Relationship Between Plant Type and Grain Quality of Japonica Hybrid Rice in Northern China

Plant type and grain quality are two major aspects in rice breeding. Using canonical correlation analysis and canonical redundancy analysis, the relationship between plant type traits and rice grain quality traits was studied with 100 crosses derived from 10 sterile lines × 10 restorer lines. There was a complex relationship between parts of the traits of the two aspects. The angle of the 2nd leaf from the top and single panicle weight played important roles in plant type system and amylose content and grain length in grain quality system. The angle of the 2nd leaf from the top, plant height and single panicle weight had a great effect on grain quality traits, and amylose content, brown rice rate and translucency were easily influenced by plant type traits. Selection index model indicated that japonica hybrid rice in Northern China with good quality was characterized by broad flag leaf and 2nd leaf from the top, narrow and short 3rd leaf from the top, low plant height, short culm, long and more panicles and low single panicle weight.

Improvement of Fiber Quality by Distant Hybridization in the Green Cotton

In order to improve fiber quality of green cotton,a wide hybrid was used between a green fiber cotton and Sea Island cotton.The results show that the hybrid F1 plants were stable,but F2

Breeding of a New Fine Quality Fragrant Hybrid Rice Combination Taoxiangyoulijing

Taoxiangyoulijing is a new fine quality fragrant hybrid combination bred by matching the fine quality indica sterile line Taoxiang A with the fine quality restorer line R Lijing by Hunan Taohuayuan Agricultural Science and Technology Co.Ltd,Changsha Zhulixiang Agricultural Science and Technology Co.Ltd and Hunan Zhihe Seed Technology Co.,Ltd.The combination is featured with wide adaptability,high yield,strong resistance to rice blast,and GB class 2 high quality.In October 2019,Taoxiangyoulijing was approved by the National Crop Variety Certification Committee and it reached the second class standard of quality score according to the Standard for Fine Quality Rice,Ministry of Agriculture,China.

Preliminary studies on rice quality of japonica-indica hybrid rice

It has been proved that high yield combina-tions can be obtained via hybridization betweenindica and japonica rice. However, people haveworried about the quality of this kind of ricefor a long time. Our researches were mainlybased on the mating pattern of "japonica malesterile line/indica restorer line" to generateand select elite japonicalinous crosses. Ricequality is shown in table 1 and 2. The scores of rice quality of 7 crossesranged from 56-59, and met the high quality

Analysis of seed and maternal genetic effects on cooking quality characters in indica hybrid rice

We analysed seed and maternal genetic effects on characters of cooking quality in indica hybrid rice by using the model for quantitative characters of seeds of cereal crops. Incomplete diallel crosses were made by using six male sterile lines (Zhenshan 97A, Erjiuqing A, Erjiunan 1A, V20A, Zhe’nan 1A and Zhe’nan 3A)as females and three restorer lines(Cezao 2-2, T49 and 26715)as males. Sampled seeds were used to measure the cooking quality characters, including amylose content(%), gelatinization temperature(alkali spreading score)and gel consistency(mm). Results indicated that some rice cooking quality characters were controlled by both seed genes and maternal genes (see table). Gel consistency was mainly controlled by maternal effects, but also

Recognition of Hybrid PQ Disturbances Based on Multi-Resolution S-Transform and Decision Tree

Aiming at the problems of multiple types of power quality composite disturbances,strong feature correlation and high recognition error rate,a method of power quality composite disturbances identification based on multiresolution S-transform and decision tree was proposed.Firstly,according to IEEE standard,the signal models of seven single power quality disturbances and 17 combined power quality disturbances are given,and the disturbance waveform samples are generated in batches.Then,in order to improve the recognition accuracy,the adjustment factor is introduced to obtain the controllable time-frequency resolution through multi-resolution S-transform time-frequency domain analysis.On this basis,five disturbance time-frequency domain features are extracted,which quantitatively reflect the characteristics of the analyzed power quality disturbance signal,which is less than the traditional method based on S-transform.Finally,three classifiers such as K-nearest neighbor,support vector machine and decision tree algorithm are used to effectively complete the identification of power quality composite disturbances.Simulation results showthat the classification accuracy of decision tree algorithmis higher than that of K-nearest neighbor and support vector machine.Finally,the proposed method is compared with other commonly used recognition algorithms.Experimental results show that the proposedmethod is effective in terms of detection accuracy,especially for combined PQ interference.