Understanding how summer warming influences the parent and daughter shoot production in a perennial clonal grass is vital for comprehending the response of grassland productivity to global warming.Here,we conducted a s...Understanding how summer warming influences the parent and daughter shoot production in a perennial clonal grass is vital for comprehending the response of grassland productivity to global warming.Here,we conducted a simulated experiment using potted Leymus chinensis,to study the relationship between the photosynthetic activ-ity of parent shoots and the production of daughter shoots under a whole(90 days)summer warming scenario(+3°C).The results showed that the biomass of parents and buds decreased by 25.52%and 33.45%,respectively,under warming conditions.The reduction in parent shoot biomass due to warming directly resulted from decreased leaf area(18.03%),chlorophyll a(18.27%),chlorophyll b(29.21%)content,as well as a reduction in net photosynthetic rate(7.32%)and the maximum quantum efficiency of photosystem II(PSII)photochemistry(4.29%).The decline in daughter shoot biomass was linked to a decrease in daughter shoot number(33.33%)by warming.However,the number of belowground buds increased by 46.43%.The results indicated that long-term summer warming reduces biomass accumulation in parent shoot by increasing both limitation of stoma and non-stoma.Consequently,the parent shoot allocates relatively more biomass to the belowground organs to maintain the survival and growth of buds.Overall,buds,as a potential aboveground population,could remedy for the cur-rent loss of parent shoot density by increasing the number of future daughter shoots if summer warming subsides.展开更多
Tea leaf picking is a crucial stage in tea production that directly influences the quality and value of the tea.Traditional tea-picking machines may compromise the quality of the tea leaves.High-quality teas are often...Tea leaf picking is a crucial stage in tea production that directly influences the quality and value of the tea.Traditional tea-picking machines may compromise the quality of the tea leaves.High-quality teas are often handpicked and need more delicate operations in intelligent picking machines.Compared with traditional image processing techniques,deep learning models have stronger feature extraction capabilities,and better generalization and are more suitable for practical tea shoot harvesting.However,current research mostly focuses on shoot detection and cannot directly accomplish end-to-end shoot segmentation tasks.We propose a tea shoot instance segmentation model based on multi-scale mixed attention(Mask2FusionNet)using a dataset from the tea garden in Hangzhou.We further analyzed the characteristics of the tea shoot dataset,where the proportion of small to medium-sized targets is 89.9%.Our algorithm is compared with several mainstream object segmentation algorithms,and the results demonstrate that our model achieves an accuracy of 82%in recognizing the tea shoots,showing a better performance compared to other models.Through ablation experiments,we found that ResNet50,PointRend strategy,and the Feature Pyramid Network(FPN)architecture can improve performance by 1.6%,1.4%,and 2.4%,respectively.These experiments demonstrated that our proposed multi-scale and point selection strategy optimizes the feature extraction capability for overlapping small targets.The results indicate that the proposed Mask2FusionNet model can perform the shoot segmentation in unstructured environments,realizing the individual distinction of tea shoots,and complete extraction of the shoot edge contours with a segmentation accuracy of 82.0%.The research results can provide algorithmic support for the segmentation and intelligent harvesting of premium tea shoots at different scales.展开更多
