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Osmotic stress caused by low-temperature, drought and salinity was a prevalent abiotic stress in plant that severely inhibited plant development and agricultural yield, particularly in tea plant. Jasmonic acid (JA) is an important phytohormone involving in plant stress. However, underlying molecular mechanisms of JA modulated osmotic stress response remains unclear. In this study, high concentration of mannitol induced JA accumulation and increase of peroxidase activity in tea plant. Integrated transcriptome mined a JA signaling master, MYC2 transcription factor is shown as a hub regulator that induced by mannitol, expression of which positively correlated with JA biosynthetic genes (LOX and AOS) and peroxidase genes (PER). CsMYC2 was determined as a nuclei-localized transcription activator, furthermore, Protein-DNA interaction analysis indicated that CsMYC2 was positive regulator that activated the transcription of CsLOX7, CsAOS2, CsPER1 and CsPER3 via bound with their promoters, respectively. Suppression of CsMYC2 expression resulted in a reduced JA content and peroxidase activity and osmotic stress tolerance of tea plant. Overexpression of CsMYC2 in Arabidopsis improved JA content, peroxidase activity and plants tolerance against mannitol stress. Together, we proposed a positive feedback loop mediated by CsMYC2, CsLOX7 and CsAOS2 which constituted to increase the tolerance of osmotic stress through fine-tuning the accumulation of JA levels and increase of POD activity in tea plant.

Tea plants, which are among the world’s most economically important beverage crops, exhibit extensive genetic diversity and are rich in secondary metabolites. While structural variations (SVs) drive phenotypic diversification, their regulatory roles in transcriptional networks and agronomic traits remain underexplored in this perennial crop. Here, we construct a pangenome from 22 representative tea accessions and their wild relatives. Genomic SV analysis reveals that 22% of the gene promoters contain variants influencing flavonoid, amino acid, and terpenoid biosynthesis. Population SV analysis of 275 tea accessions reveals three haplotypes in the ANS3 promoter, with Hap1, containing a 192 bp insertion, predominantly found in wild relatives but largely lost in modern cultivars. This insertion increases CtANS3 expression and anthocyanin content in wild relatives. Additionally, a 159 bp insertion in the CtLRR1 promoter reduces resistance to Colletotrichum gloeosporioides in wild relatives. Our findings underscore SVs as pivotal regulators of flavor differentiation and adaptive evolution during tea plant domestication. The regulatory roles of structural variations (SVs) in transcriptional networks and agronomic traits of tea plants are largely unexplored. Here, the authors assemble the pangnome from 22 representative tea accessions and their wild relative and reveal SVs driving gene expression alteration and agronomic traits diversification.

Background: Optimized nitrogen (N) application and planting density can enhance sweet potato yield. However, the agronomic mechanisms underlying their effects on photosynthetic efficiency and carbohydrate metabolism in sweet potato remain unclear. Methods: To address this, a two-year field experiment was conducted using a split-plot design with two varieties (YS-25 and GX-14), three N levels (60, 90, and 120 kg/ha; designated N60, N90, and N120, respectively), and three planting densities (D1–D3: 50,000, 62,500, and 83,333 plants/ha). Each treatment was replicated three times. Results: The results showed that the N60D2 treatment (60 kg/ha N; 62,500 plants/ha) optimized canopy light distribution by significantly increasing IPAR, light transmission rate, and extinction coefficient (K). This treatment enhanced individual plant photosynthetic capacity (higher photosynthetic rate: Pn, Ci, Gs, and Tr) and light energy use efficiency (Fv/Fm, Y(II), ETR, and qP), and promoted carbohydrate metabolism (sucrose, starch, fructose, and glucose) by increasing enzyme activities (Rubisco, SuSy, SPS, NI, SSS, and AGPase) in functional leaves and roots. These effects improved source–sink coordination, ultimately increasing storage root yield by 63.27–95.47% compared with the control plants (N120D1). Correlation analysis revealed that single-plant root weight and medium-sized root count were important yield determinants for both varieties. Conclusions: These results indicate that reducing nitrogen fertilizer combined with dense planting shapes a reasonable canopy structure for light distribution at the population level and optimizes light and carbon use efficiency at the individual plant level, thereby improving storage root yield and commercial characteristics of sweet potato.

