Frontiers in Plant Science最新文献

Citrus species are among the most important fruit tree crops grown worldwide. Their long juvenile period joined with their complex genetic and reproductive characteristics severely hampers genomic studies and the improvement of traits of interest. Among these, seedlessness represents a major fruit quality trait. Genetic engineering is the fastest way to unequivocally characterize the function of citrus genes and to develop better varieties. In this study, two genes from Citrus clementina Hort. ex Tan., CcGLT1 and CcRBP1, that putatively encode a glycosyltransferase-like (GLT) protein and an RNA binding (RBP) family protein, respectively, were characterized as highly expressed in male and female reproductive tissues and then evaluated as candidate genes involved in male and/or female gametic development by silencing them using RNA interference (RNAi) in Carrizo citrange, used as model citrus type easy to transform. Concurrently, the early flowering and fruiting phenotype was induced by ectopic overexpression of the citrus ortholog of the floral integrator FLOWERING LOCUS T gene (FT) which enabled flower and fruit production less than six months after transformation. Histological observations of flower tissues from genetically modified plants showed that silencing CcGLT1 affects pollen performance by reducing pollen germinability and viability which results in an increased rate of ovule abortion resulting in fewer seeds in self-pollinated fruits. Conversely, the silencing of CcRBP1 led to severe alterations in plant growth and development in the transgenic RBP lines preventing the characterization of its role in fertility, which therefore remains unresolved. These results provide useful insights into male and female sterility in citrus for the genetic improvement of commercial varieties aimed to obtain seedless fruits.

Controlled drainage (CD) can improve crop yield by optimizing the soil water and nutrient environment. Nevertheless, the combined effects of reduced nitrogen fertilization and CD on crop leaf senescence characteristics is unclear. Thus, a two-year field experiment was conducted to address the effects of nitrogen fertilizer rates (280, 252, 224, and 196 kg N ha^-1, denoted as N1, N2, N3, and N4, respectively) on the leaf area index (LAI), SPAD value, net photosynthetic rate (P _n), activities of superoxide dismutase (SOD), peroxidases (POD), catalase (CAT), and the contents of soluble protein (SP) and malondialdehyde (MDA) in plant leaves, and the seed yield of cotton under CD and free drainage (FD). CD resulted in greater LAI, SPAD value, P _n, SOD, POD, and CAT activities, and SP content, and smaller MDA content at the three reduced nitrogen rates, and thus obtained a relatively high seed cotton yield. The delayed leaf senescence characteristics were due to greater soil moisture and NO₃ ^--N content in the plough (0-40 cm) layer under CD. Notably, all reduced nitrogen rates significantly decreased the cottonseed yield under FD, but N2 and N3 had comparable cottonseed yields under CD. Therefore, we concluded that controlled drainage could stabilize seed cotton yield by improving photosynthesis, the antioxidant defenses and osmoregulation at 80%-90% of normal nitrogen fertilizer rate. The results also reveal the physiological mechanisms through which the drainage regime mediates crop yield under varying nitrogen rates.

The continuous increase in the cost of water and fertilizers associated with increasing global demand for food driven by population growth and the growing concern on the current environmental impact of agriculture led us to the urgent search for more sustainable agronomic practices. Among these, the use of biostimulants has emerged as a promising strategy to enhance crop productivity and resource-use efficiency while reducing reliance on conventional inputs. Nevertheless, identifying the most suitable type of biostimulant, along with the optimal method, dosage, and timing of application, remains particularly critical for staple crops such as rice, being an area that requires further in-depth research. In the present experiment, two silicon-based biostimulant formulations were tested under controlled conditions at two different concentrations and applied at different key phenological stages in rice through foliar spraying. Agronomical components (plant height, tiller number, aerial dry weight, grain yield, and harvest index), whole plant physiological parameters (vegetation indices such as NGRDI, TGI, GA and GGA readings), leaf traits (photosynthetic and transpirative gas exchange, total nitrogen and carbon concentration and the stable isotopic composition, pigment content), and the grains characteristics (mineral composition (macronutrients and heavy metal concentrations) were evaluated. Among the tested products, the Simosa formulation was the most effective, significantly enhancing tiller number, aerial dry weight, grain yield, chlorophyll concentration and nitrogen balance index. Nevertheless, no consistent dose-dependent effects were observed. In contrast, Siliforce-4 did not demonstrate clear effects on either biomass accumulation or physiological traits. Regarding rice grain consumption, only copper concentrations exceeded the threshold established by EFSA, 2009. Overall, these results underscore the need for further studies to determine the most effective silicon foliar fertilizer formulations, as well as optimal dose and timing of application for boosting rice productivity.

Introduction: The BASIC PENTACYSTEINE (BPC) family comprises plant-specific transcription factors that regulate diverse developmental programs and stress responses. Pear (Pyrus bretschneideri), an economically significant fruit crop, often experiences marked declines in fruit yield and quality under drought stress. Although BPC genes have been identified in several plant species, a comprehensive characterization of this family in pear is lacking.

Methods: In this study, we systematically characterized PbBPC genes in the pear genome using various bioinformatic approaches. We examined their expression profiles across diverse tissues and under dehydration conditions and further validated the role of PbBPC5 in drought tolerance using virus-induced gene silencing (VIGS).

