Frontiers In Plant Science[JOURNAL]
Sun
200 papers
Genome-wide analysis of the ALDH superfamily in highlights roles in abiotic stress responses.
Wang X, Zhang T, Tian Y … +6 more , Wang J, Liu X, Zhang G, Wang D, Zhang H, Yu L
Front Plant Sci · 2026 · PMID 42318124 · Full text
Abiotic stresses significantly impede the growth and yield of plants. In this context, the aldehyde dehydrogenase (ALDH) superfamily is integral to plant stress responses. To date, the systematic identification and funct...
Abiotic stresses significantly impede the growth and yield of plants. In this context, the aldehyde dehydrogenase (ALDH) superfamily is integral to plant stress responses. To date, the systematic identification and functional characterization of the ALDH superfamily have not been reported. This study represents the first genome-wide systematic analysis of the CmALDH superfamily, identifying 25 genes across nine families. Phylogenetic analysis suggests that members of the CmALDH superfamily underwent purifying selection during evolution, predominantly driven by dispersed duplication events. Collinearity analysis demonstrated both conservation and species-specific variations of genes between and several other species. Examination of -acting elements revealed that promoter regions contain numerous elements associated with hormone response, abiotic stress, and light response. Transcriptome data analysis for six abiotic stresses (high temperature, low temperature, drought, salt, alkalinity, and shading) and RT-qPCR validation (high temperature, low temperature, salt, and alkaline stresses) revealed differential expression of various genes, suggesting their potential roles in stress responses. This study systematically elucidates the evolutionary characteristics and abiotic stress response mechanisms of the CmALDH superfamily, providing valuable genetic resources and a theoretical basis for further analysis of the molecular underpinnings of stress resistance in woody plants and for the genetic enhancement of resistance in .
Robust multi-target multi-scale tomato leaf disease detection for precision agriculture applications.
Pan JZ, Xie Y, Zhao SY … +6 more , Kang YL, Yin SH, Fan ZQ, Guo LF, Qi LM, Si CJ
Front Plant Sci · 2026 · PMID 42318123 · Full text
The tomato is one of the most important economic crops worldwide; frequent occurrences of foliar diseases can severely affect its quality and yield, resulting in substantial economic losses. However, state-of-the-art met...
The tomato is one of the most important economic crops worldwide; frequent occurrences of foliar diseases can severely affect its quality and yield, resulting in substantial economic losses. However, state-of-the-art methods still struggle with multi-target, multi-scale disease detection in complex scenarios, lacking accuracy and speed for tomato leaf diagnosis. A novel improved YOLO v8s model is proposed in this study to achieve high-precision and fast identification of multi-target and multi-scale tomato leaf diseases. First, a multi-target, multi-scale image dataset encompassing seven typical tomato diseases was developed to effectively enhance the model's robustness under complex practical scenario by integrating multiple public datasets and employing diverse data augmentation techniques. Second, a transfer learning strategy was employed to transfer high-quality features from a pretrained model to the disease detection task, thereby improving convergence speed and generalization ability. Finally, the CBAM (Convolutional Block Attention Module) channel-spatial attention mechanism was introduced into the YOLO v8s network, enabling the model to adaptively focus on critical regions and significantly enhance feature extraction and target localization performance. Experimental results demonstrate that the improved YOLOv8s-CBAM model achieves superior performance in complex scenarios, with a precision of 96.9%, recall of 97.3%, F1 score of 97.0%, and mAP@0.5 of 99.1%, representing improvements of 2.5%, 2.0%, 2.2%, and 1.8%, respectively, over the original YOLO v8s model. Moreover, the model size was reduced to 24.8 MB, a decrease of 11.7 MB compared to the original, achieving an effective balance between accuracy and lightweight design. These results indicate that the proposed method exhibits enhanced feature extraction and localization stability in multi-target, multi-scale disease identification tasks, providing an effective technical solution for automated detection in complex agricultural disease scenarios.
Geminivirus-derived replicons: assessment for transient GFP expression in tobacco and tomato.
Tsakirpaloglou N, Melita O, Kaldis A … +2 more , Polidoros A, Voloudakis A
Front Plant Sci · 2026 · PMID 42318122 · Full text
Global food security requires innovative strategies for sustainable crop improvement. Gene editing offers a precise and rapid approach to plant modification, but its success depends on efficient delivery and robust expre...
