Xinjiang Agricultural University

Nuclear factor Y (NF-Y) is a ubiquitous transcription factor composed of three distinct subunits (NF-YA, NF-YB, and NF-YC). We found that the Arabidopsis thaliana NFYA5 transcript is strongly induced by drought stress in an abscisic acid (ABA)-dependent manner. Promoter:beta-glucuronidase analyses showed that NFYA5 was highly expressed in vascular tissues and guard cells and that part of the induction by drought was transcriptional. NFYA5 contains a target site for miR169, which targets mRNAs for cleavage or translational repression. We found that miR169 was downregulated by drought stress through an ABA-dependent pathway. Analysis of the expression of miR169 precursors showed that miR169a and miR169c were substantially downregulated by drought stress. Coexpression of miR169 and NFYA5 suggested that miR169a was more efficient than miR169c at repressing the NFYA5 mRNA level. nfya5 knockout plants and plants overexpressing miR169a showed enhanced leaf water loss and were more sensitive to drought stress than wild-type plants. By contrast, transgenic Arabidopsis plants overexpressing NFYA5 displayed reduced leaf water loss and were more resistant to drought stress than the wild type. Microarray analysis indicated that NFYA5 is crucial for the expression of a number of drought stress-responsive genes. Thus, NFYA5 is important for drought resistance, and its induction by drought stress occurs at both the transcriptional and posttranscriptional levels.

Phenolic compounds arise from the shikimic and acetic acid (polyketide) metabolic pathways in plants. They are but one category of the many secondary metabolites implicated in plant allelopathy. Phenolic allelochemicals have been observed in both natural and managed ecosystems, where they cause a number of ecological and economic problems, such as declines in crop yield due to soil sickness, regeneration failure of natural forests, and replanting problems in orchards. Phenolic allelochemical structures and modes of action are diverse and may offer potential lead compounds for the development of future herbicides or pesticides. This article reviews allelopathic effects, analysis methods, and allelopathic mechanisms underlying the activity of plant phenolic compounds. Additionally, the currently debated topic in plant allelopathy of whether catechin and 8-hydroxyquinoline play an important role in Centaurea maculata and Centaurea diffusa invasion success is discussed. Overall, the main purpose of this review is to highlight the allelopacthic potential of phenolic compounds to provide us with methods to solve various ecology problems, especially in regard to the sustainable development of agriculture, forestry, nature resources and environment conservation.

Despite evidence from experimental grasslands that plant diversity increases biomass production and soil organic carbon (SOC) storage, it remains unclear whether this is true in natural ecosystems, especially under climatic variations and human disturbances. Based on field observations from 6,098 forest, shrubland, and grassland sites across China and predictions from an integrative model combining multiple theories, we systematically examined the direct effects of climate, soils, and human impacts on SOC storage versus the indirect effects mediated by species richness (SR), aboveground net primary productivity (ANPP), and belowground biomass (BB). We found that favorable climates (high temperature and precipitation) had a consistent negative effect on SOC storage in forests and shrublands, but not in grasslands. Climate favorability, particularly high precipitation, was associated with both higher SR and higher BB, which had consistent positive effects on SOC storage, thus offsetting the direct negative effect of favorable climate on SOC. The indirect effects of climate on SOC storage depended on the relationships of SR with ANPP and BB, which were consistently positive in all biome types. In addition, human disturbance and soil pH had both direct and indirect effects on SOC storage, with the indirect effects mediated by changes in SR, ANPP, and BB. High soil pH had a consistently negative effect on SOC storage. Our findings have important implications for improving global carbon cycling models and ecosystem management: Maintaining high levels of diversity can enhance soil carbon sequestration and help sustain the benefits of plant diversity and productivity.

Human selection has reshaped crop genomes. Here we report an apple genome variation map generated through genome sequencing of 117 diverse accessions. A comprehensive model of apple speciation and domestication along the Silk Road is proposed based on evidence from diverse genomic analyses. Cultivated apples likely originate from Malus sieversii in Kazakhstan, followed by intensive introgressions from M. sylvestris. M. sieversii in Xinjiang of China turns out to be an "ancient" isolated ecotype not directly contributing to apple domestication. We have identified selective sweeps underlying quantitative trait loci/genes of important fruit quality traits including fruit texture and flavor, and provide evidences supporting a model of apple fruit size evolution comprising two major events with one occurring prior to domestication and the other during domestication. This study outlines the genetic basis of apple domestication and evolution, and provides valuable information for facilitating marker-assisted breeding and apple improvement.Apple is one of the most important fruit crops. Here, the authors perform deep genome resequencing of 117 diverse accessions and reveal comprehensive models of apple origin, speciation, domestication, and fruit size evolution as well as candidate genes associated with important agronomic traits.

