Search Results (5,424)

Sustained abiotic stress severely impairs fruit crop growth and development. As plants’ primary environmental sensing organ, fruit tree roots experience disrupted morphogenesis and physiological functions, reducing yield, lowering fruit quality, and threatening orchard ecosystem stability. Abiotic stress is diverse: water deficit from drought, extreme temperature fluctuations, and salinization-induced ion imbalance, heavy metal accumulation, or nutrient disorders. Its complexity requires synergistic and crosstalk regulation of multiple root-specific signaling modules and pathways in root stress perception and transduction. When responding to stress, roots activate hormone, reactive oxygen species (ROS), and calcium ion (Ca²⁺) signaling. These pathways mediate early stress recognition and regulate downstream gene expression and physiological metabolic reprogramming via transcription factors (TFs) and other regulators, determining stress tolerance and adaptability. Using typical abiotic stresses as models, this review outlines the composition, activation mechanisms, specificity, and synergistic effects of root-specific signaling modules/pathways, along with modern biotechnologies for decoding these modules and current research limitations, aiming to reveal the root signal network’s integration mode. Full article

Aquaponic systems are the integration of aquaculture and hydroponic systems to enhance productivity, reduce land use, and improve sustainability. This review focused on commonly used life cycle assessment (LCA) methodologies, system boundaries, and functional units used in aquaponics, standard impact categories, and identified hotspots. The scope is worldwide and encompasses a variety of aquaponic designs, fish species, and crops, illustrating the diversity of the systems examined. The analysis indicates that aquaponics provides the considerable environmental advantages of decreased fertilizer consumption and water conservation in comparison with aquaculture and hydroponic system. However, aquaponics systems are characterized by high energy consumption and may produce greater greenhouse gas (GHG) emissions compared to traditional farming methods when reliant on fossil fuel energy sources. Studies show that fish feed production, system infrastructure, and electricity usage for pumps, lights, heating, and other controls are hotspots. Harmonized comparisons of previous studies show methodological differences, especially in fish–plant co-production. Despite these variations, most believe that energy efficiency, renewable energy, feed optimization, and waste reuse may make aquaponics more sustainable. The study recommends the inclusion of broader environmental and social impacts. Also, future focus might be on making a standard functional unit or specifying system boundaries which might provide different accurate outcomes. Full article

Globally, grasslands, savannas, and wetlands are degrading rapidly and increasingly being replaced by woody vegetation. Woody Plant Encroachment (WPE) disrupts natural landscapes and has significant consequences for biodiversity, ecosystem functioning, and key ecosystem services. This review synthesizes findings from 159 peer-reviewed studies identified through a PRISMA-guided systematic literature review to evaluate the drivers of WPE, its ecological impacts, and the remote sensing (RS) approaches used to monitor it. The drivers of WPE are multifaceted, involving interactions among climate variability, topographic and edaphic conditions, hydrological change, land use transitions, and altered fire and grazing regimes, while its impacts are similarly diverse, influencing land cover structure, water and nutrient cycles, carbon and nitrogen dynamics, and broader implications for ecosystem resilience. Over the past two decades, RS has become central to WPE monitoring, with studies employing classification techniques, spectral mixture analysis, object-based image analysis, change detection, thresholding, landscape pattern and fragmentation metrics, and increasingly, machine learning and deep learning methods. Looking forward, emerging advances such as multi-sensor fusion (optical– synthetic aperture radar (SAR), Light Detection and Ranging (LiDAR)–hyperspectral), cloud-based platforms including Google Earth Engine, Microsoft Planetary Computer, and Digital Earth, and geospatial foundation models offer new opportunities for scalable, automated, and long-term monitoring. Despite these innovations, challenges remain in detecting early-stage encroachment, subcanopy woody growth, and species-specific patterns across heterogeneous landscapes. Key knowledge gaps highlighted in this review include the need for long-term monitoring frameworks, improved socio-ecological integration, species- and ecosystem-specific RS approaches, better utilization of SAR, and broader adoption of analysis-ready data and open-source platforms. Addressing these gaps will enable more effective, context-specific strategies to monitor, manage, and mitigate WPE in rapidly changing environments. Full article