Plants are capable of regulating their shoot architecture in response to diverse internal and external environments.The circadian clock is an adaptive mechanism that integrates information from internal and ambient co...Plants are capable of regulating their shoot architecture in response to diverse internal and external environments.The circadian clock is an adaptive mechanism that integrates information from internal and ambient conditions to help plants cope with recurring environmental fluctuations.Despite the current understanding of plant circadian clock and genetic framework underlying plant shoot architecture,the intricate connection between these two adaptive mechanisms remains largely unclear.In this study,we elucidated how the core clock gene LUX ARRHYTHMO(LUX)regulates shoot architecture in the model legume plant Medicago truncatula.We show that mtlux mutant displays increased main stem height,reduced lateral shoot length,and decreased the number of lateral branches and biomass yield.Gene expression analysis revealed that Mt LUX regulated shoot architecture by repressing the expression of strigolactone receptor MtD14 and MtTB1/MtTCP1A,a TCP gene that functions centrally in modulating shoot architecture.In vivo and in vitro experiments showed that Mt LUX directly binds to a cis-element in the promoter of MtTB1/MtTCP1A,suggesting that Mt LUX regulates branching by rhythmically suppressing MtTB1/MtTCP1A.This work demonstrates the regulatory effect of the circadian clock on shoot architecture,offering a new understanding underlying the genetic basis towards the flexibility of plant shoot architecture.展开更多
This paper presents an enhanced version of the standard shooting method that enables problems with two unknown parameters to be solved.A novel approach is applied to the analysis of the natural vibrations of Euler-Ber...This paper presents an enhanced version of the standard shooting method that enables problems with two unknown parameters to be solved.A novel approach is applied to the analysis of the natural vibrations of Euler-Bernoulli beams.The proposed algorithm,named as two-parameter multiple shooting method,is a new powerful numerical tool for calculating the natural frequencies and modes of multi-segment prismatic and non-prismatic beams with different boundary conditions.The impact of the axial force and additional point masses is also taken into account.Due to the fact that the method is based directly on the fourth-order ordinary differential equation,the structures do not have to be divided into many small elements to obtain an accurate enough solution,even though the geometry is very complex.To verify the proposed method,three different examples are considered,i.e.,a three-segment non-prismatic beam,a prismatic column subject to non-uniformly distributed compressive loads,and a two-segment beam with an additional point mass.Numerical analyses are carried out with the software MATHEMATICA.The results are compared with the solutions computed by the commercial finite element program SOFiSTiK.Good agreement is achieved,which confirms the correctness and high effectiveness of the formulated algorithm.展开更多
The present paper proposes a mathematical method to numerically treat a class of third-order linear Boundary Value Problems (BVPs). This method is based on the combination of the Adomian Decomposition Method (ADM) and...The present paper proposes a mathematical method to numerically treat a class of third-order linear Boundary Value Problems (BVPs). This method is based on the combination of the Adomian Decomposition Method (ADM) and, the modified shooting method. A complete derivation of the proposed method has been provided, in addition to its numerical implementation and, validation via the utilization of the Runge-Kutta method and, other existing methods. The method has been applied to diverse test problems and turned out to perform remarkably. Lastly, the simulated numerical results have been graphically illustrated and, also supported by some absolute error comparison tables.展开更多
为提高离散元法对指导油菜薹有序采收装备设计与优化的准确性和可靠性,该研究以双行垄作移栽的“农大1号”双低甘蓝型油菜机械化适收期油菜薹夹段茎秆为对象,测定其本征参数、表面接触参数以及破碎力学参数,利用EDEM仿真软件Hertz-Mind...为提高离散元法对指导油菜薹有序采收装备设计与优化的准确性和可靠性,该研究以双行垄作移栽的“农大1号”双低甘蓝型油菜机械化适收期油菜薹夹段茎秆为对象,测定其本征参数、表面接触参数以及破碎力学参数,利用EDEM仿真软件Hertz-Mindlin无滑移模型和Hertz-Mindlin with bonding粘结模型建立夹段茎秆堆积仿真标定模型和破碎仿真标定模型。采用逐步调整仿真参数使仿真试验值与物理试验值逼近的方法,利用夹段茎秆堆积仿真标定模型,以休止角仿真试验值与实际物理试验值的相对误差为目标,完成夹段茎秆表面接触参数的标定与优化;利用破碎仿真标定模型,以轴向压缩和弯曲仿真试验与实际物理试验的最大轴向压缩力和最大弯曲力的相对误差为目标,利用标定后的表面接触参数完成夹段茎秆粘结参数的标定与优化。最后,利用夹段茎秆的径向压缩与剪切、内芯与表皮拉伸的破碎仿真力学试验和有序采收EDEM-Recurdyn耦合仿真试验验证标定后的表面接触参数和粘结参数。结果表明,仿真与实测试验的破碎力学参数相对误差在5%以内,且仿真与实测的“时间-载荷”曲线变化趋势一致,低速、中速和高速档的有序采收仿真试验结果与实际物理试验结果相对误差在7.0%以内。研究结果表明,采用离散元仿真方法研究油菜薹采收过程具有可行性,标定结果可用于指导油菜薹机械化生产。展开更多
基金funded by the NSFC(32371669)the Science and Technology Talent Project for Distinguished Young Scholars of Jilin Province(20240602009RC)+1 种基金the NSF of Jilin Province(20240101207JC)the Scientific Research Project of the Department of Education,Jilin Province(JJKH20230687KJ).