Abstract Increasing the power conversion efficiency (PCE) of the two‐dimensional (2D) perovskite‐based solar cells (PVSCs) is really a challenge. Vertical orientation of the 2D perovskite film is an efficient strategy to elevate the PCE. In this work, vertically orientated highly crystalline 2D (PEA) 2 (MA) n–1 Pb n I 3n+1 (PEA= phenylethylammonium, MA = methylammonium, n = 3, 4, 5) films are fabricated with the assistance of an ammonium thiocyanate (NH 4 SCN) additive by a one‐step spin‐coating method. Planar‐structured PVSCs with the device structure of indium tin oxide (ITO)/poly(3,4‐ethylenedioxythiophene):poly(styrenesulfonate)/(PEA) 2 (MA) n–1 Pb n I 3n+1 /[6,6]‐phenyl‐C61‐butyric acid methyl ester/bahocuproine/Ag are fabricated. The PCE of the PVSCs is boosted from the original 0.56% (without NH 4 SCN) to 11.01% with the optimized NH 4 SCN addition at n = 5, which is among the highest PCE values for the low‐ n ( n < 10) 2D perovskite‐based PVSCs. The improved performance is attributed to the vertically orientated highly crystalline 2D perovskite thin films as well as the balanced electron/hole transportation. The humidity stability of this oriented 2D perovskite thin film is also confirmed by the almost unchanged X‐ray diffraction patterns after 28 d exposed to the moisture in a humidity‐controlled cabinet ( H r = 55 ± 5%). The unsealed device retains 78.5% of its original PCE after 160 h storage in air atmosphere with humidity of 55 ± 5%. The results provide an effective approach toward a highly efficient and stable PVSC for future commercialization.

Brassicaceae is one of the most diverse and economically valuable angiosperm families with widely cultivated vegetable crops and scientifically important model plants, such as Arabidopsis thaliana. The evolutionary history, ecological, morphological, and genetic diversity, and abundant resources and knowledge of Brassicaceae make it an excellent model family for evolutionary studies. Recent phylogenetic analyses of the family revealed three major lineages (I, II, and III), but relationships among and within these lineages remain largely unclear. Here, we present a highly supported phylogeny with six major clades using nuclear markers from newly sequenced transcriptomes of 32 Brassicaceae species and large data sets from additional taxa for a total of 55 species spanning 29 out of 51 tribes. Clade A consisting of Lineage I and Macropodium nivale is sister to combined Clade B (with Lineage II and others) and a new Clade C. The ABC clade is sister to Clade D with species previously weakly associated with Lineage II and Clade E (Lineage III) is sister to the ABCD clade. Clade F (the tribe Aethionemeae) is sister to the remainder of the entire family. Molecular clock estimation reveals an early radiation of major clades near or shortly after the Eocene-Oligocene boundary and subsequent nested divergences of several tribes of the previously polytomous Expanded Lineage II. Reconstruction of ancestral morphological states during the Brassicaceae evolution indicates prevalent parallel (convergent) evolution of several traits over deep times across the entire family. These results form a foundation for future evolutionary analyses of structures and functions across Brassicaceae.

Plastic pollution is a global concern given its prevalence in aquatic and terrestrial ecosystems. Studies have been conducted on the distribution and impact of plastic pollution in marine ecosystems, but little is known on terrestrial ecosystems. Plastic mulch has been widely used to increase crop yields worldwide, yet the impact of plastic residues in cropland soils to soil health and crop production in the long term remained unclear. In this paper, using a global meta-analysis, we found that the use of plastic mulch can indeed increase crop yields on average by 25%-42% in the immediate season due to the increase of soil temperature (+8%) and moisture (+17%). However, the unabated accumulation of film residues in the field negatively impacts its physicochemical properties linked to healthy soil and threatens food production in the long term. It has multiple negative impacts on plant growth including crop yield (at the mean rate of -3% for every additional 100 kg/ha of film residue), plant height (-2%) and root weight (-5%), and soil properties including soil water evaporation capacity (-2%), soil water infiltration rate (-8%), soil organic matter (-0.8%) and soil available phosphorus (-5%) based on meta-regression. Using a nationwide field survey of China, the largest user of plastic mulch worldwide, we found that plastic residue accumulation in cropland soils has reached 550,800 tonnes, with an estimated 6%-10% reduction in cotton yield in some polluted sites based on current level of plastic residue content. Immediate actions should be taken to ensure the recovery of plastic film mulch and limit further increase in film residue loading to maintain the sustainability of these croplands.

