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The simulation of gas–liquid-particles dam-break multiphase flow has long been a focal point and a significant challenge in many fields such as water conservancy, chemical engineering, and energy. This study developed a CLSVOF-DEM model (coupled level set and volume of fluid-discrete element method), which falls under the category of Eulerian-Lagrangian hybrid models. Initially, the CLSVOF method couples the LS (level set) method and the VOF (volume of fluid) model and introduces a secondary reconstruction of the interface to obtain an accurate gas–liquid interface. Subsequently, DEM (discrete element method) takes into account the contact model and collision model of solid particles. Finally, the integration of CLSVOF and DEM achieves strong fluid-solid coupling by incorporating various mechanical interactions between fluid (gas and liquid phases) and solid particles, which are implanted into the control equations. Furthermore, the rationality and accuracy of the model are verified by four typical cases (particles column dam-break into water, dam-break of submerged particles column, silted-up air–water-particles dam-break flow in a tank, and silted-up air–water-particles dam-break in complex terrain). This study provides a new solution for dam-break multiphase flow simulation, which offers valuable insights and establishes a foundation for advancing the gas–liquid-particles dam-break multiphase flow model.

Low temperature storage is widely used for storage and transportation of fruits and vegetables after harvest. As a cold-sensitive fruit vegetable, post-harvest solanaceous vegetables and fruits are susceptible to chilling injury during low temperature storage, which reduces its sensory quality and edible quality and shortens its storage period, thus leading to huge economic losses. Therefore, it is an essential to clarify the occurrence mechanism of chilling injury caused by low temperature storage in solanaceous vegetables and fruits, and to propose corresponding prevention and control measures for chilling injury. In recent years, a series of progress has been made in the research on chilling injury prevention and control and low temperature stress tolerance of solanaceous vegetables and fruits. This paper describes the chilling injury symptoms of postharvest solanaceous vegetables and fruits, clarifies the physiological and biochemical mechanisms in the chilling injury process, the molecular mechanisms, and prevention and control measures, and summarizes the latest research advancements on chilling injury and chilling tolerance regulation of solanaceous vegetables and fruits, which can provide valuable references for low temperature storage and chilling injury prevention and control measures of solanaceous vegetables and fruits.

Radish ( Raphanus sativus L.) is a vegetable crop with economic value and ecological significance in the genus Radish, family Brassicaceae . In recent years, developed countries have attached great importance to the collection and conservation of radish germplasm resources and their research and utilization, but the lack of population genetic information and molecular markers has hindered the development of the genetic breeding of radish. In this study, we integrated the radish genomic data published in databases for the development of single-nucleotide polymorphism (SNP) markers, and obtained a dataset of 308 high-quality SNPs under strict selection criteria. With the support of Kompetitive Allele-Specific PCR (KASP) technology, we screened a set of 32 candidate core SNP marker sets to analyse the genetic diversity of the collected 356 radish varieties. The results showed that the mean values of polymorphism information content (PIC), minor allele frequency (MAF), gene diversity and heterozygosity of the 32 candidate core SNP markers were 0.32, 0.30, 0.40 and 0.25, respectively. Population structural analysis, principal component analysis and genetic evolutionary tree analysis indicated that the 356 radish materials were best classified into two taxa, and that the two taxa of the material were closely genetically exchanged. Finally, on the basis of 32 candidate core SNP markers we calculated 15 core markers using a computer algorithm to construct a fingerprint map of 356 radish varieties. Furthermore, we constructed a core germplasm population consisting of 71 radish materials using 32 candidate core markers. In this study, we developed SNP markers for radish cultivar identification and genetic diversity analysis, and constructed DNA fingerprints, providing a basis for the identification of radish germplasm resources and molecular marker-assisted breeding as well as genetic research.

