[Objective] The aim was to build an evaluation method rapidly identifying wheat drought tolerance with near infrared diffuse reflectance spectroscopy. [Method] In the research, 36 wheat varieties in 2007-2009 were cho...[Objective] The aim was to build an evaluation method rapidly identifying wheat drought tolerance with near infrared diffuse reflectance spectroscopy. [Method] In the research, 36 wheat varieties in 2007-2009 were chosen and drought-tolerance degrees of wheat were graded and identified according to Winter-wheat Drought Tol- erance Evaluation Technical Standards （GB/T 21127-2007）, and harvest wheat grains underwent spectrum collection, with a full-spectrum analyzer, to establish a database. [Result] Based on qualitative analysis and full-spectrum correlation research, the coef- ficient of determination （RSQ） and cross-validation coefficient of determination （1-VR） were concluded at 0.697 5 and 0.600 2, showing near-infrared diffuse reflectance spectroscopy is of significant differences among wheat varieties and of significant or extremely significant correlation with drought-tolerance indices. [Conclusion] The re- search indicates that to evaluate drought-tolerance of wheat with near-infrared diffuse reflectance spectroscopy is a rapid and feasible way, which is simple, convenient without damages on grains, and of practical values for construction wheat drought-tol- erance evaluation index system and identification of breeding materials.展开更多
In order to precisely predict the hazard degree of goaf(HDG), the RS-TOPSIS model was built based on the results of expert investigation. To evaluate the HDG in the underground mine, five structure size factors, i.e. ...In order to precisely predict the hazard degree of goaf(HDG), the RS-TOPSIS model was built based on the results of expert investigation. To evaluate the HDG in the underground mine, five structure size factors, i.e. goaf span, exposed area, goaf height, goaf depth, and pillar width, were selected as the evaluation indexes. And based on rough dependability in rough set(RS)theory, the weights of evaluation indexes were identified by calculating rough dependability between evaluation indexes and evaluation results. Fourty goafs in some mines of western China, whose indexes parameters were measured by cavity monitoring system(CMS), were taken as evaluation objects. In addition, the characteristic parameters of five grades' typical goafs were built according to the interval limits value of single index evaluation. Then, using the technique for order preference by similarity to ideal solution(TOPSIS), five-category classification of HDG was realized based on closeness degree, and the HDG was also identified.Results show that the five-category identification of mine goafs could be realized by RS-TOPSIS method, based on the structure-scale-effect. The classification results are consistent with those of numerical simulation based on stress and displacement,while the coincidence rate is up to 92.5%. Furthermore, the results are more conservative to safety evaluation than numerical simulation, thus demonstrating that the proposed method is more easier, reasonable and more definite for HDG identification.展开更多
A new kind of region pair grey difference classifier was proposed. The regions in pairs associated to form a feature were not necessarily directly-connected, but were selected dedicatedly to the grey transition betwee...A new kind of region pair grey difference classifier was proposed. The regions in pairs associated to form a feature were not necessarily directly-connected, but were selected dedicatedly to the grey transition between regions coinciding with the face pattern structure. Fifteen brighter and darker region pairs were chosen to form the region pair grey difference features with high discriminant capabilities. Instead of using both false acceptance rate and false rejection rate, the mutual information was used as a unified metric for evaluating the classifying performance. The parameters of specified positions, areas and grey difference bias for each single region pair feature were selected by an optimization processing aiming at maximizing the mutual information between the region pair feature and classifying distribution, respectively. An additional region-based feature depicting the correlation between global region grey intensity patterns was also proposed. Compared with the result of Viola-like approach using over 2 000 features, the proposed approach can achieve similar error rates with only 16 features and 1/6 implementation time on controlled illumination images.展开更多
Tea plant is cross pollinated plant, it forms a variety of the tea Germplasm constantly in the long-term breeding process. Tea Germplasm resources are the material foundation for improving varieties and also the basic...Tea plant is cross pollinated plant, it forms a variety of the tea Germplasm constantly in the long-term breeding process. Tea Germplasm resources are the material foundation for improving varieties and also the basic research which is good for developing and expanding tea well-bred varieties in tea field, especially in quality selection and biotechnology research. Furthermore, excellent tea germplasm is primary condition for tea breeding and quality. Therefore, identification and screening excellent tea germplasm become particularly important. We need accelerate develop high-quality tea varieties, and it need to base on exploring and studying tea germplasm. This paper reviews the research progress of tea germplasm on identification from morphological characteristic, biological characteristic, quality characteristic, resistance and heredity. However, there are still some problems on identification and screening of tea germplasm, no effective methods have been found so far which apply on early identification and genetic engineering, so we should make intensive and long lasting study tea germplasm and analyze systematically various identification, which are benefit for breeding high-quality seeds, shortening the breeding period and summing the new way of breeding. We expect them to play the key roles and provide the theory basis for genetic improvement, classification and breeding in tea plant.展开更多
基金Supported by National Wheat Industry System(CARS-E-2-36)Henan Wheat Industry System(S2010-10-02)National Science and Technology Support Plan(2011BAD35B-03)~~
文摘[Objective] The aim was to build an evaluation method rapidly identifying wheat drought tolerance with near infrared diffuse reflectance spectroscopy. [Method] In the research, 36 wheat varieties in 2007-2009 were chosen and drought-tolerance degrees of wheat were graded and identified according to Winter-wheat Drought Tol- erance Evaluation Technical Standards （GB/T 21127-2007）, and harvest wheat grains underwent spectrum collection, with a full-spectrum analyzer, to establish a database. [Result] Based on qualitative analysis and full-spectrum correlation research, the coef- ficient of determination （RSQ） and cross-validation coefficient of determination （1-VR） were concluded at 0.697 5 and 0.600 2, showing near-infrared diffuse reflectance spectroscopy is of significant differences among wheat varieties and of significant or extremely significant correlation with drought-tolerance indices. [Conclusion] The re- search indicates that to evaluate drought-tolerance of wheat with near-infrared diffuse reflectance spectroscopy is a rapid and feasible way, which is simple, convenient without damages on grains, and of practical values for construction wheat drought-tol- erance evaluation index system and identification of breeding materials.
