Frontiers in Plant Science最新文献

Introduction: Improving phosphorus (P)-use efficiency (PUE) while increasing crop yield is one of the greatest challenges in sustainable P management for sustainable agriculture. Types of P fertilizers and soil water supply impact P availability and crop growth, but how to optimize P fertilizer and water supply to enhance the foraging capacity of roots for P remains unclear. This study was aimed at characterizing the effects of different combinations of P fertilizers and water supply on maize growth, root properties and PUE in calcareous soil.

Methods: A pot experiment with four P fertilizers [monoammonium phosphate (MAP), diammonium phosphate (DAP), ammonium polyphosphate (APP) and urea phosphate (UP)] was conducted under well-watered (watered) and water-deficit (dry) conditions using maize (Zea mays L.) in a greenhouse during the seedling stage.

Results: The interaction between P fertilizers and water supply significantly promoted the growth and P uptake of maize by modifying the root morphological and physiological traits. MAP and APP exhibited greater (by up to 62%) total root length in the watered than the dry treatments, resulting in a significant increase in the efficiency of root P acquisition. The APase activity in the rhizosphere soil of MAP and DAP declined (by 37%-62%) significantly, and the rhizosphere soil pH in the DAP treatment was 0.4 units lower in the watered than the dry treatments. APP improved the soil P availability more than the other P fertilizers (17%-41% higher in soil Olsen-P concentration) regardless of water supply.

Conclusion: Optimal combination of P fertilizers and water supply promotes maize growth and PUE due to stimulating the root capacity to forage for nutrient and water resources by regulating the root morphological and physiological traits. Engineering root/rhizosphere by manipulating the interactions of P fertilizer types and water supply can improve nutrient use-efficiency and sustainable crop production.

Introduction: Species composition, interspecific associations, and community stability play crucial roles in shaping individual plant survival and population dynamics. Research in this area carries multidimensional significance for forest conservation, contributing to the maintenance of ecological balance and the enhancement of biodiversity. To explore interspecific interactions among dominant species in evergreen broad-leaved forest communities and promote favorable community development, we selected two representative communities dominated by Castanopsis eyrei and Castanopsis carlesii for detailed investigation.

Methods: Using methods such as niche analysis, variance ratio (VR), chi-square test (χ²), and Spearman's rank correlation, we analyzed the niche characteristics and interspecific association patterns of the 13 tree species with the highest importance values (IV) in each community.

Results: Our results revealed high species richness, with Castanopsis carlesii exhibiting the highest importance value and a relatively wide niche breadth, confirming its dominant role. However, the ranking of niche breadth did not correspond directly to the importance value ranking, suggesting that species distribution frequency plays a key role in determining niche width. The average niche overlap (0.26) and niche similarity coefficient (0.29) among dominant species were low, indicating limited resource sharing. Overall, interspecific associations showed a non-significant negative trend, both χ² and Spearman's tests positive-to-negative association ratio was 0.77.

Discussion: Contrary to previous studies that suggest relative stability in evergreen broad-leaved forests, our findings indicate that the studied communities are currently in a relatively unstable developmental stage. This instability highlights the need for strategic adjustments in species composition and enhanced promotion of positive interspecific relationships. We therefore recommend deliberate optimization of tree species assemblages to strengthen facilitative interactions and improve community resilience.

The genus Gentiana is concentrated in the Qinghai-Tibet Plateau and adjacent Hengduan Mountains, with its distribution pattern reflecting the synergistic effects of geological and climatic changes. This study employs the MaxEnt model integrated with ArcGIS spatial analysis to predict the potential geographical distribution of three medicinal Gentiana species (G. rhodantha, G. cephalantha, and G. rigescens) in China under current and future climate scenarios (SSP126 and SSP585). Under future climate warming, our projections indicate an overall reduction in suitable habitat area for all three species, with G. rigescens experiencing the most severe habitat loss. Furthermore, the centroid of suitable habitats is projected to shift towards higher latitudes and elevations, reflecting a spatial adaptation strategy to climate change. The key environmental drivers of distribution were identified: annual precipitation (Bio12) and minimum temperature of the coldest month (Bio6) primarily determine the distribution of G. rhodantha, while temperature seasonality (Bio4) and altitude are the dominant factors for G. cephalantha and G. rigescens. Our projections indicate an overall reduction in suitable habitat area for all three species under climate warming, with G. rigescens experiencing the most severe loss. Furthermore, the centroid of suitable habitats is projected to shift northwestward and upward in elevation. These findings highlight species-specific responses to climatic factors and provide a scientific basis for prioritizing the conservation of current highly suitable areas (e.g., Yunnan, Sichuan, and Guizhou), establishing ecological corridors, and implementing ex-situ conservation and sustainable cultivation practices to mitigate the impacts of climate change on these valuable medicinal resources.

