Search Results (139)

The increasing demand for fresh fruits and vegetables has been accompanied by a rise in foodborne illness outbreaks linked to fresh produce. Traditional antimicrobial washing treatments, such as chlorine and peroxyacetic acid, have limitations in efficacy and pose environmental and worker health concerns. This study evaluated the effectiveness of organic acids (citric, malic, and lactic acid) and power ultrasound, individually and in combination, for the reduction in Salmonella enterica and Listeria monocytogenes on four fresh produce types: romaine lettuce, cucumber, tomato, and strawberry. Produce samples were inoculated with bacterial cocktails at 8–9 log CFU/unit and treated with organic acids at 2 or 5% for 2 or 5 min, with or without power ultrasound (40 kHz). Results showed that pathogen reductions varied based on the produce matrix with smoother surfaces such as tomato, exhibiting greater reductions than rougher surfaces (e.g., romaine lettuce and strawberry). Lactic and malic acids were the most effective treatments, with 5% lactic acid achieving a reduction of >5 log CFU/unit for S. enterica and 4.53 ± 0.71 log CFU/unit for L. monocytogenes on tomatoes. The combination of organic acids and power ultrasound demonstrated synergistic effects, further enhancing pathogen reduction by <1.87 log CFU/unit. For example, S. enterica on cucumbers was reduced by an additional 1.87 log CFU/unit when treated with 2% malic acid and power ultrasound for 2 min compared to malic acid alone. Similarly, L. monocytogenes on strawberries was further reduced by 1.84 log CFU/unit when treated with 5% malic acid and power ultrasound for 2 min. These findings suggest that organic acids, particularly malic and lactic acids, combined with power ultrasound, may serve as an effective hurdle technology for enhancing the microbial safety of fresh produce. Future research can include validating these treatments in an industrial processing environment. Full article

Bananas, one of the most widely consumed tropical fruits in the world, are susceptible to attack by the anthracnose fungus Colletotrichum musae during the post-harvest period. Currently, fungus control is generally based on the use of chemical products, often applied a few days before harvest, which could lead to a risk of residues in the fruit, thus creating a high demand for fresh and organic fruits. Therefore, essential oils present an emerging alternative for the treatment of anthracnose. Here, we evaluated the chemical composition and potential of Morinda citrifolia essential oil as a preventive and curative measure to control C. musae in bananas, also considering the quality of the fruit. In addition, computational docking analysis was conducted to predict potential molecular interactions between octanoic and butanoic acids and the enzyme Tyrosine tRNA, as a potential target for the M. citrifolia essential oil fungicide actions. We also evaluated the essential oil’s safety for beneficial organisms such as the fungus Trichoderma asperellum and the ladybugs Eriopis connexa Germar and Coleomegilla maculata DeGeer. Initially, in vitro growth inhibition tests were performed with doses of 10.0, 30.0, and 50.0 µL/mL of M. citrifolia essential oil, as well as an assessment of the phytotoxic effects on the fruit. Subsequently, using non-phytotoxic doses, we evaluated the effect of the essential oil as a preventive and curative measure against anthracnose and its impact on fruit quality. Our results showed that octanoic, butanoic, and hexanoic acids were the major compounds in M. citrifolia essential oil, inhibiting the growth of C. musae by interacting with the Tyrosine tRNA enzyme of C. musae. The non-phytotoxic dose on the fruit was 10 µL/mL of noni essential oil, which reduced C. musae growth by 30% when applied preventively and by approximately 25% when applied as a curative measure. This significantly reduced the Area Under the Disease Progress Curve without affecting the fruit weight, although there was a slight reduction in °Brix. The growth of non-target organisms, such as T. asperellum and the insect predators Co. maculata and E. connexa, was not affected. Collectively, our findings suggest that M. citrifolia essential oil is a promising alternative for the prevention and control of anthracnose in banana fruit caused by C. musae, without adversely affecting its organoleptic characteristics or non-target organisms. Full article

