Apple replant disease(ARD)has led to severe yield and quality reduction in the apple industry.Fusarium solani(F.solani)has been identified as one of the main microbial pathogens responsible for ARD.Auxin(indole-3-acet...Apple replant disease(ARD)has led to severe yield and quality reduction in the apple industry.Fusarium solani(F.solani)has been identified as one of the main microbial pathogens responsible for ARD.Auxin(indole-3-acetic acid,IAA),an endogenous hormone in plants,is involved in almost all plant growth and development processes and plays a role in plant immunity against pathogens.Gretchen Hagen3(GH3)is one of the early/primary auxin response genes.The aim of this study was to evaluate the function of MdGH3-2 and MdGH3-12 in the defense response of F.solani by treating MdGH3-2/12 RNAi plants with F.solani.The results show that under F.solani infection,RNAi of MdGH3-2/12 inhibited plant biomass accumulation and exacerbated root damage.After inoculation with F.solani,MdGH3-2/12 RNAi inhibited the biosynthesis of acid-amido synthetase.This led to the inhibition of free IAA combining with amino acids,resulting in excessive free IAA accumulation.This excessive free IAA altered plant tissue structure,accelerated fungal hyphal invasion,reduced the activity of antioxidant enzymes(SOD,POD and CAT),increased the reactive oxygen species(ROS)level,and reduced total chlorophyll content and photosynthetic ability,while regulating the expression of PR-related genes including PR1,PR4,PR5 and PR8.It also changed the contents of plant hormones and amino acids,and ultimately reduced the resistance to F.solani.In conclusion,these results demonstrate that MdGH3-2 and MdGH3-12 play an important role in apple tolerance to F.solani and ARD.展开更多
Apple leaf spot,caused by the Alternaria alternata apple pathotype(AAAP),is an important fungal disease of apple.To understand the molecular basis of resistance and pathogenesis in apple leaf spot,the transcriptomes o...Apple leaf spot,caused by the Alternaria alternata apple pathotype(AAAP),is an important fungal disease of apple.To understand the molecular basis of resistance and pathogenesis in apple leaf spot,the transcriptomes of two apple cultivars‘Hanfu'(HF)(resistant)and‘Golden Delicious'(GD)(susceptible)were analyzed at 0,6,18,24 and 48 h after AAAP inoculation by RNA-Seq.At each time point,a large number of significantly differentially expressed genes(DEGs)were screened between AAAP-inoculated and uninoculated apple leaves.Analysis of the common DEGs at four time points revealed significant differences in the resistance of‘HF'and‘GD'apple to AAAP infection.RLP,RNL,and JA signal-related genes were upregulated in both cultivars to restrict AAAP development.However,genes encoding CNLs,TNLs,WRKYs,and AP2s were only activated in‘HF'as part of the resistance response,of which,some play major roles in the regulation of ET and SA signal transduction.Further analysis showed that many DEGs with opposite expression trends in the two hosts may play important regulatory roles in response to AAAP infection.Transient expression of one such gene MdERF110 in‘GD'apple leaves improved AAAP resistance.Collectively,this study highlights the reasons for differential resistance to AAAP infection between‘HF'and‘GD'apples which can theoretically assist the molecular breeding of disease-resistant apple crops.展开更多
Apple replant disease(ARD)negatively affects plant growth and reduces yields in replanted orchards.In this study,biochar was applied to apple replant soil with Fusarium oxysporum.Our aim was to investigate whether bio...Apple replant disease(ARD)negatively affects plant growth and reduces yields in replanted orchards.In this study,biochar was applied to apple replant soil with Fusarium oxysporum.Our aim was to investigate whether biochar could promote plant growth and alleviate apple replant disease by reducing the growth of harmful soil microorganisms,changing soil microbial community structure and improving the soil environment.This experiment included five treatments:apple replant soil(CK),methyl bromide fumigation apple replant soil(FM),replant soil with biochar addition(2%),replant soil with F.oxysporum spore solution(8×10^(7)spores·mL^(-1)),and replant soil with biochar and F.oxysporum spore solution addition.Seedling biomass,the activity of antioxidant enzymes in the leaves and roots,and soil environmental variables were measured.Microbial community composition and community structure were analyzed using 16SrDNA and ITS2 gene sequencing.Biochar significantly reduced the abundance of F.oxysporum and increased soil microbial diversity and richness.Biochar also increased the soil enzyme activities(urease,invertase,neutral phosphatase,and catalase),the biomass(plant height,fresh weight,dry weight)and the activity of antioxidant enzymes(superoxide dismutase,peroxidase,and catalase).The root indexes of apple seedlings was also increased in replant soil by biochar.In sum,biochar promoted the growth of plants,improved the replant soil environment,and alleviated apple replant disease.展开更多
