Flag leaf angle(FLANG)is one of the key traits in wheat breeding due to its impact on plant architecture,light interception,and yield potential.An image-based method of measuring FLANG in wheat would reduce the labor ...Flag leaf angle(FLANG)is one of the key traits in wheat breeding due to its impact on plant architecture,light interception,and yield potential.An image-based method of measuring FLANG in wheat would reduce the labor and error of manual measurement of this trait.We describe a method for acquiring in-field FLANG images and a lightweight deep learning model named LeafPoseNet that incorporates a spatial attention mechanism for FLANG estimation.In a test dataset with wheat varieties exhibiting diverse FLANG,LeafPoseNet achieved high accuracy in predicting the FLANG,with a mean absolute error(MAE)of 1.75°,a root mean square error(RMSE)of 2.17°,and a coefficient of determination(R2)of 0.998,significantly outperforming established models such as YOLO12x-pose,YOLO11x-pose,HigherHRNet,Lightweight-OpenPose,and LitePose.We performed phenotyping and genome-wide association study to identify the genomic regions associated with FLANG in a panel of 221 diverse bread wheat genotypes,and identified 10 quantitative trait loci.Among them,qFLANG2B.2 was found to harbor a potential causal gene,TraesCS2B01G313700,which may regulate FLANG formation by modulating brassinosteroid levels.This method provides a low-cost,high-accuracy solution for in-field phenotyping of wheat FLANG,facilitating both wheat FLANG genetic studies and ideal plant type breeding.展开更多
[Objectives] This study was conducted to analyze the composition of volatile oil in different parts of fennel(Foenicuzu vulgare Mill.) and to compare the differences in the composition of volatile oil in different par...[Objectives] This study was conducted to analyze the composition of volatile oil in different parts of fennel(Foenicuzu vulgare Mill.) and to compare the differences in the composition of volatile oil in different parts of fennel.[Methods]The steam distillation method was applied to extract volatile oil from different parts of fennel,and the components of volatile oil from different parts of fennel were separated and identified by GC-MS.The relative content of each component was determined by the peak area normalization method.[Results]37,33,18,and 44 chemical components were separated from the volatile oil of fennel roots,stems,young leaves and fruit,respectively,accounting for 98.64%,99.34%,99.59% and 95.99% of the total volatile oil of corresponding parts.A total of 77 chemical components were identified in the four parts,of which 5 were common components.The main component of the volatile oil in the stems and young leaves was trans-anethole.The main components of the volatile oil in fruit were estragole and trans-anethole.And the main component of the volatile oil in the roots was dill apiol.The components in the volatile oil of fennel roots,stems,young leaves and fruit were different in type and content.[Conclusions]This study provides a theoretical reference for the further effective development and utilization of fennel resources.展开更多
Excess calcium(Ca)in soils of semi-arid and arid regions has negative effects on soil structure and chemical properties,which limits the crop root growth as well as the availability of soil water and nutrients.Quantif...Excess calcium(Ca)in soils of semi-arid and arid regions has negative effects on soil structure and chemical properties,which limits the crop root growth as well as the availability of soil water and nutrients.Quantifying the spatial variability of soil Ca contents may reveal factors influencing soil erosion and provide a basis for site-specific soil and crop management in semi-arid regions.This study sought to assess the spatial variability of soil Ca in relation to topography,hydraulic attributes,and soil types for precision soil and crop management in a 194-ha production field in the Southern High Plains of Texas,USA.Soils at four depth increments(0-2,0-15,15-30,and 30-60 cm)were sampled at 232 points in the spring of 2017.The Ca content of each sample was determined with a DP-6000 Delta Premium portable X-ray fluorescence(PXRF)spectrometer.Elevation data was obtained using a real-time kinematic GPS receiver with centimeter-level accuracy.A digital elevation model(DEM)was derived from the elevation data,and topographic and hydraulic attributes were generated from this DEM.A generalized least-squares model was then developed to assess the relationship between soil Ca contents of the four layers and the topographic and hydraulic attributes.Results showed that topographic attributes,especially slope and elevation,had a significant effect on soil Ca content at different depths(P<0.01).In addition,hydraulic attributes,especially flow length and sediment transport index(STI),had a significant effect on the spatial distribution of soil Ca.Spatial variability of soil Ca and its relationships with topographic and hydraulic attributes and soil types indicated that surface soil loss may occur due to water or wind erosion,especially on susceptible soils with high slopes.Therefore,this study suggests that the application of PXRF in assessing soil Ca content can potentially facilitate a new method for soil erosion evaluation in semi-arid lands.The results of this study provide valuable information for site-specific soil conservation and crop management.展开更多