Current tomato harvesters rely primarily on external color as the sole indicator of ripeness. However, this approach often results in premature harvesting, leading to insufficient lycopene accumulation and a suboptimal nutritional content for human consumption. Such limitations are especially critical in controlled-environment agriculture (CEA) systems, where maximizing fruit quality and nutrient density is essential for both the yield and consumer health. To address that challenge, this study introduces a novel, multimodal harvest readiness framework tailored to nutrient film technology (NFT)-based smart farms. The proposed approach integrates plant-level stress diagnostics and fruit-level phenotyping using wearable biosensors, AI-assisted computer vision, and non-invasive physiological sensing. Key physiological markers—including the volatile organic compound (VOC) methanol, phytohormones salicylic acid (SA) and indole-3-acetic acid (IAA), and nutrients nitrate and ammonium concentrations—are combined with phenomic traits such as fruit color (a*), size, chlorophyll index (rGb), and water status. The innovation lies in a four-stage decision-making pipeline that filters physiologically stressed plants before selecting ripened fruits based on internal and external quality indicators. Experimental validation across four plant conditions (control, water-stressed, light-stressed, and wounded) demonstrated the efficacy of VOC and hormone sensors in identifying optimal harvest candidates. Additionally, the integration of low-cost electrochemical ion sensors provides scalable nutrient monitoring within NFT systems. This research delivers a robust, sensor-driven framework for autonomous, data-informed harvesting decisions in smart indoor agriculture. By fusing real-time physiological feedback with AI-enhanced phenotyping, the system advances precision harvest timing, improves fruit nutritional quality, and sets the foundation for resilient, feedback-controlled farming platforms suited to meeting global food security and sustainability demands. Full article

(1) Background: Eggplant is a widely grown, high-value vegetable crop whose commercial demand has increased in recent years owing to its unique nutritional features. Variations in its agronomic and nutritional traits are of great importance in the selection of eggplant varieties. (2) Methods: In this study, 30 different eggplant varieties were evaluated concerning the morphological characteristics and nutritional value of their fruits. (3) Results: Among the eight morphological characteristics evaluated, the coefficient of variation was highest for fruit calyx thorns, pericarp brightness, and fruit shape index. The diversity index (H’) for pulp color was the largest, followed by pericarp brightness, but was the smallest for fruit weight. Principal component analysis showed that the morphological characteristics contributed 73.20% for the observed diversity among the 30 eggplant varieties, whereas eggplant fruit quality traits had a minor effect. Of note, significant differences in the soluble protein, vitamin C, nitrate, soluble sugar, organic acid, and mineral contents was observed within the samples, with organic acids, vitamin C, and hardness contributing more to the total variation observed. Multiple sets of correlations among the indices were found, with significant positive correlations between transverse diameter and hardness, fruit weight and fruit shape index, as well as between malic acid, fructose, and sucrose; (4) Conclusions: Altogether, these findings may help create breeding strategies to promote the selection of superior genotypes and help guide future germplasm collection. Full article

With the increasing consumer demand for healthy and natural foods, strawberries have emerged as one of the most popular small berries globally. Consequently, careful investigation of the relationship between leaf photosynthetic activity (source strength) and fruit development (sink strength) during strawberry growth provides important insights for maximizing the production potential of this crop. This objective necessitates accurate strawberry organ segmentation. Recently, advancements in deep learning (DL) have driven the development of numerous semantic segmentation models that have performed effectively on benchmark datasets. Nevertheless, their small-organ plant segmentation efficacy remains insufficiently explored. Consequently, this study evaluates eight representative point-based semantic segmentation models for the strawberry organ segmentation task: PointNet++, PointMetaBase, Point Transformer V2, Swin3D, KPConv, RandLA-Net, PointCNN, and Sparse UNet. The employed dataset comprises two components: the open-source LAST-Straw strawberry dataset and a custom Japanese strawberry dataset. Strawberry point cloud organs were categorized into four classes: leaf, stem, flower, and berry. The sparse convolution-based Sparse UNet achieved the highest mean intersection over union of 81.3, followed by the PointMetaBase model at 80.7. This study provides insights into the strengths and limitations of existing architectures, assisting researchers and practitioners in selecting appropriate models for strawberry organ segmentation tasks. Full article