A three-cycle field experiment was conducted to investigate the underlying agronomic mechanism on modulating the root lodging resistance and yield stability of sweet corn in response to the planting density and nitrogen rate during different growth seasons. The experiment comprised two factors with six treatments and was conducted in a split-plot design. Two nitrogen (N) rates (200 kg ha -1 , N200; 150 kg ha -1 ,N150) applied to the main plots and three planting densities (20 cm plant space, D20; 25 cm plant space, D25; and 30 cm plant space, D30; 60 cm rows space for all plots) as subplots. The results indicated that the plants in N150D25 presented better root system architecture, greater root biomass, and more roots per plant. These effects are mediated by the underlying metabolism of endogenous phytohormones, which balance the absorbing and anchoring function of the root system. This further improved the development of plant crown architecture, including stem nodes and ear leaf traits, and further coordinated dry matter dynamics and lignin metabolism between the root and shoot organs. These observations may account for the resistance of the roots to lodging in this treatment. The maximum yield output was achieved in the plants under N150D25 via a significant increase in individual ear fresh weight, kernel number per row, and grain number per ear via path analysis. Compared with that of N200D30 (local field management), the yield of N150D25 plants increased by 22.33%–30.00% during the three growing seasons. Notably, the yield stability was achieved by significantly reducing the coefficient of variation (CV) of cob length and diameter, ear diameter, kernel row number per plant and grain number per plant. Among these factors, the planting date had a considerable effect on ear fresh weight, cob fresh weight, ear length, cob diameter, cob length and kernel row number by significantly increasing the degree of variation. This finding indicated that the planting date is a crucial factor that should be accounted in field crop management. Our findings provide a scientific basis for high-yield production of sweet corn in tropical regions during the “off season” period.

Context: Optimizing nitrogen application and planting density is critical for achieving high yields and increasing lodging resistance in crops. However, the agronomic mechanisms underlying these benefits remain unclear. Objectives: This study aimed to elucidate the relationships among light distribution within the canopy, photosynthetic capacity, root architecture, yield, and lodging resistance in sweet corn. Methods: A two-year field experiment (2024–2025) was conducted using a split-plot design with two factors: nitrogen application levels as main plots (namely, N150 and N200; 150 kg/ha and 200 kg/ha, respectively) and three planting densities as sub-plots (D20, D25, and D30, representing plant spacing of 20 cm, 25 cm, and 30 cm, respectively, with a fixed row spacing of 80 cm). Results: At a given planting density, N150-treated plants exhibited significantly enhanced basal stem node strength and root architecture compared to those treated with N200. These improvements were closely associated with the increase in light interception rate (IR) into the lower canopy under N150. Consequently, root-lodging resistance increased, reducing the root lodging rate by 80.82% (7.32% vs. 13.21% under N200). Due to these advantages, the average yield of N150-treated plants was higher than that of N200-treated plants (+3.16%). Notably, increasing planting density emerged as the primary factor driving ear yield improvement, with the highest yield observed under the N150D20 group plants, which can reach ~29 t/ha. Conclusion: Coordinating nitrogen input with appropriate planting density improves vertical light distribution, particularly in the middle and lower canopy, thereby strengthening the basal stem and root systems and enhancing root lodging resistance and yield. Implication: These findings offer practical guidance for achieving high sweet corn yields by integrating canopy light management with optimized nitrogen application and planting density, and provide scientific guidance on “smart canopy” selection for sweet corn breeding.

Planting density is a crucial factor in sweet potato output. However, the relationship among photosynthetic performance, yield, and storage root commercial features that respond to planting density is not well understood. We conducted a three-year field experiment with four planting densities (83,280 plants hm−2, plant spacing 15 cm, D15; 62,520 plants hm−2, plant spacing 20 cm, D20; 50,025 plants hm−2, panting spacing 25 cm, D25; and 41,640 plants hm−2, 30 cm, D30; 80 cm row space for all) to investigate the dynamic of photosynthetic performance, dry matter, yield, carbohydrate metabolism, and commercial features of storage root. The result showed that the highest yield was observed in the D20 treatment, and the yield increment was by 8.47–24.92% when compared to the D25 control treatment during the three growth periods. The observation can be attributed to the fact that appropriate planting density D20 can shape a good canopy structure to improve photosynthetic performance by significantly increasing IPAR, TPAR, light transmission, and extinction coefficient through different canopy levels. Hence, the Pn, Tr, Ci, Gs and WUE, and the chlorophyll fluorescence parameters were significantly improved. Eventually, promoting root sink development by up-regulating starch, fructose, glucose, and sucrose in storage roots, resulting in vigorous carbon flux from the source toward the root sink. Therefore, the optimal planting density D20 treatment increased individual plant yield and commercial features by increasing the number of storage roots, particularly medium-sized ones. Herein, we claim that optimizing the plant population density of sweet potatoes can be a good way to increase the yield and commercial features, and our results are great and important for improving the market value and profits of sweet potatoes.

An appropriate planting density could realize the maximum yield potential of crops, but the mechanism of sweet potato storage root formation in response to planting density is still rarely investigated. Four planting densities, namely D15, D20, D25, and D30, were set for 2-year and two-site field experiments to investigate the carbohydrate and lignin metabolism in potential storage roots and its relationship with the storage root number, yield, and commercial characteristics at the harvest period. The results showed that an appropriate planting density (D20 treatment) stimulated cambium cell differentiation, which increased carbohydrate accumulation and inhibited lignin biosynthesis in potential storage roots. At canopy closure, the D20 treatment produced more storage roots, particularly developing ones. It increased the yield by 10.18–19.73% compared with the control D25 treatment and improved the commercial features by decreasing the storage root length/diameter ratio and increasing the storage root weight uniformity. This study provides a theoretical basis for the high-value production of sweet potato.