Global food security requires innovative strategies for sustainable crop improvement. Gene editing offers a precise and rapid approach to plant modification, but its success depends on efficient delivery and robust expression systems. Geminivirus-derived replicons (GVRs) enhance transient expression by amplifying introduced DNA within plant cells. In this study, we evaluated three previously deconstructed geminiviral backbones -Bean yellow dwarf virus (BeYDV), Tomato leaf curl virus (ToLCV), and Wheat dwarf virus (WDV)- against a non-replicating T-DNA control for their ability to sustain GFP expression in tobacco () and tomato (). Constructs were delivered via , and GVR circularization was verified, with accumulation levels dependent on the specific replicon and host species. GFP RNA and protein accumulation was assessed by RT-qPCR, fluorescence imaging, and ELISA; all GVRs prolonged GFP fluorescence relative to control. In tobacco, transcript levels increased significantly by 3 days post infiltration (dpi), reaching up to 221- fold by 6 dpi with BeYDV, while BeYDV and ToLCV produced approximately fivefold higher protein levels. In tomato, ToLCV and WDV showed the strongest enhancement, with transcript and protein levels increasing up to 6.3-fold and 2.4-fold, respectively. These results demonstrate that GVRs markedly enhance and extend transient gene expression in solanaceous hosts, with performance dependent on the replicon and plant species. ToLCV and BeYDV were most effective in tobacco, whereas ToLCV and WDV performed best in tomato. Overall, GVRs represent versatile tools for transient protein production and for improving the delivery and efficiency of genome-editing reagents in plants.
The relationship of rice yield and quality with the utilization of temperature and light resources in regions at different altitudes.
Li R, Luo Y, Lu T … +12 more , Wang A, Ni J, Chen K, Sun Y, Luo G, Yuan X, Liao Q, Zhao Y, Wang Z, Yang Z, Ma J, Sun Y
Front Plant Sci · 2026 · PMID 42318121 · Full text
INTRODUCTION: Existing studies on the effects of altitude on rice yield and quality have drawn different conclusions. However, the underlying mechanisms of how altitude-induced differences in the utilization of temperatu...
INTRODUCTION: Existing studies on the effects of altitude on rice yield and quality have drawn different conclusions. However, the underlying mechanisms of how altitude-induced differences in the utilization of temperature and light resources drive the differential responses of yield and quality formation remain unclear. In particular, the synergistic effects of the ecological adaptability of rice varieties, altitude-mediated distribution of light and temperature resources, and nitrogen regulation on rice yield and grain quality have not yet been clearly elucidated. METHODS: A two-year field experiment was conducted in low-altitude (520.70 m) and high-altitude (1640.56 m) rice-growing regions using two rice varieties with differential altitude responsiveness of core agronomic traits, Meixiangzhan 2 and Yunjing 39. Under a nitrogen (N) application rate of 150 kg N ha-1, three N management strategies with basal: tiller: panicle fertilizer ratios of 5:3:2 (N1), 3:3:4 (N2), and 3:1:6 (N3) were implemented, with a no-N treatment (N0) as the control. RESULTS: Altitude, variety, and N management significantly affected grain yield, rice quality, and the utilization of temperature and light resources. Compared with the low-altitude site, the rice growth period at high altitude was prolonged by 27.25-30.77 days, while effective panicles and seed-setting rates increased by 16.53%-27.37% and 2.71%-6.68%, respectively, contributing to a 4.10%-4.12% yield increase. Meixiangzhan 2 showed higher yields at low altitude (4.84%-8.12%) but significantly lower yields at high altitude (19.80%-25.13%) compared with Yunjing 39. High altitude improved grain quality by increasing head rice rate (5.10%-9.42%) and reducing chalkiness (2.87%-6.38%), although lower temperatures from the heading to maturity stage increased amylose content (13.71%-19.82%) and reduced taste value (2.29%-5.22%). Among the N treatments, N2 consistently improved both yield and rice quality of two varieties at different altitudes. DISCUSSION: Optimizing temperature and light resource allocation during key growth stages-particularly increasing the effective accumulated temperature over the entire rice growth period, the diurnal temperature range from heading to maturity stage, the average daily sunshine hours, and the solar radiation-is critical for achieving high yield, high quality, and efficient resource utilization across altitudes.
Habitat suitability for the soybean aphid, , and its natural enemies: implications for biological control and soybean protection.
Wang Z, Yang M, Li Z … +9 more , Miao X, Liu J, Zhang J, Xie L, Xu K, Ding W, Zhang W, Dai P, Ma K
Front Plant Sci · 2026 · PMID 42318120 · Full text
The soybean aphid, Matsumura, is one of the most destructive pests affecting soybean production, frequently inflicting substantial economic losses. In this study, an optimized MaxEnt model was employed to predict the ha...