文摘Understanding how summer warming influences the parent and daughter shoot production in a perennial clonal grass is vital for comprehending the response of grassland productivity to global warming.Here,we conducted a simulated experiment using potted Leymus chinensis,to study the relationship between the photosynthetic activ-ity of parent shoots and the production of daughter shoots under a whole(90 days)summer warming scenario(+3°C).The results showed that the biomass of parents and buds decreased by 25.52%and 33.45%,respectively,under warming conditions.The reduction in parent shoot biomass due to warming directly resulted from decreased leaf area(18.03%),chlorophyll a(18.27%),chlorophyll b(29.21%)content,as well as a reduction in net photosynthetic rate(7.32%)and the maximum quantum efficiency of photosystem II(PSII)photochemistry(4.29%).The decline in daughter shoot biomass was linked to a decrease in daughter shoot number(33.33%)by warming.However,the number of belowground buds increased by 46.43%.The results indicated that long-term summer warming reduces biomass accumulation in parent shoot by increasing both limitation of stoma and non-stoma.Consequently,the parent shoot allocates relatively more biomass to the belowground organs to maintain the survival and growth of buds.Overall,buds,as a potential aboveground population,could remedy for the cur-rent loss of parent shoot density by increasing the number of future daughter shoots if summer warming subsides.
基金This research was supported by the National Natural Science Foundation of China No.62276086the National Key R&D Program of China No.2022YFD2000100Zhejiang Provincial Natural Science Foundation of China under Grant No.LTGN23D010002.
文摘Tea leaf picking is a crucial stage in tea production that directly influences the quality and value of the tea.Traditional tea-picking machines may compromise the quality of the tea leaves.High-quality teas are often handpicked and need more delicate operations in intelligent picking machines.Compared with traditional image processing techniques,deep learning models have stronger feature extraction capabilities,and better generalization and are more suitable for practical tea shoot harvesting.However,current research mostly focuses on shoot detection and cannot directly accomplish end-to-end shoot segmentation tasks.We propose a tea shoot instance segmentation model based on multi-scale mixed attention(Mask2FusionNet)using a dataset from the tea garden in Hangzhou.We further analyzed the characteristics of the tea shoot dataset,where the proportion of small to medium-sized targets is 89.9%.Our algorithm is compared with several mainstream object segmentation algorithms,and the results demonstrate that our model achieves an accuracy of 82%in recognizing the tea shoots,showing a better performance compared to other models.Through ablation experiments,we found that ResNet50,PointRend strategy,and the Feature Pyramid Network(FPN)architecture can improve performance by 1.6%,1.4%,and 2.4%,respectively.These experiments demonstrated that our proposed multi-scale and point selection strategy optimizes the feature extraction capability for overlapping small targets.The results indicate that the proposed Mask2FusionNet model can perform the shoot segmentation in unstructured environments,realizing the individual distinction of tea shoots,and complete extraction of the shoot edge contours with a segmentation accuracy of 82.0%.The research results can provide algorithmic support for the segmentation and intelligent harvesting of premium tea shoots at different scales.