Introduction: Accurate detection of Taiqiu sweet persimmon in orchards is essential for estimating yield, planning harvest operations, and supporting intelligent management in precision agriculture. However, current fruit-detection approaches for this cultivar, especially during the color-transition period, suffer from highly subjective and inefficient manual inspection and from poor adaptability of existing deep-learning models to complex field scenes.

Methods: In this study, we propose an improved YOLO11-based detector, YOLO11-FC2T, for robust detection under conditions with strong color-background coupling, small or adherent fruits, and uneven illumination. YOLO11-FC2T introduces four key architectural modifications: (1) a C3k2_FasterBlock to improve gradient-efficient feature learning; (2) a C2PSA_CGA module to enhance channel-spatial focus via coordinate-guided aggregation; (3) a three-layer Dysample-T structure to strengthen multi-scale representation; and (4) a cross-scale attention fusion module, CAFMAttention, to better decouple fruits from cluttered backgrounds. To further enhance generalization in complex orchard scenes without additional labeling cost, we introduced the DiffuseMix data-augmentation method and apply it to color-transition images.

Results: Experiments show that YOLO11-FC2T clearly outperforms the YOLO11 baseline. The model achieves a precision of 91.7% (+1.0%), recall of 86.7% (+2.8%), mAP@0.5 of 94.8% (+1.6%), and mAP@0.5-0.95 of 81.2% (+4.0%), where mAP@0.5 uses an IoU threshold of 0.50. On a challenging tail-case set of 537 images, the false detection rate is 1.30%, with a 45.2% reduction in errors relative to YOLO11. In the performance evaluation stage, we first perform causal-effect analysis based on the Average Treatment Effect (ATE) to quantify the independent and joint contributions of each architectural component and of DiffuseMix; at the same time, the efficiency of the model is analyzed by the number of parameters (Params, M) and per-image inference latency (ms). in addition, we construct and use a dedicated tail-case dataset as a supplementary experiment to further verify the robustness and effectiveness of these improvements in the most difficult scenes. Finally, we introduced cross-condition test set to further validate the generalization capability of YOLO11-FC2T. The above results indicate that YOLO11-FC2T not only improves the indicators, but also possesses reliable generalization ability and stability.

Discussion: Overall, YOLO11-FC2T addresses key detection challenges during the color-transition period and provides a practical, portable solution for automated fruit identification and counting in precision agriculture. The above results indicate that YOLO11-FC2T not only improves the indicators, but also possesses reliable generalization ability and stability.

Micropropagation is an important method within plant biotechnology, allowing the bulk multiplication of high-quality, disease-free plants to occur; however, micropropagation faces several challenges, such as microbial contamination, the expensive chemical products used, and losses occurring during the key acclimatization phase of the micropropagation process. Plant growth-promoting microorganisms (PGPMs) have been shown to ameliorate many of these challenges. These microorganisms support growth and development throughout micropropagation via mechanisms such as nutrient solubilization, phytohormone production and inhibition, and inactivation of pathogens. This review focuses on the potential of the use of PGPMs in the explant initiation, shoot multiplication, rooting, and acclimatization stages and is supported by recent research and the mechanisms of action, challenges, and future perspectives of PGPMs.

Introduction: Peanuts (Arachis hypogaea L.) exhibit a high demand for calcium, second only to nitrogen and potassium, with calcium playing a critical role in their growth, development, and nitrogen fixation. However, the mechanisms underlying calcium-mediated regulation of peanut growth and nitrogen fixation remain poorly understood.

Methods: In this study, we employed nitrogen-efficient (Puhua 66, Huayu 20) and nitrogen-inefficient (Puhua 28, Shanhua 14) peanut varieties in a two-year field experiment using a split-plot design. The main plots comprised two treatments: standard fertilization (CK) and calcium supplementation (Ca), while the sub-plots consisted of different peanut varieties. We analyzed growth parameters, physiological responses, and transcriptomic profiles.

Results: Our results demonstrated that calcium application significantly increased malondialdehyde (MDA) content in leaves while reducing peroxidase (POD) activity, enhancing pod dry matter accumulation, and promoting earlier plant maturation. Additionally, calcium application elevated the activities of nitrate reductase (NR) and glutamine synthetase (GS) (P < 0.01), thereby improving nitrogen and calcium accumulation in pods, their allocation efficiency, and the overall utilization rates of nitrogen and calcium fertilizers. Transcriptomic analysis revealed 166 differentially expressed genes (DEGs) in nitrogen-efficient varieties and 343 DEGs in nitrogen-inefficient varieties under calcium supplementation, with 67 DEGs shared between the two groups. Functional annotation and qRT-PCR validation were performed on these DEGs.Furthermore, weighted gene co-expression network analysis (WGCNA) indicated that calcium supplementation significantly up-regulated genes associated with sucrose synthase, β-amylase, GTPase-activating proteins, light-harvesting chlorophyll-protein complexes (Lhca2, Lhca3), photosynthetic electron transport (PetF, PetJ), phosphatidylinositol phospholipase C2, inositol-3-phosphate synthase, TMV resistance protein, ABC transporters, ethylene-responsive transcription factors (EIN1, EIN2, EIN3), alkylamine oxidase, glutamate dehydrogenase, and aspartate synthase.

