Frontiers in Plant Science最新文献

Background: Spodoptera frugiperda is a highly invasive pest that significantly threatens maize production globally. This work aims to report the physiological and biochemical impacts of different chemical treatments (DMSO, methyl oleate, DMF, xylene, uniconazole, azadirachtin, and chlorantraniliprole) on maize photosynthetic capacity and resistance response mechanisms from S. frugiperda.

Results: We found a dose-dependent effect on maize photosynthesis; lower concentrations of these chemicals promoted photosynthetic rate, whereas higher concentrations inhibited photosynthesis, especially in lower leaves. Mortality bioassays proved the dose-related response to the toxic potential of DMSO, DMF and xylene. However, the Y-tube bioassay revealed no remarkable changes in olfactory responses, thus indicating that the observed mortality was largely contributed by direct chemical toxicity rather than behavioral alterations. At the molecular level, cytochrome P450 genes (Sf CYP6AB12, Sf CYP6AE43, Sf CYP9A58 and Sf CYP9A59) were significantly overexpressed by chlorantraniliprole, and they were considered to be resistant genes against insecticides. Likewise, other compounds such as azadirachtin and uniconazole also selectively affected some P450 genes, providing additional evidence of the involvement of P450s in S. frugiperda metabolic resistance.

Conclusions: These results demonstrate the involvement of P450s in the development of insecticide resistance and suggest the importance of chemical dose on control of insect pests.

The main disease that affects chickpea production worldwide is Aschochyta blight (AB), caused by the fungus Aschochyta rabiei. The identification of cultivars with stacking resistance genes is crucial for controlling these diseases. This work aimed to evaluate the effect of stacking two resistance-related genes, chitinase and vst-1, on disease response in chickpea (Cicer arietinum L.). Gene stacking was achieved through conventional hybridization between three transgenic inbred lines: N292 and N346 (both carrying chitinase), and N52 (carrying vst-1). PCR confirmed the stable inheritance of both transgenes in F1 and F2 generations, although segregation ratios deviated from Mendelian expectations. Functional assays were conducted using protein extracts to test inhibition of fungal spore germination and mycelium formation, followed by detached-leaf and whole-plant infection assays. Protein extracts from stacked lines significantly reduced spore germination (up to 90% inhibition, P < 0.01) and suppressed mycelium development compared to controls. Detached-leaf assays revealed a reduced disease severity in stacked lines (mean DS = 74 vs. 89 in controls), while whole-plant assays confirmed lower severity scores (mean 4-6 vs. 8 in controls) despite no reduction in infection incidence. The hybrid N346 × N52 exhibited the strongest resistance phenotype across assays. These results demonstrate that stacking chitinase and vst-1 increases tolerance to A. rabiei in chickpea by reducing disease severity, providing a promising strategy for developing tolerant cultivars. This study is a successful tool for developing gene stacking technology in crops to contribute to improving the resistance of chickpea plants to Ascochyta disease.

Fruit recognition and ripeness detection are crucial steps in selective harvesting. To better address the difficulties of fruit recognition and ripeness detection techniques in complex facility environments, a novel lightweight tomato ripeness detection network model based on an improved YOLO v8s is proposed (called TRD-Net). Here, a tomato dataset including 3,330 images from real scenarios was constructed, and an accurate lightweight tomato ripeness detection model trained on the captured images was developed. The TRD-Net model achieves efficient detection of tomatoes affected by overlapping occlusions, lighting variations, and capture angles, offering swifter detection speeds and lower computational demands. Specifically, the feature extraction module of YOLO v8s was refactored by employing spatial and channel reconstruction convolution (SCRConv) and adding the SimAM attention mechanism. The CIoU loss function was replaced by the MPDIoU loss function. The performance of the novel TRD-Net was comprehensively investigated. The proposed TRD-Net achieved an mAP@0.5 of 0.9581 with an improvement of 4.32 percentage points, and the model size decreased from 22.5 M to 17.6 M with an inference time of 8.7 ms per image. The number of model parameters and floating-point operations per second (FLOPs) decreased by 19.69% and 22.03%, respectively. Compared with state-of-the-art models, the proposed TRD-Net is notably promising for real-time tomato recognition and maturity detection. The study contributes to the establishment of a machine vision sensing system for a selective harvesting robot in a complex gardening environment.

Pestalotioid fungi have traditionally been regarded as secondary or opportunistic pathogens of strawberries, which has led to limited research attention. However, recent outbreaks of Neopestalotiopsis have demonstrated its potential to act as a primary pathogen, posing a significant threat to strawberry production worldwide. Current management strategies primarily involve propagation of pathogen-free plants, cultural practices such as field sanitation, crop rotation, and the removal of infected plants, supplemented by the application of biocontrol agents and fungicides. Advances in molecular diagnostic tools have improved early detection and monitoring of Neopestalotiopsis spp. Furthermore, initial efforts have begun to identify sources of genetic resistance in strawberry, thereby supporting future breeding programs. Despite these advancements, a considerable gap remains in our understanding of the host's defense mechanisms, the pathogen's infection strategies, the dynamics of their interactions, and the pathogen's ecology. The taxonomy's complexity and the variability in virulence among its isolates further complicate diagnosis and control efforts. Addressing these challenges is crucial to developing sustainable, integrated disease management strategies and advancing resistance breeding, thereby ensuring the long-term productivity and resilience of the strawberry industry. This review consolidates the current understanding of Neopestalotiopsis spp., evaluates the available diagnostic tools and management strategies, discusses recent progress in genetics and genomics for breeding resistance to this pathogen, and identifies areas for further research.

