Search Results (388)

Understanding the metabolic characteristics of pineapple varieties is crucial for market expansion and diversity. This study performed comparative metabolomic analysis on the “Comte de Paris” (BL) and three Taiwan-introduced varieties: “Tainong No. 11” (XS), “Tainong No. 23” (MG), and “Tainong No. 13” (DM). A total of 551 metabolites were identified across the four varieties, with 231 metabolites exhibiting no significant differences between all varieties. This included major sugars such as sucrose, glucose, and fructose, as well as key acids like citric, malic, and quinic acids, indicating that the in-season maturing fruits of different pineapple varieties can all achieve good sugar–acid accumulation under suitable conditions. The differentially accumulated metabolites (DAMs) that were identified among the four varieties all primarily belonged to several major subclasses, including phenolic acids, flavonoids, amino acids and derivatives, and alkaloids, but the preferentially accumulated metabolites in each variety varied greatly. Specifically, branched-chain amino acids (L-leucine, L-isoleucine, and L-valine) and many DAMs in the flavonoid, phenolic acid, lignan, and coumarin categories were most abundant in MG, which might contribute to its distinct and enriched flavor and nutritional value. XS, meanwhile, exhibited a notable accumulation of aromatic amino acids (L-phenylalanine, L-tryptophan), various phenolic acids, and many lignans and coumarins, which may be related to its unique flavor profile. In DM, the dominant accumulation of jasmonic acid might contribute to its greater adaptability to low temperatures during autumn and winter, allowing off-season fruits to maintain good quality. The main cultivar BL exhibited the highest accumulation of L-ascorbic acid and many relatively abundant flavonoids, making it a good choice for antioxidant benefits. These findings offer valuable insights for promoting different varieties and advancing metabolome-based pineapple improvement programs. Full article

In recent decades, the rapid expansion of the food processing industry has led to significant losses and waste, with the fruit and vegetable sector among the most affected. According to the Food and Agriculture Organization of the United Nations (FAO), losses in this category can reach up to 60%. Vegetable waste includes edible parts discarded during processing, packaging, distribution, and consumption, often comprising by-products rich in bioactive compounds such as polyphenols, carotenoids, dietary fibers, vitamins, and enzymes. The underutilization of these resources constitutes both an economic drawback and an environmental and ethical concern. Current recovery practices, including their use in animal feed or bioenergy production, contribute to a circular economy but are often limited by high operational costs. In this context, fermentation has emerged as a promising, sustainable approach for converting vegetable by-products into value-added food ingredients. This process improves digestibility, reduces undesirable compounds, and introduces probiotics beneficial to human health. The present review examines how fermentation can improve the nutritional, sensory, and functional properties of plant-based foods. By presenting several case studies, it illustrates how fermentation can effectively valorize vegetable processing by-products, supporting the development of novel, health-promoting food products with improved technological qualities. Full article

Flammulina velutipes is a widely cultivated edible mushroom in East Asia, recognized for its nutritional benefits and distinct morphology characterized by a long stipe and a compact, hemispherical pileus. The pileus not only plays a critical biological role in reproduction through spore formation but also serves as a key commercial trait influencing consumer preference and market value. Despite its economic importance, pileus development in F. velutipes is highly sensitive to environmental factors, among which carbon dioxide (CO₂) concentration is particularly influential under indoor cultivation conditions. While previous studies have reported that elevated CO₂ levels can inhibit pileus expansion in other mushroom species, the molecular mechanisms by which CO₂ affects pileus growth in F. velutipes remain poorly understood. In this study, we investigated the impact of CO₂ concentration on pileus morphology and gene expression in F. velutipes by cultivating fruiting bodies under two controlled atmospheric conditions: low (1000 ppm) and high (10,000 ppm) CO₂. Morphometric analysis revealed that elevated CO₂ levels significantly suppressed pileus expansion, reducing the average diameter by more than 50% compared to the low CO₂ condition. To elucidate the underlying genetic response, we conducted RNA sequencing and identified 102 differentially expressed genes (DEGs), with 78 being downregulated under elevated CO₂. Functional enrichment analysis highlighted the involvement of cyclin-dependent protein kinase regulatory pathways in this response. Two cyclin genes were found to be significantly downregulated under elevated CO₂ conditions, and their suppression was validated through quantitative real-time PCR. These genes, possessing conserved cyclin_N domains, are implicated in the regulation of the eukaryotic cell cycle, particularly in mitotic growth. These results indicate that CO₂-induced downregulation of cyclin genes may underlie cell cycle arrest, contributing to inhibited pileus development. This study is the first to provide transcriptomic evidence that elevated CO₂ concentrations specifically repress PHO80-like cyclin genes in F. velutipes, revealing a molecular mechanism by which CO₂ stress inhibits pileus development. These findings suggest that elevated CO₂ triggers a morphogenetic checkpoint by repressing PHO80-like cyclins, thereby modulating cell cycle progression during fruiting body development. This study provides the first evidence of such a transcriptional response in edible mushrooms and offers promising molecular targets for breeding CO₂-resilient strains and optimizing commercial cultivation conditions. Full article

