Search Results (909)

The artichoke (Cynara cardunculus L. subsp. scolymus) is an endemic perennial plant of the Mediterranean area commonly consumed as food. It is known since ancient times for its beneficial properties for human health, among which its antioxidant activity due to polyphenolics stands out. In the frame of our ongoing studies aiming to highlight the biodiversity and the chemodiversity of natural resources, we investigated the phenolic and saponin content of the cultivar “Carciofo di Procida” collected at Procida, an island of the Gulf of Naples (Italy). Along with the edible part of the immature flower, we included in our analyses the stem and the external bracts, generally discarded for food consuming or industrial preparations. The LCMS quali-quantitative profiling of polyphenols (including anthocyanins) and cynarasaponins of this cultivar is reported for the first time. In addition to antioxidant properties, we observed a significant cytotoxic activity due to extracts from external bracts against human neuroblastoma SH-SY5Y cell lines with 43% of cell viability, after 24 h from the treatment (50 μg/mL), and less potent but appreciable effects also against human colorectal adenocarcinoma CaCo-2 cells. This suggests that the different metabolite composition may be responsible for the bioactivity of extracts obtained from specific parts of artichoke and foresees a possible exploitation of the discarded material as a source of beneficial compounds. Full article

The advancement of Artificial Intelligence (AI) has significantly accelerated progress across various research domains, with growing interest in plant science due to its substantial economic potential. However, the integration of AI with digital vegetation analysis remains underexplored, largely due to the absence of large-scale, real-world plant datasets, which are crucial for advancing this field. To address this gap, we introduce the PP3D dataset—a meticulously labeled collection of about 500 potted plants represented as 3D point clouds, featuring fine-grained annotations for approximately 20 species. The PP3D dataset provides 3D phenotypic data for about 20 plant species spanning model organisms (e.g., Arabidopsis thaliana), potted plants (e.g., Foliage plants, Flowering plants), and horticultural plants (e.g., Solanum lycopersicum), covering most of the common important plant species. Leveraging this dataset, we propose the panoptic plant recognition task, which combines semantic segmentation (stems and leaves) with leaf instance segmentation. To tackle this challenge, we present SCNet, a novel dual-representation learning network designed specifically for plant point cloud segmentation. SCNet integrates two key branches: a cylindrical feature extraction branch for robust spatial encoding and a sequential slice feature extraction branch for detailed structural analysis. By efficiently propagating features between these representations, SCNet achieves superior flexibility and computational efficiency, establishing a new baseline for panoptic plant recognition and paving the way for future AI-driven research in plant science. Full article

Allium ursinum (wild garlic) has long been collected and consumed as food and medicine in the north temperate zone, where its popularity is growing. Colchicum autumnale and Convallaria majalis contain toxic alkaloids. Their habitats overlap, and without flowers, their vegetative organs are similar. Confusing the leaves of Colchicum or Convallaria with the leaves of wild garlic has repeatedly led to serious human and animal poisonings. Our goal was to find a histological characteristic that makes the separation of these leaves clear. We compared the anatomy of foliage leaves of these three species grown in the same garden (Debrecen, Hungary, Central Europe). We used a bright-field microscope to characterize the transversal sections of leaves. Cell types of epidermises were compared based on peels and different impressions. We established some significant differences in the histology of leaves. The adaxial peels of Allium consist of only “long” cells without stomata, but the abaxial ones show “long”, “short” and “T” cells with wavy cell walls as a peculiarity, and stomata. Convallaria and Colchicum leaves are amphystomatic, but in the case of Allium, they are hypostomatic. These traits were confirmed with herbarium specimens. Our results help to clearly identify these species even in mixed, dried plant material and may be used for diagnostic purposes. Full article

