The genetic similarity and genetic difference among improved japonica rice varieties from different countries (or regions and organizations) were detected. The aim is to provide genetic basis to the breeding of japo...The genetic similarity and genetic difference among improved japonica rice varieties from different countries (or regions and organizations) were detected. The aim is to provide genetic basis to the breeding of japonica rice varieties. The genetic similarity and cluster of 313 improved japonica varieties from 20 countries (or regions and organizations) were analyzed using the SSR marker. With 34 SSR primers which were polymorphic and uniformly distributed in rice genome, totally 198 alleles were detected among these improved varieties with the average number of alleles per pair of primers of 5.8235. RM320, RM531, RM1, RM21, and RM336 located more alleles, which were 16, 13, 12, 10, and 10 respectively. RM320, RM336, RM286, RM531, and RM21 showed higher genetic diversity indexes, which were 2.3668, 2.0041, 1.9684, 1.9508, and 1.7203, respectively. The genetic similarity for improved japonica varieties among different countries (or regions and organizations) were ranged from 0.279 to 0.918, and the mean value was 0.653. The rice varieties from countries whose latitude and geography position were all nearer were clustered together with higher genetic similarity indexes. The rice varieties from countries who had more different latitude and far geography position were clustered separately with lower genetic similarity indexes. The results indicated the genetic similarity indexes among improved japonica varieties had a close relationship with the geographical position, especially with the latitude.展开更多
This paper gives a practical schema for using DSP boards to construct Vehicle License Plate Recognition (VLPR) modules that could be embedded in any Intelligent Transportation System (ITS). Using DSP can avoid the hea...This paper gives a practical schema for using DSP boards to construct Vehicle License Plate Recognition (VLPR) modules that could be embedded in any Intelligent Transportation System (ITS). Using DSP can avoid the heavy investment in dedicated VLPR system and improve the computational power compared to PC software environment. Low cost, high computational power, and high flexibility of DSP provide the License Plate Recognition System (LPRS) an excellent cost-effective solution to execute the major part of the recognition tasks. This paper describes a successful implementation of VLPR system based on Texas Instruments (TI)'s TMS320DM642. The DSP board acquires video (which could be output to a monitor for surveillance) from a camera, captures images from the video, locates and recognizes the license plates in images, and then sends the recognized results and related images after compression to a host PC through the network. Finally, the overall software is optimized according to the features of DM642 chip. Experiments showed that the DSP VLPR system performs well on the local license plates, and that the processing speed and accuracy can meet the requirement of practical applications.展开更多
Video object segmentation is important for video surveillance, object tracking, video object recognition and video editing. An adaptive video segmentation algorithm based on hidden conditional random fields (HCRFs) is...Video object segmentation is important for video surveillance, object tracking, video object recognition and video editing. An adaptive video segmentation algorithm based on hidden conditional random fields (HCRFs) is proposed, which models spatio-temporal constraints of video sequence. In order to improve the segmentation quality, the weights of spatio-temporal con- straints are adaptively updated by on-line learning for HCRFs. Shadows are the factors affecting segmentation quality. To separate foreground objects from the shadows they cast, linear transform for Gaussian distribution of the background is adopted to model the shadow. The experimental results demonstrated that the error ratio of our algorithm is reduced by 23% and 19% respectively, compared with the Gaussian mixture model (GMM) and spatio-temporal Markov random fields (MRFs).展开更多
The culm length, panicle length, spikelets per panicle and panicle exsertion were evaluated by using F2:3 population including 200 lines derived from the cross of indica and japonica Milyang 23/Jileng 1 under five di...The culm length, panicle length, spikelets per panicle and panicle exsertion were evaluated by using F2:3 population including 200 lines derived from the cross of indica and japonica Milyang 23/Jileng 1 under five different environments of Beijing (natural normal growing environment), Kunming (natural cold environment), Gongzhuling of China (cold water irrigation) and Chuncheon of Korea (natural normal growing environment and cold water irrigation), and QTLs of these traits were analyzed by using SSR markers. The results showed that 44 QTLs related to these agronomic traits were detected under five different growing environments, and these QTLs have been located on 11 chromosomes except chromosome 9. The QTLs for qCLla, qCL1b, qCL5a, qCL6b, qPLla, qPL3a, qPL6b, qPL6c, qPL7b, qSP8b, qSPlc, qSP11a, qSP12, and qPE1 have been detected under more than two growing environments, and those that were little affected by environments, were stable QTLs. Among them, qCLla, qCLlb, qPLla, qSPlc, and qPE1 explained 24.2-55.2%, 22.7-39.9%, 12.5-27.7%, 14.4-33.5%, and 26.6-28.7% of observed phynotypic variation, respectively, which were major genes mainly appearing as overdominance. These QTLs cause the increase in action to culm length, panicle length, spikelets per panicle, and panicle exsertion under cold environment, showing that these QTLs were correlated with cold tolerance.展开更多