Chestnut flour, obtained through drying and milling of Castanea sativa fruits, has evolved from a subsistence food into a sought-after niche product, appreciated for its naturally gluten-free profile, high starch content, and richness in micronutrients. Over the past decade, its demand has steadily increased due to consumer perception of the health benefits associated with chestnut consumption. As the market for chestnut flour expanded from small-scale to large-scale production, alternative methods to the traditional process were developed. Its distinctive aroma and flavor are strongly influenced by processing methods, which are the focus of this study. Two drying approaches were compared: a traditional smoke-based method (drying house named metato) characterized by a wood-drying method and a controlled laboratory process using a forced-air dryer that maintained a constant temperature of 40 °C. The impact of these methods on the physico-chemical composition, volatile organic compounds (VOCs), and sensory properties of the flour was evaluated using chemical, instrumental, and sensory analyses. The traditional method enhanced the flour’s aromatic complexity and typicity through the application of smoke, which has been demonstrated to generate volatile organic compounds (VOCs), such as guaiacol, furfural, and o-creosol, that are associated with the smoked aroma. Nevertheless, if not properly managed, it can lead to undesirable sensory notes due to excessive smoke exposure. In contrast, the laboratory-controlled process ensured better preservation of bioactive compounds—such as polyphenols (351 mg GAE/100 g dm) and ascorbic acid (322 mg/kg dm)—while retaining the aroma notes associated with fresh chestnuts. Optimizing processing methods may support the valorization of chestnut flour as a high-quality ingredient in the modern gluten-free and functional food market. Full article

The increasing demand for sustainable agricultural practices necessitates strategies such as organic fertilizer alternatives and residual nutrient use to enhance crop productivity while maintaining soil health. This study investigates the residual effects of vermicompost on strawberry growth and physiology after a corn cropping cycle. The objectives were to assess how different vermicompost application rates impact strawberry yield, biomass, chlorophyll content, and fruit quality. The experiment was conducted over six months, using raised beds previously cultivated with corn and treated with six nutrient management strategies, namely, V0 (control), VC1, VCT100, VC1+VCT50, VC3, and VC3+VCT50. Metrics such as SPAD values, Brix sugar content, and stomatal conductance were measured throughout the growing season to assess physiological responses. Soil and plant chemical concentrations were determined at the end of the study to evaluate nutrient status. Results showed that the VC1 treatment produced the highest yield (11,573 kg/acre) and biomass (38,364 kg/acre), with significantly improved fruit quality (Brix sugar content of 8.3%) compared to the control (6.8%). SPAD values declined over time and showed no statistically significant differences among treatments. In the surface soil, VC3+VCT50 exhibited the highest N, P, Mg, Na, organic matter, and cation exchange capacity (CEC), and it also resulted in the highest leaf N. Leaves had higher N, P, K, and Mg concentrations, while Fe, Mn, and Cu were more concentrated in roots. Spectral reflectance data indicated reduced chlorophyll content in the VC3+VCT50-treated plants. These findings suggest that moderate vermicompost applications, such as VC1, can significantly contribute to sustainable agriculture by enhancing strawberry productivity and reducing dependence on synthetic fertilizers. However, high-rate applications, especially VC3 and VC3+VCT50, reduced plant vigor and yield, possibly due to salinity stress and the high sodium content in the vermicompost used in this study. Such outcomes may vary depending on feedstock composition, highlighting the importance of salinity screening when using organic amendments in salt-sensitive crops like strawberries. Full article

To address the challenge of low operational efficiency in apple harvesting robots, this study proposes an adaptive grasping sequence planning methodology that combines Self-Organizing Maps (SOMs) and genetic algorithms (GAs). The proposed adaptive SOM—GA hybrid algorithm aims to minimize cycle time by optimizing the path planning between the fruit detection and grasping phases. First of all, we propose a density-aware adaptive mechanism that dynamically adjusts planning strategies based on fruit count thresholds. In addition, the proposed grasping sequence planning framework for high-density dwarf cultivation (HDDC) orchards is validated through threshold sensitivity analysis and empirical analysis of over 500 real-world fruit distribution samples. Finally, comparative experiments demonstrate that our proposed method reduces path length in high-density scenarios. Statistical analysis reveals a bimodal fruit distribution, which aligns the algorithm’s adaptive thresholds with real-world operational demands. These advancements improve theoretical research and enhance the commercial viability in agricultural robotics. Full article

Large-scale agricultural and animal husbandry production in Shaanxi Province of China has led to significant environmental pollution, due to the incineration of vast amounts of agricultural waste annually. As the land area used for vegetable cultivation expands and farming practices evolve, the demand for organic substrates continues to grow. To optimize cost savings and enhance efficiency, this study investigated the effects of different organic substrate compositions on cucumber (Cucumis sativus) yield and quality, using ‘Jinyou 35’ cucumber as the experimental model. The results demonstrated that the blended organic substrates derived from agricultural waste met key physicochemical requirements for cucumber cultivation across both seedling establishment and fruit development stages. Compared with the control, the T4 treatment (mushroom residue/cattle manure = 1:1) increased the cucumber yield and its content of total sugar, vitamin C, and fatty acids. Furthermore, the T6 treatment (mushroom residue/cattle manure = 3:1) produced the highest total aroma and the lowest soluble protein content compared to the other treatments, and the level of C6 aldehydes in the cucumber fruits was significantly higher (p < 0.05) in this treatment group than in the control group. The findings suggest that properly formulated organic substrate blends can serve as effective growing media for cucumber cultivation, while simultaneously mitigating environmental pollution. This study provides a theoretical foundation for the sustainable utilization of agricultural waste-derived organic substrates in vegetable production. Full article