The aquatic plant family Lemnaceae, commonly called duckweed or water lentil, has attracted increasing interest in the scientific literature over the past two decades. It holds extraordinary potential as a new crop due to its multiple applications: as an alternative protein source for feed and food production, as a starch producer for renewable biofuel, and for its capacity to provide valuable ecosystem services. Its high biomass productivity, ability to thrive under a wide range of environmental conditions, lack of requirement for arable land, and aptitude for nutrient recycling from wastewater align with the criteria for future sustainable crops. The Lemnaceae is a small plant family comprising a still uncertain number of species and hybrids with largely unexplored genetic diversity, owing to its taxonomic complexity. We focus on critical aspects that must be addressed to establish duckweed as a viable crop: the availability and accessibility of genomic resources to understand the genetic basis of key agronomic traits; the development of protocols for flower induction and crossing; and the establishment of effective methods for genetic transformation and plant regeneration, all aimed at enabling selection and breeding strategies. We highlight the importance of duckweed germplasm collections, including accessions from a wide geographic and ecological range, as essential resources for addressing duckweed diversity and supporting both fundamental research and agronomic applications. Full article

Plant-derived natural products are an invaluable source of structurally diverse secondary metabolites with ecological and pharmacological significance. Geranium macrorrhizum, a species known for producing essential oils rich in monoterpenoids and sesquiterpenes, has been scarcely explored for its antiparasitic potential. This study represents the first comprehensive evaluation of the antiprotozoal activity of G. macrorrhizum obtained from cultivated plants. Plant material was produced under controlled greenhouse cultivation systems, ensuring high-quality and reproducible metabolite profiles. Essential oils were obtained through hydrodistillation and chemically characterized by Gas Chromatography-Mass Spectrometry (GC–MS). In vitro assays were conducted against Giardia duodenalis, Trichomonas gallinae, and Leishmania infantum to assess antiparasitic efficacy and cytotoxicity. The results demonstrated strong activity of essential oils against Trichomonas gallinae, and Leishmania infantum, indicating the relevance of lipophilic compounds—especially germacrone—as key bioactive constituents. Germacrone exhibited strong and selective antiparasitic activity, outperforming its structural analogues. Microscopic analyses revealed distinct parasite-specific morphological alterations, differing from those induced by conventional drugs such as metronidazole and amphotericin B. These findings highlight G. macrorrhizum obtained through biotechnological cultivation as a novel and sustainable source of natural antiprotozoal agents. The study underscores the importance of integrating controlled cultivation with phytochemical and biological evaluation to advance the discovery of innovative bioactive compounds. Full article

Tropical forests are the most plant-diverse ecosystems on Earth, characterized by extremely high species richness and playing essential roles in ecosystem stability, carbon sequestration, and hydrological regulation. Although remote sensing has been widely applied to monitoring tropical forest plant diversity in recent decades, a systematic understanding of its actual monitoring capacity remains limited. Based on a bibliometric analysis of 15,878 publications from 1960 to 2025, this study draws several key conclusions: (1) Global research is highly unevenly distributed, with most studies concentrated in China’s tropical monsoon forests, Brazil’s Amazon rainforest, Costa Rica’s tropical rainforests, and Mexico’s tropical dry forests, while many other regions remain understudied; (2) The Sentinel-2 and Landsat series are the most widely used satellite sensors, and indirect indicators are applied more frequently than direct spectral metrics in monitoring models. Hyperspectral data, Light Detection and Ranging (LiDAR), and nonlinear models generally achieve higher accuracy than multispectral data, Synthetic Aperture Radar (SAR), and linear models; (3) Sampling scales range from 64 m² to 1600 ha, with the highest accuracy achieved when plot size is within 400 m² < Area ≤ 2500 m², and spatial resolutions below 10 m perform best. Based on these findings, we propose four priority directions for future research: (1) Quantifying spectral indicators and models; (2) Assessing the influence of canopy structure on biodiversity remote sensing accuracy; (3) Strengthening the application of high-resolution data and reducing intraspecific spectral variability; and (4) Enhancing functional diversity monitoring and advancing research on the relationship between biodiversity and ecosystem functioning. Full article