To provide a genetic basis for japonica rice breeding, the genetic similarity and cluster of 139 accessions of improved japonica rice varieties from 12 provinces and cities of China were analyzed using 34 SSR markers....To provide a genetic basis for japonica rice breeding, the genetic similarity and cluster of 139 accessions of improved japonica rice varieties from 12 provinces and cities of China were analyzed using 34 SSR markers. Totally 198 alleles were detected among these improved japonica rice varieties with the average number of alleles per pair of primers was 5.3235. RM320, RM531, RM1, RM286, and RM336 showed more alleles, which were 15, 12, 11, 9, and 9, respectively. RM320, RM336, RM286 and RM531 showed higher genetic diversity indexes; which were 2.3324, 2.0292, 1.8996, and 1.7820, respectively. The range of genetic similar index among improved japonica rice varieties from different provinces was from 0.321 to 0.914, with the average of 0.686. There was a high genetic similarity among improved japonica rice varieties from Heilongjiang, Jilin, Liaoning, Ningxia, and Yunnan, which were located in similar latitude or similar ecological environment, while there was a low genetic similarity between improved japonica rice varieties from Guizhou and Jiangsu, and other provinces which were located in more different latitudes and ecological environments. The markers of RM320, RM531, RM1, RM286, and RM336 fit to be used in analysis of genetic diversity for improved japonica rice variety. The genetic similarity among improved japonica rice varieties from different provinces was closely associated with genetic basis of parents, and was also correlated with latitude and ecological environment where the varieties were bred.展开更多
基金supported by the National Key Tech-nology Research and Development Program of China(2006BAD13B01)the Protective Program of Crop Germpalsm of China (NB05-070401-22-01)the Cooperative Research between China and Korea (2004-2007)
文摘The genetic similarity and genetic difference among improved japonica rice varieties from different countries (or regions and organizations) were detected. The aim is to provide genetic basis to the breeding of japonica rice varieties. The genetic similarity and cluster of 313 improved japonica varieties from 20 countries (or regions and organizations) were analyzed using the SSR marker. With 34 SSR primers which were polymorphic and uniformly distributed in rice genome, totally 198 alleles were detected among these improved varieties with the average number of alleles per pair of primers of 5.8235. RM320, RM531, RM1, RM21, and RM336 located more alleles, which were 16, 13, 12, 10, and 10 respectively. RM320, RM336, RM286, RM531, and RM21 showed higher genetic diversity indexes, which were 2.3668, 2.0041, 1.9684, 1.9508, and 1.7203, respectively. The genetic similarity for improved japonica varieties among different countries (or regions and organizations) were ranged from 0.279 to 0.918, and the mean value was 0.653. The rice varieties from countries whose latitude and geography position were all nearer were clustered together with higher genetic similarity indexes. The rice varieties from countries who had more different latitude and far geography position were clustered separately with lower genetic similarity indexes. The results indicated the genetic similarity indexes among improved japonica varieties had a close relationship with the geographical position, especially with the latitude.
基金the National Natural Science Foundation of China (No. 60473106)the Hi-Tech Research and Development Program (863) of China (Nos. 2007AA01Z311 and 2007AA04ZA5)
文摘This paper gives a practical schema for using DSP boards to construct Vehicle License Plate Recognition (VLPR) modules that could be embedded in any Intelligent Transportation System (ITS). Using DSP can avoid the heavy investment in dedicated VLPR system and improve the computational power compared to PC software environment. Low cost, high computational power, and high flexibility of DSP provide the License Plate Recognition System (LPRS) an excellent cost-effective solution to execute the major part of the recognition tasks. This paper describes a successful implementation of VLPR system based on Texas Instruments (TI)'s TMS320DM642. The DSP board acquires video (which could be output to a monitor for surveillance) from a camera, captures images from the video, locates and recognizes the license plates in images, and then sends the recognized results and related images after compression to a host PC through the network. Finally, the overall software is optimized according to the features of DM642 chip. Experiments showed that the DSP VLPR system performs well on the local license plates, and that the processing speed and accuracy can meet the requirement of practical applications.