Pear fruit quality is a key determinant of consumer preference, yet it remains insufficiently characterized in many newly developed cultivars. This study aimed to evaluate 25 pear genotypes (Pyrus communis L.), internationally renowned cultivars and new cultivars developed through Romanian breeding programs, with distinct ripening periods, using an integrative approach based on morphological, biochemical, and sensory traits. Standardized methods were applied to assess attributes including fruit size, firmness, soluble solids, organic acid composition, skin color, and hedonic sensory responses for taste, aroma, texture, and visual appeal. Results revealed significant variability across ripening groups, with several cultivars, such as ‘Paradox’, ‘Pandora’, ‘Isadora’, and ‘Daciana’, displaying favorable combinations of appearance, internal quality, and consumer-rated acceptability. ‘Paradox’ and ‘Pandora’ achieved the highest sensory scores, comparable to or surpassing those of commercial standards like ‘Packham’s Triumph’. Multivariate analyses confirmed trait correlations and distinct phenotypic profiles among cultivars. These findings underscore the utility of multidimensional quality assessment for selecting cultivars suited to modern market demands, both for fresh consumption and processing. Moreover, several genotypes demonstrated potential as parental sources in pear breeding programs targeting improved organoleptic and physicochemical traits. The study suggests that a differentiated sensory scoring approach, rather than a uniform 1–9 hedonic scale, may more effectively identify high-quality pear cultivars for breeding programs. Full article

The production of organic strawberries (Fragaria × ananassa) in Texas is becoming more popular because consumers prefer locally grown berries and are willing to pay premium prices. However, local climatic conditions pose a high risk for insect problems and fungal diseases; hence, effective pest and disease management strategies are needed. Developing effective and safe methods of producing organic strawberries is necessary for meeting local consumer demand. Therefore, the objective of this study was to evaluate the impacts of selected commercially available soil-applied biopesticides on yield and the quality of Camino Real strawberries established using bare roots on plastic mulch-covered beds with drip irrigation. The ten biopesticide treatments were replicated three times in a completely randomized design. The berries used for this study were subsampled from harvests made in mid-April, late April, and mid-May 2019. Yield, biometrical characteristics, and physicochemical analyses such as pH, acidity, total soluble solids, sugars and organic acid contents, firmness, and instrumental color were determined for fresh strawberries after each harvest period. Experimental data were analyzed using the PROC Mixed model procedure. The effects of the soil-applied biopesticide treatments on strawberry yield varied. The results of strawberry yield suggest that biopesticides applied at the right time and frequency have the potential to perform at similar levels to their conventional counterparts. Camino Real strawberries treated with biopesticides, harvested during mid-April, late April, or mid-May, exhibited acceptable flavor based on the recommended values of TA and TSS for strawberries. The biopesticides showed no negative effects on yield and fruit quality and thus they could serve as alternatives to conventional products used. Full article

Bats are the only mammals with the ability to fly and are the second largest order after rodents, with 20 families and 1213 species (over 3000 subspecies) and are widely distributed in regions around the world except for Antarctica. What makes bats unique are their biological traits: a tolerance to zoonotic infections without getting clinical symptoms, long lifespans, a low incidence of tumors, and a high metabolism. As a result, they are receiving increasing attention in the field of life sciences, particularly in medical research. The rapid advancements in sequencing technology have made it feasible to comprehensively analyze the diverse biological characteristics of bats. This review comprehensively discusses the following: (1) The assembly and annotation overview of 77 assemblies from 54 species across 11 families and the transcriptome sequencing overview of 42 species from 7 families, focused on a comparative analysis of genomic architecture, sensory adaptations (auditory, visual, and olfactory), and immune functions. Key findings encompass marked interspecies divergence in genome size, lineage-specific expansions/contractions of immune-related gene families (APOBEC, IFN, and PYHIN), and sensory gene adaptations linked to ecological niches. Notably, echolocating bats exhibited convergent evolution in auditory genes (SLC26A5 and FOXP2), while fruit-eating bats displayed a degeneration of vision-associated genes (RHO), reflecting trade-offs between sensory specialization and ecological demands. (2) The annotation of the V (variable), D (diversity), J (joining), and C (constant) gene families in the TR and IG loci of 12 species from five families, with a focus on a comparative analysis of the differences in TR and IG genes and CDR3 repertoires between different bats and between bats and other mammals, provides us with a deeper understanding of the development and function of the immune system in organisms. Integrated genomic, transcriptomic, and immune repertoire analyses reveal that bats employ distinct antiviral strategies, primarily mediated by enhanced immune tolerance and suppressed inflammatory responses. This review provides foundational information, collaboration directions, and new perspectives for various laboratories conducting basic and applied research on the vast array of bat biology. Full article

