To dissect the genetic mechanism of multi-seed pod in peanut, we explored the QTL/gene controlling multi-seed pod and analyzed the interaction effect of QTL and environment. Two hundred and forty eight recombinant inb...To dissect the genetic mechanism of multi-seed pod in peanut, we explored the QTL/gene controlling multi-seed pod and analyzed the interaction effect of QTL and environment. Two hundred and forty eight recombinant inbred lines(RIL) from cross Silihong × Jinonghei 3 were used as experimental materials planted in 8 environments from 2012 to 2017. Three methods of analysis were performed. These included individual environment analysis, joint analysis in multiple environments, and epistatic interaction analysis for multi-seed pod QTL. Phenotypic data and best linear unbiased prediction(BLUP) value of the ratio of multi-seed pods per plant(RMSP) were used for QTL mapping. Seven QTL detected by the individual environmental mapping analysis and were distributed on linkage groups 1, 6, 9, 14, 19(2), and 21. Each QTL explained 4.42%–11.51% of the phenotypic variation in multi-seed pod, and synergistic alleles of5 QTL were from the Silihong parent. One QTL, explaining 4.93% of the phenotypic variation was detected using BLUP data, and this QTL mapped in the same interval as q RMSP19.1 detected in the individual environment analysis. Seventeen additive QTL were identified by joint analysis across multiple environments. A total of 43 epistatic QTL were detected by ICIM-EPI mapping in the multiple environment trials(MET) module, and involved 57 loci. Two main-effect QTL related to multi-seed pod in peanut were filtered. We also found that RMSP had a highly significant positive correlation with pod yield per plant(PY), and epistatic effects were much more important than additive effects. These results provide theoretical guidance for the genetic improvement of germplasm resources and further fine mapping of related genes in peanut.展开更多
The key problem of securing multieast is to generate, distribute and update Session Encryption Key（SEK）. Polynomial expansion with multi-seed （MPE） scheme is an approach which is based on Polynomial expansion （PE...The key problem of securing multieast is to generate, distribute and update Session Encryption Key（SEK）. Polynomial expansion with multi-seed （MPE） scheme is an approach which is based on Polynomial expansion （PE） scheme and overcomes PE＇s shortage. Its operation is demonstrated by using multi-seed, the group member is partitioned to many subgroups. While updating the SEK, computation is needed only in one of subgroups, the other of them will use the computation history to update their SEK. The key problems to design a MPE scheme application includes to find a feasible one way function as well as to generate a Strict Prime Number （SPN）. Those technologies with multi-seed and computation history concepts make MPE as a good choice in practical applications. A prototype test system is designed and solutions of all above mentioned problems are included in this proposed paper.展开更多