Bacterial wilt caused by Ralstonia solanacearum is a major constraint on tomato (Solanum lycopersicum L.) production, yet the molecular basis of quantitative resistance remains poorly understood. In this study, comparative transcriptome profiling was performed on resistant (‘ZM3’) and susceptible (‘ZM86’) tomato inbred lines following pathogen inoculation in roots, stems, and leaves. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were conducted to identify resistance-associated regulatory modules and hub genes. The results revealed distinct gene expression patterns between the two genotypes after infection. Several co-expression modules were significantly associated with resistance or susceptibility traits. Functional enrichment analysis showed that differentially expressed genes were mainly involved in plant hormone signal transduction, plant–pathogen interaction, phenylpropanoid biosynthesis, and cell wall modification. Genes related to ethylene and salicylic acid signaling were strongly induced following infection, whereas brassinosteroid-associated genes showed genotype-dependent expression patterns. Network analysis further identified several hub genes within defense-related modules, including ACO (Solyc04g007980), ERF1 (Solyc09g091950), MAPK9, receptor-like kinase RLK (Solyc07g006770), and a dirigent family gene (Solyc10g008900). Taken together, our results suggest that tomato resistance to Ralstonia solanacearum involves a coordinated defense network integrating hormone-mediated transcriptional regulation and structural reinforcement, and provides candidate genes for breeding bacterial wilt-resistant cultivars.

Pathogen genetic diversity varies in response to environmental changes. However, it remains unclear whether plant barriers to invasion could be considered a genetic bottleneck for phytopathogen populations. Here, we implement a barcoding approach to generate a pool of 90 isogenic and individually barcoded Ralstonia solanacearum strains. We used 90 of these strains to inoculate tomato plants with different degrees of physical permeability to invasion (intact roots, wounded roots and xylem inoculation) and quantify the phytopathogen population dynamics during invasion. Our results reveal that the permeability of plant roots impacts the degree of population bottleneck, genetic diversity, and composition of Ralstonia populations. We also find that selection is the main driver structuring pathogen populations when barriers to infection are less permeable, i.e., intact roots, the removal of root physical and immune barriers results in the predominance of stochasticity in population assembly. Taken together, our study suggests that plant root permeability constitutes a bottleneck for phytopathogen invasion and genetic diversity. Bottleneck effects of plant barriers on pathogenic invasions remain unclear. Using a random barcoding approach, this study investigates how plant root permeability limits the invasion and population bottlenecks of a phytopathogenic Ralstonia.

Solanum torvum (Swartz) (2n = 24) is a wild Solanaceae plant with high economic value that is used as a rootstock in grafting for Solanaceae plants to improve the resistance to a soil-borne disease caused by root-knot nematodes (RKNs). However, the lack of a high-quality reference genome of S . torvum hinders research on the genetic basis for disease resistance and application in horticulture. Herein, we present a chromosome-level assembly of genomic sequences for S . torvum combining PacBio long reads (HiFi reads), Illumina short reads and Hi-C scaffolding technology. The assembled genome size is ~1.25 Gb with a contig N50 and scaffold N50 of 38.65 Mb and 103.02 Mb, respectively as well as a BUSCO estimate of 98%. GO enrichment and KEGG pathway analysis of the unique S . torvum genes, including NLR and ABC transporters, revealed that they were involved in disease resistance processes. RNA-seq data also confirmed that 48 NLR genes were highly expressed in roots and fibrous roots and that three homologous NLR genes ( Sto0288260.1 , Sto0201960.1 and Sto0265490.1 ) in S. torvum were significantly upregulated after RKN infection. Two ABC transporters, ABCB9 and ABCB11 were identified as the hub genes in response to RKN infection. The chromosome-scale reference genome of the S . torvum will provide insights into RKN resistance.