The soybean aphid, Matsumura, is one of the most destructive pests affecting soybean production, frequently inflicting substantial economic losses. In this study, an optimized MaxEnt model was employed to predict the habitat suitability of , its host plant , and four key natural enemies (, , , and ). Furthermore, the overlaying ranges of suitable habitats of and these natural enemies were identified. Results indicated that the area under the receiver operating characteristic (AUC) values of the six models ranged from 0.856 to 0.981 and the true skill statistic (TSS) values from 0.470 to 0.733. The highest contributing variables for the models of , , , , , and were BIO04 (temperature seasonality), BIO18 (precipitation of warmest quarter), BIO14 (precipitation of driest month), BIO01 (annual mean temperature), BIO18, and BIO17 (precipitation of driest quarter), respectively. Different natural enemies exhibited distinct niche overlaps with in spatial distribution. For instance, the overlaying range between and were distributed across East China, Korea, and Japan, whereas those between and were mainly concentrated in parts of South China and most of Japan. The differences suggest that priority regions for the release of different enemies can be identified to potentially control . Compared with previous modeling study on , this study adopted a MaxEnt parameter optimization approach and defined the suitable habitats of under the presence of its host . The results could enhance the understanding of the potential distribution of and effectively facilitate the selection and application of natural enemies for regional biological control of this pest.
Bifunctional metal nanoparticles in agriculture: an opinion on their role as fungicides and fertilizers.
Rosas-Diaz J, Cruz-López V, Hernández-Ramírez C … +4 more , Echeverría-Pérez EG, Martínez-Carreón MJ, Matadamas-Ortiz PT, Cruz-Martínez H
Front Plant Sci · 2026 · PMID 42318119 · Full text
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Genome-wide association analysis identifies SNP loci for multi-stage yield-related traits in wheat.
Li M, He R, Chai Q … +4 more , Wang X, Fu Y, Liu R, Zhao Y
Front Plant Sci · 2026 · PMID 42318118 · Full text
INTRODUCTION: Wheat is a major global food crop, and improving its yield is essential for food security. Identifying genetic loci and candidate genes associated with yield-related traits is crucial for molecular breeding...
INTRODUCTION: Wheat is a major global food crop, and improving its yield is essential for food security. Identifying genetic loci and candidate genes associated with yield-related traits is crucial for molecular breeding. METHODS: A panel of 768 common wheat varieties from domestic and international sources was evaluated over two consecutive years (2024 and 2025) in Tai'an. Three growth-stage traits, eight agronomic traits, and three seedling-stage traits, including root length, seedling weight, and seedling height, were measured. Genotyping was performed using a 55K SNP array, and a genome-wide association study was conducted using a linear mixed model. RESULTS: Population structure and kinship analyses classified the varieties into primitive landraces and modern cultivars. A total of 49,768 high-quality SNPs were identified, covering 82.73% of the genome with an average marker density of 0.29 Mb. Among them, 17,293, 18,313, and 14,162 SNPs were located on the A, B, and D subgenomes, respectively. Association analysis revealed 544 SNP loci significantly associated with yield-related traits across 21 chromosomes, of which 49 were consistently detected in both years. Additionally, 60 loci were associated with two or more traits, indicating potential pleiotropic effects, and were distributed on 16 chromosomes (excluding 3D, 4B, 4D, 7A, and 7B). DISCUSSION: This study identifies SNP markers associated with key traits across growth stages in common wheat and provides a basis for the discovery of candidate genes and favorable alleles. These findings may facilitate the utilization of elite genetic resources for yield improvement in wheat breeding.
Metabolic engineering strategies for optimized lignan production in plants.
Choi S, Lee SB, Kim BG
Front Plant Sci · 2026 · PMID 42318117 · Full text
Plant secondary metabolites, including lignans, play essential roles in plant defense and adaptation, and their pharmacological properties are increasingly valued for human health. Lignans are dimers derived from the phe...
Plant secondary metabolites, including lignans, play essential roles in plant defense and adaptation, and their pharmacological properties are increasingly valued for human health. Lignans are dimers derived from the phenylpropanoid pathway whose biosynthesis is tightly controlled by dirigent proteins, laccases, and other redox-related enzymes. Recent advances in plant metabolic engineering have progressed from simple single-gene overexpression to integrated strategies that combine transcriptional regulation, metabolic flux optimization, and CRISPR-based genome editing. This review proposes the "Push-Pull-Release" framework to organize these approaches. This framework utilizes three complementary mechanisms: "Push" strategies to increase precursor supply through master transcription factors such as AtMYB85 and enzymatic overexpression; "Pull" methods to redirect flux by attenuating competing metabolic sinks, including CHS- and F5H-associated branches; and "Release" mechanisms that alleviate intrinsic pathway repression by targeting MYB repressors and post-translational regulators such as KFB proteins. Advanced control is further achieved through synthetic biology principles, including modular pathway reconstruction, multiplex genome editing, and spatiotemporal regulation through tissue-specific, inducible, and subcellular engineering strategies. Case studies on sesamin, podophyllotoxin, and a proposed SDG production framework in flax illustrate how these multi-layered strategies may be integrated in plant systems. However, maximizing lignan yield must be balanced against trade-offs in plant structural integrity and disease resistance. Accordingly, future lignan metabolic engineering should integrate multi-layered controls with spatiotemporal regulation and systematic phenotypic evaluation to achieve sustainable production while preserving plant fitness.
