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<jats:p>Large-scale afforestation is considered a natural way to address climate challenges (e.g., the greenhouse effect). However, there is a paucity of evidence linking plant diversity to soil carbon sequestration pathways during long-term natural restoration of temperate vegetation. In particular, the carbon sequestration mechanisms and functions of woody plants require further study. Therefore, we conducted a comparative study of plant diversity and soil carbon sequestration characteristics during 150 years of natural vegetation restoration in the temperate zone to provide a comprehensive assessment of the effects of long-term natural vegetation restoration processes on soil organic carbon stocks. The results suggested positive effects of woody plant diversity on carbon sequestration. In addition, fine root biomass and deadfall accumulation were significantly positively correlated with soil organic carbon stocks, and carbon was stored in large grain size aggregates (1–5 mm). Meanwhile, the diversity of Fabaceae and Rosaceae was observed to be important for soil organic carbon accumulation, and the carbon sequestration function of shrubs should not be neglected during vegetation restoration. Finally, we identified three plants that showed high potential for carbon sequestration: <jats:italic>Lespedeza bicolor</jats:italic>, <jats:italic>Sophora davidii</jats:italic>, and <jats:italic>Cotoneaster multiflorus</jats:italic>, which should be considered for inclusion in the construction of local artificial vegetation. Among them, <jats:italic>L. bicolor</jats:italic> is probably the best choice.</jats:p>

<jats:p>Recently, entire genebank collections of wheat have been extensively characterized with sequencing data. We have identified introgressions using these genotyping-by-sequencing and whole-genome sequencing data. On the basis of our results, we provide information about predicted introgressions at 1-Mb resolution for 9,172 wheat samples as a resource for breeders and scientists. We recommend that all plant genetic resources, including genebank collections, be characterized using a combination of variant calling and introgression prediction. This is necessary to identify potential duplicates in collections efficiently and reliably, and to select promising germplasms with potentially beneficial introgressions for further characterization and prospective breeding application.</jats:p>

<jats:sec><jats:title>Introduction</jats:title><jats:p>Cotton (<jats:italic>Gossypium hirsutum</jats:italic> L.) is one of the most important staple fibrous crops cultivated in India and globally. However, its production and quality are greatly hampered by cotton leaf curl disease (CLCuD) caused by cotton leaf curl virus (CLCuV). Therefore, the aim of the present study was to investigate the biochemical mechanisms associated with CLCuD resistance in contrasting cotton genotypes.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Four commercial cotton varieties with susceptible (HS 6 and RCH-134 BG-II) and resistant (HS 1236 and Bunty) responses were used to analyze the role of primary (sugar, protein, and chlorophyll) and secondary (gossypol, phenol, and tannin) biochemical compounds produced by the plants against infection by CLCuV. The resistant cultivars with increased activity of protein, phenol, and tannin exhibited biochemical barriers against CLCuV infection, imparting resistance in cotton cultivars.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Reducing sugar in the healthy plants of the susceptible Bt cultivar RCH 134 BG-II exhibited the highest value of 1.67 mg/g at 90 days. In contrast, the lowest value of 0.07 mg g<jats:sup>-1</jats:sup> was observed at 60 DAS in the highly diseased plants of the susceptible hybrid HS 6. Higher phenol content (0.70 mg g<jats:sup>-1</jats:sup>) was observed at 90 DAS in resistant cultivars, whereas highly susceptible plants exhibited the least phenol (0.25 mg g<jats:sup>-1</jats:sup>) at 90 DAS. The lowest protein activity was observed at 120 DAS in susceptible cultivars HS 6 (9.4 mg g<jats:sup>-1</jats:sup>) followed by RCH 134 BG-II (10.5 mg g<jats:sup>-1</jats:sup>). However, other biochemical compounds, including chlorophyll, sugar, and gossypol, did not show a significant role in resistance against CLCuV. The disease progression analysis in susceptible cultivars revealed non-significant differences between the two susceptible varieties.</jats:p></jats:sec><jats:sec><jats:title>Discussion</jats:title><jats:p>Nevertheless, these compounds are virtually associated with the basic physiological and metabolic mechanisms of cotton plants. Among the primary biochemical compounds, only protein activity was proposed as the first line of defense in cotton against CLCuV. The secondary level of defense line in resistance showed the activity of secondary biochemical compounds phenol and tannins, which displayed a significant increase in their levels while imparting resistance against CLCuV in cotton.</jats:p></jats:sec>