Accurate diagnosis of apple leaf diseases is crucial for improving the quality of apple production and promoting the development of the apple industry. However, apple leaf diseases do not differ significantly from ima...Accurate diagnosis of apple leaf diseases is crucial for improving the quality of apple production and promoting the development of the apple industry. However, apple leaf diseases do not differ significantly from image texture and structural information. The difficulties in disease feature extraction in complex backgrounds slow the related research progress. To address the problems, this paper proposes an improved multi-scale inverse bottleneck residual network model based on a triplet parallel attention mechanism, which is built upon ResNet-50, while improving and combining the inception module and ResNext inverse bottleneck blocks, to recognize seven types of apple leaf(including six diseases of alternaria leaf spot, brown spot, grey spot, mosaic, rust, scab, and one healthy). First, the 3×3 convolutions in some of the residual modules are replaced by multi-scale residual convolutions, the convolution kernels of different sizes contained in each branch of the multi-scale convolution are applied to extract feature maps of different sizes, and the outputs of these branches are multi-scale fused by summing to enrich the output features of the images. Second, the global layer-wise dynamic coordinated inverse bottleneck structure is used to reduce the network feature loss. The inverse bottleneck structure makes the image information less lossy when transforming from different dimensional feature spaces. The fusion of multi-scale and layer-wise dynamic coordinated inverse bottlenecks makes the model effectively balances computational efficiency and feature representation capability, and more robust with a combination of horizontal and vertical features in the fine identification of apple leaf diseases. Finally, after each improved module, a triplet parallel attention module is integrated with cross-dimensional interactions among channels through rotations and residual transformations, which improves the parallel search efficiency of important features and the recognition rate of the network with relatively small computational costs while the dimensional dependencies are improved. To verify the validity of the model in this paper, we uniformly enhance apple leaf disease images screened from the public data sets of Plant Village, Baidu Flying Paddle, and the Internet. The final processed image count is 14,000. The ablation study, pre-processing comparison, and method comparison are conducted on the processed datasets. The experimental results demonstrate that the proposed method reaches 98.73% accuracy on the adopted datasets, which is 1.82% higher than the classical ResNet-50 model, and 0.29% better than the apple leaf disease datasets before preprocessing. It also achieves competitive results in apple leaf disease identification compared to some state-ofthe-art methods.展开更多
林木腐烂病是苹果树、梨树和杨树等林木枝干的重要真菌性病害。为了筛选出对苹果树腐烂病菌Valsa mali var.mali、梨树腐烂病菌V.mali var.pyri和杨树腐烂病菌V.sordida等3种不同寄主腐烂病菌都能有效防控的杀菌剂,本研究开展室内毒力...林木腐烂病是苹果树、梨树和杨树等林木枝干的重要真菌性病害。为了筛选出对苹果树腐烂病菌Valsa mali var.mali、梨树腐烂病菌V.mali var.pyri和杨树腐烂病菌V.sordida等3种不同寄主腐烂病菌都能有效防控的杀菌剂,本研究开展室内毒力试验比较了7种杀菌剂对3种腐烂病病原菌菌丝生长和分生孢子萌发的抑制效果,并进一步通过田间活性测定试验比较7种杀菌剂对梨树腐烂病病斑扩展和分生孢子发生的防治效果,同时测定了增效剂8.6%聚乙二醇(PEG)对7种杀菌剂的增效作用。毒力测定结果表明,苯醚甲环唑、戊唑醇、吡唑醚菌酯和丙唑·多菌灵对3种腐烂病病原菌菌丝生长和分生孢子萌发的抑制作用较强,其中EC_(50)平均值最低的是苯醚甲环唑,而戊唑醇的MIC平均值最低,在0.33 mg/L浓度下对3种腐烂病病原菌的菌丝生长和分生孢子萌发抑制率均达到100%。田间试验结果表明,45%苯醚甲环唑SC、43%戊唑醇SC和35%丙唑·多菌灵SE对梨树腐烂病病斑扩展和分生孢子萌发的防治效果突出,其中45%苯醚甲环唑SC 30.00 mg/L对病斑扩展防治效果达到82.23%,孢子萌发抑制效果达到85.96%,田间防治效果最好。10%丙硫唑SC+8.6%PEG处理组对病斑扩展防治效果提高了15.39百分点,达到73.46%,分生孢子萌发抑制率提高了23.75百分点,达到83.06%,增效作用显著。本研究为苹果树、梨树和杨树等3种寄主腐烂病的化学防控提供了科学依据。展开更多
基金supported by the Earmarked Fund for the China Agriculture Research System(CARS-27)the Key Science and Technology Special Projects of Shaanxi Province,China(2020zdzx03-01-02).