Enhancing photosynthetic efficiency is a major goal for improving crop yields under agricultural field conditions and is associated with chloroplast biosynthesis and development.In this study,we demonstrate that Golde...Enhancing photosynthetic efficiency is a major goal for improving crop yields under agricultural field conditions and is associated with chloroplast biosynthesis and development.In this study,we demonstrate that Golden2-like 1a(BnGLK1a)plays an important role in regulating chloroplast development and photosynthetic efficiency.Overexpressing BnGLK1a resulted in significant increases in chlorophyll content,the number of thylakoid membrane layers and photosynthetic efficiency in Brassica napus,while knocking down BnGLK1a transcript levels through RNA interference(RNAi)had the opposite effects.A yeast two-hybrid screen revealed that BnGLK1a interacts with the abscisic acid receptor PYRABACTIN RESISTANCE 1-LIKE 1-2(BnPYL1-2)and CONSTITUTIVE PHOTOMORPHOGENIC 9 SIGNALOSOME 5A subunit(BnCSN5A),which play essential roles in regulating chloroplast development and photosynthesis.Consistent with this,BnGLK1a-RNAi lines of B.napus display hypersensitivity to the abscisic acid(ABA)response.Importantly,overexpression of BnGLK1a resulted in a 10%increase in thousand-seed weight,whereas seeds from BnGLK1a-RNAi lines were 16%lighter than wild type.We propose that BnGLK1a could be a potential target in breeding for improving rapeseed productivity.Our results not only provide insights into the mechanisms of BnGLK1a function,but also offer a potential approach for improving the productivity of Brassica species.展开更多
[Objectives]This study was conducted to establish a method for determining the contents of Chaenomeles cathayensis(Hemsl.)Schneid.,and analyze the changes in effective components of C.cathayensis grown in Guizhou,so a...[Objectives]This study was conducted to establish a method for determining the contents of Chaenomeles cathayensis(Hemsl.)Schneid.,and analyze the changes in effective components of C.cathayensis grown in Guizhou,so as to provide data support for the production and quality control of C.cathayensis.[Methods]The contents of ursolic acid and oleanolic acid in C.cathayensis in different areas of Guizhou were determined.The HPLC method was adopted under following conditions:chromatographic column waters C18 column(4.6 mm×150 mm,5.0μm);mobile phase:methanol-0.1 mol/L ammonium acetate(85∶15);column temperature:25℃;detection wavelength:257 nm;flow rate 1.0 ml/min.[Results]Through methodological investigations,HPLC could be used to detect the contents of the two terpenoids oleanolic acid and ursolic acid in C.cathayensis from Guizhou.The content of oleanolic acid ranged from 0.076%to 0.144%,and the content of ursolic acid ranged from 0.201%to 0.439%.[Conclusions]A method for determining the contents of C.cathayensis was established using the HPLC method with oleanolic acid and ursolic acid as the index components.The method is accurate,reliable,and simple and easy to implement,and can serve as a reference and support for quality evaluation and standard improvement of C.cathayensis.展开更多
Freeze injury during the seedling stage significantly impacts wheat growth and yield,making the development of freeze-tolerant varieties crucial for ensuring stable yields.To identify key genetic factors for wheat fre...Freeze injury during the seedling stage significantly impacts wheat growth and yield,making the development of freeze-tolerant varieties crucial for ensuring stable yields.To identify key genetic factors for wheat freeze tolerance,an accurate assessment of freeze tolerance is necessary.However,traditional methods,such as visual inspection,are subjective and can vary significantly among observers.In this study,we developed FreezeNet,a lightweight deep learning model designed to accurately quantify freeze injury using an image-based phenotyping method.Freeze tolerance traits,including vegetation area(VA),green vegetation area(GVA),yellow vegetation fraction(YVF),and mean hue value(mHue),were extracted for freeze tolerance assessment.We captured standardized images with a smartphone and used FreezeNet to extract the freeze tolerance traits for 220 wheat accessions.These traits were strongly correlated with traditional injury scores estimated through visual in-spection.Moreover,they presented relatively high heritability.Using these traits,we conducted genome-wide association studies(GWASs)to identify genetic loci associated with freeze tolerance.Eleven significant QTLs associated with freeze tolerance were identified,including 8 novel loci.By integrating four of these loci into a wheat germplasm that lacked any of the 11 QTLs,we significantly enhanced its freeze resistance,demonstrating the practical application of these genetic loci in breeding for improved freeze tolerance.Our results highlight FreezeNet as an advanced tool for assessing wheat freeze injury and identifying the genetic factors responsible for freeze tolerance,with the potential to guide breeding efforts toward the development of more resilient wheat varieties.展开更多
