Background Cotton is a significant crop for fiber production;however,seed shape-related traits have been less investigated in comparison to fiber quality.Comprehending the genetic foundation of traits associated with ...Background Cotton is a significant crop for fiber production;however,seed shape-related traits have been less investigated in comparison to fiber quality.Comprehending the genetic foundation of traits associated with seed shape is crucial for improving the seed and fiber quality in cotton.Results A total of 238 cotton accessions were evaluated in four different environments over a period of two years.Traits including thousand grain weight(TGW),aspect ratio(AR),seed length,seed width,diameter,and roundness demonstrated high heritability and significant genetic variation,as indicated by phenotypic analysis.The association analysis involved 145 simple sequence repeats(SSR)markers and identified 50 loci significantly associated with six traits related to seed shape.The markers MON_DPL0504aa and BNL2535ba were identified as influencing multiple traits,including aspect ratio and thousand grain weight.Notably,markers such as HAU2588a and MUSS422aa had considerable influence on seed diameter and roundness.The identified markers represented an average phenotypic variance between 3.92%for seed length and 16.54%for TGW.Conclusions The research finds key loci for seed shape-related traits in cotton,providing significant potential for marker-assisted breeding.These findings establish a framework for breeding initiatives focused on enhancing seed quality,hence advancing the cotton production.展开更多
视触觉增强现实是将触觉感知加入到增强现实中的一种新技术。不仅可以融合真实场景和虚拟对象,还能实现视觉和触觉的同步感知。基于3D Systems Touch触觉设备提出一种新的视触觉交互算法。首先,基于Marker-SLAM算法搭建增强现实环境,用...视触觉增强现实是将触觉感知加入到增强现实中的一种新技术。不仅可以融合真实场景和虚拟对象,还能实现视觉和触觉的同步感知。基于3D Systems Touch触觉设备提出一种新的视触觉交互算法。首先,基于Marker-SLAM算法搭建增强现实环境,用于实时获得相机在地图中的位姿;其次,为了将触觉信息融入到增强现实环境中,提出基于无跟踪器的触控笔尖端姿态优化算法;最后,分别采集测量点在触觉和世界坐标系中的三维信息,通过确定两个坐标系间的刚性变换,将触觉设备的正向运动模型映射到增强现实空间中。所提出的跟踪注册方法的注册准确率均达到90%以上,与基于跟踪器的方法相比,所提出的姿态优化算法获得的校正位置的平均误差为2.3±0.2 mm。展开更多
基金supported by the Fund for BTNYGG(NYHXGG,2023AA102)the National Natural Science Foundation of China(32260510)+3 种基金the Key Project for Science,Technology Development of Shihezi city,Xinjiang Production and Construction Crops(2022NY01)Shihezi University high-level talent research project(RCZK202337)Science and Technology Major Project of the Department of Science and Technology of Xinjiang Uygur Autonomous region(2022A03004-1)the Key Programs for Science and Technology Development in Agricultural Field of Xinjiang Production and Construction Corps。
文摘Background Cotton is a significant crop for fiber production;however,seed shape-related traits have been less investigated in comparison to fiber quality.Comprehending the genetic foundation of traits associated with seed shape is crucial for improving the seed and fiber quality in cotton.Results A total of 238 cotton accessions were evaluated in four different environments over a period of two years.Traits including thousand grain weight(TGW),aspect ratio(AR),seed length,seed width,diameter,and roundness demonstrated high heritability and significant genetic variation,as indicated by phenotypic analysis.The association analysis involved 145 simple sequence repeats(SSR)markers and identified 50 loci significantly associated with six traits related to seed shape.The markers MON_DPL0504aa and BNL2535ba were identified as influencing multiple traits,including aspect ratio and thousand grain weight.Notably,markers such as HAU2588a and MUSS422aa had considerable influence on seed diameter and roundness.The identified markers represented an average phenotypic variance between 3.92%for seed length and 16.54%for TGW.Conclusions The research finds key loci for seed shape-related traits in cotton,providing significant potential for marker-assisted breeding.These findings establish a framework for breeding initiatives focused on enhancing seed quality,hence advancing the cotton production.
文摘视触觉增强现实是将触觉感知加入到增强现实中的一种新技术。不仅可以融合真实场景和虚拟对象,还能实现视觉和触觉的同步感知。基于3D Systems Touch触觉设备提出一种新的视触觉交互算法。首先,基于Marker-SLAM算法搭建增强现实环境,用于实时获得相机在地图中的位姿;其次,为了将触觉信息融入到增强现实环境中,提出基于无跟踪器的触控笔尖端姿态优化算法;最后,分别采集测量点在触觉和世界坐标系中的三维信息,通过确定两个坐标系间的刚性变换,将触觉设备的正向运动模型映射到增强现实空间中。所提出的跟踪注册方法的注册准确率均达到90%以上,与基于跟踪器的方法相比,所提出的姿态优化算法获得的校正位置的平均误差为2.3±0.2 mm。