Pulses (edible dry seeds from legumes) are among the most important crops worldwide. These legumes contain a diverse range of carbohydrates, some of which, such as RFOs (raffinose family oligosaccharides), are considered antinutritional factors due to their negative impact on digestion. An analytical method based on high-power ultrasound-assisted extraction and HPLC analysis was developed and validated for the quantitative determination of soluble carbohydrates (verbascose, stachyose, raffinose, sucrose, galactinol, glucose, galactose, fructose, and myo-inositol) in common beans (Phaseolus vulgaris) and peas (Pisum sativum). The proposed method is fast (extraction time: 1 min), reproducible (RDS: 6.9%), accurate (97.5%), and environmentally sustainable. The method was applied to local collections of P. vulgaris (n = 12) and P. sativum (n = 34), revealing similar qualitative profiles but notable quantitative differences. In P. vulgaris, sucrose and stachyose were predominant, while in P. sativum, verbascose stood out. The total sugar content was higher in peas, especially in commercial varieties, which also showed elevated sucrose levels. Some local varieties combined high sugar content with favorable relative levels between RFOs and other sugars, making them valuable candidates for breeding programs. Linear discriminant analysis enabled classification and prediction of species and varieties, confirming the usefulness of soluble carbohydrates as tools for characterizing these plant materials. Full article

In southwest China, vegetation restoration is widely used in karst rocky desertification control projects. However, mechanistic evidence explaining how plant community composition and species diversity regulate cadmium (Cd) bioavailability remains limited. Here, the plant community’s species diversity, soil properties, Cd, and available Cd contents were evaluated. Four plant community types, NR (natural recovery), PMC (Pistacia weinmannifolia + Medicago sativa + Chrysopogon zizanioides), and PME (Pistacia weinmannifolia + Medicago sativa + Eragrostis curvula), were selected as the research objects. The species composition was recorded, and dominant plant species and soil samples were collected to analyze Cd accumulation characteristics. Relative to NR, composite restorations increased plant diversity and soil nutrient availability and reduced soil compaction, with PMC showing the strongest remediation, decreasing total Cd by 49.4% and available Cd by 59.5%. Model-averaged regression and hierarchical partitioning analyses further identified nitrogen availability and community structure as the dominant drivers. Specifically, available nitrogen (AN), vegetation coverage, Margalef species richness (DMG), ammonium nitrogen (NH₄⁺–N), and total N (TN) were the main factors of soil total Cd, and BD, TN, nitrate nitrogen (NO₃⁻–N), mean crown diameter (MCD), and Shannon–Wiener index (H′) were the main factors of soil available Cd. The results indicate that PMC provides a plant community structure configuration decisions of a scalable, site-adaptable strategy for durable Cd stabilization and soil conservation in thin, carbonate-rich karst soils. Full article

Fungal diseases continue to limit global crop production and drive major economic losses. Conventional diagnostic and control approaches depend on time-consuming culture-based methods and broad-spectrum chemicals, which offer limited precision. Advances in molecular identification have changed this landscape. PCR, qPCR, LAMP, sequencing and portable platforms enable rapid and species-level detection directly from plant tissue. These tools feed into RNA-based control strategies, where knowledge of pathogen genomes and sRNA exchange enables targeted suppression of essential fungal genes. Host-induced and spray-induced gene silencing provide selective control without the long-term environmental costs associated with chemical use. CRISPR/Cas9 based tools now refine both diagnostics and resistance development, and bioinformatics improves target gene selection. Rising integration of artificial intelligence indicates a future in which disease detection, prediction and management connect in near real time. The major challenge lies in limited field validation and the narrow range of fungal species with complete molecular datasets, yet coordinated multi-site trials and expansion of annotated genomic resources can enable wider implementation. The combined use of molecular diagnostics and RNA-based strategies marks a shift from disease reaction to disease prevention and moves crop protection towards a precise, sustainable and responsive management system. This review synthesizes the information related to current molecular identification tools and RNA-based management strategies, and evaluates how their integration supports precise and sustainable approaches for fungal disease control under diverse environmental settings. Full article