文摘Apple replant disease(ARD)has led to severe yield and quality reduction in the apple industry.Fusarium solani(F.solani)has been identified as one of the main microbial pathogens responsible for ARD.Auxin(indole-3-acetic acid,IAA),an endogenous hormone in plants,is involved in almost all plant growth and development processes and plays a role in plant immunity against pathogens.Gretchen Hagen3(GH3)is one of the early/primary auxin response genes.The aim of this study was to evaluate the function of MdGH3-2 and MdGH3-12 in the defense response of F.solani by treating MdGH3-2/12 RNAi plants with F.solani.The results show that under F.solani infection,RNAi of MdGH3-2/12 inhibited plant biomass accumulation and exacerbated root damage.After inoculation with F.solani,MdGH3-2/12 RNAi inhibited the biosynthesis of acid-amido synthetase.This led to the inhibition of free IAA combining with amino acids,resulting in excessive free IAA accumulation.This excessive free IAA altered plant tissue structure,accelerated fungal hyphal invasion,reduced the activity of antioxidant enzymes(SOD,POD and CAT),increased the reactive oxygen species(ROS)level,and reduced total chlorophyll content and photosynthetic ability,while regulating the expression of PR-related genes including PR1,PR4,PR5 and PR8.It also changed the contents of plant hormones and amino acids,and ultimately reduced the resistance to F.solani.In conclusion,these results demonstrate that MdGH3-2 and MdGH3-12 play an important role in apple tolerance to F.solani and ARD.
基金financially supported by the National Natural Science Foundation of China(Grant No.32202463)China Agriculture Research System(Grant No.CARS-27)the Agricultural Science and Technology Innovation Program(Grant No.CAAS-ASTIP-2021-RIP-02)。
文摘Apple leaf spot,caused by the Alternaria alternata apple pathotype(AAAP),is an important fungal disease of apple.To understand the molecular basis of resistance and pathogenesis in apple leaf spot,the transcriptomes of two apple cultivars‘Hanfu'(HF)(resistant)and‘Golden Delicious'(GD)(susceptible)were analyzed at 0,6,18,24 and 48 h after AAAP inoculation by RNA-Seq.At each time point,a large number of significantly differentially expressed genes(DEGs)were screened between AAAP-inoculated and uninoculated apple leaves.Analysis of the common DEGs at four time points revealed significant differences in the resistance of‘HF'and‘GD'apple to AAAP infection.RLP,RNL,and JA signal-related genes were upregulated in both cultivars to restrict AAAP development.However,genes encoding CNLs,TNLs,WRKYs,and AP2s were only activated in‘HF'as part of the resistance response,of which,some play major roles in the regulation of ET and SA signal transduction.Further analysis showed that many DEGs with opposite expression trends in the two hosts may play important regulatory roles in response to AAAP infection.Transient expression of one such gene MdERF110 in‘GD'apple leaves improved AAAP resistance.Collectively,this study highlights the reasons for differential resistance to AAAP infection between‘HF'and‘GD'apples which can theoretically assist the molecular breeding of disease-resistant apple crops.