Effective utilization of wild relatives is key to overcoming challenges in genetic improvement of cultivated tomato, which has a narrow genetic basis; however, current efforts to decipher high-quality genomes for tomato wild species are insufficient. Here, we report chromosome-scale tomato genomes from nine wild species and two cultivated accessions, representative of Solanum section Lycopersicon, the tomato clade. Together with two previously released genomes, we elucidate the phylogeny of Lycopersicon and construct a section-wide gene repertoire. We reveal the landscape of structural variants and provide entry to the genomic diversity among tomato wild relatives, enabling the discovery of a wild tomato gene with the potential to increase yields of modern cultivated tomatoes. Construction of a graph-based genome enables structural-variant-based genome-wide association studies, identifying numerous signals associated with tomato flavor-related traits and fruit metabolites. The tomato super-pangenome resources will expedite biological studies and breeding of this globally important crop.

Crop yields need to be improved in a sustainable manner to meet the expected worldwide increase in population over the coming decades as well as the effects of anticipated climate change. Recently, genomics-assisted breeding has become a popular approach to food security; in this regard, the crop breeding community must better link the relationships between the phenotype and the genotype. While high-throughput genotyping is feasible at a low cost, high-throughput crop phenotyping methods and data analytical capacities need to be improved.

Vertically oriented highly crystalline 2D layered (BA) 2 (MA) n −1 Pb n I 3 n +1 (BA = CH 3 (CH 2 ) 3 NH 3 , MA = CH 3 NH 3 , n = 3, 4) perovskite thin‐films are fabricated with the aid of ammonium thiocyanate (NH 4 SCN) additive through one‐step spin‐coating process. The humidity‐stability of the film is certified by the almost unchanged X‐ray diffraction patterns after exposed to humid atmosphere ( H r = 55 ± 5%) for 40 d. The photovoltaic devices with the structure of indium tin oxide(ITO)/poly(3,4‐ethylenedioxythiophene):poly(styrene‐sulfonate)/(BA) 2 (MA) n −1 Pb n I 3 n +1 ( n = 3,4)/[6,6]‐phenyl‐C 61 ‐butyric acid methyl ester/Bathocuproine/Ag are fabricated. The devices based on (BA) 2 (MA) 2 Pb 3 I 10 perovskite ( n = 3) with the precursor composition of BAI:methylammonium iodide:PbI 2 :NH 4 SCN = 2:2:3:1 (by molar ratio) show an averaged power conversion efficiency (PCE) of 6.82%. In the case of (BA) 2 (MA) 3 Pb 4 I 13 ( n = 4), a higher PCE of 8.79% is achieved. Both of the unsealed devices perform unique stability with almost unchanged PCE during the period of storage in purified N 2 glove box. This work provides a simple and effective method to enhance the efficiency of the 2D perovskite solar cell.

