Search Results (293)

Leaf senescence is the final, programmed stage of leaf development, marked by nutrient remobilization and tightly regulated molecular events. Although alternative splicing has emerged as a major regulator of plant development, its role in isoform switching during leaf aging remains poorly understood. To address this, we conducted a genome-wide analysis of isoform switching in Arabidopsis, leveraging publicly available RNA-seq data from mature (16-day-old) and senescent (30-day-old) leaves, analyzed with the IsoformSwitchAnalyzeR package. Between these two developmental stages, we identified 269 genes exhibiting 377 significant isoform switches collectively predicted to alter protein localization, coding potential, and transcript stability. Experimental validation confirmed predicted switching at the PUS3 (Pseudouridine Synthase 3) locus, with sequence analysis revealing an age-dependent shift from mitochondrial-targeted to cytoplasmic isoforms. Gene Ontology enrichment analysis of switching genes revealed 82 significant terms, prominently associated with metabolism, gene expression, developmental regulation, and stress responses. Interestingly, we found nearly one-third of switching genes to overlap with known targets of the splicing factor SR45, with enrichment in pathways related to nucleotide and amino acid metabolism, energy production, and developmental processes. Correspondingly, dark-induced senescence assays revealed accelerated senescence in the sr45 mutant, confirming SR45′s role in regulating leaf aging. Specific complementation of SR45′s two isoforms revealed contrasting functions, with SR45.1 restoring normal senescence timing while SR45.2 failed to complement. Taken together, our findings demonstrate that differential isoform usage, orchestrated by specific splicing regulators, plays a critical role in leaf aging. This insight opens new avenues for manipulating senescence and engineering stay-green traits in crops. Full article

Rice (Oryza sativa L.) is one of the major food crops. Yield and quality are affected by premature leaf senescence, a complex and tightly regulated developmental process. To elucidate the molecular regulatory mechanism controlling rice leaf senescence, the integrative transcriptome, metabolome and weighted gene co-expression network analysis (WGCNA) of flag leaves in five development stages (FL1–FL5) was performed. In this study, a total of 9412 differential expressed genes (DEGs) were identified. To further mine DEGs related to leaf senescence, a total of five stage-specific modules were characterized by WGCNA. Among them, two modules displayed continuous down-regulated and up-regulated trends from stages FL1 to FL5, which were considered to be highly negatively and positively correlated with the senescence trait, respectively. GO enrichment results showed that the genes clustered in stage-specific modules were significantly enriched in a vast number of senescence-associated biological processes. Furthermore, large numbers of senescence-related genes were identified, mainly participating in transcription regulation, hormone pathways, degradation of chlorophyll, ROS metabolism, senescence-associated genes (SAGs), and others. Most importantly, a total of 40 hub genes associated with leaf senescence were identified. In addition, the metabolome analysis showed that a total of 309 differential metabolites (DMs) were identified by WGCNA. The integrative transcriptome and metabolome analysis identified a key hub gene OsBELH4A based on the correlation analysis conducted between 40 hub genes and 309 DMs. The results of function validation showed that OsBELH4A overexpression lines displayed delayed leaf senescence, and significantly increased grain number per plant and grain number per panicle. By contrast, its knockout lines displayed premature leaf senescence and reduced grain yield. Exogenous hormone treatment showed that OsBELH4A significantly responded to SA and auxin. These findings provide novel insights into leaf senescence, and further contribute to providing genetic resources for the breeding of crops resistant to premature senescence. Full article

Maize, one of the most cultivated crops worldwide, has multiple uses, one of which is human food. Maize flour intended for human consumption is preferably produced from var. indurata. This maize variety, although it has some desirable traits, generally has a lower yield capacity. In order to obtain high-yielding hybrids that would have some traits necessary to obtain flour for human consumption, fourteen lines with dent or semi-dent grains were crossed with four inbred lines with flint grain in a cyclic system. The 56 resulting hybrids were tested in two experimental years for yield, the percentage of unlodged plants, grain dry matter at harvest, as well as other traits, such as ASI (anthesis-to-silking interval), the interval from sowing to the appearance of stigmas and to physiological maturity, and plant senescence. The maternal lines A478 and A480 were noted for transmitting higher yields. Three hybrids were identified with higher yields, good silking–flowering coincidence, stay-green, and a high unlodged plants percentage: A478 × D328, A480 × B330, and A480 × D328. Full article