Flowering is a key agronomic trait that directly influences the yield of the tea-oil tree (Camellia oleifera). Floral initiation, which precedes flower bud differentiation, represents a critical developmental stage affecting the flowering outcomes. However, the molecular mechanisms underlying floral initiation in C. oleifera remain poorly understood. In this study, buds from five key developmental stages of a 12-year-old C. oleifera cultivar ‘changlin53’ were collected as experimental samples. Scanning electron microscopy was employed to identify the stage of floral initiation. UPLC-MS/MS was used to analyze endogenous gibberellin (GA) concentrations, while transcriptomic analysis was performed to reveal the underlying transcriptional regulatory network. Six GA types were detected during floral initiation and petal development. GA₄ was exclusively detected at the sprouting stage (BII), while GA₃ was present in all samples but was significantly lower in BII and the flower bud primordium formation stage (BIII) than in the other samples. A total of 64 differentially expressed genes were concurrently enriched in flower development, reproductive shoot system development, and shoot system development. Weighted gene co-expression network analysis (WGCNA) identified eight specific modules significantly associated with different developmental stages. The magenta module, containing Unigene0084708 (CoFT) and Unigene0037067 (CoLEAFY), emerged as a key regulatory module driving floral initiation. Additionally, GA20OX1 and GA2OX8 were identified as candidate genes involved in GA-mediated regulation of floral initiation. Based on morphological and transcriptomic analyses, we conclude that floral initiation of C. oleifera is a continuous regulatory process governed by multiple genes, with the FT-LFY module playing a central role in the transition from apical meristem to floral meristem. Full article

Bombus haematurus (Hymenoptera: Apidae), which arrived from the Balkan Peninsula, was first reported in Italy in 2020 in the Friuli Venezia Giulia region (FVG) (northeastern Italy) near the border with Slovenia. To study the spread and biology of the species, a survey was conducted at several sites of the FVG in the period 2023–2025. Bombus haematurus was recorded at 22 new sites across all four districts of the FVG (Trieste, Gorizia, Udine, and Pordenone), indicating its expansion towards the west. Bumblebees of this species were detected in plain and hilly areas at sites between 10 and 364 m a.s.l. They were observed more frequently at forest edges, undergrowth paths or clearings and meadows adjacent to woods, confirming the species is hylophilous. The activity of adults from February to July confirms that the bumblebee is an univoltine spring species. Specimens were observed foraging on the flowers of 19 wild and ornamental plants belonging to 12 families (in particular, Lamiaceae), confirming that the species is polylectic. The data collected indicate that B. haematurus are permanently established in the FVG and that a further spread of the species towards the west in the neighbouring Veneto region is likely. Full article

The quality of Crocus sativus L. flowers, beyond their stigmas, is influenced by the presence of bioactive metabolites also in their floral bio-residues. Given the effect of climatic and soil variables on these bioactive compounds, the aim of this research was to develop an agroecological zoning of saffron crop areas within the Protected Designation of Origin (PDO) La Mancha region (Castilla-La Mancha, Spain) by integrating the floral metabolite content with climatic and soil variables. To achieve this, a total of 173 samples were collected during the 2022 and 2023 harvests and analyzed via RP-HPLC-DAD to determine crocins, picrocrocin, kaempferols, and anthocyanins. Two new indices, Cropi (crocins + picrocrocin) and Kaeman (kaempferols + anthocyanins), were defined to classify flowers into four quality categories (A–D). High-quality classifications (A and B) were consistently associated with plots grouped in the meteorological stations of Ontur, El Sanchón, and Bolaños, indicating favorable edaphoclimatic conditions and climatic parameters, such as moderate temperatures and reduced humidity, for metabolite biosynthesis. In contrast, plots included in the meteorological stations of Tarazona and Pedernoso were mostly assigned to lower categories (C and D). Spatial analysis using thematic maps revealed that areas with an intermediate carbonate content, less calcareous soils, and higher organic matter levels were linked to higher flower quality. These findings highlight the influence of soil characteristics and climate, with distinct seasonal contrasts, that positively influence metabolite synthesis and flower quality. Full article

Crop fidelity is a desirable trait for managed pollinators and is influenced by factors like competing forage sources and colony knowledge of the surrounding environment. In European honey bees (Apis mellifera L.), colonies deployed when the crop is flowering display the highest fidelity. We tested for a similar outcome using a stingless bee species that is being increasingly used as a managed pollinator in Australian macadamia orchards. We observed Tetragonula carbonaria (Smith) colonies deployed in macadamia orchards at three time points: (1) before crop flowering (“permanent”), (2) early flowering (“early”), and (3) later in the flowering period (“later”). We captured returning pollen foragers weekly and estimated crop fidelity from the proportion of macadamia pollen they collected, using light microscopy. Pollen foraging activity was also assessed via weekly hive entrance filming. The early and later introduced colonies initially exhibited high fidelity, collecting more macadamia pollen than the permanent colonies. In most cases, the permanent colonies were already collecting diverse pollen species from the local environment and took longer to shift over to macadamia. Pollen diversity increased over time in all colonies, which was associated with an increase in the proportion of pollen foragers. Our results indicate that stingless bees can initially prioritize a mass-flowering crop, even when flowering levels are low, but that they subsequently reduce fidelity over time. Our findings will inform pollinator management strategies to help growers maximize returns from pollinator-dependent crops like macadamia. Full article