BACKGROUND: Identification of loci for grain yield (GY) and related traits, and dissection of the genetic architecture are important for yield improvement through marker-assisted selection (MAS). Two genome-wide association study (GWAS) methods were used on a diverse panel of 166 elite wheat varieties from the Yellow and Huai River Valleys Wheat Zone (YHRVWD) of China to detect stable loci and analyze relationships among GY and related traits. RESULTS: A total of 326,570 single nucleotide polymorphism (SNP) markers from the wheat 90 K and 660 K SNP arrays were chosen for GWAS of GY and related traits, generating a physical distance of 14,064.8 Mb. One hundred and twenty common loci were detected using SNP-GWAS and Haplotype-GWAS, among which two were potentially functional genes underpinning kernel weight and plant height (PH), eight were at similar locations to the quantitative trait loci (QTL) identified in recombinant inbred line (RIL) populations in a previous study, and 78 were potentially new. Twelve pleiotropic loci were detected on eight chromosomes; among these the interval 714.4-725.8 Mb on chromosome 3A was significantly associated with GY, kernel number per spike (KNS), kernel width (KW), spike dry weight (SDW), PH, uppermost internode length (UIL), and flag leaf length (FLL). GY shared five loci with thousand kernel weight (TKW) and PH, indicating significantly affected by two traits. Compared with the total number of loci for each trait in the diverse panel, the average number of alleles for increasing phenotypic values of GY, TKW, kernel length (KL), KW, and flag leaf width (FLW) were higher, whereas the numbers for PH, UIL and FLL were lower. There were significant additive effects for each trait when favorable alleles were combined. UIL and FLL can be directly used for selecting high-yielding varieties, whereas FLW can be used to select spike number per unit area (SN) and KNS. CONCLUSIONS: The loci and significant SNP markers identified in the present study can be used for pyramiding favorable alleles in developing high-yielding varieties. Our study proved that both GWAS methods and high-density genetic markers are reliable means of identifying loci for GY and related traits, and provided new insight to the genetic architecture of GY.

Fault diagnosis technology is key to the safe and stable operation of wind turbines. An effective fault diagnosis technology for wind turbines can quickly identify fault types to reduce the operation and maintenance costs of wind farms and improve power generation efficiency. Currently, most wind farms obtain operation and maintenance data via supervisory control and data acquisition (SCADA) systems, which contain rich information related to the operation characteristics of wind turbines. However, few SCADA systems provide fault diagnosis functionality. Support vector machines (SVMs) are a popular intelligence method in the fault diagnosis of wind turbines. SVM parameter selection is key for accurate model classification. The sparrow search algorithm (SSA) is a novel and highly efficient optimization method used to optimize the penalty factor and kernel function parameter of SVM in this paper and to construct the SSA-SVM wind turbine fault diagnosis model. Data are acquired from a wind farm SCADA system and form a faulting set after preprocessing and feature selection. Experiments show that the SSA-SVM diagnostic model effectively improves the accuracy of wind turbine fault diagnosis compared with the GS-SVM, GA-SVM and PSO-SVM models and has fast convergence speed and strong optimization ability. Moreover, the SSA-SVM diagnostic model can be used to diagnose faults in practical engineering applications.

In this study, a series of nanofibrous membranes were prepared from cellulose acetate (CA) and polyester urethane (PEU) using coelectrospinning or blend-electrospinning. The drug release, in vitro antimicrobial activity and in vivo wound healing performance of the nanofiber membranes were evaluated for use as wound dressings. To prevent common clinical infections, an antimicrobial agent, polyhexamethylene biguanide (PHMB) was incorporated into the electrospun fibers. The presence of CA in the nanofiber membrane improved its hydrophilicity and permeability to air and moisture. CA fibers became slightly swollen upon contacting with liquid phase. CA not only increased the liquid uptake but also created a moist environment for the wound, which accelerated wound recovery. PHMB release dynamics of the membranes was controlled by the structure and component ratios of the membranes. The lower ratio of CA: PEU helped to preserve the physical and thermal properties of the membranes, and also reduced the burst release effectively and slowed down diffusion of PHMB during in vitro tests. The controlled-diffusion membranes exerted long-term antimicrobial effect for wound healing.

Abstract In the context of the outbreak of the COVID‐19 pandemic and China's “digital power” strategy, the realization of a green shift of manufacturing has become a necessary condition to promote the economy, and the digital factor has increasingly become a new driving force. The DEA‐Malmquist index and entropy method were used to measure the manufacturing green total factor productivity (GTFP) and the level of digital economy level from 2011 to 2018, respectively. This study then explored the impact of digital economy on manufacturing GTFP based on the system generalized method of moments (GMM) model, as well as the adjustment effects of talent aggregation and financial scale according to the moderating model. This research came to four conclusions. (1) The digital economy can significantly improve the manufacturing GTFP of China, and the influence shows the characteristic of a “marginal increase”; (2) notably, the perspective of manufacturing GTFP decomposition indicates that the digital economy exerts a significant positive effect on manufacturing technical efficiency during the current period but obviously hinders technical progress; (3) interestingly, a mechanistic test showed that the two dimensions of innovation environment—talent aggregation (0.385) and financial scale (0.359)—play critical moderating roles in the influencing process; and (4) the influence has evident regional heterogeneity—it is significantly positive in the east and negative in the central region and west. Finally, corresponding policy suggestions are suggested.