Wheat spike morphology plays a critical role in determining grain yield and has garnered significant interest in genetics and breeding research.However,traditional measurement methods are limited to simple traits and ...Wheat spike morphology plays a critical role in determining grain yield and has garnered significant interest in genetics and breeding research.However,traditional measurement methods are limited to simple traits and fail to capture complex spike phenotypes with high precision,thus limiting progress in yield-related trait analysis.In this study,a deep learning pipeline,called Speakerphone,for acquiring precise wheat spike phenotypes was developed.Our pipeline achieved a mean intersection over union(mIoU)of 0.948 in spike segmentation.Additionally,the spike traits measured by our method strongly agreed with the manually measured values,with Pearson correlation coefficients of 0.9865 for spike length,0.9753 for the number of spikelets per spike,and 0.9635 for fertile spikelets.Using experimental data of 221 wheat cultivars from various regions of Zhao County,Hebei Province,China,our pipeline extracted 45 phenotypes and analyzed their correlations with thousand-grain weight(TGW)and spike yield.Our findings indicate that precise measurements of spike area,spikelet area,and other phenotypic traits clarify the correlation between spike morphology and wheat yield.Through hierarchical clustering on the basis of spike morphology,we categorized wheat spikes into six classes and identified the phenotypic differences among these classes and their effects on TGW and yield.Furthermore,phenotypic dif-ferences among wheat cultivars from different geographical regions and over decades were revealed in this study,with an increase in the number of large-spike cultivars over time,especially in southern China.This research may help breeders understand the relationship between wheat spike morphology and yield,thus providing an important basis for future wheat breeding efforts.展开更多
基金supported by the Biological Breeding-National Science and Technology Major Project(2023ZD04076)the National Key Research and Development Program of China(2023YFF1000100)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA0450000).
文摘Flag leaf angle(FLANG)is one of the key traits in wheat breeding due to its impact on plant architecture,light interception,and yield potential.An image-based method of measuring FLANG in wheat would reduce the labor and error of manual measurement of this trait.We describe a method for acquiring in-field FLANG images and a lightweight deep learning model named LeafPoseNet that incorporates a spatial attention mechanism for FLANG estimation.In a test dataset with wheat varieties exhibiting diverse FLANG,LeafPoseNet achieved high accuracy in predicting the FLANG,with a mean absolute error(MAE)of 1.75°,a root mean square error(RMSE)of 2.17°,and a coefficient of determination(R2)of 0.998,significantly outperforming established models such as YOLO12x-pose,YOLO11x-pose,HigherHRNet,Lightweight-OpenPose,and LitePose.We performed phenotyping and genome-wide association study to identify the genomic regions associated with FLANG in a panel of 221 diverse bread wheat genotypes,and identified 10 quantitative trait loci.Among them,qFLANG2B.2 was found to harbor a potential causal gene,TraesCS2B01G313700,which may regulate FLANG formation by modulating brassinosteroid levels.This method provides a low-cost,high-accuracy solution for in-field phenotyping of wheat FLANG,facilitating both wheat FLANG genetic studies and ideal plant type breeding.
基金Supported by Anshun Science and Technology Innovation Platform Construction Project(ASKP[2017]03)。
文摘[Objectives] This study was conducted to analyze the composition of volatile oil in different parts of fennel(Foenicuzu vulgare Mill.) and to compare the differences in the composition of volatile oil in different parts of fennel.[Methods]The steam distillation method was applied to extract volatile oil from different parts of fennel,and the components of volatile oil from different parts of fennel were separated and identified by GC-MS.The relative content of each component was determined by the peak area normalization method.[Results]37,33,18,and 44 chemical components were separated from the volatile oil of fennel roots,stems,young leaves and fruit,respectively,accounting for 98.64%,99.34%,99.59% and 95.99% of the total volatile oil of corresponding parts.A total of 77 chemical components were identified in the four parts,of which 5 were common components.The main component of the volatile oil in the stems and young leaves was trans-anethole.The main components of the volatile oil in fruit were estragole and trans-anethole.And the main component of the volatile oil in the roots was dill apiol.The components in the volatile oil of fennel roots,stems,young leaves and fruit were different in type and content.[Conclusions]This study provides a theoretical reference for the further effective development and utilization of fennel resources.