Knowledge about the composition (volatile and non-volatile) and functionality of natural extracts from Mediterranean plants serves as a basis for their further application. In this study, five selected plants were used for the extraction of plant metabolites. Leaves and flowers of Critmum maritimum, Rosmarinus officinalis, Olea europea, Phylliera latifolia and Mellisa officinalis were collected, and a total of 12 extracts were prepared. Extractions were performed under microwave-assisted conditions, with two solvent types: water (W) and a hydroalcoholic (ethanolic) solution (HA). Detailed extract analysis was conducted. Phenolics were analyzed by detecting individual bioactive compounds using high-performance liquid chromatography and by calculating total phenolic and total flavonoid content through spectrophotometric analysis. Higher concentrations of total phenolics and total flavonoids were obtained in the hydroalcoholic extracts, with the significantly highest total phenolic and flavonoid values in the rosemary hydroalcoholic extract (3321.21 mg_GAE/L) and sea fennel flower extract (1794.63 mg_QE/L), respectively; and the lowest phenolics in the water extract of olive leaves (204.55 mg_GAE/L) and flavonoids in the water extracts of sea fennel leaves, rosemary, olive and mock privet (around 100 mg_QE/L). Volatile organic compounds (VOC) were detected using HS-SPME/GC–MS (Headspace Solid-Phase Microextraction coupled with Gas Chromatography-Mass Spectrometry), and antioxidant capacity was estimated using DPPH (2,2-diphenyl-1-picrylhydrazyl assay) and FRAP (Ferric Reducing Antioxidant Power) methods. HS-SPME/GC–MS analysis of samples revealed that sea fennel had more versatile profile, with the presence of 66 and 36 VOCs in W and HA sea fennel leaf extracts, 52 and 25 in W and HA sea fennel flower extracts, 57 in rosemary W and 40 in HA, 20 in olive leaf W and 9 in HA, 27 in W mock privet and 11 in HA, and 35 in lemon balm W and 10 in HA extract. The lowest values of chlorophyll a were observed in sea fennel leaves (2.52 mg/L) and rosemary (2.21 mg/L), and chlorophyll b was lowest in sea fennel leaf and flower (2.47 and 2.25 mg/L, respectively), while the highest was determined in olive (6.62 mg/L). Highest values for antioxidant activity, determined via the FRAP method, were obtained in the HA plant extracts (up to 11,216 mg_AAE/L for lemon balm), excluding the sea fennel leaf (2758 mg_AAE/L) and rosemary (2616 mg_AAE/L). Considering the application of these plants for fresh fish preservation, antimicrobial activity of water extracts was assessed against Vibrio fischeri JCM 18803, Vibrio alginolyticus 3050, Aeromonas hydrophila JCM 1027, Moraxella lacunata JCM 20914 and Yersinia ruckeri JCM 15110. No activity was observed against Y. ruckeri and P. aeruginosa, while the sea fennel leaf showed inhibition against V. fisheri (inhibition zone of 24 mm); sea fennel flower was active against M. lacunata (inhibition zone of 14.5 mm) and A. hydrophila (inhibition zone of 20 mm); and rosemary and lemon balm showed inhibition only against V. fisheri (inhibition zone from 18 to 30 mm). This study supports the preparation of natural extracts from Mediterranean plants using green technology, resulting in extracts rich in polyphenolics with strong antioxidant potential, but with no clear significant antimicrobial efficiency at the tested concentrations. Full article

(1) The primary objective was to determine whether, within this taxonomically challenging group, the closely related European species and their subspecies exhibit distinct inflorescence characters that allow for unambiguous differentiation. This study focuses on two closely related species within the genus Hierochloë: Hierochloë hirta (Schrank) Borbás and Hierochloë odorata (L.) Beauv. (2) For four subspecies, data were collected from 15 inflorescences each, while for one subspecies, 10 inflorescences were examined. From each inflorescence, six spikelets were selected. The statistical analyses were non-parametric methods, the Kruskal–Wallis test, and principal component analysis. (3) Morphological traits showed consistent patterns within each subspecies, indicating their suitability for taxonomic differentiation. The most reliable diagnostic traits were the length of the outer glume of the first flower and the lengths of the awns. (4) The study concludes that while some subspecies can be clearly distinguished based on inflorescence morphology, no single trait is sufficient to completely separate all taxa. The authors recommend recognizing Hierochloë odorata subsp. praetermissa as a subspecies rather than a distinct species and affirm the validity of the species names Hierochloë hirta and Hierochloë odorata. Full article

