nanocomposite exhibited significant antifungal activity against Aspergillus flavus. In conclusion, this study provides novel insights for sustainable food security and waste control in the agricultural and food industries.

A Descriptive Study of Food Waste-Related Practices and Policies among Food Pantries in Central and Eastern North Carolina

Food pantries play a key role in addressing food insecurity, relying, in part, on foods nearing their sell-by dates to address needs. Yet, little is known about pantries' food waste-related practices and policies. In an online survey of 84 pantries in North Carolina, fresh produce was reported as the most discarded category and spoilage as the primary reason for discarding food. Most pantries (87%) had an extension dates policy for guiding decisions related to foods past their sell-by date. These findings demonstrate that, while many pantries strive to mitigate waste, broader implementation of food waste-related policies may be beneficial.

Applied insight: studying reducing the carbon footprint of the drying process and its environmental impact and financial return

Harnessing solar energy is one of the most important practical insights highlighted to mitigate the severe climate change (CC) phenomenon. Therefore, this study aims to focus on the use of hybrid solar dryers (HSDs) within an environmentally friendly framework, which is one of the promising applications of solar thermal technology to replace traditional thermal technology that contributes to increasing the severity of the CC phenomenon. The HSD, based on a traditional electrical energy source (HSTEE) and electrical energy from photovoltaic panels (HSPVSE), was evaluated compared to a traditional electrical (TE) dryer for drying some medicinal and aromatic plants (MAPs). This is done by evaluating some of the drying outputs, energy consumed, carbon footprint, and financial return at 30, 40, and 50°C. The best quality of dried MAP samples in terms of essential oil (EO, %) and microbial load was achieved at 40°C. The HSTEE dryer has reduced energy consumption compared to the TE dryer by a percentage ranging from 37% to 54%. The highest CO2 mitigated ratio using the HSTEE dryer was recorded in thyme, marjoram, and lemongrass samples, with values ranging from 45% to 54% at 30, 40, and 50°C. The highest financial return obtained from energy consumption reduction and carbon credit footprint was achieved at 50°C, with values ranging from 5,313.69 to 6,763.03 EGP/year (EGP ≈ 0.0352 USD) when coal was used as a fuel source for the generation of electricity. Moreover, the HSPVSE dryer achieved a 100% reduction in traditional energy consumption and then reduced CO2 emissions by 100%, which led to a 100% financial return from both energy reduction and carbon credit. The highest financial returns were observed at 50°C, with values ranging from 13,872.56 to 15,007.02, 12,927.28 to 13,984.43, and 11,981.99 to 12,961.85 EGP/year (EGP ≈ 0.0352 USD) for coal, oil, and natural gas, respectively. The HS dryers show potential for environmental conservation contribution; furthermore, earning money from energy savings and carbon credit could help improve the living standards and maximize benefits for stakeholders.

The roles of novel chitooligosaccharide-peanut oligopeptide carbon dots in improving the flavor quality of Chinese cabbage

Carbon dots (CDs), a novel type of nanomaterial, play crucial roles in the agriculture field. However, it remains unclear their impacts on the flavor quality of vegetables. The present study synthesized a novel chitooligosaccharide-peanut oligopeptide-carbon dots (COS-POP-CDs) material through the chitooligosaccharide (COS) and peanut oligopeptide (POP) high temperature Maillard reactions and studied its effect on the flavor quality of Chinese cabbage (Choy sum). Results indicated that COS-POP-CDs emit blue visible light that readily absorbed by chloroplasts, while also demonstrating some degree of antibacterial and antioxidant activities. After transplanting of Choy sum, foliar spraying 0.12 mg/mL COS-POP-CDs twice can increase the content of soluble proteins, Vitamin C, and enhance the strawberry and spicy flavors of Choy Sum. After harvest of Choy Sum, foliar spraying 0.12 mg/mL COS-POP-CDs once can slow down the spoilage. These results suggest that COS-POP-CDs have significant potential to improve crop quality.