Diversity and composition of root-associated fungal communities in critically small population of .
Hua M, Jiang H, Yuan R … +1 more , Kong J
Front Plant Sci · 2026 · PMID 42318116 · Full text
is a critically small population wild orchid. Understanding the composition and diversity of its root- associated fungal communities is essential for its conservation and artificial propagation. Illumina Novaseq high- th...
is a critically small population wild orchid. Understanding the composition and diversity of its root- associated fungal communities is essential for its conservation and artificial propagation. Illumina Novaseq high- throughput sequencing was used to analyze the diversity and composition of fungal communities in the root-endosphere and rhizosphere soil of collected from different regions, habitats, and population types in Yunnan Province. The number of amplicon sequence variants (ASVs) differed by only 0.33% between root-endosphere and rhizosphere soil samples. A total of 34,564 ASVs were detected in root-associated samples from Wenshan Prefecture (Maguan, Malipo, Xichou), accounting for 87.76% of the total ASVs across all samples. Fungal richness of root-associated samples in was highest in Wenshan, followed by Baoshan, Nujiang, and Kunming. Three fungal ASVs were shared between root-endosphere and rhizosphere soil across 120 samples from 12 habitats. Fungal community composition and diversity differed significantly between root-endosphere and rhizosphere soil samples. Samples from Wenshan showed the highest species richness, evenness, and diversity, whereas those from Kunming exhibited the lowest. In Malipo County, fungal abundance and diversity did not differ significantly between wild and introduced populations, but both were significantly higher than in seed-propagated populations in Kunming. Notable regional variations in dominant fungi were observed: Mortierella dominated Wenshan samples, dominated Nujiang samples, dominated Baoshan samples, and dominated Kunming cultivated samples. NMDS analysis showed Wenshan samples aggregated closely, while other regions' samples were dispersed. Core fungal species including sp., , and ., which were distributed across all regions. This study reveals clear regional and habitat- driven patterns in root- associated fungal communities of . The findings provide a reliable scientific basis for the conservation and artificial propagation of this endangered orchid.
An integrated Msr-antioxidase-host gene circuit maintains redox homeostasis in legume-rhizobium symbiosis.
Si Z, Wang Y, Shen M … +7 more , Yu Y, Wei F, Lu Y, Long X, Yi Y, Lin H, Li Y
Front Plant Sci · 2026 · PMID 42318115 · Full text
Methionine sulfoxide reductases (Msrs) play a critical role in oxidative stress resistance; however, their functions in rhizobium-legume symbiotic nitrogen fixation (SNF) are not well understood. In this study, we system...
Methionine sulfoxide reductases (Msrs) play a critical role in oxidative stress resistance; however, their functions in rhizobium-legume symbiotic nitrogen fixation (SNF) are not well understood. In this study, we systematically characterized four Msrs (MsrA1, MsrB1, MsrA2, MsrB2) from 7653R, a symbiotic partner of . Sequence and phylogenetic analyses confirmed the presence of conserved catalytic domains and revealed genus-specific clustering of these Msrs. Expression profiling demonstrated distinct patterns: and were transiently induced during early symbiotic infection, whereas and exhibited biphasic upregulation at both early infection and nodule maturation stages. Notably, responded specifically to HO, and all genes were induced by sodium hypochlorite in a concentration-dependent manner. Phenotypic analyses of overexpression (OE) and deletion (Δ) strains indicated that Msrs modulate key bacterial physiological traits. Deletion mutants showed impaired motility, reduced biofilm formation, and decreased activities of antioxidant enzymes (catalase, glutathione peroxidase, superoxide dismutase), accompanied by elevated intracellular superoxide anion and HO content. In contrast, overexpression enhanced oxidative stress resistance but suppressed bacterial growth. In symbiotic assays, overexpression of , , or resulted in leaf chlorosis, reduced nodule number, and impaired nitrogen fixation efficiency, while and mutants affected nodulation without compromising plant vigor. Further investigation revealed that Msrs regulate host root antioxidant responses and the transcription of symbiotic-related genes (, ) and defense-related genes (, ). Bacterial two-hybrid assays identified physical interactions between Msrs and chaperone proteins (GroEL1/2/3), antioxidant enzymes (SodA/B, KatE/G), and the LysR-type transcriptional regulator LsrB, suggesting the formation of an integrated redox regulatory network. Collectively, our findings demonstrate functional specialization of Msrs in 7653R, mediating oxidative stress resistance, bacterial physiology, and host-symbiont crosstalk. We propose a "Msr - antioxidant enzyme - host gene" regulatory model that maintains redox homeostasis during SNF. This study provides novel insights into the roles of rhizobial Msrs and offers potential targets for engineering high-efficiency nitrogen-fixing strains.