Results: This study identified seven PbBPC genes in the pear genome, which were subsequently classified into three distinct groups through phylogenetic analysis. Comprehensive bioinformatics analyses were performed, examining their phylogenetic relationships, gene structures, conserved motifs, protein domains, chromosomal locations, and gene duplication events. Promoter analyses showed that all PbBPC genes contained various cis-acting elements associated with growth and development, stress response, and phytohormone signaling. Quantitative real-time PCR (qRT-PCR) showed that most PbBPC transcripts were upregulated by dehydration, with PbBPC5 exhibiting the strongest upregulation. Furthermore, subcellular localization experiments indicated that PbBPC5 was localized to the nucleus. Silencing PbBPC5 reduced drought tolerance, as indicated by more severe wilting under water deficit, lower relative water content, higher electrolyte leakage, and elevated malondialdehyde levels. PbBPC5 silencing also weakened antioxidant defenses during drought by reducing antioxidant enzyme activities. These results suggest that PbBPC5 functions on drought tolerance regulation in pear mainly by influencing reactive oxygen species scavenging.

Discussion: This study provides a genome-wide characterization of the PbBPC family and reveals PbBPC5 as a key regulator of the drought response, offering a foundation for improving pear drought tolerance through genetic approaches.

Microspore embryogenesis (ME) relies on the cellular reprogramming of the default gametophytic developmental pathway, which normally directs microspores toward pollen formation, into an embryogenic pathway that leads to the development of embryo-like structures (ELS) and, subsequently, haploid or doubled haploid (DH) plants. To test how redox control underpins this switch, we have carried out an extended in silico analysis of previously published RNA-seq data from two barley cultivars differing in ME competence (Igri, responsive; Golden Promise, recalcitrant) across four early induction stages (0-III). A curated set of 472 antioxidant/redox genes-core detoxification enzymes, the ASC-GSH cycle, TRX/GRX/PRX systems and GSTs-was examined. The analysis revealed that the expression of antioxidative defense genes is dynamically modulated during ME induction, underscoring the importance of redox homeostasis in successful microspore reprogramming. Both cultivars shared a late (stages II-III) program with increased SODs, selected CAT/GPX genes, rising MDHARs, deployment of specific TRX/GRX/PRX members and broad GSTs upregulation. Divergence emerged during progression: Igri showed a pronounced stage-III rise of GRs and targeted TRX/GRX/PRX transcripts, together with stronger activation of multiple GSTs. When considered alongside diverse experimental data, these stage-restricted, cultivar-biased signatures support a hypothetical model in which strengthened ASC-GSH recycling and thiol-redox hubs sustain H₂O₂ signaling while limiting oxidative damage. Targeting MDHARs, GRs, selected TRX/GRX/PRX genes, and GST subsets could improve ME efficiency and accelerate the integration of DH technology into modern crop breeding programs.

In the context of precision agriculture, the problems of adhesion of rice plant features and background interference in UAV remote sensing images make traditional models difficult to meet the requirements of individual plant-level detection. To address this, this paper proposes an Information Vortex-based progressive fusion YOLO (IV-YOLO) model. Firstly, a Multi-scale Spiral Information Vortex (MSIV) module is designed, which achieves the disentanglement of adhered rice plant features and decoupling of background clutter through multi-scale rotational kernel convolution and channel-spatial joint reconstruction. Secondly, a Gradual Feature Fusion Neck (GFEN) is constructed to synergize the high-resolution details of shallow features (such as tiller edges and panicle textures) with the high semantic information of deep features, generating multi-scale feature representations with both discriminativeness and completeness. Experiments conducted on the public DRPD dataset show that IV-YOLO achieves a Precision of 0.8581, outperforming YOLOv5-YOLOv11 and FRPNet across all metrics. This study provides a reliable technical solution for individual plant-level rice monitoring and facilitates the large-scale implementation of precision agriculture.

Pineapple is widely favored by consumers for its rich proteins, vitamin C and other nutrients. Soluble solids content (SSC) has long been the core indicator for pineapple quality assessment, directly affecting its market acceptability and sales. To accurately detect pineapple SSC, this study used a hyperspectral imaging system to collect hyperspectral images in the 400-1700 nm range, with SSC measured by an Atago PAL-1 digital sugar meter as the reference. Five pretreatments (including multiple scattering correction (MSC), polynomial smoothing (SG) and mathematical transformations) were applied to raw spectral data, and three prediction models (partial least squares regression (PLSR), Lasso regression, ridge regression (RR)) were established. All models performed well: PLSR showed R²=0.9459 and RMSE = 0.5746, Lasso R²=0.8965 and RMSE = 1.0221, RR R²=0.8560 and RMSE = 1.2632. After screening characteristic bands via Successive Projections Algorithm (SPA) and re-modeling, the ddA-PLSR model was optimal (R²=0.9869, RMSE = 0.1250), with four key wavelengths (673-676nm, 711-715nm, 971-990nm, 1357-1367nm) extracted. This confirms hyperspectral imaging (HSI) enables efficient and accurate SSC detection in pineapples, with great application potential in pineapple quality identification.

Tomato (Solanum lycopersicum) has emerged as a promising platform for the sustainable production of high-value metabolites. In this study, we demonstrate that plant architecture remodeling via genome editing can be exploited as a chassis optimization strategy in plant biofactories. Building on the previously established Tomaffron line, which accumulates saffron apocarotenoids in the fruit, and based on the established knowledge that mutations in SELF-PRUNING (SP) and SP5G genes generate compact, determinate tomato plants, we used CRISPR/Cas9 to edit the SP and SP5G genes in Tomaffron to improve crocin production. The resulting sp sp5g double mutants exhibited a compact growth habit combined with significantly higher fruit yield, total crocin content, and firmer ripe fruits compared with non-mutants. Remarkably, crocin yields per square meter increased nearly fourfold compared to non-mutant Tomaffron plants grown at the same density, representing progress toward achieving the crocin yields of Crocus sativus and offering the advantage of easier cultivation and harvesting in the tomato system. Our results show that genome editing of plant architecture is not only a tool for agronomic improvement but also a powerful strategy to fine-tune our tomato biofactory performance, offering a scalable and sustainable approach for the production of valuable metabolites.