Dissolved oxygen (DO) concentration in nutrient solution is critical for maximizing yield and optimizing quality traits of lettuce plants grown in floating systems. This study evaluated the effects of two aeration systems—a Venturi system (V) and a Venturi system combined with a nanobubble generator using electromagnetic waves (VN)—compared with a non-aerated control (C), on quali-quantitative traits of lettuce plants grown in a floating system over two consecutive harvests. Both aeration treatments significantly increased DO levels in the nutrient solution compared to C, with the VN treatment maintaining the highest value throughout the crop cycle. Although no significant differences in lettuce yield were observed, both aeration treatments enhanced the leaf concentration of P, Mn, Zn, and Cu in the second harvest, and Mg in both harvests. Moreover, the VN treatment lowered leaf nitrate concentration in both harvests compared to the other treatments. The increase in DO in the nutrient solution delayed leaf senescence, as evidenced by higher chlorophyll index and lower anthocyanin levels in the lettuce leaves harvested at the end of the trial for both aeration systems. These results suggest that aeration, particularly with nanobubbles, can be an effective and sustainable strategy to enhance the quality traits of lettuce grown in a floating system. Full article

The present study is part of the efforts to develop a micropropagation protocol for Arracacia xanthorrhiza, focusing on improving in vitro establishment, reducing senescence, and balancing plant growth regulators. To control bacterial contamination during culture initiation, ampicillin and tetracycline were tested using impregnated paper disks. Ampicillin at 100 mg·L⁻¹ achieved 92.4% survival and reduced bacterial contamination to 25.2%, compared to 65.6% in the untreated control, confirming its effectiveness as a low-cost and non-toxic solution. Senescence reduction was evaluated through the addition of activated charcoal and silver nitrate (AgNO₃); the latter, at 26 µM, significantly enhanced explant survival, reduced leaf senescence, and promoted shoot and sprout formation. Three plant growth regulators—6-benzylaminopurine (BAP), kinetin (KIN), and meta-topolin (mT)—were tested at multiple concentrations. Meta-topolin at 1 µM produced 3.5 sprouts and 7.2 leaves per plant, demonstrating three times greater biological activity than BAP and optimal morphogenetic response. The integration of antimicrobial control, ethylene inhibition, and cytokinin optimization resulted in a reliable and scalable protocol for A. xanthorrhiza micropropagation. As a concluding remark, these findings provide a practical and efficient framework for clean plant production, with direct applications in conservation, breeding, and commercial propagation of this underutilized Andean crop, while highlighting the need for further validation across genotypes. Full article

Combined application of controlled-release urea (CRU) and urea (U) improves yield and nitrogen use efficiency (NUE) in various crops, but the optimal blending ratio and related mechanisms in peanut production, particularly regarding antioxidant enzyme responses, remain insufficiently studied. To address this, a two-year field experiment was conducted with six fertilization treatments at a nitrogen rate of 120 kg·ha⁻¹: CK (no nitrogen), T1 (100% U), T2 (100% CRU), T3 (50% CRU + 50% U), T4 (70% CRU + 30% U), and T5 (30% CRU + 70% U). The results showed that compared with T1, the blended treatments significantly increased yield by 5.41–10.88% and improved NUE by 35.90–64.37%, with T4 performing the best. The T4 treatment significantly enhanced photosynthetic characteristics, promoted dry matter accumulation, coordinated nitrogen supply across growth stages, strengthened nitrogen metabolism enzyme activity, and delayed leaf senescence. At harvesting stage, the activities of SOD, POD, and CAT in T4 were 12.82%, 22.37%, and 23.32% higher, respectively, than those in T1, while MDA content decreased by 11.29%. This study demonstrates that in the ridge-furrow plastic film mulching cultivation system of Shandong’s brown soil, coapplying 70% CRU with 30% U is an effective nitrogen management strategy for peanuts. This approach achieves high and stable yields by improving nitrogen metabolism and antioxidant capacity. The findings provide a theoretical basis and technical reference for sustainable intensification of peanut production in similar ecological regions and cultivation systems. Full article