太赫兹成像技术虽已被证实能够用于检测葵花籽内部品质,然而其成像速度较为缓慢,难以实现切实且迅速的检测。为了实现对葵花籽饱满度的快速检测,该研究将压缩感知与注意力增强超分辨率生成对抗网络(A-ESRGAN)模型相结合应用于太赫兹成...太赫兹成像技术虽已被证实能够用于检测葵花籽内部品质,然而其成像速度较为缓慢,难以实现切实且迅速的检测。为了实现对葵花籽饱满度的快速检测,该研究将压缩感知与注意力增强超分辨率生成对抗网络(A-ESRGAN)模型相结合应用于太赫兹成像领域。首先,选用压缩采样匹配追踪(compressive sampling matching pursuit,CoSaMP)重构算法来验证不同测量矩阵的性能,根据最佳综合性能选取高斯矩阵作为测量矩阵。其次,通过比较基于交替方向乘子法(alternating direction method of multipliers,ADMM)结合全变分(total variation,TV)正则化(ADMM_TV)和子空间追踪(subspace pursuit,SP)等5种重构算法的峰值信噪比和重构时间等评价指标评估图像重建质量。结果表明ADMM_TV在峰值信噪比、均方误差、结构相似性指数表现最佳,自然图像质量评估器在测量比例超过6.0%最低,尽管重构时间无明显优势,但综合表现优于其他算法。最后,运用多尺度注意力增强超分辨率生成对抗网络(A-ESRGANmulti)模型对压缩感知不同采样率的重构图像进行处理,其效果优于真实图像增强超分辨率生成对抗网络(RealESRGAN)和单尺度注意力增强超分辨率生成对抗网络(A-ESRGAN-single),提升了图像质量,使边缘对比度得以提高,为后续的图像分割提供了便利。研究表明,压缩感知与A-ESRGAN-multi模型相结合用于检测葵花籽饱满度是可行的,验证集的饱满度误差平均为2.50%,最大检测误差为6.41%。综上所述,将压缩感知与A-ESRGAN-multi模型相结合,能够有效地节省82.5%的采样时间,为葵花籽的品质检测开辟了新的途径。展开更多
针对现有水平吸盘式排种器种盘结构复杂、整体气腔体积大、气压分布不均匀、气流不稳定、受风量和压力因素影响大等问题,该文设计了一种多气道气吸板式排种器。排种器吸种板采用分气道组合气腔结构,依靠吸种板的来回翻转和种箱的上下移...针对现有水平吸盘式排种器种盘结构复杂、整体气腔体积大、气压分布不均匀、气流不稳定、受风量和压力因素影响大等问题,该文设计了一种多气道气吸板式排种器。排种器吸种板采用分气道组合气腔结构,依靠吸种板的来回翻转和种箱的上下移动来实现充种和排种;按超级稻每个取秧面积2±1粒的机插育秧播种要求,吸种板采用在单位取秧面积内双孔对角布置的吸种气孔设计方案;对研制的排种器,以两优培九超级稻为试验对象,选取真空度、种箱移动速度、充种角度以及吸孔直径作为试验因素,进行充种性能的正交试验,通过试验得出充种性能最优参数组合为种箱移动速度0.12 m/s、真空度1.5 k Pa、充种角度120°、吸孔直径1.0 mm,最优参数组合下的充种合格率94.26%、漏播率2.47%、重播率3.27%;在充种性能最优参数组合下,选择不同播种效率作进一步播种性能试验,当播种效率为300盘/h时,合格率达到90.52%,满足了超级稻精密育秧播种要求。研究结果对保证超级稻育苗质量、实现机械化种植、增加产量和收益具有重要意义。展开更多
基金supported by the China Agriculture Research System(CARS-13)the National Natural Science Foundation of China(31771833)+1 种基金the Hebei Province Science and Technology Support Program(16226301D)Key Projects of Science and Technology Research in Higher Education Institution of Hebei province(ZD2015056)
文摘To dissect the genetic mechanism of multi-seed pod in peanut, we explored the QTL/gene controlling multi-seed pod and analyzed the interaction effect of QTL and environment. Two hundred and forty eight recombinant inbred lines(RIL) from cross Silihong × Jinonghei 3 were used as experimental materials planted in 8 environments from 2012 to 2017. Three methods of analysis were performed. These included individual environment analysis, joint analysis in multiple environments, and epistatic interaction analysis for multi-seed pod QTL. Phenotypic data and best linear unbiased prediction(BLUP) value of the ratio of multi-seed pods per plant(RMSP) were used for QTL mapping. Seven QTL detected by the individual environmental mapping analysis and were distributed on linkage groups 1, 6, 9, 14, 19(2), and 21. Each QTL explained 4.42%–11.51% of the phenotypic variation in multi-seed pod, and synergistic alleles of5 QTL were from the Silihong parent. One QTL, explaining 4.93% of the phenotypic variation was detected using BLUP data, and this QTL mapped in the same interval as q RMSP19.1 detected in the individual environment analysis. Seventeen additive QTL were identified by joint analysis across multiple environments. A total of 43 epistatic QTL were detected by ICIM-EPI mapping in the multiple environment trials(MET) module, and involved 57 loci. Two main-effect QTL related to multi-seed pod in peanut were filtered. We also found that RMSP had a highly significant positive correlation with pod yield per plant(PY), and epistatic effects were much more important than additive effects. These results provide theoretical guidance for the genetic improvement of germplasm resources and further fine mapping of related genes in peanut.