In order to meet the needs for the rapid detection of crop growth and support variable management in farmland, an intelligent chlorophyll content in cotton leaves (CCC) detection system based on hyperspectral imaging (HSI) technology was designed and developed. The system includes a near-infrared (NIR) hyperspectral image acquisition module, a spectral extraction module, a main control processor module, a model acceleration module, a display module, and a power module, which are used to achieve rapid and non-destructive detection of chlorophyll content. Firstly, spectral images of cotton canopy leaves during the seedling, budding, and flowering-boll stages were collected, and the dataset was optimized using the first-order differential algorithm (1D) and Savitzky–Golay five-term quadratic smoothing (SG) algorithm. The results showed that SG had better processing performance. Secondly, the sparrow search algorithm optimized backpropagation neural network (SSA-BPNN) and one-dimensional convolutional neural network (1DCNN) algorithms were selected to establish a chlorophyll content detection model. The results showed that the determination coefficients $R_p^2$ of the chlorophyll SG-1DCNN detection model during the seedling, budding, and flowering-boll stages were 0.92, 0.97, and 0.95, respectively, and the model performance was superior to SG-SSA-BPNN. Therefore, the SG-1DCNN model was embedded into the detection system. Finally, a CCC intelligent detection system was developed using Python 3.12.3, MATLAB 2020b, and ENVI, and the system was subjected to application testing. The results showed that the average detection accuracy of the CCC intelligent detection system in the three stages was 98.522%, 99.132%, and 97.449%, respectively. Meanwhile, the average detection time for the samples is only 20.12 s. The research results can effectively solve the problem of detecting the nutritional status of cotton in the field environment, meet the real-time detection needs of the field environment, and provide solutions and technical support for the intelligent perception of crop production. Full article

In this study the objective was to morphologically characterize fruits, seeds and seedlings of Cereus fernambucensis Lem., as well as evaluate the seed germination and phenological dynamics of these columnar cacti, native to Brazil, which occur in restinga ecosystems. Biometric and morphological determinations were performed using 100 fruits, describing seed morphology in external and internal aspects and considering five stages of development for the characterization of seedlings. In the study of seed germination, two light conditions (12 h photoperiod and complete darkness) were tested under 25 °C, in a completely randomized design with four replicates of 50 seeds each. In the estimation of reproductive phenology, information was collected from herbarium specimens on the SpeciesLink online platform, and the exsiccatae were analyzed for the notes on their labels to evaluate reproductive aspects. Fruits showed an average mass of 21.11 g, length of 44.76 mm, diameter of 28.77 mm and about 336 seeds per fruit. Seeds behave as positive photoblastic, with a high percentage of germination under controlled conditions (94%). Germination is epigeal and phanerocotylar, with slow growth and, at 30 days after sowing, the seedling measures approximately 2 cm, which makes it possible to visualize the appearance of the epicotyl and the first spines. The species blooms and bears fruit throughout the year, with peaks of flowering and fruiting in January and March, respectively. The various characteristics make C. fernambucensis a key species for maintaining the biodiversity of restingas. Full article

As one component of a study to improve Medicago spp. germplasm in eastern Australia, fifteen phenotypic and agronomic attributes were recorded for 4715 plants grown from the seed of 90 accessions of the widely naturalized pasture legume Medicago polymorpha from 90 sites in eight regions of inland New South Wales. The species expressed wide polymorphism. However, many leaflet attributes were associated with specific climate and soil characteristics, which varied from east to west across the collection zone. Discriminant analysis showed that accessions from the four most northern (summer dominant rainfall) and western (arid–semiarid) regions (Group A) differed from accessions from the most southern, temperate (winter dominant rainfall) and eastern (higher rainfall) regions (Group B). Group A flowered earlier and had shorter pod spines. Group B had lower plant vigor. Regions from which Group A accessions were collected had higher soil pH, lower winter rainfall, and higher minimum winter temperature than Group B regions. The diversity in the population, particularly the difference in flowering times among accessions collected from drier, warmer regions and those from more mesic, cooler regions, and the wide variation in flowering time measured among plants grown from accessions within all collection regions, is likely to ensure the long-term persistence of M. polymorpha in a changing climate. Elite lines were subsequently identified and lodged in National and International Genebanks for future research. Full article

