Fraxinus velutina Torr with high salt tolerance has been widely grown in saline lands in the Yellow River Delta, China. However, the salt-tolerant mechanisms of F. velutina remain largely elusive. Here, we identified two contrasting cutting clones of F. velutina, R7 (salt-tolerant), and S4 (salt-sensitive) by measuring chlorophyll fluorescence characteristics (Fv/Fm ratio) in the excised leaves and physiological indexes in roots or leaves under salt treatment. To further explore the salt resistance mechanisms, we compared the transcriptomes of R7 and S4 from leaf and root tissues exposed to salt stress. The results showed that when the excised leaves of S4 and R7 were, respectively, exposed to 250 mM NaCl for 48 h, Fv/Fm ratio decreased significantly in S4 compared with R7, confirming that R7 is more tolerant to salt stress. Comparative transcriptome analysis showed that salt stress induced the significant upregulation of stress-responsive genes in R7, making important contributions to the high salt tolerance. Specifically, in the R7 leaves, salt stress markedly upregulated key genes involved in plant hormone signaling and mitogen-activated protein kinase signaling pathways; in the R7 roots, salt stress induced the upregulation of main genes involved in proline biosynthesis and starch and sucrose metabolism. In addition, 12 genes encoding antioxidant enzyme peroxidase were all significantly upregulated in both leaves and roots. Collectively, our findings revealed the crucial defense pathways underlying high salt tolerance of R7 through significant upregulation of some key genes involving metabolism and hub signaling pathways, thus providing novel insights into salt-tolerant F. velutina breeding.

Walnut anthracnose (Colletotrichum gloeosporioides) reduces walnut yield and quality and seriously threatens the healthy development of the walnut industry. WRKY transcription factors (TFs) are crucial regulatory factors involved in plant-pathogen interactions. Our previous transcriptome analysis results indicate that JrWRKY4 responds to infection by C. gloeosporioides, but its specific regulatory network and disease resistance mechanism are still unclear. Herein, the characteristics of JrWRKY4 as a transcription activator located in the nucleus were first identified. Gain-of-function and loss-of-function analyses showed that JrWRKY4 could enhance walnut resistance against C. gloeosporioides. A series of molecular experiments showed that JrWRKY4 directly interacted with the promoter region of JrSTH2L and positively regulated its expression. In addition, JrWRKY4 interacted with JrVQ4 to form the protein complex, which inhibited JrWRKY4 for the activation of JrSTH2L. Notably, a MYB TF JrPHL8 interacting with the JrWRKY4 promoter has also been identified, which directly bound to the MBS element in the promoter of JrWRKY4 and induced its activity. Our study elucidated a novel mechanism of the JrPHL8-JrWRKY4-JrSTH2L in regulating walnut resistance to anthracnose. This mechanism improves our understanding of the molecular mechanism of WRKY TF mediated resistance to anthracnose in walnut, which provides new insights for molecular breeding of disease-resistant walnuts in the future.

INMATEH Agricultural Engineering is an open access international journal that publishes reviewed original research papers of both experimental and theoretical nature in the following areas: Technologies and technical equipment for agriculture and food industry, Environmental-friendly agriculture, Renewable energies, Technical equipment testing, Environment, Transport in agriculture, others