Background: Rhizosphere microorganisms play a critical role in plant growth and medicinal quality, yet their altitudinal patterns and interactions with soil nutrients and bioactive compounds in Angelica sinensis (A. sinensis) remain poorly understood.

Methods: Using Illumina MiSeq sequencing, we analyzed bacterial, fungal, arbuscular mycorrhizal (AM) fungal, and archaeal diversity across an altitudinal gradient, alongside soil physicochemical characteristics and bioactive components.

Results: As cultivation elevation increased, bacterial and fungal diversity initially increased significantly and then stabilized (p < 0.05). In contrast, AM fungal and archaeal communities remained relatively stable. Bacterial communities varied significantly across altitudes (stress < 0.1, p = 0.001), as did soil nutrients and enzyme activities (p < 0.05). Bioactive components, except for ferulic acid, varied significantly with altitude. Redundancy analysis (RDA) confirmed that altitude and soil factors are key drivers of microbial community assembly. Mantel tests and structural equation modeling (SEM) demonstrated significant correlations between soil properties, microbial diversity, and medicinal properties of A. sinensis (p < 0.05).

Conclusion: The mid-to high elevation zone (2520-2717 m) was identified as optimal for both yield and bioactive compound accumulation. These findings deepen the understanding of how microbes adapt to different altitudes in medicinal plants and offer a framework for precise cultivation of A. sinensis, thereby supporting the high-altitude symbiosis theory.

Abiotic stress and low resource-use efficiency are among the main challenges in agricultural production systems. Stress management is key to sustainable production. It is still challenging to identify and manage prevailing stresses under field conditions due to limited knowledge of the mechanisms of multiple abiotic stressors in crops. Crop models are becoming popular in agriculture because of their diversified nature in identifying multiple abiotic stresses and resource-use management in the complex nature of agricultural production systems. This study combined field measurements and crop modeling to improve the understanding of below- and above-ground resources use (water, nutrients, and light) and their impact on crop productivity and stress management under various planting conditions. A two-year field trial was conducted in the Thai uplands, comparing six treatments: (T1) maize sole crop with tillage and fertilization; (T2) maize-chili intercropping with tillage and fertilization; (T3) same as T2 but with minimum tillage and Canavalia ensiformis relay cropping; (T4) same as T3 plus Leucaena hedgerows; (T5) same as T3 without fertilization; and (T6) same as T4 without fertilization. The Water Nutrient and Light Capture in Agroforestry Systems (WaNuLCAS) model was calibrated using data from T1, T4, and T6 and evaluated against independent observations from T2, T3, and T5. Row-wise aboveground biomass, grain nitrogen (N) and phosphorous (P) concentrations, δ¹³C values, soil volumetric water content, and root length density were measured over two growing seasons. Grain δ¹³C values were significantly less negative in rows near the hedge (-10.33‰) than in distant rows (-10.64‰). More negative grain δ¹³C values (-9.32‰, p ≤0.001) were observed in T6. Both field observations and model simulations showed reduced maize biomass and lower grain N and P concentrations in rows closest to the hedgerows, driven by root competition for nutrients. Soil moisture was consistently higher in intercropped systems, and hedgerow height control prevented shading, indicating no water or light limitations. From the results it is concluded that WaNuLCAS model accurately reproduced spatial biomass patterns (EF = 0.95, RMSE = 0.98, and R2 = 0.96) and correctly identified nitrogen and phosphorus stress in maize rows planted closely with leucaena hedgerows. Scenario simulations demonstrated that balanced increases in both N and P inputs most effectively alleviated nutrient competition and improved the long-term system productivity. This integrated field-model approach provides a robust framework for diagnosing resource competition and optimizing nutrient management in hedgerow-based agroforestry systems under upland conditions.

The plant homeodomain (PHD) finger constitutes a subgroup of transcription factors that contribute to the coordination of plant growth, morphogenesis, and adaptation to environmental stress mechanisms. In this study, we identified and functionally characterized the BrPHD58 gene from Brassica rapa. Using sequence analysis, subcellular localization of BrPHD58-GFP fusion proteins, and transgenic Arabidopsis thaliana lines ectopically expressing BrPHD58, we investigated its role in salt stress responses, including seedling phenotypes and expression of salt-responsive genes. Subcellular localization analysis indicated that BrPHD58 predominantly accumulates within the nuclear compartment. Ectopic expression of BrPHD58 in A. thaliana significantly reduced seedling survival rates and root lengths under varying concentrations of NaCl compared to wild-type (WT) plants. Under soil-grown conditions, transgenic lines overexpressing BrPHD58 exhibited markedly decreased tolerance to salt stress. Moreover, ectopic expression of BrPHD58 led to a down regulation of key salt-responsive genes, AtRD22, AtRD29A, and AtLEA14, under salt stress conditions. Collectively, all these findings indicate that BrPHD58 acts as a negative modulator of salt stress tolerance in transgenic plants. Further investigation involving the development and analysis of BrPHD58 loss-of-function mutants in B. rapa is necessary to fully elucidate its physiological role in salinity adaptation.

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.