This paper presents a dataset for a comparative analysis of direct (spectrophotometric) and indirect (multispectral imagery-based) methods for quantifying crop leaf chlorophyll content. The dataset originates from a study conducted in the Department of Cauca, Colombia, a region characterized by diverse agricultural production. Data collection focused on seven economically important crops, namely coffee (Coffea arabica), Hass avocado (Persea americana), potato (Solanum tuberosum), tomato (Solanum lycopersicum), sugar cane (Saccharum officinarum), corn (Zea mays) and banana (Musa paradisiaca). Sampling was conducted across various locations and phenological stages (healthy, wilted, senescent), with each leaf subdivided into six sections (A–F) to facilitate the analysis of intra-leaf chlorophyll distribution. Direct measurements of leaf chlorophyll content were obtained by laboratory spectrophotometry following the method of Jeffrey and Humphrey, allowing for the determination of chlorophyll A and B content. Simultaneously, indirect estimates of leaf chlorophyll content were obtained from multispectral images captured at the leaf level using a MicaSense Red-Edge camera under controlled illumination. A set of 32 vegetation indices was then calculated from these multispectral images using MATLAB. Both direct and indirect methods were applied to the same leaf samples to allow for direct comparison. The dataset, provided as an Excel (.xlsx) file, comprises raw data covering laboratory-measured chlorophyll A and B content and calculated values for the 32 vegetation indices. Each row of the tabular dataset represents an individual leaf sample, identified by plant species, leaf identifier, and phenological stage. The resulting dataset, containing 16,660 records, is structured to support research evaluating the direct relationship between spectrophotometric measurements and multispectral image-based vegetation indices for estimating leaf chlorophyll content. Spearman’s correlation coefficient reveals significant positive relationships between leaf chlorophyll content and several vegetation indices, highlighting its potential for a nondestructive assessment of this pigment. Therefore, this dataset offers significant potential for researchers in remote sensing, precision agriculture, and plant physiology to assess the accuracy and reliability of various vegetation indices in diverse crops and conditions, develop and refine chlorophyll estimation models, and execute meta-analyses or comparative studies on leaf chlorophyll quantification methodologies. Full article

Leaf senescence is the final stage of plant leaf development, closely related to the yield and quality of cereal crops. However, the molecular regulatory mechanism of rice (Oryza sativa L.) leaf senescence is not yet very clear. This study conducted weighted gene co-expression network analysis (WGCNA) using two independent senescence-related transcriptome datasets of rice. Modules positively/negatively correlated with leaf senescence were obtained for each dataset. The additional intersection analysis screened out 180 and 248 common genes highly and positively/negatively correlated with leaf senescence. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses showed that these identified common genes were mainly enriched in senescence-related biological processes and pathways, such as reactive oxygen metabolism, hormone pathway, cell death regulation, stimulus–response, amino acid metabolism, photosynthetic metabolism, etc. Transcription factors and studied genes were identified from these common genes, finding that transcription regulation, hormone regulation, reactive oxygen species metabolism, and photosynthesis pathways play an essential role in rice leaf senescence. Protein–protein interaction (PPI) network analysis identified 28 key genes probably involved in leaf senescence. Hub network analysis identified 68 hub genes probably participating in leaf senescence. Twelve genes from the PPI network and the hub gene network were selected for RT-qPCR validation of their expression patterns during leaf senescence. The functions of the senescence-correlated genes identified in this study are discussed in detail. These results provide valuable insights into the regulatory mechanisms of leaf senescence in rice and lay a foundation for functional research on candidate senescence genes. Full article

Oat is a dual-purpose crop valued for both grain and forage. The stay-green (SG) trait, which delays leaf senescence and prolongs photosynthesis, has been shown to increase yield and quality in several crop species, yet its performance across diverse environments in oats remains underexplored. In this study, multi-location field trials were conducted in Ledu, Huangzhong and Haiyan, Qinghai Province, China, to comprehensively evaluate the performance of stay-green oat lines. The traits evaluated included grain yield components, nutritional quality, and seedling establishment traits. A TOPSIS (technique for order preference by similarity to an ideal solution) model, coefficient of variation (CV) and G × E (genotype × environment) visualization were used to assess adaptability, stability, and genotype × environment interactions. On average, the stay-green lines exhibited an 16.00% increase in plot yield and a 22.93% increase in thousand-grain weight compared to controls. Notable improvements were also observed in the starch (7.58% LN_SG in HZ and HY) and protein (3.58%, QY5_SG all the sites) contents, as well as multiple seedling establishment indices, with the seedling vigor indices increasing by more than 50%. Stability analysis further showed that the stay-green lines were stable in spike length, thousand-grain weight, water-soluble carbohydrates, and seed and seedling vigor. TOPSIS analysis identified ‘LN_SG’ as the top-performing and most adaptable genotype across all environments. Overall, stay-green oat lines demonstrated superior performance in grain yield, nutritional quality, and seedling establishment. These findings highlight their potential for field application and their value as parental materials in oat breeding programs enhancing environmental adaptability and stability. Full article

