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Wheat leaf diseases are considered to be the foremost threat to wheat yield. In the realm of crop disease detection, convolutional neural networks (CNNs) have emerged as important tools. The training strategy and the initial learning rate are key factors that impact the performance and training speed of the model in CNNs. This study employed six training strategies, including Adam, SGD, Adam + StepLR, SGD + StepLR, Warm-up + Cosine annealing + SGD, Warm-up + Cosine, and annealing + Adam, with three initial learning rates (0.05, 0.01, and 0.001). Using the wheat stripe rust, wheat powdery mildew, and healthy wheat datasets, five lightweight CNN models, namely MobileNetV3, ShuffleNetV2, GhostNet, MnasNet, and EfficientNetV2, were evaluated. The results showed that upon combining the SGD + StepLR with the initial learning rate of 0.001, the MnasNet obtained the highest recognition accuracy of 98.65%. The accuracy increased by 1.1% as compared to that obtained with the training strategy with a fixed learning rate, and the size of the parameters was only 19.09 M. The above results indicated that the MnasNet was appropriate for porting to the mobile terminal and efficient for automatically identifying wheat leaf diseases.
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Wheat stripe rust (WSR) is an airborne disease that causes severe damage to wheat. The rapid and early detection of WSR is essential for the prevention and control of this disease. The minimum detection limit (MDL) is one of the most important characteristics of quantitative methods that can be used to determine the scope and applicability of a measurement technique. Three wheat cultivars were inoculated with Puccinia striiformis f.sp. tritici (Pst), and a spectrometer was used to collect the canopy hyperspectral data, and the Pst content was obtained via a duplex real-time polymerase chain reaction (PCR) during the latent period, respectively. The disease index (DI) and molecular disease index (MDI) were calculated. The regression tree algorithm was used to determine the MDL of the Pst based on hyperspectral feature parameters. The logistic, IBK, and random committee algorithms were used to construct the classification model based on the MDL. The results showed that when the MDL was 0.7, IBK had the best recognition accuracy. The optimal model, which used the spectral feature R_2nd.dv ((the second derivative of the original hyperspectral value)) and the modeling ratio 2:1, had an accuracy of 91.67% on the testing set and 90.67% on the 10-fold cross-validation. Thus, during the latent period, the MDL of Pst was determined using hyperspectral technology as 0.7.
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Molecular Sierpinski triangles (STs), a family of elegant and well-known fractals, can be prepared on surfaces with atomic precision. Up to date, several kinds of intermolecular interactions such as hydrogen bond, halogen bond, coordination, and even covalent bond have been employed to construct molecular STs on metal surfaces. Herein a series of defect-free molecular STs have been fabricated via electrostatic attraction between potassium cations and electronically polarized chlorine atoms in 4,4â³-dichloro-1,1':3',1â³-terphenyl (DCTP) molecules on Cu(111) and Ag(111). The electrostatic interaction is confirmed both experimentally by scanning tunneling microscopy and theoretically by density functional theory calculations. These findings illustrate that electrostatic interaction can serve as an efficient driving force to construct molecular fractals, which enriches our toolbox for the bottom-up fabrication of complex functional supramolecular nanostructures.
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A molecular investigation of Cu-elimination and subsequent C-C coupling of DCTP (4,4''-dichloro-1,1':3',1''-terphenyl)-Cu organometallic (OM) polymers on Cu(111) is conducted by scanning tunneling microscopy and spectroscopy, revealing that the Cu adatoms embedded in the DCTP-Cu chains are located at the hollow and bridge sites on the Cu(111) surface. The difference in the catalytic activities of these surface sites leads to stepwise elimination of Cu adatoms in the OM chains. Moreover, the interchain interaction plays an important role in the Cu-elimination process of the DCTP-Cu chains as well. The interchain steric hindrance, on the one hand, induces the formation of Cu-eliminated intermediates that are scarcely observed in other Ullmann coupling systems, and on the other hand, promotes the cooperative Cu-elimination and C-C coupling of the OM segments in neighboring chains. These findings demonstrate the key role of the molecule-substrate and intermolecular interactions in mediating the reaction processes of the extended molecular systems on the surface.