B-box (BBX) transcription factors are critical regulators of light-mediated anthocyanin biosynthesis, influencing peel coloration in plants. To explore their role in red mango cultivars, we identified 32 BBX genes (MiBBX1–MiBBX32) in the mango (Mangifera indica L.) genome using a genome-wide analysis. Phylogenetic and structural analyses classified these genes into five subfamilies based on conserved domains. A collinearity analysis revealed segmental duplication as the primary mechanism of MiBBX gene family expansion, with purifying selection shaping their evolution. A promoter analysis identified numerous light- and hormone-responsive cis-elements, indicating regulatory roles in the light and hormonal signaling pathways. Expression profiling in the ‘Sensation’ cultivar revealed organ-specific patterns, with several MiBBX genes showing higher expression in the peel than in the flesh. Many of these genes also consistently exhibited elevated expression in the peel of red-skinned cultivars (‘Sensation’ and ‘Guifei’) compared to yellow and green cultivars, suggesting their role in red peel pigmentation. Furthermore, postharvest light treatment of ‘Hongmang No. 6’ fruit significantly upregulated multiple MiBBX genes, suggesting their involvement in light-induced anthocyanin accumulation in red mango peel. These findings provide valuable insights into the molecular mechanisms governing light-regulated peel coloration in mango and establish a foundation for functional studies of MiBBX genes in fruit pigmentation. Full article

This study evaluated the influence of different male date palm cultivars, distinguished by their chloroplast haplotypes, on pollen quality, pollination efficiency, metaxenia effects, and gene expression during fruit development. Chloroplast DNA analysis of 37 male trees revealed multiple haplotypes, from which cultivars B25, P8, C22, and B46 were selected for further investigation. Pollen viability varied significantly among cultivars, with P8 and B25 exhibiting the highest germination rates and pollen tube elongation, while C22 showed the lowest. These differences correlated with pollination success: P8 and B25 achieved fertilization rates near 99%, whereas C22 remained below 43%. Pollination outcomes also varied in fruit traits. Despite its low pollen performance, C22 induced the production of larger fruits at the Bleh (Kimri) stage, potentially due to compensatory physiological mechanisms. Phytochemical profiling revealed significant cultivar effects: fruits from B25-pollinated trees had with lower moisture and polyphenol content but the higher sugar levels and soluble solids, suggesting accelerated maturation. Ripening patterns confirmed this finding, with B25 promoting the earliest ripening and B46 causing the most delayed. Gene expression analysis supported these phenotypic differences. Fruits pollinated by P8, B25, and B46 exhibited elevated levels of cell-division-related transcripts, particularly the PdCD_1 gene (PDK_XM_008786146.4, a gene encoding a cell division control protein), which was most abundant in P8. In contrast, fruits from C22-pollinated trees had the lowest expression of growth-related genes, suggesting a shift toward cell expansion rather than division. Overall, the results show the critical role of male genotype in influencing fertilization outcomes and fruit development, offering valuable insights for targeted breeding strategies at enhancing date palm productivity and fruit quality. Full article

With the continuous expansion of the orchard planting area, there is an urgent need for autonomous orchard vehicles that can reduce the labor intensity of fruit farmers and improve the efficiency of operations to assist operators in the process of orchard operations. An object detection system that can accurately identify potholes, trees, and other orchard objects is essential to achieve unmanned operation of the orchard vehicle. Aiming to improve upon existing object detection algorithms, which have the problem of low object recognition accuracy in orchard operation scenes, we propose an orchard vehicle object detection algorithm based on Attention-Guided Orchard PointPillars (AGO-PointPillars). Firstly, we use an RGB-D camera as the sensing hardware to collect the orchard road information and convert the depth image data obtained by the RGB-D camera into 3D point cloud data. Then, Efficient Channel Attention (ECA) and Efficient Up-Convolution Block (EUCB) are introduced based on the PointPillars, which can enhance the ability of feature extraction for orchard objects. Finally, we establish an orchard object detection dataset and validate the proposed algorithm. The results show that, compared to the PointPillars, the AGO-PointPillars proposed in this study has an average detection accuracy improvement of 4.64% for typical orchard objects such as potholes and trees, which can prove the reliability of our algorithm. Full article