<jats:p>Intraorganismal genetic heterogeneity (IGH) exists when an individual organism harbors more than one genotype among its cells. In general, intercellular DNA diversity occurs at a very low frequency and cannot be directly detected by DNA sequencing from bulk tissue. In this study, based on Sanger and high-throughput sequencing, different species, different organs, different DNA segments and a single cell were employed to characterize nucleotide mutations in Leymus chinensis. The results demonstrated that 1) the nuclear DNA showed excessive genetic heterogeneity among cells of an individual leaf or seed but the chloroplast genes remained consistent; 2) a high density of SNPs was found in the variants of the unique DNA sequence, and the similar SNP profile shared between the leaf and seed suggested that nucleotide mutation followed a certain rule and was not random; and 3) the mutation rate decreased from the genomic DNA sequence to the corresponding protein sequence. Our results suggested that Leymus chinensis seemed to consist of a collection of cells with different genetic backgrounds.</jats:p>

<jats:p>The endoplasmic reticulum (ER) serves essential functions in eukaryotic cells, including protein folding, transport of secretory proteins, and lipid synthesis. The ER is a highly dynamic organelle that generates various types of compartments. Among them, the ER body is specifically present in plants in the <jats:italic>Brassicaceae</jats:italic> family and plays a crucial role in chemical defense against pathogens. The NAI2 protein is essential for ER body formation, and its ectopic overexpression is sufficient to induce ER body formation even in the leaves of <jats:italic>Nicotiana benthamiana</jats:italic>, where the ER body does not naturally exist. Despite the significance of NAI2 in ER body formation, the mechanism whereby NAI2 mediates ER body formation is not fully clear. This study aimed to investigate how two domains of <jats:italic>Arabidopsis</jats:italic> NAI2, the Glu-Phe-Glu (EFE) domain (ED) and the NAI2 domain (ND), contribute to ER body formation in <jats:italic>N. benthamiana</jats:italic> leaves. Using co-immunoprecipitation and bimolecular fluorescence complementation assays, we found that the ND is critical for homomeric interaction of NAI2 and ER body formation. Moreover, deletion of ED induced the formation of enlarged ER bodies, suggesting that ED plays a regulatory role during ER body formation. Our results indicate that the two domains of NAI2 cooperate to induce ER body formation in a balanced manner.</jats:p>

<jats:p>Rice leaf diseases are important causes of poor rice yields, and accurately identifying diseases and taking corresponding measures are important ways to improve yields. However, rice leaf diseases are diverse and varied; to address the low efficiency and high cost of manual identification, this study proposes a stacking-based integrated learning model for the efficient and accurate identification of rice leaf diseases. The stacking-based integrated learning model with four convolutional neural networks (namely, an improved AlexNet, an improved GoogLeNet, ResNet50 and MobileNetV3) as the base learners and a support vector machine (SVM) as the sublearner was constructed, and the recognition rate achieved on a rice dataset reached 99.69%. Different improvement methods have different effects on the learning and training processes for different classification tasks. To investigate the effects of different improvement methods on the accuracy of rice leaf disease diagnosis, experiments such as comparison experiments between single models and different stacking-based ensemble model combinations and comparison experiments with different datasets were executed. The model proposed in this study was shown to be more effective than single models and achieved good results on a plant dataset, providing a better method for plant disease identification.</jats:p>