Trichomes are specialized epidermal structures that protect plants from environmental stresses, regulated by transcription factors integrating hormonal and environmental cues. This study investigates the roles of two C2H2 zinc finger proteins, GIS2 and ZFP8, in regulating trichome patterning in Arabidopsis thaliana. Using dexamethasone-inducible overexpression lines, transcriptomic profiling, and chromatin immunoprecipitation, we identified 142 GIS2- and 138 ZFP8-associated candidate genes involved in sterol metabolism, senescence, and stress responses. GIS2 positively and directly regulated the expression of SQE5, linked to sterol biosynthesis and drought tolerance, and repressed SEN1, a senescence marker associated with abscisic acid and phosphate signaling. ZFP8 modulated stress-related target genes, including PR-4 and SPL15, with partial functional overlap between GIS family members. Spatially, GIS2 functions in inflorescence trichomes via integrating gibberellin-cytokinin pathways, while ZFP8 influences leaf trichomes through cytokinin and abscisic acid signal. Gibberellin treatment stabilized GIS2 protein and induced SQE5 expression, whereas SEN1 repression was gibberellin-independent. Chromatin immunoprecipitation and DEX-CHX experiment confirmed GIS2 binding to SQE5 and SEN1 promoters at conserved C2H2 motifs. These findings highlight hormone-mediated transcriptional regulation of trichome development by GIS2 and ZFP8, offering mechanistic insight into signal integration. The results provide a foundation for future crop improvement strategies targeting trichome-associated stress resilience. Full article

GOLDEN2-LIKEs (GLKs) are important transcription factors for the chloroplast development influencing photosynthesis, nutrition, senescence, and stress response in plants. Sunflower (Helianthus annuus) is a highly photosynthetic plant; here, a GLK-homologues gene HaGLK was identified from the sunflower genome by bioinformatics. To analyze the bio-function of HaGLK, transgenic rice plants overexpressing HaGLK (HaGLK-OE) were constructed and characterized via phenotype. Compared to the wild-type control rice variety Zhonghua 11 (ZH11), the HaGLK-OE lines exhibited increased photosynthetic pigment contents, higher net photosynthetic rates, and enlarged chloroplast area; meanwhile, genes involved in both photosynthesis and chlorophyll biosynthesis were also significantly up-regulated. Significantly, the HaGLK-OE plants showed a 12–13% increase in yield per plant. Additionally, the HaGLK-OE plants were demonstrated to have improved salt and drought tolerance compared to the control ZH11. Our results indicated that the HaGLK gene could play multiple roles in photosynthesis and stress response in rice, underscoring its potential value for improving crop productivity and environmental adaptability in breeding. Full article

The response of plants to elevated atmospheric [CO₂] is highly dynamic and influenced by developmental stage, yet its role in photosynthetic acclimation remains underexplored. This study examines the physiological and molecular responses of wheat (Triticum durum, var. Amilcar) to elevated [CO₂] (700 ppm vs. 400 ppm) at two distinct developmental stages: the vegetative stage at the end of the elongation stage and the reproductive stage at the beginning of ear emergence (Z39 and Z51, respectively). Wheat plants at the developmental stage Z39, cultivated under elevated [CO₂], maintained photosynthetic rates despite a carbohydrate build-up. However, at Z51, photosynthetic acclimation became more evident as the decline in Rubisco carboxylation capacity (Vc_max) persisted, but also stomatal conductance and diffusion were decreased. This was accompanied by the up-regulation of the CA1 and CA2 genes, likely as a compensatory mechanism to maintain CO₂ supply. Additionally, hormonal adjustments under elevated [CO₂], including increased auxin and bioactive cytokinins (zeatin and isopentenyl adenine), may have contributed to delayed senescence and nitrogen remobilization, sustaining carbon assimilation despite biochemical constraints. These findings highlight the developmental regulation of photosynthetic acclimation, emphasizing the need for the stage-specific assessments of crop responses to future atmospheric conditions. Full article