Potassium (K), a critical macronutrient for the growth and development of Korla fragrant pear (Pyrus sinkiangensis Yu), plays a pivotal regulatory role in sugar-acid metabolism. Furthermore, K exhibits a highly specific response in near-infrared (NIR) spectroscopy compared to elements such as nitrogen (N) and phosphorus (P). Given its fundamental impact on fruit quality parameters, the development of rapid and non-destructive techniques for K determination is of significant importance for precision fertilization management. By measuring leaf potassium content at the fruit setting, expansion, and maturity stages (decreasing from 1.60% at fruit setting to 1.14% at maturity), this study reveals its dynamic change pattern and establishes a high-precision prediction model by combining near-infrared spectroscopy (NIRS) with machine learning algorithms. “Near-infrared spectroscopy coupled with machine learning can enable accurate, non-destructive monitoring of potassium dynamics in Korla pear leaves, with prediction accuracy (R²) exceeding 0.86 under field conditions.” We systematically collected a total of 9000 leaf samples from Korla fragrant pear orchards and acquired spectral data using a benchtop near-infrared spectrometer. After preprocessing and feature extraction, we determined the optimal modeling method for prediction accuracy through comparative analysis of multiple models. Multiplicative scatter correction (MSC) and first derivative (FD) are synergistically employed for preprocessing to eliminate scattering interference and enhance the resolution of characteristic peaks. Competitive adaptive reweighted sampling (CARS) is then utilized to screen five potassium-sensitive bands, specifically in the regions of 4003.5–4034.35 nm, 4458.62–4562.75 nm, and 5145.15–5249.29 nm, among others, which are associated with O-H stretching vibration and changes in water status. A comparison between random forest (RF) and BP neural network indicates that the MSC + FD–CARS–BP model exhibits the optimal performance, achieving coefficients of determination (R²) of 0.96% and 0.86% for the training and validation sets, respectively, root mean square errors (RMSE) of 0.098% and 0.103%, a residual predictive deviation (RPD) greater than 3, and a ratio of performance to interquartile range (RPIQ) of 4.22. Parameter optimization revealed that the BPNN model achieved optimal stability with 10 neurons in the hidden layer. The model facilitates rapid and non-destructive detection of leaf potassium content throughout the entire growth period of Korla fragrant pears, supporting precision fertilization in orchards. Moreover, it elucidates the physiological mechanism by which potassium influences spectral response through the regulation of water metabolism. Full article

Fruit shape diversity in melon is governed by complex genetic networks, with ethylene biosynthesis playing a pivotal yet poorly characterized role. In this study, we identified a rare CmACS7^{A57V/frameshift} double mutant through fine mapping of the fsq2 locus. Ethylene-mediated ovary growth regulation has been completely lost in the CmACS7^{A57V/frameshift} double mutant, driving a transition from elongated to spherical fruit. Transcriptome analysis was performed to clarify the core role of CmACS7 in the ethylene signaling pathway. The loss of CmACS7 function regulates key genes in the ethylene responsive factor, cytokinin signaling pathway, and auxin-related genes, resulting in an imbalance in hormone levels. This imbalance directly affects the coordination of cell proliferation and expansion and ultimately determines the fruit morphology. A genetic diversity analysis of public melon germplasm resources indicated that while the CmACS7^{A57V/frameshift} mutation accounts for only 0.5% of the germplasm, it is strongly correlated with the round fruit phenotype and is important for breeding in Xinjiang. The results of this study suggest that CmACS7^{A57V/frameshift} could be used as a molecular marker to accelerate the breeding of melon varieties with excellent fruit morphology and, at the same time, reveal the coevolutionary significance of this gene in the domestication of Cucurbitaceae crops. Full article

This study performed a phylogenomic analysis of the C2H2 gene family across 30 Basidiomycota species, identifying 1032 genes distributed across six evolutionary clades (Groups I–VI). Functional diversification and lineage-specific expansions were observed: Group II (37.1%) formed a conserved core, while wood decayers (e.g., Schizophyllum commune) and edible fungi (e.g., Pleurotus ostreatus) exhibited clade-specific expansions in Groups III and V, respectively. Physicochemical profiling revealed an acidic bias in Agaricomycotina proteins (pI 4.3–5.8) compared to alkaline trends in pathogens (Ustilaginomycotina/Pucciniomycotina; pI 8.3–8.6). Comparative genomics indicated that saprotrophs retained long genes (12.4 kb) with abundant introns (mean = 6.2/gene), whereas pathogens exhibited genomic streamlining (introns ≤ 2). Synteny network analysis revealed high ancestral conservation in core clusters (Cluster_1–2: 58% homologs) under strong purifying selection (Ka/Ks = 0.18–0.22), while peripheral clusters (Cluster_Mini) approached neutral evolution (Ka/Ks = 0.73). This study reveals stage-specific expression dynamics of 17 C2H2 zinc finger genes in Sarcomyxa edulis, highlighting their roles in coordinating developmental transitions (e.g., SeC2H2_1 in low-temperature adaptation, SeC2H2_7/12 in primordia initiation, and SeC2H2_8/9/13 in fruiting body maturation) through temporally partitioned regulatory programs, providing insights into fungal morphogenesis and stress-responsive adaptation. These findings underscore the dual role of C2H2 genes in sustaining conserved regulatory networks and facilitating ecological adaptation, providing new insights into fungal genome evolution. Full article