Yellowhorn (Xanthoceras sorbifolium) is a deciduous shrub or small tree native to China. The content of oil in kernels is 52.7% to 58.0%, of which is the source of neuroic acid (3.7-4.4%). (Liang et al. 2022). In recent years, yellowhorn, as a woody oleiferous crop, has been cultivated in northern China (Xiao et al. 2023). In late June 2019, an unknown collar rot was observed on yellowhorn in Tai'an, and Weifang City, Shandong Province, China. Infected plants had dark brown to black lesions at the base of the stem, about 10 to 15 cm from the ground, bark dehiscence and rot, resulting in wilting, withering, and death of plants. The disease incidence in the field was 35-48%. Representative symptomatic samples were collected randomly from the collar of 8 plants, and 24 samples were cut from the diseased tissue into 5 mm square pieces, surface disinfected with 75% alcohol for 30s and then with 0.1% mercury bichloride for 1min, plated onto potato dextrose agar (PDA), and incubated at 28°C in the dark for 2 to 3 days. Isolation frequency of the pathogen from symptomatic collar was 83.3%. The colonies were subcultured three times on PDA to obtained the purified colonies. The colonies appeared flocculent mycelia incubated on PDA at 28°C for 7 days. The color of the surface and the reverse colony was white and cream, respectively. The chlamydosposres were smooth with thick walled, and are formed singly. Microconidia were oval or ellipsoidal, with 0-1 septum; macroconidia end cells curved to slightly, with 3- or 5-septate, and measured 17.3 to 23.1 × 4.9 to 6.5 µm (avg. 21.3 × 5.9 μm, n = 60). The morphological characteristics fit the descriptions of Fusarium spp. (Hafizi et al. 2013; Crespo et al 2019). Genomic DNA extracted from four representative isolates (XSTA4, XSTA7, XSWF6 and XSWF8), and the internal transcribed spacer region (ITS) of ribosomal DNA, translation elongation factor 1-alpha (EF1-α), RNA polymerase I beta subunit (RPB1), and RNA polymerase II beta subunit (RPB2) genes were amplified using the primer pairs ITS1/ITS4 (White et al. 1990), EF-1/EF-2, RPB-1F/1R, and RPB2-5F2/11aR (O'Donnell et al 2010), respectively. Amplicons were sequenced and compared in GenBank using a BLAST analysis. The ITS sequences (OR672118, OR669008, OR669039, and OR669279) had 100% similarity with the sequences of F. solani (MT560378, MG561938, MN989030 and OP630608, respectively). The EF1-α sequences (OR934984, OR934985, OR934986, and OR934987) matched 100% with the sequences of F. solani (OQ511088, MW332044, MW620166 and MT379886). The RPB-1 sequences (PP896852, PP896853, PP896854, and PP896855) had 100% similarity with the sequences of F. solani (OL474057, OR916019, MT305118 and MT305118, respectively). The RPB2 sequences (PP896856, PP896857, PP896858, and PP896859) matched 100% with the sequences of F. solani (OR371884, OK880266, OP784447 and OL474055, respectively). A phylogenetic analysis based on ITS, RPB2 and EF1-α sequences placed the four obtained isolates within the same clade containing the F. solani isolates A6, 91-84-1 and UCR1780. Pathogenicity tests were carried out in late-June 2020. Fifty 120-day-old healthy seedlings were wounded with 2 mm deep at stems in the collar region of plants at 5 cm above the soil for tested. The seedlings were inoculated on the wound with 3-mm mycelial discs from a 7-day-old culture of each four representative strains of 10 repeated, respectively. Ten seedlings inoculated on the wound with sterile PDA served as control. All plants were grown in an incubator with a 28°C temperature. After 20 days, the stems which were inoculated the representative strain turned brown, with 2 - 5 cm length lesion, and the plants developed typical wilting and withering symptoms which similar to those observed in the field. The control remained asymptomatic. The pathogen was reisolated from the inoculated stems and its identity confirmed with both morphology and using molecular tools. These results indicated that the pathogens of yellowhorn collar rot is F. solani. To our knowledge, this is the first report of F. solani causing collar rot of yellowhorn in China.

Short videos, as one of the most popular forms of multimedia, impose stringent transmission requirements on wireless networks. A Cell-Free network with numerous access points and a cloud server based on artificial intelligence is a promising approach for improving users' quality of experience. This research presents a federated reinforcement learning based radio resource scheduling method for access points to construct a global model at the cloud server to explore the potential of the Cell-Free networks while avoiding privacy leakage. First of all, local access points train their local models and upload their weights to cloud server. Then, the server aggregates the local models to obtain the global model, which is subsequently sent back to the access points. Finally, the access points update their local models with the latest global model. The simulation results show that the advantages of the proposed algorithm are the effective resource scheduling policy, the convergence speed and the scalability. Meanwhile, the proposed algorithm outperforms baselines with significant performance improvement.