基金Supported by the National Natural Science Foun-dation of China (60473072)
文摘The key problem of securing multieast is to generate, distribute and update Session Encryption Key（SEK）. Polynomial expansion with multi-seed （MPE） scheme is an approach which is based on Polynomial expansion （PE） scheme and overcomes PE＇s shortage. Its operation is demonstrated by using multi-seed, the group member is partitioned to many subgroups. While updating the SEK, computation is needed only in one of subgroups, the other of them will use the computation history to update their SEK. The key problems to design a MPE scheme application includes to find a feasible one way function as well as to generate a Strict Prime Number （SPN）. Those technologies with multi-seed and computation history concepts make MPE as a good choice in practical applications. A prototype test system is designed and solutions of all above mentioned problems are included in this proposed paper.
文摘太赫兹成像技术虽已被证实能够用于检测葵花籽内部品质,然而其成像速度较为缓慢,难以实现切实且迅速的检测。为了实现对葵花籽饱满度的快速检测,该研究将压缩感知与注意力增强超分辨率生成对抗网络(A-ESRGAN)模型相结合应用于太赫兹成像领域。首先,选用压缩采样匹配追踪(compressive sampling matching pursuit,CoSaMP)重构算法来验证不同测量矩阵的性能,根据最佳综合性能选取高斯矩阵作为测量矩阵。其次,通过比较基于交替方向乘子法(alternating direction method of multipliers,ADMM)结合全变分(total variation,TV)正则化(ADMM_TV)和子空间追踪(subspace pursuit,SP)等5种重构算法的峰值信噪比和重构时间等评价指标评估图像重建质量。结果表明ADMM_TV在峰值信噪比、均方误差、结构相似性指数表现最佳,自然图像质量评估器在测量比例超过6.0%最低,尽管重构时间无明显优势,但综合表现优于其他算法。最后,运用多尺度注意力增强超分辨率生成对抗网络(A-ESRGANmulti)模型对压缩感知不同采样率的重构图像进行处理,其效果优于真实图像增强超分辨率生成对抗网络(RealESRGAN)和单尺度注意力增强超分辨率生成对抗网络(A-ESRGAN-single),提升了图像质量,使边缘对比度得以提高,为后续的图像分割提供了便利。研究表明,压缩感知与A-ESRGAN-multi模型相结合用于检测葵花籽饱满度是可行的,验证集的饱满度误差平均为2.50%,最大检测误差为6.41%。综上所述,将压缩感知与A-ESRGAN-multi模型相结合,能够有效地节省82.5%的采样时间,为葵花籽的品质检测开辟了新的途径。
基金国家自然科学基金(the National Natural Science Foundation of China under Grant No.60603053)国家教育部重点科技项目(the Key Technologies Project of the Ministry of Education of China No.05128)。
文摘针对现有水平吸盘式排种器种盘结构复杂、整体气腔体积大、气压分布不均匀、气流不稳定、受风量和压力因素影响大等问题,该文设计了一种多气道气吸板式排种器。排种器吸种板采用分气道组合气腔结构,依靠吸种板的来回翻转和种箱的上下移动来实现充种和排种;按超级稻每个取秧面积2±1粒的机插育秧播种要求,吸种板采用在单位取秧面积内双孔对角布置的吸种气孔设计方案;对研制的排种器,以两优培九超级稻为试验对象,选取真空度、种箱移动速度、充种角度以及吸孔直径作为试验因素,进行充种性能的正交试验,通过试验得出充种性能最优参数组合为种箱移动速度0.12 m/s、真空度1.5 k Pa、充种角度120°、吸孔直径1.0 mm,最优参数组合下的充种合格率94.26%、漏播率2.47%、重播率3.27%;在充种性能最优参数组合下,选择不同播种效率作进一步播种性能试验,当播种效率为300盘/h时,合格率达到90.52%,满足了超级稻精密育秧播种要求。研究结果对保证超级稻育苗质量、实现机械化种植、增加产量和收益具有重要意义。