Peach fruit faces severe postharvest losses due to thin epidermis and susceptibility to Rhizopus stolonifer-induced soft rot. Chemical control risks residue and resistance issues, demanding eco-friendly alternatives. This study elucidated the mechanism by which trans-2-hexenal (E2H) mitigated postharvest soft rot caused by Rhizopus stolonifer in peach (Prunus persica cv. Hujing Milu) fruit. The results demonstrated that E2H treatment significantly delayed lesion expansion by 44.7% and disease incidence by 23.9% while effectively maintaining fruit quality by delaying firmness loss, reducing juice leakage, and suppressing malondialdehyde (MDA) accumulation. E2H treatment upregulated phenylpropanoid pathway gene expression, enhancing key phenylpropanoid metabolism enzymes activities (phenylalanine ammonia-lyase (PAL), cinnamate 4-hydroxylase (C4H), 4-coumarate-CoA ligase (4CL), polyphenol oxidase (PPO), peroxidase (POD)), leading to the increase of total phenolics by 7.9%. E2H treatment analysis revealed significant enhancements in both chitinolytic activity (CHI) and β-1,3-glucanase (GLU) activity by 85.7% and 12.9%, indicating potentiation of the enzymatic defense system. Concurrently, E2H treatment could improve the redox modulation capacity of peach fruits through promoting catalytic efficiency of redox-regulating enzymes, increasing the accumulation of ascorbic acid (AsA) by 8.1%, inhibiting the synthesis of dehydroascorbic acid (DHA) by 18.6%, as well as suppressing the biosynthesis of reactive oxygen species (ROS). These coordinated enhancements in pathogenesis-related proteins (CHI, GLU), phenylpropanoid metabolism activation, and antioxidant systems are strongly associated with E2H-induced resistance against Rhizopus stolonifer, though contributions from other factors may also be involved. Full article

Non-structural carbohydrates (NSCs), the main substrates and energy carriers of plants, play an important role in mediating the source-sink balance of carbon (C). However, the trade-offs in the allocation of NSCs remain unclear at critical stages of fruit development. In this study, we evaluated the dynamic and allometric partitioning characteristics of NSCs at the key stage of fruit development in Camellia oleifera. The seed NSCs pool was the highest in the middle stage of rapid fruit expansion, and an inverted “V” shape appeared from July to September and peaked in August. Notably, although the NSC pool of twigs was the smallest and did not change significantly at each stage, the starch pool was the largest. Significant correlations existed between the NSC content of different organs in C. oleifera in the early stage of slow development and the middle stage of rapid fruit expansion. In particular, NSC components, both of the twigs in the early stage and of the twigs and seeds in the middle stage, showed significant allometric partitioning relationships. In summary, seeds are the main carbon sink for fruit development trade-offs of C. oleifera, and twigs may play an important role in transferring C to seeds at the early and middle stages of fruit development. In the future, attention should be paid to controlling the factors affecting the balance of plant C during the rapid fruit expansion period to ensure high yield. Full article

The SEPALLATA3 (SEP3)-like MADS-box genes play crucial roles in determining petal identity and development in the petunia and tomato of Solanaceae. Solanum nigrum is a self-pollinating plant in the Solanaceae family, and produces white flowers. However, the mechanisms controlling the transition from green to white petals during flower development remain poorly understood. In this study, we isolated a flower-specific SEP3-like gene, SnMADS37, from S. nigrum, and investigated its potential role in chlorophyll metabolism during petal development. Our results show that quantitative RT-PCR analysis demonstrates that SnMADS37 is exclusively expressed in petals and stamens during early floral bud development. Overexpression of SnMADS37 clearly enhanced the number of petals, promoting the formation of additional petal-like tissues in stamens and extra organs in some fruits. Moreover, fully opened transformed petals exhibited notable chlorophyll accumulation at their tips and veins, whereas silencing of Snmads37 clearly inhibited petal expansion and reduced green pigmentation in early flower buds. Additionally, the transformed green petals exhibited distinct conical epidermal cells in the green regions, similar to wild type (WT) petals. Our results demonstrate that SnMADS37 plays a critical role in regulating petal identity, expansion, and chlorophyll metabolism during petal development. These findings provide new insights into the functional diversification of SEP3-like MADS-box genes in angiosperms. Full article