Conclusion: These findings suggest that calcium application modulates carbohydrate metabolism, nitrogen assimilation, plant-pathogen interactions, and photosynthetic processes through differential gene expression, ultimately enhancing leaf physiological activity, dry matter partitioning, pod yield, and early maturation in peanuts.

Prosopis juliflora (Neltuma juliflora) is a globally invasive tree species threatening arid ecosystems. Its invasion success is driven by specific seed traits that function as an adaptive bet-hedging strategy. The impermeable seed coat enforces physical dormancy and enables the formation of a persistent soil seed bank that buffers against environmental stochasticity (population insurance). Conversely, rapid germination allows the species to exploit short-lived moisture pulses and outcompete native vegetation. Livestock-mediated endozoochory further facilitates directed dispersal by depositing scarified seeds in favorable microsites. This mini-review synthesizes current knowledge on these anatomical and physiological mechanisms and examines how they interact with climate change variables, specifically rising temperatures and altered precipitation on intensifying invasion dynamics. Finally, we discuss integrated management strategies targeting seed bank depletion and dispersal pathways.

Introduction: Extreme winter cold in the Lancang River dry-hot valley limits vegetation establishment. Selecting cold-tolerant native species is therefore critical for ecological restoration and for maintaining stable agro-vegetation. This study aimed to assess cold tolerance in representative native shrubs and herbs using an integrated physiological and biochemical approach.

Methods: Seedlings of three shrubs (Sophora davidii, Vitex negundo var. microphylla, Rumex hastatus) and two herbs (Arthraxon lanceolatus, Artemisia vestita) were exposed to temperatures from 25°C down to -35°C in growth chambers. We quantified membrane injury (relative electrolyte leakage and semilethal temperature, LT50), gas exchange, chlorophyll fluorescence, osmolyte levels (proline, soluble sugars), and antioxidant enzyme activities (e.g., superoxide dismutase). Multivariate analyses (principal component analysis and membership functions) were used to develop an integrated cold-tolerance index.

Results: Semilethal temperature (LT50) differed markedly among species (approximately -27°C in S. davidii vs -5°C in A. lanceolatus), indicating a wide range of freezing tolerance. Across the freezing gradient, S. davidii maintained the lowest electrolyte leakage and partial Photosystem II efficiency, while accumulating high proline and soluble sugar levels and sharply increasing superoxide dismutase activity. In contrast, A. lanceolatus showed rapid membrane leakage and fluorescence declines. The most informative cold-response traits were Photosystem II efficiency and electrolyte leakage. An integrated cold-tolerance index based on multiple physiological metrics ranked species from highest to lowest tolerance as A. vestita > A. lanceolatus > V. negundo > R. hastatus > S. davidii. This ranking differed notably from the ranking based on LT50 alone.

Discussion: The discrepancy between the multi-trait index and single-trait (LT50) ranking highlights the risk of inferring cold tolerance from one metric. Acute stress responses (membrane stability, photosynthesis) and long-term freezing thresholds capture complementary aspects of cold tolerance. The derived physiological thresholds and the multi-indicator framework provide practical guidance for selecting and breeding native species for ecological restoration and cold-resilient agriculture in dry-hot valleys.

Introduction: Enhancing vegetable growth and fruit quality in greenhouse production systems through sustainable nutrient management is a key challenge in modern horticulture. Therefore, this study evaluated the effects of mechanically produced compost and nano-foliar spray application on the growth and fruit quality of sweet pepper (Capsicum annuum L.) grown in a greenhouse under sand and clay soil conditions.

Methods: The experiment was conducted in a controlled plastic greenhouse located at Al-Azhar University, Cairo, Egypt (30° 2' 44'' N, 31° 15' 44'' E), over the 2022-2023 growing season. It was conducted using a factorial design consisting of compost at five volumetric rates (0%, 10%, 15%, 20%, and 25%), two soil types (sand and clay), and nano foliar spray at three concentrations (0, 1, and 2 cm³ L^-1), with three replicates per treatment. Plant growth characteristics and fruit quality parameters were measured. The data were analyzed using three-way analysis of variance, and treatment means were compared using Duncan's multiple range test (p ≤ 0.05).

Results: The results indicated that the level of compost, soil type, and foliar nano-spray significantly affect pepper growth and fruit quality. The treatment (20% compost in sandy soil + 2 cm³ L^-1 of nano-fertilizer) showed better performance in most vegetative growth characteristics and fruit quality traits compared to the other treatments, with a yield of 72.4 tons/ha. Furthermore, Multivariate analyses, including Principal Component Analysis (PCA) and correlation analysis, highlighted strong associations between yield and physiological traits related to photosynthetic capacity and antioxidant status.

Discussion: The proposed approach highlights the integration of organic amendments and nano-based nutrient management as an effective strategy to increase productivity and produce more sustainable vegetables.