<jats:p>Flavor and quality are the major drivers of fruit consumption in the US. However, the poor flavor of modern commercial tomato varieties is a major cause of consumer dissatisfaction. Studies in flavor research have informed the role of volatile organic compounds in improving overall liking and sweetness of tomatoes. These studies have utilized and applied the tools of molecular biology, genetics, biochemistry, omics, machine learning, and gene editing to elucidate the compounds and biochemical pathways essential for good tasting fruit. Here, we discuss the progress in identifying the biosynthetic pathways and chemical modifications of important tomato volatile compounds. We also summarize the advances in developing highly flavorful tomato varieties and future steps toward developing a “perfect tomato”.</jats:p>

<jats:p>Grassland health assessment (GHA) is a bridge of study and management of grassland ecosystem. However, there is no standardized quantitative indicators and long-term monitor methods for GHA at a large scale, which may hinder theoretical study and practical application of GHA. In this study, along with previous concept and practices (i.e., CVOR, the integrated indexes of condition, vigor, organization and resilience), we proposed an assessment system based on the indicators monitored by unmanned aerial vehicles (UAVs)-UAV<jats:italic><jats:sub>CVOR</jats:sub></jats:italic>, and tested the feasibility of UAV<jats:italic><jats:sub>CVOR</jats:sub></jats:italic> at typical household pastures on the Qinghai-Tibetan Plateau, China. Our findings show that: (1) the key indicators of GHA could be measured directly or represented by the relative counterpart indicators that monitored by UAVs, (2) there was a significantly linear relationship between CVOR estimated by field- and UAV-based data, and (3) the CVOR decreased along with the increasing grazing intensity nonlinearly, and there are similar tendencies of CVOR that estimated by the two methods. These findings suggest that UAVs is suitable for GHA efficiently and correctly, which will be useful for the protection and sustainable management of grasslands.</jats:p>

<jats:p>Recently, biochar (B) and vermicompost (V) have been widely used as amendments to improve crop productivity and soil quality. However, the ameliorative effects of biochar and vermicompost on the continuous cropping of pepper under open-air conditions, particularly in the karst areas of southwestern China, remain unclear. A field experiment was conducted to study the effects of biochar and vermicompost application, alone or in combination, on the yield, quality, nutrient accumulation, fertilizer utilization, and economic benefits of continuous pepper cropping from 2021 to 2022. The experiment included six treatments: CK (no fertilizer), TF (traditional fertilization of local farmers), TFB (TF combined with biochar of 3000 kg·ha<jats:sup>-1</jats:sup>), TFV (TF combined with vermicompost of 3000 kg·ha<jats:sup>-1</jats:sup>), TFBV1 (TF combined with biochar of 1500 kg·ha<jats:sup>-1</jats:sup> and vermicompost of 1500 kg·ha<jats:sup>-1</jats:sup>), and TFBV2 (TF combined with biochar of 3000 kg·ha<jats:sup>-1</jats:sup> and vermicompost of 3000 kg·ha<jats:sup>-1</jats:sup>). Compared with the TF treatment, biochar and vermicompost application alone or in combination increased the yield of fresh pod pepper by 24.38–50.03% and 31.61–88.92% in 2021 and 2022, respectively, whereas the yield of dry pod pepper increased by 14.69–40.63% and 21.44–73.29% in 2021 and 2022, respectively. The application of biochar and vermicompost reduced the nitrate content and increased the vitamin C (VC) and soluble sugar content of the fruits, which is beneficial for improving their quality. Biochar and vermicompost application alone or in combination not only increased nutrient uptake but also significantly improved agronomic efficiency (AE) and recovery efficiency (RE). In addition, although the application of biochar or vermicompost increased production costs, the increase in yield improved net income (ranging from 0.77 to 22.34% in 2021 and 8.82 to 59.96% in 2022), particularly in the TFBV2 treatment. In conclusion, the use of biochar and vermicompost amendments had a positive effect on the productivity and economic benefits of continuous pepper cropping, and the co-application of biochar and vermicompost could be an effective nutrient management strategy for the continuous cropping of pepper in the karst mountain areas of southwest China.</jats:p>