Navigating heavy metal stress: emerging roles of TOR and SnRK signaling in plant tolerance.
Naaz S, Laxmi A
Front Plant Sci · 2026 · PMID 42318114 · Full text
This review explores emerging insights about how plants regulate their responses to heavy metal stress through the coordinated actions of the Target of Rapamycin (TOR) and Sucrose Non-Fermenting-1-Related Kinase (SnRK) s...
This review explores emerging insights about how plants regulate their responses to heavy metal stress through the coordinated actions of the Target of Rapamycin (TOR) and Sucrose Non-Fermenting-1-Related Kinase (SnRK) signaling pathways. Toxic heavy metals such as As, Pb, Cd and Hg cause severe metabolic and oxidative stress in plants, which reduces their growth and development and ultimately disrupts cellular homeostasis. In this review, we highlight the unique direction of research that focuses on TOR-SnRK interaction under heavy metal exposure, emphasizing their opposite yet interconnected roles in metabolic reprogramming, stress tolerance, and in growth regulation. Under heavy metal stress, SnRK kinases are activated, which triggers the expression of stress-responsive genes and activates autophagy, while downregulating TOR activity to conserve energy and divert resources toward defense, which maintains redox homeostasis, allows plants able to survive. TOR-SnRK pathways interacts with calcium, hormonal, and redox signaling networks, which further strengthen plant stress responses and regulate tolerance mechanisms. Understanding the TOR-SnRK pathway provides a deepened understanding of how plants regulate energy under toxic environmental conditions. In addition to these, targeting these pathways assists in designing crops and agricultural products that are more resilient to heavy metal toxicity, promoting sustainable agriculture in contaminated areas.
DESI-MSI applications for direct (spatial) biomolecular analysis of South African natural medicinal products.
Mohlamonyane KN, Ncube EN, Giampà M … +5 more , Chen W, Zeiss D, Verhaert PD, Ghesquière B, Viljoen AM
Front Plant Sci · 2026 · PMID 42318113 · Full text
INTRODUCTION: In pharmacognosy, conventional analytical methods provide important chemical information on metabolite identities and relative quantities. However, analysis and the mapping of the spatial distribution of m...
INTRODUCTION: In pharmacognosy, conventional analytical methods provide important chemical information on metabolite identities and relative quantities. However, analysis and the mapping of the spatial distribution of metabolites remain underexplored. Mass spectrometry (MS) imaging techniques, specifically desorption electrospray ionization-MS imaging (DESI-MSI), enables the analysis and visualization of the spatial distribution of metabolites in different plant tissues. This study aimed to demonstrate the application of DESI-MSI for the analysis and visualization of the spatial distribution of metabolites in selected South African medicinal plants and natural products. METHODS: DESI-MSI was used to putatively assign antimicrobial compounds from propolis HPTLC-bioautography assay and to visualize the spatial distribution of various compounds, including coumarins in the roots of and , pyrrolizidine alkaloids in the stems of , and aspalathin in the leaves of RESULTS: The antimicrobial compounds of South African propolis were putatively assigned as chrysin, pinocembrin, galangin, pinobanksin and its derivatives. The technique enabled the differentiation between and based on the location and spatial distribution of umckalin, dihydroxy-dimethoxycoumarin and isofraxidin sulphite in the root samples. Furthermore, the spatial distribution of pyrrolizidine alkaloids (PAs) was mapped in the pith, epidermis, and cortex regions of stems, while aspalathin was mapped in the margins and tips (upper and lower epidermal regions) of leaf samples. CONCLUSION: This study demonstrates the feasibility of using DESI-MSI for chemical profiling of commercially important South African medicinal plants and natural products, supporting their identification and differentiation for quality control.
Habitat suitability and driving factors of the endangered medicinal plant under climate and land use change.
Tu GH, Liu L, Chen F … +4 more , Xi SY, Guo XD, Jing ZX, Jin L
Front Plant Sci · 2026 · PMID 42318112 · Full text
INTRODUCTION: Climate change and land-use change pose significant threats to the survival of endangered medicinal plants. This study focuses on the endangered medicinal plant . METHODS: Using 268 distribution records and...