基金supported by Laboratory of Lingnan Modern Agriculture Project(NZ2021001)State Key Laboratory for Conservation and Utilization of Subtropical Agrobioresources(SKICUSA-a202007)Natural Science Foundation of Guangdong Province(2022A1515011027,2019A1515012009)。
文摘Plants are capable of regulating their shoot architecture in response to diverse internal and external environments.The circadian clock is an adaptive mechanism that integrates information from internal and ambient conditions to help plants cope with recurring environmental fluctuations.Despite the current understanding of plant circadian clock and genetic framework underlying plant shoot architecture,the intricate connection between these two adaptive mechanisms remains largely unclear.In this study,we elucidated how the core clock gene LUX ARRHYTHMO(LUX)regulates shoot architecture in the model legume plant Medicago truncatula.We show that mtlux mutant displays increased main stem height,reduced lateral shoot length,and decreased the number of lateral branches and biomass yield.Gene expression analysis revealed that Mt LUX regulated shoot architecture by repressing the expression of strigolactone receptor MtD14 and MtTB1/MtTCP1A,a TCP gene that functions centrally in modulating shoot architecture.In vivo and in vitro experiments showed that Mt LUX directly binds to a cis-element in the promoter of MtTB1/MtTCP1A,suggesting that Mt LUX regulates branching by rhythmically suppressing MtTB1/MtTCP1A.This work demonstrates the regulatory effect of the circadian clock on shoot architecture,offering a new understanding underlying the genetic basis towards the flexibility of plant shoot architecture.
文摘This paper presents an enhanced version of the standard shooting method that enables problems with two unknown parameters to be solved.A novel approach is applied to the analysis of the natural vibrations of Euler-Bernoulli beams.The proposed algorithm,named as two-parameter multiple shooting method,is a new powerful numerical tool for calculating the natural frequencies and modes of multi-segment prismatic and non-prismatic beams with different boundary conditions.The impact of the axial force and additional point masses is also taken into account.Due to the fact that the method is based directly on the fourth-order ordinary differential equation,the structures do not have to be divided into many small elements to obtain an accurate enough solution,even though the geometry is very complex.To verify the proposed method,three different examples are considered,i.e.,a three-segment non-prismatic beam,a prismatic column subject to non-uniformly distributed compressive loads,and a two-segment beam with an additional point mass.Numerical analyses are carried out with the software MATHEMATICA.The results are compared with the solutions computed by the commercial finite element program SOFiSTiK.Good agreement is achieved,which confirms the correctness and high effectiveness of the formulated algorithm.
文摘The present paper proposes a mathematical method to numerically treat a class of third-order linear Boundary Value Problems (BVPs). This method is based on the combination of the Adomian Decomposition Method (ADM) and, the modified shooting method. A complete derivation of the proposed method has been provided, in addition to its numerical implementation and, validation via the utilization of the Runge-Kutta method and, other existing methods. The method has been applied to diverse test problems and turned out to perform remarkably. Lastly, the simulated numerical results have been graphically illustrated and, also supported by some absolute error comparison tables.
文摘为提高离散元法对指导油菜薹有序采收装备设计与优化的准确性和可靠性,该研究以双行垄作移栽的“农大1号”双低甘蓝型油菜机械化适收期油菜薹夹段茎秆为对象,测定其本征参数、表面接触参数以及破碎力学参数,利用EDEM仿真软件Hertz-Mindlin无滑移模型和Hertz-Mindlin with bonding粘结模型建立夹段茎秆堆积仿真标定模型和破碎仿真标定模型。采用逐步调整仿真参数使仿真试验值与物理试验值逼近的方法,利用夹段茎秆堆积仿真标定模型,以休止角仿真试验值与实际物理试验值的相对误差为目标,完成夹段茎秆表面接触参数的标定与优化;利用破碎仿真标定模型,以轴向压缩和弯曲仿真试验与实际物理试验的最大轴向压缩力和最大弯曲力的相对误差为目标,利用标定后的表面接触参数完成夹段茎秆粘结参数的标定与优化。最后,利用夹段茎秆的径向压缩与剪切、内芯与表皮拉伸的破碎仿真力学试验和有序采收EDEM-Recurdyn耦合仿真试验验证标定后的表面接触参数和粘结参数。结果表明,仿真与实测试验的破碎力学参数相对误差在5%以内,且仿真与实测的“时间-载荷”曲线变化趋势一致,低速、中速和高速档的有序采收仿真试验结果与实际物理试验结果相对误差在7.0%以内。研究结果表明,采用离散元仿真方法研究油菜薹采收过程具有可行性,标定结果可用于指导油菜薹机械化生产。