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Chlorophyll content of the flag leaf is an important trait for drought resistance in wheat under drought stress. Understanding the regulatory mechanism of flag leaf chlorophyll content could accelerate breeding for drought resistance. In this study, we constructed a recombinant inbred line (RIL) population from a cross of drought-sensitive variety DH118 and drought-resistant variety Jinmai 919, and analyzed the chlorophyll contents of flag leaves in six experimental locations/years using the Wheat90K single-nucleotide polymorphism array. A total of 29 quantitative trait loci (QTLs) controlling flag leaf chlorophyll were detected with contributions to phenotypic variation ranging from 4.67 to 23.25%. Twelve QTLs were detected under irrigated conditions and 18 were detected under dryland (drought) conditions. Most of the QTLs detected under the different water regimes were different. Four major QTLs (Qchl.saw-3B.2, Qchl.saw-5A.2, Qchl.saw-5A.3, and Qchl.saw-5B.2) were detected in the RIL population. Qchl.saw-3B.2, possibly more suitable for marker-assisted selection of genotypes adapted to irrigated conditions, was validated by a tightly linked kompetitive allele specific PCR (KASP) marker in a doubled haploid population derived from a different cross. Qchl.saw-5A.3, a novel stably expressed QTL, was detected in the dryland environments and explained up to 23.25% of the phenotypic variation, and has potential for marker-assisted breeding of genotypes adapted to dryland conditions. The stable and major QTLs identified here add valuable information for understanding the genetic mechanism underlying chlorophyll content and provide a basis for molecular marker-assisted breeding.
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Among the multitudinous methodologies to steer on-surface reactions, less attention has been paid to the effect of externally introduced halogen atoms. Herein, highly selective trans-dehydrogenation coupling at the specific meta-C-H site of two poly(p-phenylene) molecules, p-quaterphenyl (Ph4) and p-quinquephenyl (Ph5), is achieved on Cu(111) by externally introduced bromine atoms. Scanning tunneling microscopy/spectroscopy experiments reveal that the formed molecular assembly structure at a stoichiometric ratio of 4:1 for Br to Ph4 or 5:1 for Br to Ph5 can efficiently promote the reactive collision probability to trigger the trans-coupling reaction at the meta-C-H site between two neighboring Ph4 or Ph5 molecules, leading to an increase in the coupling selectivity. Such Br atoms can also affect the electronic structure and adsorption stability of the reacting molecules. It is conceptually demonstrated that externally introduced halogen atoms, which can provide an adjustable halogen-to-precursor stoichiometry, can be employed to efficiently steer on-surface reactions.
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Potassium (K) cations are spontaneously formed upon thermal deposition of low-coverage K onto an ultrathin CuO monolayer grown on Cu(110) and they were explored by low-temperature scanning tunneling microscopy (STM) and X-ray photoemission spectroscopy. The formed K cations are highly immobile and thermally stable. The local work function around an individual K cation decreases by 1.5±0.3â eV, and a charging zone underneath it is established within about 1.0â nm. The cationic and neutral states of the K atom are switchable upon application of an STM bias voltage pulse, which is simultaneously accompanied by an adsorption site relocation.
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The adsorption and assembly of sub-monolayered bowl-shaped corannulene (COR) on Cu(111) and Ag(111) are investigated by scanning tunneling microscopy (STM). Three COR configurations, namely, up, down, and tilted ones, are formed on Cu(111), as unraveled by high-resolution STM images. It is also experimentally revealed that monodispersed, hexagonal, and evenly spaced stripe patterns develop on both Cu(111) and Ag(111). A quantitative evaluation of the long-range intermolecular interaction on Cu(111) mediated by electrostatic repulsion and surface-state mediation is presented. At 0.05 monolayer (ML), the long-range monodispersed pattern is mainly induced by electrostatic interaction. At 0.24 and 0.47 ML, however, surface-state mediation plays a dominant role, and the electrostatic interaction is leveled due to the identical static environment for each molecule.
