Soybean is one of the most important sources of edible oil and proteins in the world. However, it suffers from many kinds of fungal diseases which is a major limiting factor in soybean production. The fungal disease c...Soybean is one of the most important sources of edible oil and proteins in the world. However, it suffers from many kinds of fungal diseases which is a major limiting factor in soybean production. The fungal disease can be effectively controlled by breeding plant cultivars with genetic transformation. In this study, the resistance to Phytophthora sojae of five bivalent transgenic soybean lines was identified using the hypocotyls inoculation technique. The lines were the T2 of the transgenic soybean which were transformed with kidney bean chitinase gene and barley ribosome inactivating protein gene, and were positive by Southern Blot analysis. The resistance difference was studied through comparing the death percentage of transgenic soybean with the control. The results showed that four lines were more resistant to P sojae, whereas other one had no significant difference in comparison with the control. These transgenic soybean lines with enhanced resistance to P sojae will be useful in soybean resistance breeding.展开更多
Plants have developed a complicated defense mechanism during evolution to resist the harmful pathogens they encountered.The mechanism involves the interaction of the plant resistance(R)
The all traditional electrical resistance tomography (ERT) sensors have a static structure, which cannot satisfy the intelligent requirements for adaptive optimization to ERT sensors that is subject to flow pattern ch...The all traditional electrical resistance tomography (ERT) sensors have a static structure, which cannot satisfy the intelligent requirements for adaptive optimization to ERT sensors that is subject to flow pattern changes during the real-time detection of two-phase flow. In view of this problem, an adaptive ERT sensor with a dynamic structure is proposed. The electrodes of the ERT sensor are arranged in an array structure, the flow pattern recognition technique is introduced into the ERT sensor design and accordingly an ERT flow pattern recognition method based on signal sparsity is proposed. This method uses the sparse representation of the signal to express the sampling voltage of the ERT system as a sparse combination and find its sparse solution to achieve the classification of different flow patterns. With the introduction of flow identification information, the sensor has an intelligent function of adaptively and dynamically adapting the sensor structure according to the real-time flow pattern change. The experimental results show that the sensor can automatically identify four typical flow patterns: core flow, bubble flow, laminar flow and circulation flow with recognition rates of 91%, 93%, 90% and 88% respectively. For different flow patterns, the dynamically optimized sensor can significantly improve the quality of ERT image reconstruction.展开更多
基金Supported by the National Items of Research and Industrial Development of Transgenic Plants(J99-B-013)
文摘Soybean is one of the most important sources of edible oil and proteins in the world. However, it suffers from many kinds of fungal diseases which is a major limiting factor in soybean production. The fungal disease can be effectively controlled by breeding plant cultivars with genetic transformation. In this study, the resistance to Phytophthora sojae of five bivalent transgenic soybean lines was identified using the hypocotyls inoculation technique. The lines were the T2 of the transgenic soybean which were transformed with kidney bean chitinase gene and barley ribosome inactivating protein gene, and were positive by Southern Blot analysis. The resistance difference was studied through comparing the death percentage of transgenic soybean with the control. The results showed that four lines were more resistant to P sojae, whereas other one had no significant difference in comparison with the control. These transgenic soybean lines with enhanced resistance to P sojae will be useful in soybean resistance breeding.
文摘Plants have developed a complicated defense mechanism during evolution to resist the harmful pathogens they encountered.The mechanism involves the interaction of the plant resistance(R)
基金Projects(51405381,51674188)supported by the National Natural Science Foundation of China
文摘The all traditional electrical resistance tomography (ERT) sensors have a static structure, which cannot satisfy the intelligent requirements for adaptive optimization to ERT sensors that is subject to flow pattern changes during the real-time detection of two-phase flow. In view of this problem, an adaptive ERT sensor with a dynamic structure is proposed. The electrodes of the ERT sensor are arranged in an array structure, the flow pattern recognition technique is introduced into the ERT sensor design and accordingly an ERT flow pattern recognition method based on signal sparsity is proposed. This method uses the sparse representation of the signal to express the sampling voltage of the ERT system as a sparse combination and find its sparse solution to achieve the classification of different flow patterns. With the introduction of flow identification information, the sensor has an intelligent function of adaptively and dynamically adapting the sensor structure according to the real-time flow pattern change. The experimental results show that the sensor can automatically identify four typical flow patterns: core flow, bubble flow, laminar flow and circulation flow with recognition rates of 91%, 93%, 90% and 88% respectively. For different flow patterns, the dynamically optimized sensor can significantly improve the quality of ERT image reconstruction.