The rapid, recent development of image recognition technologies has led to the widespread use of convolutional neural networks (CNNs) in automated image classification and in the recognition of plant diseases. Aims: The aim of the present study was to develop a deep CNNs to identify tea plant disease types from leaf images. Materials: A CNNs model named LeafNet was developed with different sized feature extractor filters that automatically extract the features of tea plant diseases from images. DSIFT (dense scale-invariant feature transform) features are also extracted and used to construct a bag of visual words (BOVW) model that is then used to classify diseases via support vector machine(SVM) and multi-layer perceptron(MLP) classifiers. The performance of the three classifiers in disease recognition were then individually evaluated. Results: The LeafNet algorithm identified tea leaf diseases most accurately, with an average classification accuracy of 90.16%, while that of the SVM algorithm was 60.62% and that of the MLP algorithm was 70.77%. Conclusions: The LeafNet was clearly superior in the recognition of tea leaf diseases compared to the MLP and SVM algorithms. Consequently, the LeafNet can be used in future applications to improve the efficiency and accuracy of disease diagnoses in tea plants.

In this work, nanofibre membranes have been produced from polyvinyl alcohol (PVA), polycaprolactone (PCL), polyacrylonitrile (PAN), poly (vinylidene fluoride-co-hexafluoropropene) (PVdF-HFP), and polymer blend of PAN and polyurethane (PEU) using an electrospinning technique, and wound healing performance of the as-spun nanofibre membranes was examined in vivo using female Sprague-Dawley rats. To understand the nutrition effect, a wool protein was coated on PVA and PCL nanofibres and incorporated into PVA nanofibres via coelectrospinning of a PVA solution containing the wool protein. Silver nanoparticles were also applied to PVA nanofibres to improve antibacterial activity. It was found that the wound healing performance is mainly influenced by the porosity, air permeability, and surface wettability of the nanofibre membranes. A nanofibre membrane with good hydrophilicity and high porosity considerably facilitates the healing of wound especially at the early healing stage. However, the fiber diameter and antibacterial activity have little effect on the wound healing efficiency. As pores in nanofibre membranes are typically smaller than that of conventional cotton gauze, the nanofibre membrane should be able to decontaminate and prevent exogenous infections via sieve effect. This work provides basic understanding of material structure-property relationship for further design of efficient nanofibre-based wound dressing materials.

Hydrogen sulfide (H2S) is an important gaseous molecule in various plant developmental processes and plant stress responses. In this study, the transgenic Arabidopsis thaliana plants with modulated expressions of two cysteine desulfhydrases, and exogenous H2S donor (sodium hydrosulfide, NaHS) and H2S scavenger (hypotaurine, HT) pre-treated plants were used to dissect the involvement of H2S in plant stress responses. The cysteine desulfhydrases overexpressing plants and NaHS pre-treated plants exhibited higher endogenous H2S level and improved abiotic stress tolerance and biotic stress resistance, while cysteine desulfhydrases knockdown plants and HT pre-treated plants displayed lower endogenous H2S level and decreased stress resistance. Moreover, H2S upregulated the transcripts of multiple abiotic and biotic stress-related genes, and inhibited reactive oxygen species (ROS) accumulation. Interestingly, MIR393-mediated auxin signaling including MIR393a/b and their target genes (TIR1, AFB1, AFB2, and AFB3) was transcriptionally regulated by H2S, and was related with H2S-induced antibacterial resistance. Moreover, H2S regulated 50 carbon metabolites including amino acids, organic acids, sugars, sugar alcohols, and aromatic amines. Taken together, these results indicated that cysteine desulfhydrase and H2S conferred abiotic stress tolerance and biotic stress resistance, via affecting the stress-related gene expressions, ROS metabolism, metabolic homeostasis, and MIR393-targeted auxin receptors.