FLOWERING LOCUS T (FT) is a key integrator of flowering pathways. White lupin, a grain legume, encodes four FT homologs: LalbFTa1, LalbFTa2, LalbFTc1, and LalbFTc2. Widespread distribution of white lupin implies diverse phenological adaptations to contrasting ecosystems. Recent studies highlighted associations between FT indels and flowering regulation. Therefore, we surveyed the global white lupin collection for the presence of such indels and potential links to phenology. A panel of 626 white lupin genotypes, representing several European and African agro-climates, was phenotyped under a long-day photoperiod in a two-year study, showing up to 80 days of flowering time difference between early landraces from Eastern Mediterranean and late accessions from France, Madeira, the Canaries, Greece, Italy, and the Azores. As many as seventeen indel variants were identified for LalbFTc1, twelve for LalbFTa2, nine for LalbFTa1, and four for LalbFTc2, yielding roughly three hundred allelic combinations. Significant correlations with phenology were confirmed for one LalbFTa1 indel and twelve LalbFTc1 indels. A large, highly correlated LalbFTc1 indel was revealed to be conserved among all domesticated Old World lupins, carrying all FTc1-promoter candidate binding sites of the same major floral repressor, AGAMOUS-LIKE 15. A small LalbFTa1 indel, providing additional contribution to earliness, showed homology between white and yellow lupins. LalbFTc1 indel-based PCR markers revealed high discriminatory power towards early (PR_42a and PR_71b) or late (PR_58c, PR_36b, PR_80, and PR_60b) flowering. Full article

The Bignoniaceae family encompasses numerous species of ecological, medicinal, and cultural significance, yet its ethnobotanical value remains underexplored in many regions of Thailand. This study investigates the diversity, phenology, cultural relevance, and traditional uses of Bignoniaceae species in Maha Sarakham Province, Northeastern Thailand. Through semi-structured interviews with 260 local informants across 13 districts—alongside field observations and herbarium voucher collections—we documented 27 species across 21 genera. These integrated methods enabled the identification of key culturally significant species and provided insights into their traditional uses. Phenological data revealed clear seasonal patterns in flowering and fruiting, aligned with the regional climatic cycle. Quantitative ethnobotanical indices—including Species Use Value (SUV), Genera Use Value (GUV), Relative Frequency of Citation (RFC), Cultural Importance Index (CI), and Cultural Food Significance Index (CFSI)—were employed to evaluate species significance. Results indicate that species such as Dolichandrone serrulata, D. spathacea, and Oroxylum indicum hold high cultural and practical value, particularly in traditional medicine, spiritual practices, and local landscaping. These findings underscore the critical role of Bignoniaceae in sustaining biocultural diversity and emphasize the urgency of preserving traditional botanical knowledge amid environmental and socio-economic change. Moreover, the insights contribute to broader efforts in cultural heritage preservation and biodiversity conservation across tropical and subtropical regions. Full article

Reliable early-stage yield forecasts are essential in precision viticulture, enabling timely interventions such as harvest planning, canopy management, and crop load regulation. Since grape yield is directly related to the number and size of bunches, the early detection of inflorescences and bunches, carried out even before flowering, provides a valuable foundation for estimating potential yield far in advance of veraison. Traditional yield prediction methods are labor-intensive, subjective, and often restricted to advanced phenological stages. This study presents a deep learning-based approach for detecting grapevine inflorescences and bunches during early development, assessing how phenological stage and illumination conditions influence detection performance using the YOLOv11 architecture under commercial field conditions. A total of 436 RGB images were collected across two phenological stages (pre-bloom and fruit-set), two lighting conditions (daylight and artificial night-time illumination), and six grapevine cultivars. All images were manually annotated following a consistent protocol, and models were trained using data augmentation to improve generalization. Five models were developed: four specific to each condition and one combining all scenarios. The results show that the fruit-set stage under daylight provided the best performance (F1 = 0.77, R² = 0.97), while for inflorescences, night-time imaging yielded the most accurate results (F1 = 0.71, R² = 0.76), confirming the benefits of artificial lighting in early stages. These findings define optimal scenarios for early-stage organ detection and support the integration of automated detection models into vineyard management systems. Future work will address scalability and robustness under diverse conditions. Full article