基金supported by Texas Tech UniversityCotton IncorporatedTexas Water Development Board,USA。
文摘Excess calcium(Ca)in soils of semi-arid and arid regions has negative effects on soil structure and chemical properties,which limits the crop root growth as well as the availability of soil water and nutrients.Quantifying the spatial variability of soil Ca contents may reveal factors influencing soil erosion and provide a basis for site-specific soil and crop management in semi-arid regions.This study sought to assess the spatial variability of soil Ca in relation to topography,hydraulic attributes,and soil types for precision soil and crop management in a 194-ha production field in the Southern High Plains of Texas,USA.Soils at four depth increments(0-2,0-15,15-30,and 30-60 cm)were sampled at 232 points in the spring of 2017.The Ca content of each sample was determined with a DP-6000 Delta Premium portable X-ray fluorescence(PXRF)spectrometer.Elevation data was obtained using a real-time kinematic GPS receiver with centimeter-level accuracy.A digital elevation model(DEM)was derived from the elevation data,and topographic and hydraulic attributes were generated from this DEM.A generalized least-squares model was then developed to assess the relationship between soil Ca contents of the four layers and the topographic and hydraulic attributes.Results showed that topographic attributes,especially slope and elevation,had a significant effect on soil Ca content at different depths(P<0.01).In addition,hydraulic attributes,especially flow length and sediment transport index(STI),had a significant effect on the spatial distribution of soil Ca.Spatial variability of soil Ca and its relationships with topographic and hydraulic attributes and soil types indicated that surface soil loss may occur due to water or wind erosion,especially on susceptible soils with high slopes.Therefore,this study suggests that the application of PXRF in assessing soil Ca content can potentially facilitate a new method for soil erosion evaluation in semi-arid lands.The results of this study provide valuable information for site-specific soil conservation and crop management.
基金This work was funded by the National Natural Science Foundation of China(32172597 and 31830067)the Chongqing Talents of Exceptional Young Talents Project,China(CQYC202005097,cstc2021ycjh-bgzxm0204,and cstc2021jcyj-bshX0002)+2 种基金the China Agriculture Research System of MOF and MARA(CARS-12)the 111 Project,China(B12006)the Germplasm Creation Special Program of Southwest University,China。
文摘Enhancing photosynthetic efficiency is a major goal for improving crop yields under agricultural field conditions and is associated with chloroplast biosynthesis and development.In this study,we demonstrate that Golden2-like 1a(BnGLK1a)plays an important role in regulating chloroplast development and photosynthetic efficiency.Overexpressing BnGLK1a resulted in significant increases in chlorophyll content,the number of thylakoid membrane layers and photosynthetic efficiency in Brassica napus,while knocking down BnGLK1a transcript levels through RNA interference(RNAi)had the opposite effects.A yeast two-hybrid screen revealed that BnGLK1a interacts with the abscisic acid receptor PYRABACTIN RESISTANCE 1-LIKE 1-2(BnPYL1-2)and CONSTITUTIVE PHOTOMORPHOGENIC 9 SIGNALOSOME 5A subunit(BnCSN5A),which play essential roles in regulating chloroplast development and photosynthesis.Consistent with this,BnGLK1a-RNAi lines of B.napus display hypersensitivity to the abscisic acid(ABA)response.Importantly,overexpression of BnGLK1a resulted in a 10%increase in thousand-seed weight,whereas seeds from BnGLK1a-RNAi lines were 16%lighter than wild type.We propose that BnGLK1a could be a potential target in breeding for improving rapeseed productivity.Our results not only provide insights into the mechanisms of BnGLK1a function,but also offer a potential approach for improving the productivity of Brassica species.