基金Project(51074178)supported by the National Natural Science Foundation of ChinaProject(2011ssxt274)supported by the Graduated Students’ Research and Innovation Foundation of Central South University of China+1 种基金Project(2011QNZT087)supported by the Graduated Students’ Free Exploration Foundation of Central South University of ChinaProject(1343-76140000011)supported by Scholarship Award for Excellent Doctoral Student granted by Ministry of Education,China
文摘In order to precisely predict the hazard degree of goaf(HDG), the RS-TOPSIS model was built based on the results of expert investigation. To evaluate the HDG in the underground mine, five structure size factors, i.e. goaf span, exposed area, goaf height, goaf depth, and pillar width, were selected as the evaluation indexes. And based on rough dependability in rough set(RS)theory, the weights of evaluation indexes were identified by calculating rough dependability between evaluation indexes and evaluation results. Fourty goafs in some mines of western China, whose indexes parameters were measured by cavity monitoring system(CMS), were taken as evaluation objects. In addition, the characteristic parameters of five grades' typical goafs were built according to the interval limits value of single index evaluation. Then, using the technique for order preference by similarity to ideal solution(TOPSIS), five-category classification of HDG was realized based on closeness degree, and the HDG was also identified.Results show that the five-category identification of mine goafs could be realized by RS-TOPSIS method, based on the structure-scale-effect. The classification results are consistent with those of numerical simulation based on stress and displacement,while the coincidence rate is up to 92.5%. Furthermore, the results are more conservative to safety evaluation than numerical simulation, thus demonstrating that the proposed method is more easier, reasonable and more definite for HDG identification.
基金Supported by the Joint Research Funds of Dalian University of Technology and Shenyang Automation Institute,Chinese Academy of Sciences
文摘A new kind of region pair grey difference classifier was proposed. The regions in pairs associated to form a feature were not necessarily directly-connected, but were selected dedicatedly to the grey transition between regions coinciding with the face pattern structure. Fifteen brighter and darker region pairs were chosen to form the region pair grey difference features with high discriminant capabilities. Instead of using both false acceptance rate and false rejection rate, the mutual information was used as a unified metric for evaluating the classifying performance. The parameters of specified positions, areas and grey difference bias for each single region pair feature were selected by an optimization processing aiming at maximizing the mutual information between the region pair feature and classifying distribution, respectively. An additional region-based feature depicting the correlation between global region grey intensity patterns was also proposed. Compared with the result of Viola-like approach using over 2 000 features, the proposed approach can achieve similar error rates with only 16 features and 1/6 implementation time on controlled illumination images.
文摘Tea plant is cross pollinated plant, it forms a variety of the tea Germplasm constantly in the long-term breeding process. Tea Germplasm resources are the material foundation for improving varieties and also the basic research which is good for developing and expanding tea well-bred varieties in tea field, especially in quality selection and biotechnology research. Furthermore, excellent tea germplasm is primary condition for tea breeding and quality. Therefore, identification and screening excellent tea germplasm become particularly important. We need accelerate develop high-quality tea varieties, and it need to base on exploring and studying tea germplasm. This paper reviews the research progress of tea germplasm on identification from morphological characteristic, biological characteristic, quality characteristic, resistance and heredity. However, there are still some problems on identification and screening of tea germplasm, no effective methods have been found so far which apply on early identification and genetic engineering, so we should make intensive and long lasting study tea germplasm and analyze systematically various identification, which are benefit for breeding high-quality seeds, shortening the breeding period and summing the new way of breeding. We expect them to play the key roles and provide the theory basis for genetic improvement, classification and breeding in tea plant.