BACKGROUND: In rice, the GW2 gene, found on chromosome 2, controls grain width and weight. Two homologs of this gene, ZmGW2-CHR4 and ZmGW2-CHR5, have been found in maize. In this study, we investigated the relationship, evolutionary fate and putative function of these two maize genes. RESULTS: The two genes are located on duplicated maize chromosomal regions that show co-orthologous relationships with the rice region containing GW2. ZmGW2-CHR5 is more closely related to the sorghum counterpart than to ZmGW2-CHR4. Sequence comparisons between the two genes in eight diverse maize inbred lines revealed that the functional protein domain of both genes is completely conserved, with no non-synonymous polymorphisms identified. This suggests that both genes may have conserved functions, a hypothesis that was further confirmed through linkage, association, and expression analyses. Linkage analysis showed that ZmGW2-CHR4 is located within a consistent quantitative trait locus (QTL) for one-hundred kernel weight (HKW). Association analysis with a diverse panel of 121 maize inbred lines identified one single nucleotide polymorphism (SNP) in the promoter region of ZmGW2-CHR4 that was significantly associated with kernel width (KW) and HKW across all three field experiments examined in this study. SNPs or insertion/deletion polymorphisms (InDels) in other regions of ZmGW2-CHR4 and ZmGW2-CHR5 were also found to be significantly associated with at least one of the four yield-related traits (kernel length (KL), kernel thickness (KT), KW and HKW). None of the polymorphisms in either maize gene are similar to each other or to the 1 bp InDel causing phenotypic variation in rice. Expression levels of both maize genes vary over ear and kernel developmental stages, and the expression level of ZmGW2-CHR4 is significantly negatively correlated with KW. CONCLUSIONS: The sequence, linkage, association and expression analyses collectively showed that the two maize genes represent chromosomal duplicates, both of which function to control some of the phenotypic variation for kernel size and weight in maize, as does their counterpart in rice. However, the different polymorphisms identified in the two maize genes and in the rice gene indicate that they may cause phenotypic variation through different mechanisms.

Lumpy skin disease (LSD) is a viral disease of cattle caused by LSD virus (LSDV). This disease poses a significant threat to stockbreeding and is listed as one of bovine notifiable diseases by OIE. Before 2019, LSD has not been reported in China. The first LSD outbreak was determined in China on August 3, 2019. Since then, a total of 7 LSD outbreaks have been reported in other 6 provinces in China, infecting 91 and killing 7 cattle. As of now, LSDV was detected in western and eastern China and also in Taiwan Island outside Mainland China. LSD is undoubtedly an emerging threat to the cattle industry in China.

Detection of senescence’s dynamics in crop breeding is time consuming and needs considerable details regarding its rate of progression and intensity. Normalized difference red-edge index (NDREI) along with four other spectral vegetative indices (SVIs) derived from unmanned aerial vehicle (UAV) based spatial imagery, were evaluated for rapid and accurate prediction of senescence. For this, 32 selected winter wheat genotypes were planted under full and limited irrigation treatments. Significant variations for all five SVIs: green normalize difference vegetation index (GNDVI), simple ratio (SR), green chlorophyll index (GCI), red-edge chlorophyll index (RECI), and normalized difference red-edge index (NDREI) among genotypes and between treatments, were observed from heading to late grain filling stages. The SVIs showed strong relationship (R2 = 0.69 to 0.78) with handheld measurements of chlorophyll and leaf area index (LAI), while negatively correlated (R2 = 0.75 to 0.77) with canopy temperature (CT) across the treatments. NDREI as a new SVI showed higher correlations with ground data under both treatments, similarly as exhibited by other four SVIs. There were medium to strong correlations (r = 0.23–0.63) among SVIs, thousand grain weight (TGW) and grain yield (GY) under both treatments. Senescence rate was calculated by decreasing values of SVIs from their peak values at heading stage, while variance for senescence rate among genotypes and between treatments could be explained by SVIs variations. Under limited irrigation, 10% to 15% higher senescence rate was detected as compared with full irrigation. Principle component analysis corroborated the negative association of high senescence rate with TGW and GY. Some genotypes, such as Beijing 0045, Nongda 5181, and Zhongmai 175, were selected with low senescence rate, stable TGW and GY in both full and limited irrigation treatments, nearly in accordance with the actual performance of these cultivars in field. Thus, SVIs derived from UAV appeared as a promising tool for rapid and precise estimation of senescence rate at maturation stages.