INTRODUCTION: Climate change and land-use change pose significant threats to the survival of endangered medicinal plants. This study focuses on the endangered medicinal plant . METHODS: Using 268 distribution records and an optimized MaxEnt model (RM = 4.0, FC=LQHPT), together with an OptimalParameters Geographical Detector (OPGD), the current and future habitat suitability,driving mechanisms, and the impact of land use change under variousclimate scenarios (SSP126, SSP370, SSP585) were systematically evaluated. RESULTS: The results indicate that: (1) The current suitable habitat area for is 1.1608 × 10⁶ km², primarily distributed in Sichuan, Tibet, and Gansu along the eastern edge of the Qinghai-Tibet Plateau. High suitability areas are concentrated at altitudes between 2800-3500 m. (2) Future climate warming is projected to promote the northwestward expansion of suitable areas. Under the SSP585 scenario, the suitable habitat area is expected to increase to 1.8770 × 10⁶ km² by the 2090s, representing a 61.70% increase from the current area, with the habitat centroid shifting by 333.74 km. (3) Altitude (contribution rate of 34.5%, q = 0.245), minimum temperature of the coldest month (26.4%), and annual precipitation (20.7%) are the dominant factors influencing distribution. Interactions among environmental factors significantly enhance explanatory power, with the strongest synergistic effect observed for bio12 ∩ elevation (q = 0.685). (4) High-risk areas (as defined by the OPGD Risk Detector) cover 5.30 × 10⁴ km², with 75.3% located outside existing nature reserves. (5) Grassland (4.979 × 10⁵ km²) and forest land (4.731 × 10⁵ km²) are the primary carrier ecosystems, with moderately suitable grassland areas projected to increase under future climate scenarios. DISCUSSION: This study reveals the strict ecological requirements of for high-altitude, low-temperature, and moderate‑precipitation environments, as well as the synergistic effects of hydrothermal coupling on its distribution. The findings provide a scientific basis for conservation planning, the designation of priority conservation areas, and climate‑adaptive management of endangered medicinal plants.
Multi-scale feature fusion-based vision mamba for robust plant disease image classification on field-acquired plantdoc data.
Zhang S, Liu R
Front Plant Sci · 2026 · PMID 42318111 · Full text
INTRODUCTION: Existing convolutional neural networks and Transformers cannot effectively capture fine-grained local lesion features and long-range contextual dependencies simultaneously in field-collected plant images. T...
INTRODUCTION: Existing convolutional neural networks and Transformers cannot effectively capture fine-grained local lesion features and long-range contextual dependencies simultaneously in field-collected plant images. To address this research limitation, we aim to design an effective lightweight model suitable for plant disease identification in complex field scenarios. METHODS: This work proposes an improved Vision Mamba network for plant disease classification based on the challenging PlantDoc dataset. Three dedicated modules are embedded into the framework, including the Multi-Scale Feature Fusion Module (MFFM), Adaptive Channel Attention Mechanism (ACAM) and Lightweight Residual Connection (LRC). The MFFM fuses multi-scale texture, shape and semantic lesion features extracted from shallow, medium and deep network layers. The ACAM adaptively highlights disease-related feature channels and suppresses irrelevant background interference. The LRC structure is adopted to relieve the gradient vanishing problem existing in deep selective state space model (SSM) networks. RESULTS: Experimental results on the filtered PlantDoc dataset show that the presented model obtains an overall accuracy of 92.67%, macro precision of 91.83%, macro recall of 91.56% and macro F1-score of 91.70% on independent test samples, which outperforms the original Vision Mamba baseline by 5.33% in accuracy. Five-fold stratified cross-validation achieves stable accuracy at 92.41 ± 0.24%, and paired t-tests prove that the performance improvement is statistically significant with p<0.05. Ablation experiments confirm the combined contribution of the three designed modules. DISCUSSION: Error analysis and confusion matrix visualization reveal that the main classification errors are derived from high similarity among different plant disease categories. This study fully verifies the application potential of state space models in agricultural computer vision tasks. The proposed method can serve as an efficient technical scheme for intelligent identification of crop diseases and is well applicable to edge device deployment in precision agriculture practice.
Plant caspase-like proteins: from function identification to application in winter rapeseed genetic breeding.
Fan T, Fahim AM, Ma L … +6 more , Liu L, Pu Y, Wang W, Sun W, Yang G, Wu J
Front Plant Sci · 2026 · PMID 42318110 · Full text
Plant programmed cell death (PCD) shares striking similarities with animal apoptosis in both morphological and biochemical characteristics, yet plant genomes lack genuine orthologs of animal caspases. Instead, plants hav...
Plant programmed cell death (PCD) shares striking similarities with animal apoptosis in both morphological and biochemical characteristics, yet plant genomes lack genuine orthologs of animal caspases. Instead, plants have evolved a category of caspase-like proteins that are functionally analogous but lack sequence homology with animal caspases. This review systematically summarizes recent advances in the research of major plant caspase-like proteins, including metacaspases, vacuolar processing enzymes (VPEs), saspases, phytaspases, the proteasomal β subunit PBA1, and cathepsin B. These proteins play pivotal regulatory roles in PCD triggered during plant development, senescence, biotic and abiotic stresses, and exhibit distinctive substrate specificities, activation mechanisms, and regulatory networks. Furthermore, focusing on winter rapeseed, this review discusses the application potential of caspase-like proteins in genetic breeding, such as enhancing stress resistance by modulating their activities, optimizing yield-related traits, and improving biotechnological breeding platforms including microspore embryogenesis. Despite challenges including functional redundancy, spatiotemporal regulation, and species-specific divergence, caspase-like proteins serve as core nodes in the PCD regulatory network and provide valuable targets for crop improvement. This review offers a systematic reference for further understanding the molecular mechanisms of plant PCD and its application in crop breeding.