Low-Cost Plant-Based Metal and Metal Oxide Nanoparticle Synthesis and Their Use in Optical and Electrochemical (Bio)Sensors

Technological progress has led to the development of analytical tools that promise a huge socio-economic impact on our daily lives and an improved quality of life for all. The use of plant extract synthesized nanoparticles in the development and fabrication of optical or electrochemical (bio)sensors presents major advantages. Besides their low-cost fabrication and scalability, these nanoparticles may have a dual role, serving as a transducer component and as a recognition element, the latter requiring their functionalization with specific components. Different approaches, such as surface modification techniques to facilitate precise biomolecule attachment, thereby augmenting recognition capabilities, or fine tuning functional groups on nanoparticle surfaces are preferred for ensuring stable biomolecule conjugation while preserving bioactivity. Size optimization, maximizing surface area, and tailored nanoparticle shapes increase the potential for robust interactions and enhance the transduction. This article specifically aims to illustrate the adaptability and effectiveness of these biosensing platforms in identifying precise biological targets along with their far-reaching implications across various domains, spanning healthcare diagnostics, environmental monitoring, and diverse bioanalytical fields. By exploring these applications, the article highlights the significance of prioritizing the use of natural resources for nanoparticle synthesis. This emphasis aligns with the worldwide goal of envisioning sustainable and customized biosensing solutions, emphasizing heightened sensitivity and selectivity.

Nano and Technological Frontiers as a Sustainable Platform for Postharvest Preservation of Berry Fruits

Berries are highly perishable and susceptible to spoilage, resulting in significant food and economic losses. The use of chemicals in traditional postharvest protection techniques can harm both human health and the environment. Consequently, there is an increasing interest in creating environmentally friendly solutions for postharvest protection. This article discusses various approaches, including the use of "green" chemical compounds such as ozone and peracetic acid, biocontrol agents, physical treatments, and modern technologies such as the use of nanostructures and molecular tools. The potential of these alternatives is evaluated in terms of their effect on microbial growth, nutritional value, and physicochemical and sensorial properties of the berries. Moreover, the development of nanotechnology, molecular biology, and artificial intelligence offers a wide range of opportunities to develop formulations using nanostructures, improving the functionality of the coatings by enhancing their physicochemical and antimicrobial properties and providing protection to bioactive compounds. Some challenges remain for their implementation into the food industry such as scale-up and regulatory policies. However, the use of sustainable postharvest protection methods can help to reduce the negative impacts of chemical treatments and improve the availability of safe and quality berries.

Deep Learning in Precision Agriculture: Artificially Generated VNIR Images Segmentation for Early Postharvest Decay Prediction in Apples

Food quality control is an important task in the agricultural domain at the postharvest stage for avoiding food losses. The latest achievements in image processing with deep learning (DL) and computer vision (CV) approaches provide a number of effective tools based on the image colorization and image-to-image translation for plant quality control at the postharvest stage. In this article, we propose the approach based on Generative Adversarial Network (GAN) and Convolutional Neural Network (CNN) techniques to use synthesized and segmented VNIR imaging data for early postharvest decay and fungal zone predictions as well as the quality assessment of stored apples. The Pix2PixHD model achieved higher results in terms of VNIR images translation from RGB (SSIM = 0.972). Mask R-CNN model was selected as a CNN technique for VNIR images segmentation and achieved 58.861 for postharvest decay zones, 40.968 for fungal zones and 94.800 for both the decayed and fungal zones detection and prediction in stored apples in terms of F1-score metric. In order to verify the effectiveness of this approach, a unique paired dataset containing 1305 RGB and VNIR images of apples of four varieties was obtained. It is further utilized for a GAN model selection. Additionally, we acquired 1029 VNIR images of apples for training and testing a CNN model. We conducted validation on an embedded system equipped with a graphical processing unit. Using Pix2PixHD, 100 VNIR images from RGB images were generated at a rate of 17 frames per second (FPS). Subsequently, these images were segmented using Mask R-CNN at a rate of 0.42 FPS. The achieved results are promising for enhancing the food study and control during the postharvest stage.

Advances Postharvest Preservation Technology

Fruits and vegetables are important sources of nutrients such as vitamins, minerals, and bioactive compounds, which provide many health benefits [...].