基金Science and Technology Innovation Platform Construction Project of Anshun City(ASKP[2017]03)。
文摘[Objectives]This study was conducted to establish a method for determining the contents of Chaenomeles cathayensis(Hemsl.)Schneid.,and analyze the changes in effective components of C.cathayensis grown in Guizhou,so as to provide data support for the production and quality control of C.cathayensis.[Methods]The contents of ursolic acid and oleanolic acid in C.cathayensis in different areas of Guizhou were determined.The HPLC method was adopted under following conditions:chromatographic column waters C18 column(4.6 mm×150 mm,5.0μm);mobile phase:methanol-0.1 mol/L ammonium acetate(85∶15);column temperature:25℃;detection wavelength:257 nm;flow rate 1.0 ml/min.[Results]Through methodological investigations,HPLC could be used to detect the contents of the two terpenoids oleanolic acid and ursolic acid in C.cathayensis from Guizhou.The content of oleanolic acid ranged from 0.076%to 0.144%,and the content of ursolic acid ranged from 0.201%to 0.439%.[Conclusions]A method for determining the contents of C.cathayensis was established using the HPLC method with oleanolic acid and ursolic acid as the index components.The method is accurate,reliable,and simple and easy to implement,and can serve as a reference and support for quality evaluation and standard improvement of C.cathayensis.
基金This work was supported by the National Key Research and Development Program of China(2023YFF1000100)the Biological Breeding-National Science and Technology Major Project(2023ZD04076).
文摘Freeze injury during the seedling stage significantly impacts wheat growth and yield,making the development of freeze-tolerant varieties crucial for ensuring stable yields.To identify key genetic factors for wheat freeze tolerance,an accurate assessment of freeze tolerance is necessary.However,traditional methods,such as visual inspection,are subjective and can vary significantly among observers.In this study,we developed FreezeNet,a lightweight deep learning model designed to accurately quantify freeze injury using an image-based phenotyping method.Freeze tolerance traits,including vegetation area(VA),green vegetation area(GVA),yellow vegetation fraction(YVF),and mean hue value(mHue),were extracted for freeze tolerance assessment.We captured standardized images with a smartphone and used FreezeNet to extract the freeze tolerance traits for 220 wheat accessions.These traits were strongly correlated with traditional injury scores estimated through visual in-spection.Moreover,they presented relatively high heritability.Using these traits,we conducted genome-wide association studies(GWASs)to identify genetic loci associated with freeze tolerance.Eleven significant QTLs associated with freeze tolerance were identified,including 8 novel loci.By integrating four of these loci into a wheat germplasm that lacked any of the 11 QTLs,we significantly enhanced its freeze resistance,demonstrating the practical application of these genetic loci in breeding for improved freeze tolerance.Our results highlight FreezeNet as an advanced tool for assessing wheat freeze injury and identifying the genetic factors responsible for freeze tolerance,with the potential to guide breeding efforts toward the development of more resilient wheat varieties.
基金This work was supported by the Biological Breeding-National Science and Technology Major Project(2023ZD04076)the National Key Research and Development Program of China(2023YFF1000100).
文摘Wheat spike morphology plays a critical role in determining grain yield and has garnered significant interest in genetics and breeding research.However,traditional measurement methods are limited to simple traits and fail to capture complex spike phenotypes with high precision,thus limiting progress in yield-related trait analysis.In this study,a deep learning pipeline,called Speakerphone,for acquiring precise wheat spike phenotypes was developed.Our pipeline achieved a mean intersection over union(mIoU)of 0.948 in spike segmentation.Additionally,the spike traits measured by our method strongly agreed with the manually measured values,with Pearson correlation coefficients of 0.9865 for spike length,0.9753 for the number of spikelets per spike,and 0.9635 for fertile spikelets.Using experimental data of 221 wheat cultivars from various regions of Zhao County,Hebei Province,China,our pipeline extracted 45 phenotypes and analyzed their correlations with thousand-grain weight(TGW)and spike yield.Our findings indicate that precise measurements of spike area,spikelet area,and other phenotypic traits clarify the correlation between spike morphology and wheat yield.Through hierarchical clustering on the basis of spike morphology,we categorized wheat spikes into six classes and identified the phenotypic differences among these classes and their effects on TGW and yield.Furthermore,phenotypic dif-ferences among wheat cultivars from different geographical regions and over decades were revealed in this study,with an increase in the number of large-spike cultivars over time,especially in southern China.This research may help breeders understand the relationship between wheat spike morphology and yield,thus providing an important basis for future wheat breeding efforts.