Fruit quality testing plays a crucial role in the advancement of fruit industry, which is related to market competitiveness, consumer satisfaction and production process optimization. In recent years, nondestructive testing technology has become a research hotspot due to its outstanding advantages. In this paper, the principle, application, advantages and disadvantages of optical, acoustic, electromagnetics, dielectric properties research and electronic nose non-destructive testing technology in fruit quality testing are systematically reviewed. These technologies can detect a variety of chemical components of fruit, realize the assessment of maturity, damage degree, disease degree, and are suitable for orchard picking, quality grading, shelf life prediction and other fields. However, there are limitations to these techniques. The optical, acoustic and electronic nose technologies are susceptible to environmental factors, the electromagnetic technology has defects in the detection of complex molecules and fruit internal quality, and the dielectric characteristics are greatly affected by the shape and state of the sample surface. In the future, efforts should be made to enhance the implementation of non-destructive testing technology in the fruit industry through technology integration, optimization algorithm, cost reduction, and expansion of industrial chain application, so as to help the premium growth of the fruit industry. Full article

Given the growing impact of climate change, this study examines the flowering phenology of Rosa rugosa Thunb. in Kupinovo (Vojvodina, Serbia). Data collected over 18 years (2007–2024) were analyzed to assess changes in primary flowering, while secondary flowering was monitored from 2022 to 2025. Phenological stages were recorded every other day, and dates were converted into day-of-year (DOY) values. Heat accumulation (GDD) was calculated using daily max/min temperatures and thresholds. In 2024, R. rugosa exhibited a 37-day earlier onset and a 50.4-day later completion of primary flowering compared to previous years. The variability of key phenological events of primary flowering was observed in the interaction with climatic parameters, with regular fruiting. The species proved tolerant to heat and drought, suggesting potential range expansion. Optimal temperatures for secondary flowering were identified: abundant flowering occurred at 13.6 °C max and 4.9 °C min, while moderate flowering occurred at 9.0 °C max and 4.2 °C min. Regression analysis confirmed the positive effect of rising temperatures on flowering intensity. While freezing halted secondary flowering and damaged open buds, unopened buds remained unaffected. These findings highlight R. rugosa as a resilient, ornamental species, relevant to climate adaptation strategies, nature-based solutions, and the preservation of ecosystem services under global warming scenarios. Full article

The chlorophyll content is an important index reflecting the growth status and nutritional level of plants. The rapid, accurate and nondestructive monitoring of the SPAD content of apple trees can provide a basis for large-scale monitoring and scientific management of the growth status of apple trees. In this study, the canopy leaves of apple trees at different growth stages in the same year were taken as the research object, and remote sensing images of fruit trees in different growth stages (flower-falling stage, fruit-setting stage, fruit expansion stage, fruit-coloring stage and fruit-maturing stage) were acquired via a DJI MAVIC 3 multispectral unmanned aerial vehicle (UAV). Then, the spectral reflectance was extracted to calculate 15 common vegetation indexes as eigenvalues, the 5 vegetation indexes with the highest correlation were screened out through Pearson correlation analysis as the feature combination, and the measured SPAD values in the leaves of the fruit trees were gained using a handheld chlorophyll meter in the same stages. The estimation models for the SPAD values in different growth stages were, respectively, established through five machine learning algorithms: multiple linear regression (MLR), partial least squares regression (PLSR), support vector regression (SVR), random forest (RF) and extreme gradient boosting (XGBoost). Additionally, the model performance was assessed by selecting the coefficient of determination (R²), root mean square error (RMSE) and mean absolute error (MAE). The results show that the SPAD estimation results vary from stage to stage, where the best estimation model for the flower-falling stage, fruit-setting stage and fruit-maturing stage is RF and those for the fruit expansion stage and fruit-coloring stage are PLSR and MLR, respectively. Among the estimation models in the different growth stages, the model accuracy for the fruit expansion stage is the highest, with R² = 0.787, RMSE = 0.87 and MAE = 0.644. The RF model, which outperforms the other models in terms of the prediction effect in multiple growth stages, can effectively predict the SPAD value in the leaves of apple trees and provide a reference for the growth status monitoring and precise management of orchards. Full article