Leaf gas films enhance metabolic responses to submergence in .
Xia F, Geng L, Chen L … +8 more , Huang F, Zhang W, Liao X, Hong J, Wang K, Lin F, Ayi Q, Zeng B
Front Plant Sci · 2026 · PMID 42312083 · Full text
Riparian plants frequently experience flooding, which imposes oxygen limitation and disrupts carbohydrate metabolism, threatening survival and post-flood recovery. Certain species, including , form leaf gas films-thin la...
Riparian plants frequently experience flooding, which imposes oxygen limitation and disrupts carbohydrate metabolism, threatening survival and post-flood recovery. Certain species, including , form leaf gas films-thin layers of air retained on hydrophobic surfaces-that may alleviate stress hypoxia. However, their effects on central carbon metabolism remain poorly understood. Here, we investigated the role of leaf gas films in the submergence tolerance of by integrating physiological measurements, non-structural carbohydrate analysis, and targeted metabolomics. Plants were subjected to complete submergence with or without gas film retention, and growth, stomatal behavior, oxygen availability, carbohydrate consumption, and metabolite profiles were monitored. Gas films formed rapidly upon submergence, enhancing stomatal opening and maintaining higher oxygen partial pressures near the leaf surface. Submerged plants with intact gas films retained more green leaves, exhibited faster stem elongation, and preserved on non-structural carbohydrates in their leaves compared with plants lacking gas films. Metabolomic analyses revealed that gas films sustained flux through the tricarboxylic acid cycle and the pentose phosphate pathway. This supported uracil biosynthesis and aerobic energy metabolism. In contrast, plants without gas films shifted towards fermentative and secondary metabolic pathways. Gas films persisted for approximately seven days, providing a transient but critical window for aerobic metabolism under flooding conditions. These findings demonstrate that leaf gas films function as an early-phase adaptive mechanism, that promotes carbohydrate homeostasis and energy balance during submergence. By sustaining aerobic respiration and growth, gas films likely contribute to individual survival, competitive advantage, and the ecological resilience of riparian communities under fluctuating water levels.
Large language model assisted decision support framework for uncertainty aware detection and management of tomato lateral shoots.
Jiang Y, Geng Y, Zheng Z … +1 more , Pang X
Front Plant Sci · 2026 · PMID 42312082 · Full text
Accurate identification of tomato lateral shoots is essential for automated pruning and plant monitoring in greenhouse production. However, complex illumination, leaf occlusion, and morphological variability often reduce...
Accurate identification of tomato lateral shoots is essential for automated pruning and plant monitoring in greenhouse production. However, complex illumination, leaf occlusion, and morphological variability often reduce detection reliability in optical vision systems. This study proposes an optical vision-based framework that integrates deep learning perception with large language model assisted pruning decision support. A tomato lateral Shoot image dataset was constructed using RGB imaging in greenhouse environments. A lightweight YOLOv8n instance segmentation model with the Convolutional Block Attention Module (CBAM) was developed to enhance feature representation. Data augmentation strategies were applied to simulate illumination variations and improve model robustness. Model interpretability was analyzed using Principal Component Analysis (PCA) and Gradient weighted Class Activation Mapping (Grad CAM). Experimental results show that the proposed YOLOv8n-seg+CBAM model achieves a mAP of 98.1% with only 3.28M parameters and an average inference time of 8.0 ms per image. Monte Carlo Dropout was further introduced to estimate the spatial uncertainty of cutting points. These structured perception features were provided to a large language model (LLM), enabling context aware pruning decision assistance. The proposed framework integrates vision-based shoot detection, uncertainty estimation, and LLM-assisted reasoning into a unified pipeline, enabling more reliable pruning decisions and improving safety and robustness compared with vision-only approaches in greenhouse environments.
Expression of the quinoa gene family and analysis of involvement in seed germination stress response.
Zhou S, Shi P
Front Plant Sci · 2026 · PMID 42312081 · Full text
The TCP transcription factor family is a key regulator of plant growth, development and stress adaptation. The TCP gene family in the stress-tolerant cereal has not been systematically characterized. In this study, 20 n...