基金supported by the earmarked fund for National Natural Science Foundation of China(Grant No.31801816)National Modern Agro-industry Technology Research System(Grant No.CARS-27)Taishan scholar funded project(Grant No.TS20190923)。
文摘Apple replant disease(ARD)negatively affects plant growth and reduces yields in replanted orchards.In this study,biochar was applied to apple replant soil with Fusarium oxysporum.Our aim was to investigate whether biochar could promote plant growth and alleviate apple replant disease by reducing the growth of harmful soil microorganisms,changing soil microbial community structure and improving the soil environment.This experiment included five treatments:apple replant soil(CK),methyl bromide fumigation apple replant soil(FM),replant soil with biochar addition(2%),replant soil with F.oxysporum spore solution(8×10^(7)spores·mL^(-1)),and replant soil with biochar and F.oxysporum spore solution addition.Seedling biomass,the activity of antioxidant enzymes in the leaves and roots,and soil environmental variables were measured.Microbial community composition and community structure were analyzed using 16SrDNA and ITS2 gene sequencing.Biochar significantly reduced the abundance of F.oxysporum and increased soil microbial diversity and richness.Biochar also increased the soil enzyme activities(urease,invertase,neutral phosphatase,and catalase),the biomass(plant height,fresh weight,dry weight)and the activity of antioxidant enzymes(superoxide dismutase,peroxidase,and catalase).The root indexes of apple seedlings was also increased in replant soil by biochar.In sum,biochar promoted the growth of plants,improved the replant soil environment,and alleviated apple replant disease.
基金supported in part by the General Program Hunan Provincial Natural Science Foundation of 2022,China(2022JJ31022)the Undergraduate Education Reform Project of Hunan Province,China(HNJG-20210532)the National Natural Science Foundation of China(62276276)。
文摘Accurate diagnosis of apple leaf diseases is crucial for improving the quality of apple production and promoting the development of the apple industry. However, apple leaf diseases do not differ significantly from image texture and structural information. The difficulties in disease feature extraction in complex backgrounds slow the related research progress. To address the problems, this paper proposes an improved multi-scale inverse bottleneck residual network model based on a triplet parallel attention mechanism, which is built upon ResNet-50, while improving and combining the inception module and ResNext inverse bottleneck blocks, to recognize seven types of apple leaf(including six diseases of alternaria leaf spot, brown spot, grey spot, mosaic, rust, scab, and one healthy). First, the 3×3 convolutions in some of the residual modules are replaced by multi-scale residual convolutions, the convolution kernels of different sizes contained in each branch of the multi-scale convolution are applied to extract feature maps of different sizes, and the outputs of these branches are multi-scale fused by summing to enrich the output features of the images. Second, the global layer-wise dynamic coordinated inverse bottleneck structure is used to reduce the network feature loss. The inverse bottleneck structure makes the image information less lossy when transforming from different dimensional feature spaces. The fusion of multi-scale and layer-wise dynamic coordinated inverse bottlenecks makes the model effectively balances computational efficiency and feature representation capability, and more robust with a combination of horizontal and vertical features in the fine identification of apple leaf diseases. Finally, after each improved module, a triplet parallel attention module is integrated with cross-dimensional interactions among channels through rotations and residual transformations, which improves the parallel search efficiency of important features and the recognition rate of the network with relatively small computational costs while the dimensional dependencies are improved. To verify the validity of the model in this paper, we uniformly enhance apple leaf disease images screened from the public data sets of Plant Village, Baidu Flying Paddle, and the Internet. The final processed image count is 14,000. The ablation study, pre-processing comparison, and method comparison are conducted on the processed datasets. The experimental results demonstrate that the proposed method reaches 98.73% accuracy on the adopted datasets, which is 1.82% higher than the classical ResNet-50 model, and 0.29% better than the apple leaf disease datasets before preprocessing. It also achieves competitive results in apple leaf disease identification compared to some state-ofthe-art methods.