Integrated application of chemical fertilizers with organic manure might improve crop yields and N-use efficiency (NUE, grain yield per unit N uptake), but the underlying physiological mechanisms are unclear. In this study, we aimed to examine the effects of combined inorganic and organic fertilizers on wheat biomass allocation, root growth, water-soluble carbohydrates (WSCs) translocation, leaf senescence, N uptake, and their relationship with yield and NUE. We established a 2-year factorial field experiment with five nutrient treatments with ratios of inorganic: organic fertilizers from 0 to 1, and three varieties—two new: Weilong169 and Zhongmai578; and one reference: Xiaoyan22. The yield ranged from 3469 to 8095 kg ha⁻¹, and it generally declined in response to a higher proportion of organic fertilizer. The NUE increased when there was a higher proportion of organic fertilizer. Weilong169 exhibited higher NUE than Zhongmai578, and both new cultivars outperformed the reference variety in the N harvest index. The yield correlated with leaf senescence traits and harvest index, and NUE was associated with WSC translocation and N uptake. The combination of fertilizers with a low portion of organic maintained yield and improved NUE; Weilong169 had the highest yield, NUE, and N harvest index. A low portion of organic manure substitution for chemical fertilizer suited all varieties. A new variety with a higher yield, N harvest index, and NUE highlights the importance of N traits in breeding programs. Full article

Global challenges such as climate change and population growth require improvements in crop monitoring models. To address these issues, this study advances the identification of potato crop phenological stages using satellite remote sensing, a field where cereals have been the primary focus. We introduce a methodology using Sentinel-1 (S1) and Sentinel-2 (S2) time series data to pinpoint critical phenological stages—emergence, canopy closure, flowering, senescence onset, and harvest timing—at the field scale. Our approach utilizes analysis of NDVI, fAPAR, and IRECI2 from S2, alongside VH and VV polarizations from S1, informed by domain knowledge of the spectral and morphological responses of potato crops. We propose the integration of NDVI and VH indices, NDVI_VH, to improve stage detection accuracy. Comparative analysis with ground-observed stages validated the method’s effectiveness, with NDVI proving to be one of the most informative indices, achieving RMSEs of 12 and 14 days for emergence and closure, and 17 days for the onset of senescence. The integrated NDVI_VH approach complemented NDVI, particularly in harvest and flowering stages, where VH enhanced accuracy, achieving an overall R² value of 0.80. The study demonstrates the potential of combining SAR and optical data for post-season crop phenology analysis, providing insights that can inform the development of new methods and strategies to enhance on-season crop monitoring and yield forecasting. Full article

Northwestern Ontario has a shorter growing season but fertile soil, affordable land, opportunities for agricultural diversification, and a demand for canola production. Canola yield mainly varies with spatial heterogeneity of soil properties, crop parameters, and meteorological conditions; thus, existing yield estimation models must be revised before being adopted in Northwestern Ontario to ensure accuracy. Region-specific canola cultivation guidelines are essential. This study utilized high spatial-resolution images to estimate flower coverage and yield in experimental plots at the Lakehead University Agricultural Research Station, Thunder Bay, Canada. Spectral profiles were created for canola flowers and pods. During the peak flowering period, the reflectance of green and red bands was almost identical, allowing for the successful classification of yellow flower coverage using a recursive partitioning and regression tree algorithm. A notable decrease in reflectance in the RedEdge and NIR bands was observed during the transition from pod maturation to senescence, reflecting physiological changes. Canola yield was estimated using selected vegetation indices derived from images, the percent cover of flowers, and the M5P Model Tree algorithm. Field samples were used to calibrate and validate prediction models. The model’s prediction accuracy was high, with a correlation coefficient (r) of 0.78 and a mean squared error of 7.2 kg/ha compared to field samples. In conclusion, this study provided an important insight into canola growth using remote sensing. In the future, when modelling, it is recommended to consider other variables (soil nutrients and climate) that might affect crop development. Full article