基金Project supported by the National Natural Science Foundation of China (Nos. 60473106, 60273060 and 60333010)the Ministry of Education of China (No. 20030335064)the Education Depart-ment of Zhejiang Province, China (No. G20030433)
文摘Video object segmentation is important for video surveillance, object tracking, video object recognition and video editing. An adaptive video segmentation algorithm based on hidden conditional random fields (HCRFs) is proposed, which models spatio-temporal constraints of video sequence. In order to improve the segmentation quality, the weights of spatio-temporal con- straints are adaptively updated by on-line learning for HCRFs. Shadows are the factors affecting segmentation quality. To separate foreground objects from the shadows they cast, linear transform for Gaussian distribution of the background is adopted to model the shadow. The experimental results demonstrated that the error ratio of our algorithm is reduced by 23% and 19% respectively, compared with the Gaussian mixture model (GMM) and spatio-temporal Markov random fields (MRFs).
基金supported by the National Natural Science Foundation of China(30070421)the 10th Five Year National Key Research Program(2004BA525B02)Cooperative Research Between China and Korea(2002-2004).
文摘The culm length, panicle length, spikelets per panicle and panicle exsertion were evaluated by using F2:3 population including 200 lines derived from the cross of indica and japonica Milyang 23/Jileng 1 under five different environments of Beijing (natural normal growing environment), Kunming (natural cold environment), Gongzhuling of China (cold water irrigation) and Chuncheon of Korea (natural normal growing environment and cold water irrigation), and QTLs of these traits were analyzed by using SSR markers. The results showed that 44 QTLs related to these agronomic traits were detected under five different growing environments, and these QTLs have been located on 11 chromosomes except chromosome 9. The QTLs for qCLla, qCL1b, qCL5a, qCL6b, qPLla, qPL3a, qPL6b, qPL6c, qPL7b, qSP8b, qSPlc, qSP11a, qSP12, and qPE1 have been detected under more than two growing environments, and those that were little affected by environments, were stable QTLs. Among them, qCLla, qCLlb, qPLla, qSPlc, and qPE1 explained 24.2-55.2%, 22.7-39.9%, 12.5-27.7%, 14.4-33.5%, and 26.6-28.7% of observed phynotypic variation, respectively, which were major genes mainly appearing as overdominance. These QTLs cause the increase in action to culm length, panicle length, spikelets per panicle, and panicle exsertion under cold environment, showing that these QTLs were correlated with cold tolerance.
基金supported by the National Key Technology R&D Program of China(2006BAD13B01)the Protective Program of Crop Germpalsm of China[NB07-2130135(25-30-01)]
文摘To provide a genetic basis for japonica rice breeding, the genetic similarity and cluster of 139 accessions of improved japonica rice varieties from 12 provinces and cities of China were analyzed using 34 SSR markers. Totally 198 alleles were detected among these improved japonica rice varieties with the average number of alleles per pair of primers was 5.3235. RM320, RM531, RM1, RM286, and RM336 showed more alleles, which were 15, 12, 11, 9, and 9, respectively. RM320, RM336, RM286 and RM531 showed higher genetic diversity indexes; which were 2.3324, 2.0292, 1.8996, and 1.7820, respectively. The range of genetic similar index among improved japonica rice varieties from different provinces was from 0.321 to 0.914, with the average of 0.686. There was a high genetic similarity among improved japonica rice varieties from Heilongjiang, Jilin, Liaoning, Ningxia, and Yunnan, which were located in similar latitude or similar ecological environment, while there was a low genetic similarity between improved japonica rice varieties from Guizhou and Jiangsu, and other provinces which were located in more different latitudes and ecological environments. The markers of RM320, RM531, RM1, RM286, and RM336 fit to be used in analysis of genetic diversity for improved japonica rice variety. The genetic similarity among improved japonica rice varieties from different provinces was closely associated with genetic basis of parents, and was also correlated with latitude and ecological environment where the varieties were bred.