This study characterizes the metabolomic profiles of three reference apricot cultivars (‘Bergeron’, ‘Currot’, and ‘Goldrich’) using ¹H NMR spectroscopy and untargeted UPLC-QToF MS/MS to support plant breeding by correlating metabolomic data with fruit phenotyping. The primary objective was to identify and quantify the key metabolites influencing fruit quality from a nutraceutical perspective. The analysis revealed significant differences in primary and secondary metabolites among the cultivars. ‘Bergeron’ and ‘Goldrich’ exhibited higher concentrations of organic acids (109 mg/g malate in ‘Bergeron’ and 202 mg/g citrate in ‘Goldrich’), flavonoids such as epicatechin (0.44 mg/g and 0.79 mg/g, respectively), and sucrose (464 mg/g and 546 mg/g), contributing to their acidity-to-sugar balance. Conversely, ‘Currot’ showed higher levels of amino acids (24.44 mg/g asparagine) and sugars, particularly fructose and glucose (79 mg/g and 180 mg/g), enhancing its characteristic sweetness. These findings suggest that metabolomic profiling can provide valuable insights into the biochemical pathways underlying apricot quality traits, aiding in the selection of cultivars with desirable characteristics. The integration of phenotyping data with ¹H NMR and UPLC-QToF MS/MS offers a comprehensive approach to understanding apricot metabolomic diversity, crucial for breeding high-quality, nutritionally enriched fruits that meet market demands. Full article

Nowadays, there is a lack of high-performing genetic materials specifically developed to thrive under low-input conditions and meet the demands of organic agriculture. This study aims to evaluate seven improved Greek tomato landraces and their (F1) hybrids designed for low-input farming systems as a potential solution to the shortage of superior varieties for organic farming in specific environments. This evaluation focuses on yield components and fruit quality parameters. According to the results, experimental genetic material matches or exceeds the performance of the commercial (F1) hybrid Formula and outperforms the control variety cv. Macedonia (pure line), indicating that selected inbred lines (S.I.L.s) originated from landraces that developed under low-input conditions and are better suited to organic farming systems. For instance, the improved line (S.I.L.) from landrace Pantaroza pink has only a 13% lower total yield compared to (F1) commercial hybrid Formula, whereas the (F1) hybrid between Pantaroza pink × Kardia vodiou surpasses it, by 23%. In conclusion, tomato landraces are an important gene pool for seed development for organic or low-input farming systems, especially under the circumstances of climate change, presenting increasing challenges. Improving these local genetic materials using mild breeding approaches under low-input conditions leads to the production of new selected pure lines (S.I.L.s) along with their (F1) hybrids, which could ensure high-quality products with satisfactory yield and low requirements, offering an innovative pathway toward sustainable agriculture. Full article

Fruit vinegar is a beverage derived from fruits or fruit processing by-products through microbial fermentation. This vinegar possesses a distinctive flavor profile and contains bioactive compounds. It is typically produced using liquid fermentation technology. As consumer demand for the flavor quality of fruit vinegar has increased, precise control over flavor compounds has become crucial for enhancing the quality of fermentation products. Vinegar contains numerous characteristic flavor compounds, including esters, aldehydes, alcohols, and organic acids. These unique flavors primarily result from the accumulation of flavor compounds generated by different raw materials and microorganisms during fermentation. Specifically, yeast and acetobacter promote the formation of distinct fruit vinegar flavors by facilitating the breakdown of carbohydrates, amino acids, and proteins in fruits, as well as the redox and esterification reactions involving alcohols. This paper reviews the metabolic pathways of yeast and acetic acid bacteria during fruit vinegar fermentation and discusses key volatile compounds that influence the flavor of fruit vinegar and their potential relationships, providing theoretical support for regulating flavor quality. Full article