The TCP transcription factor family is a key regulator of plant growth, development and stress adaptation. The TCP gene family in the stress-tolerant cereal has not been systematically characterized. In this study, 20 non-redundant members were identified genome-wide in quinoa and classified into three subfamilies (PCF, CIN and CYC/TB1) based on phylogenetic relationships. possess few introns, and their promoter regions are enriched in various cis-acting elements related to abiotic stress, hormone and light responses. They exhibit tissue-specific expression, and the expression of multiple members is significantly regulated by salt and drought stresses. Functional verification showed that is localized in the nucleus. Heterologous overexpression of this gene in significantly improved seed germination rate under salt and drought stresses, and enhanced the antioxidant capacity and osmotic adjustment ability of seedlings. This study systematically characterized the features of the quinoa TCP family and its functions in stress responses, clarified the key role of in stress resistance during seed germination, and provided candidate genes and theoretical support for the genetic improvement of stress resistance in quinoa.
Assembly and comparative analysis of the first complete mitochondrial genome of (Cactaceae).
Liu X, Zhang Y, Wang Y … +5 more , Gao S, Li N, Cui Z, Zhang L, Zhang T
Front Plant Sci · 2026 · PMID 42312080 · Full text
INTRODUCTION: The Cactaceae family exhibits remarkable adaptation to arid environments, yet mitochondrial genomic resources remain extremely scarce for this lineage. (peyote) is an ecologically and culturally significan...
INTRODUCTION: The Cactaceae family exhibits remarkable adaptation to arid environments, yet mitochondrial genomic resources remain extremely scarce for this lineage. (peyote) is an ecologically and culturally significant cactus species native to the Chihuahuan Desert, but its mitochondrial genome has never been characterized. METHODS: We assembled and annotated the first complete mitochondrial genome of using PacBio HiFi long-read sequencing, and conducted comprehensive analyses including repeat identification, codon usage, RNA editing prediction, intracellular gene transfer detection, phylogenetic reconstruction, selection pressure assessment, and synteny comparison. RESULTS: The assembled mitogenome is exceptionally large (2,422,778 bp) and structurally complex, comprising 57 contigs that resolve into five linear molecules. It encodes 33 core and 13 variable protein-coding genes, three rRNA genes, and 49 tRNA genes. A total of 587 simple sequence repeats (SSRs), 124 tandem repeats, and 5,519 interspersed repeats (≥30 bp) were identified. Codon usage bias is predominantly driven by natural selection. We predicted 431 C-to-U RNA editing sites across 32 PCGs and detected 18 chloroplast-derived DNA fragments (31,614 bp) containing 19 intact genes. Phylogenetic analysis based on 30 conserved mitochondrial PCGs placed as sister to . Most mitochondrial genes are under purifying selection, whereas and exhibit positive selection. Synteny analysis revealed extensive collinear blocks decreasing with phylogenetic distance. DISCUSSION: This first complete mitogenome of provides a fundamental genomic resource for understanding mitochondrial evolution in Cactaceae, offers high-resolution molecular markers for species identification and forensic authentication, and supports conservation genetics for this threatened species.
Decoding plant volatile stress signals across scales: from molecular responses to ecosystem dynamics.
Ogwu MC, Ulimboka R, Aliu OO
Front Plant Sci · 2026 · PMID 42312079 · Full text
Plant volatile organic compounds (VOCs) represent one of the most dynamic and integrative biochemical signaling systems linking molecular plant stress responses to ecosystem-level processes. This review provides an integ...
Plant volatile organic compounds (VOCs) represent one of the most dynamic and integrative biochemical signaling systems linking molecular plant stress responses to ecosystem-level processes. This review provides an integrative cross-scale framework for understanding the biochemical pathways, regulatory networks, ecological functions, and technological applications of stress-induced volatile emissions. At the molecular and cellular levels, VOC emissions are regulated through complex enzymatic and hormonal pathways involving jasmonates, salicylates, ethylene, and abscisic acid, enabling plants to respond rapidly to abiotic and biotic stressors such as drought, herbivory, temperature extremes, salinity, and atmospheric pollution. These volatile signals extend beyond individual plants, functioning as mediators of plant-plant communication, plant-microbe interactions, and multi-trophic ecological networks that shape community dynamics and ecosystem resilience. Recent technological advancements, including mass spectrometry platforms, remote sensing systems, biosensors, and artificial intelligence-driven analytical frameworks, have transformed the ability to detect, interpret, and predict stress-induced VOC emissions in real time. Integrating these technologies with multi-omics datasets and digital twin modeling enables the development of predictive monitoring systems capable of scaling plant stress detection from agricultural fields to regional ecosystems. Despite these advances, significant challenges remain, including variability in emission profiles across species and environments, atmospheric transformation of volatile signals, methodological inconsistencies, and limitations in large-scale monitoring infrastructure. Future research should focus on establishing global networks for monitoring plant volatiles, standardized measurement protocols, and integrated biosensing infrastructures that can link plant stress signals to Earth-system observations. Decoding plant volatile stress signaling across scales offers a transformative pathway to advance climate-resilient agriculture, biodiversity conservation, and predictive environmental intelligence systems that support adaptive ecosystem management in an era of accelerating environmental change.
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