Current eggplant variety breeding is still mainly based on conventional methods, and there remains a lack of effective molecular breeding systems for complex traits controlled by multiple genes, such as yield and quality. To accelerate the research progress of eggplant genetics and molecular breeding, it is necessary to implement a genome-based breeding strategy. Therefore, in this study, a SNP array containing 50K liquid-phase probes was designed on the basis of the resequencing data of 577 eggplants. The developed 50K liquid-phase probes were used to perform targeted capture sequencing on 12 eggplant lines, and the efficiency of probe capture exceeded 99.25%. Principal component, phylogenetic, and population structure analyses divided the 577 eggplants into 7 subgroups, and statistical analysis was performed on the fruit shape and color of the materials in the different subgroups. Further analysis of the geographical distribution of 428 Chinese eggplant materials revealed that the geographical regions of different subgroups were similar. The 50K SNP liquid-phase array was used to perform bulked- segregant analysis combined with whole-genome resequencing (BSA-seq) of fruit shape in the F population, which consisted of 1435 lines constructed with E421 as the maternal parent and 145 as the paternal parent. The BSA-seq data were located in the 78444173-84449348 interval on chromosome 3, with a size of 6 Mb, which was narrowed to 712.6 kb through fine mapping. Further sequence alignment and expression analysis revealed as a candidate gene controlling eggplant fruit shape. The 50K SNP liquid-phase array can be widely used in future eggplant molecular breeding research.

[This corrects the article DOI: 10.3389/fpls.2024.1492242.].

Early diagnosis of soil‐borne diseases like root rot is a long‐standing challenge in agriculture. While microbial functional genes are recognized as potent indicators of soil healthy, their application has been primarily limited to current or past soil conditions. Here, we demonstrate that microbial functional genes can transition from descriptive indicators to reliable predictive biomarkers. By analyzing 199 paired metagenomes from healthy and diseased medicinal plants rhizosphere soil samples, we identified a conserved core set of functional genes, specifically those governing biofilm formation, stress response, and plant‐microbe mutualism that are robustly associated with root rot disease. To bridge the gap between discovery and field application, we developed a framework that integrates cost‐effective qPCR assay for these key genes and fused their abundance data with machine learning. This model achieved over 80% accuracy in predicting disease onset from independent, pre‐symptomatic soil samples, identifying risks long before visible symptoms of infection appeared. Our findings suggest a practical path for moving beyond simple microbial correlations toward an active forecasting tool. By positioning microbial functional genes at the core of disease management, this framework provides a targeted approach for mitigating soil‐borne risks and supporting sustainable agricultural practices. Predicting soil‐borne disease moves beyond observation with a framework that elevates microbial functional genes into reliable forecasting biomarkers. By coupling targeted qPCR assays for core stress‐response genes with machine learning, this method detects root rot risks in pre‐symptomatic soils with over 80% accuracy. The approach offers a scalable, high‐precision tool for preemptive disease management and sustainable crop protection.

Heterostyly is a common floral polymorphism, but the proteomic basis of this trait is still largely unexplored. In this study, self- and cross-pollination of L-morph and S-morph flowers and comparison of embryo sac development in eggplant (Solanum melongena L.) suggested that lower fruit set from S-morph flowers results from stigma-pollen incompatibility. To explore the molecular mechanism underlying heterostyly development, we conducted isobaric tags for relative and absolute quantification (iTRAQ) proteomic analysis of eggplant pistils for L- and S-morph flowers. A total of 5,259 distinct proteins were identified during heterostyly development. Compared S-morph flowers with L-morph, we discovered 57 and 184 differentially expressed proteins (DEPs) during flower development and maturity, respectively. Quantitative real time polymerase chain reactions were used for nine genes to verify DEPs from the iTRAQ approach. During flower development, DEPs were mainly involved in morphogenesis, biosynthetic processes, and metabolic pathways. At flower maturity, DEPs primarily participated in biosynthetic processes, metabolic pathways, and the formation of ribosomes and proteasomes. Additionally, some proteins associated with senescence and programmed cell death were found to be upregulated in S-morph pistils, which may lead to the lower fruit set in S-morph flowers. Although the exact roles of these related proteins are not yet known, this was the first attempt to use an iTRAQ approach to analyze proteomes of heterostylous eggplant flowers, and these results will provide insights into biochemical events taking place during the development of heterostyly.