Background Laccase (LAC) is the pivotal enzyme responsible for the polymerization of monolignols and stress responses in plants. However, the roles of LAC genes in plant development and tolerance to diverse stresses are still largely unknown, especially in tea plant ( Camellia sinensis ), one of the most economically important crops worldwide. Results In total, 51 CsLAC genes were identified, they were unevenly distributed on different chromosomes and classified into six groups based on phylogenetic analysis. The CsLAC gene family had diverse intron–exon patterns and a highly conserved motif distribution. Cis -acting elements in the promoter demonstrated that promoter regions of CsLACs encode various elements associated with light, phytohormones, development and stresses. Collinearity analysis identified some orthologous gene pairs in C. sinensis and many paralogous gene pairs among C. sinensis , Arabidopsis and Populus . Tissue-specific expression profiles revealed that the majority of CsLACs had high expression in roots and stems and some members had specific expression patterns in other tissues, and the expression patterns of six genes by qRT‒PCR were highly consistent with the transcriptome data. Most CsLACs showed significant variation in their expression level under abiotic (cold and drought) and biotic (insect and fungus) stresses via transcriptome data. Among them, CsLAC3 was localized in the plasma membrane and its expression level increased significantly at 13 d under gray blight treatment. We found that 12 CsLACs were predicted to be targets of cs-miR397a, and most CsLACs showed opposite expression patterns compared to cs-miR397a under gray blight infection. Additionally, 18 highly polymorphic SSR markers were developed, these markers can be widely used for diverse genetic studies of tea plants. Conclusions This study provides a comprehensive understanding of the classification, evolution, structure, tissue-specific profiles, and (a)biotic stress responses of CsLAC genes. It also provides valuable genetic resources for functional characterization towards enhancing tea plant tolerance to multiple (a)biotic stresses.

Two-dimensional endoscopic images are susceptible to interferences such as specular reflections and monotonous texture illumination, hindering accurate three-dimensional lesion reconstruction by surgical robots. This study proposes a novel end-to-end disparity estimation model to address these challenges. Our approach combines a Pseudo-Siamese neural network architecture with pyramid dilated convolutions, integrating multi-scale image information to enhance robustness against lighting interferences. This study introduces a Pseudo-Siamese structure-based disparity regression model that simplifies left-right image comparison, improving accuracy and efficiency. The model was evaluated using a dataset of stereo endoscopic videos captured by the Da Vinci surgical robot, comprising simulated silicone heart sequences and real heart video data. Experimental results demonstrate significant improvement in the network’s resistance to lighting interference without substantially increasing parameters. Moreover, the model exhibited faster convergence during training, contributing to overall performance enhancement. This study advances endoscopic image processing accuracy and has potential implications for surgical robot applications in complex environments.

Bitter gourd (Momordica charantia L.), a staple crop in subtropical and tropical Asia and Africa, is valued for its nutritional and medicinal properties. Despite its significance, genetic studies on key horticultural traits remain limited. To address this, we generated F1, F2, and F2:3 populations by crossing two inbred lines, HNU004 and HNU025. Whole-genome sequencing of the parents and 178 F2 individuals enabled the construction of a high-density genetic map with 2605 bin SNP markers across 11 linkage groups. QTL mapping using Composite Interval Mapping (CIM) and Multiple QTL Model (MQM) approaches across three environments identified 22 QTLs influencing plant architecture, fruit size, and wart traits, explaining 6.14–68.12 % of phenotypic variance. This included three novel QTLs for average internode length, three for lateral branch number (LBN), and four for fruit-related traits. Five key QTLs were consistently detected: lbn3.1 on chromosome 3 (LBN), mfl5.1 and smfw5.1 on chromosome 5 (mature fruit length and single mature fruit weight), and fwf4.1 and fwf6.1 on chromosomes 4 and 6 respectively governing fruit wart characteristics. These QTLs spanned physical regions ranging from 220 kb to 2.1 Mb. Candidate genes were predicted for major QTLs, including Moc03g28260 (lbn3.1), Moc05g28880 and Moc05g29850 (mfl5.1), and Moc06g04450 and Moc06g04970 (fwf6.1). Epistatic interactions between QTLs for LBN and fruit length suggested complex genetic regulation. Molecular markers for mfl5.1, fwf4.1, and fwf6.1 were validated in an independent F2 population of 213 individuals, which confirmed their phenotypic effects. This study provides a dense and informative set of genetic markers suitable for marker-assisted selection in bitter gourd breeding and establishes a foundation for the cloning of candidate genes, thereby accelerating genetic improvement efforts.