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MAIN CONCLUSION: In wheat, a QTL QTrl.saw-2D.2 associated with the total root length was identified, presumably containing genes closely related to root development. A mapping population of 184 recombinant inbred lines derived from the cross SY95-71 × CH7034 was used to map QTL for seedling root characteristics in hydroponic culture (HC) and in soil-filled pot (SP) methods. Four traits, including maximum root length (MRL), root number (RN), total length (TRL), and root diameter (RD) were measured and used in QTL analyses. A total of 33 QTL for the four root traits were detected, 17 QTLs for TRL, six for RN, seven for MRL, and three for RD. Seven QTL were detected in both HC and SP methods, which explained 7-18% phenotypic variation. One QTL QTrl.saw-2D.2 detected in both HC and SP methods was also validated in another population comprised of 215 diverse lines. This QTL is a novel QTL that explained the highest phenotypic variation 18% in all QTL identified in the present study. Based on candidate gene and comparative genomics analyses, the QTL QTrl.saw-2D.2 may contain genes closely related to root development in wheat (Triticum aestivum L.). The two candidate genes were proposed to explore in future studies.
Asunto(s)
Sitios de Carácter Cuantitativo/genética , Triticum/genética , Mapeo Cromosómico , Sequías , Ligamiento Genético , Estudio de Asociación del Genoma Completo , Fenotipo , Raíces de Plantas/genética , Raíces de Plantas/crecimiento & desarrollo , Raíces de Plantas/fisiología , Plantones/genética , Plantones/crecimiento & desarrollo , Plantones/fisiología , Triticum/crecimiento & desarrollo , Triticum/fisiologíaRESUMEN
Drought stress is one of the most important abiotic factors limiting crop productivity. A better understanding of the effects of drought on millet (Setaria italica L.) production, a model crop for studying drought tolerance, and the underlying molecular mechanisms responsible for drought stress responses is vital to improvement of agricultural production. In this study, we exposed the drought resistant F1 hybrid, M79, and its parental lines E1 and H1 to drought stress. Subsequent physiological analysis demonstrated that M79 showed higher photosynthetic energy conversion efficiency and drought tolerance than its parents. A transcriptomic study using leaves collected six days after drought treatment, when the soil water content was about â¼20%, identified 3066, 1895, and 2148 differentially expressed genes (DEGs) in M79, E1 and H1 compared to the respective untreated controls, respectively. Further analysis revealed 17 Gene Ontology (GO) enrichments and 14 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in M79, including photosystem II (PSII) oxygen-evolving complex, peroxidase (POD) activity, plant hormone signal transduction, and chlorophyll biosynthesis. Co-regulation analysis suggested that these DEGs in M79 contributed to the formation of a regulatory network involving multiple biological processes and pathways including photosynthesis, signal transduction, transcriptional regulation, redox regulation, hormonal signaling, and osmotic regulation. RNA-seq analysis also showed that some photosynthesis-related DEGs were highly expressed in M79 compared to its parental lines under drought stress. These results indicate that various molecular pathways, including photosynthesis, respond to drought stress in M79, and provide abundant molecular information for further analysis of the underlying mechanism responding to this stress.
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F-box protein is an important subunit of SCF complex, an E3 ligase in ubiquitin system, and its function is determined through mediating the specific recognition and combining with substrate protein. TaFRA (F-box protein related to abiotic stress) was identified by RACE based on the fragments diferently expressing in wheat seedling exposed to salt stress and encodes an F-box protein. In this study, pBD-TaFRA bait expression vector was constructed, and cDNA+pGAD+pBD was directly co-transformed into yeast hybrid system to screen condidate proteins interacting with TaFRA. Fourty-four candidate proteins were obtained, in which 32 were known proteins and transcript factors related to stress tolerance such as thioredoxin, metallothinein, ATP synthase, and serine/threonine protein kinase etc. This indicates that TaFRA participates in stress response through regulating above condidate genes, which will provide basis for revealing the mechanism of TaFRA reaction to abiotic stress.