Słowiński National Park is one of the 23 national parks in Poland and one of the two situated on the Baltic Coast in the country. It was established in 1967 to protect the most valuable ecosystems: coastal lakes, marshes, peat bogs, meadows, forests, and, above all, the dune belt of the Łebska Spit with its unique moving dunes. We aimed to 1. determine the species diversity and structure of thrips assemblages in the most important biotopes of the Park; 2. determine the geographical distribution and food preferences of thrips species; and 3. determine which environmental factors influence the diversity of insect assemblages and which thrips species distinguish these assemblages. The method used in the quantitative research was based on the use of a scoop method; it was supplemented by qualitative research (shaking branches of trees and searching for insects on their host plants). The studies were carried out in 1991 and 1999–2001 in fourteen plant associations. A total of 90 thrips species (nearly 40% of the Polish fauna) were recorded, including 71 in quantitative and 74 in qualitative samples. The study also revealed a significant correlation between the thrips assemblage composition and the following environmental factors: soil moisture, light intensity, general nutrient availability, and soil salinity. In addition, the thrips species with the most significant impact on assemblage composition were identified. The relatively high number of species found, including Taeniothrips zurstrassenii Zawirska, a species new to science, and others rarely recorded in Poland, highlights the value of the SNP habitat diversity in maintaining high Thysanoptera diversity. Full article

Climate fluctuations are expected to drive a decline in the growth of many conifer and broadleaf species, especially in the Mediterranean region, where these species grow at or very near the southern limits of their distribution. Such trends have important implications not only for forest productivity but also for plant diversity, as shifts in species performance may alter competitive interactions and long-term community composition. Using tree-ring data sourced from two Abies cephalonica stands with different elevation in Mount Parnassus in Central Greece, we evaluate the growth responses of the species to climatic variability employing a dendroecological approach. We hypothesize that radial growth at higher elevations is more strongly influenced by climate variability than at lower elevations. Despite the moderate to relatively good common signal indicated by the expressed population signal (EPS: 0.645 for the high-altitude stand and 0.782 for the low-altitude stand), the chronologies for both sites preserve crucial stand-level growth patterns, providing an important basis for ecological insights. The calculation of the Average Tree-Ring Width Index (ARWI) for both sites revealed that fir in both altitudes exhibited a decline in growth rates from the late 1980s to the early 1990s, followed by a general recovery and increase throughout the late 1990s. They also both experienced a significant decline in growth between approximately 2018 and 2022. The best-fit model for annual ring-width variation at lower elevations was a simple autoregressive model of order one (AR1), where growth was driven exclusively by the previous year’s growth (p < 0.001). At the higher elevation, a more complex model emerged: while previous year’s growth remained significant (p < 0.001), other variables such as maximum growing season temperature (p = 0.041), annual temperature (inverse effect, p = 0.039), annual precipitation (p = 0.017), and evapotranspiration (p = 0.039) also had a statistically significant impact on tree growth. Our results emphasize the prominent role of carry-over effects in shaping their annual growth patterns. Full article

The use of acoustic communication and the relatively small antennae possessed by cicadas has led to the suggestion that antennal functions, specifically olfaction, are poorly developed in cicadas. The first step in determining antennal functions is to investigate the fine antennal structure. Scanning electron microscopy was used to visualize the morphology of the antennal sensilla in a diverse group of North American cicadas. The sensilla types and their distribution on the antennae of 30 species representing 12 genera, 6 tribes, and 3 subfamilies of North American cicadas are described and/or illustrated. Seven main classes and several subclasses of antennal sensilla were found: sensilla trichodea, sensilla chaetica, sensilla coeloconica, sensilla styloconica, foramina olfactoria, sensilla campaniformia, and sensilla cavitata-peg. Unique sensilla types and/or organizations of sensilla were found in many of the genera and differences between species of some genera were also present. No sexual dimorphism within species was found in the types or organizational patterns of the sensilla. The diversity of sensilla provides additional data for taxonomy and phylogenetic analyses. The potential function of the various sensilla types is hypothesized. Although relatively small, the antennae of cicadas are likely to provide significant information about their environment and increase their survival, including the selection of specific host plants and microhabitat selection observed in many species. Full article

Genome-wide association studies (GWAS) are essential for identifying genomic regions associated with agronomic traits, but Linear Mixed Model (LMM)-based GWAS face challenges in capturing complex gene interactions. This study explores the potential of machine learning (ML) methodologies to enhance marker identification and association modeling in plant breeding. Unlike LMM-based GWAS, ML approaches do not require prior assumptions about marker–phenotype relationships, enabling the detection of epistatic effects and non-linear interactions. The research sought to assess and contrast approaches utilizing ML (Decision Tree—DT; Bagging—BA; Random Forest—RF; Boosting—BO; and Multivariate Adaptive Regression Splines—MARS) and LMM-based GWAS. A simulated F₂ population comprising 1000 individuals was analyzed using 4010 SNP markers and ten traits modeled with epistatic interactions. The simulation included quantitative trait loci (QTL) counts varying between 8 and 240, with heritability levels set at 0.5 and 0.8. These characteristics simulate traits of candidate crops that represent a diverse range of agronomic species, including major cereal crops (e.g., maize and wheat) as well as leguminous crops (e.g., soybean), such as yield, with moderate heritability and a high number of QTLs, and plant height, with high heritability and an average number of QTLs, among others. To validate the simulation findings, the methodologies were further applied to a real Coffea arabica population (n = 195) to identify genomic regions associated with yield, a complex polygenic trait. Results demonstrated a fundamental trade-off between sensitivity and precision. Specifically, for the most complex trait evaluated (240 QTLs under epistatic control), Ensemble methods (Bagging and Random Forest) maintained a Detection Power (DP) exceeding 90%, significantly outperforming state-of-the-art GWAS methods (FarmCPU), which dropped to approximately 30%, and traditional Linear Mixed Models, which failed to detect signals (0%). However, this sensitivity resulted in lower precision for ensembles. In contrast, MARS (Degree 1) and BLINK achieved exceptional Specificity (>99%) and Precision (>90%), effectively minimizing false positives. The real data analysis corroborated these trends: while standard GWAS models failed to detect significant associations, the ML framework successfully prioritized consensus genomic regions harboring functional candidates, such as SWEET sugar transporters and NAC transcription factors. In conclusion, ML Ensembles are recommended for broad exploratory screening to recover missing heritability, while MARS and BLINK are the most effective methods for precise candidate gene validation. Full article

Vagococcus species have been isolated from diverse environments, including aquatic, terrestrial, food-associated, and clinical sources; however, plant- and flower-associated representatives remain poorly characterized at the genomic level. In this study, we report the complete genomic sequence and analysis of Vagococcus sp. JNUCC 83, isolated from flowers of Camellia japonica collected on Jeju Island, Republic of Korea. The genome comprises a single circular chromosome of 2,472,896 bp with a GC content of 33.5 mol% and was assembled at high depth (555.43×), resulting in a high-quality complete genome. Genome-based phylogenomic analysis using the Type (Strain) Genome Server (TYGS) showed that strain JNUCC 83 forms a distinct lineage within the genus Vagococcus. Digital DNA–DNA hybridization (dDDH) values were far below the 70% species threshold, and 16S rRNA gene-based phylogeny consistently supported its independent placement, suggesting that JNUCC 83 represents a previously undescribed genomic species. Functional annotation based on EggNOG/COG analysis indicated the enrichment of genes involved in core metabolism and genome maintenance, while antiSMASH analysis identified a terpene-precursor-type biosynthetic locus encoding a polyprenyl synthase. Overall, this study expands the genomic understanding of flower-associated Vagococcus lineages and provides a foundation for future investigations into their ecological roles and potential applications as plant-derived microbial resources. Full article

Local vegetables and spices are essential components of traditional food and health systems in northeastern Thailand, yet quantitative ethnobotanical evidence remains limited. This study documents the diversity, utilization, and cultural significance of vegetables and spices used in Sang Kho Sub-district, Phu Phan District, Sakon Nakhon Province. Ethnobotanical data were collected in 2025 through field surveys, voucher-based plant identification, semi-structured interviews, and participant observation involving 92 informants across 23 villages. Cultural significance and medicinal knowledge were evaluated using the Cultural Importance Index (CI), Informant Consensus Factor (FIC), and Fidelity Level (FL). A total of 113 taxa belonging to 94 genera and 49 plant families were recorded. Poaceae and Zingiberaceae were the most species-rich families. Native species slightly predominated (51.33%), and herbaceous taxa were most common. Leaves were the most frequently used plant part. Most taxa were used as vegetables (92 species), followed by traditional medicines (20 species), spices or seasonings (18 species), and food ingredients or culinary additives (18 species). The highest CI values were recorded for Allium ascalonicum L. (1.152), Capsicum annuum L. (1.098), and Coriandrum sativum L. (1.043). FIC values ranged from 0.60 to 1.00, with complete consensus for circulatory and neurological disorders. Cymbopogon citratus showed the highest FL (75%) for gastrointestinal uses. These findings demonstrate the close integration of food and medicine in local plant-use systems and provide baseline data for food system resilience and cultural knowledge conservation. Full article