A first generation sodium Laser Guide Star Adaptive Optics System(LGS-AOS) was developed and integrated into the Lijiang 1.8 m telescope in 2013. The LGS-AOS has three sub-systems:(1) a 20 W long pulsed sodium laser,(...A first generation sodium Laser Guide Star Adaptive Optics System(LGS-AOS) was developed and integrated into the Lijiang 1.8 m telescope in 2013. The LGS-AOS has three sub-systems:(1) a 20 W long pulsed sodium laser,(2) a 300-millimeter-diameter laser launch telescope, and(3) a 37-element compact adaptive optics system. On 2014 January 25, we obtained high resolution images of an mV8.18 star,HIP 43963, during the first light of the LGS-AOS. In this paper, the sodium laser, the laser launch telescope,the compact adaptive optics system and the first light results will be presented.展开更多
In wheat breeding, it is a difficult task to select the most suitable parents for making crosses aimed at the improvement of both grain yield and grain quality. By quantitative genetics theory,the best cross should ha...In wheat breeding, it is a difficult task to select the most suitable parents for making crosses aimed at the improvement of both grain yield and grain quality. By quantitative genetics theory,the best cross should have high progeny mean and large genetic variance, and ideally yield and quality should be less negatively or positively correlated. Usefulness is built on population mean and genetic variance, which can be used to select the best crosses or populations to achieve the breeding objective. In this study, we first compared five models(RR-BLUP, Bayes A, Bayes B, Bayes ridge regression, and Bayes LASSO) for genomic selection(GS) with respect to prediction of usefulness of a biparental cross and two criteria for parental selection, using simulation. The two parental selection criteria were usefulness and midparent genomic estimated breeding value(GEBV). Marginal differences were observed among GS models. Parental selection with usefulness resulted in higher genetic gain than midparent GEBV. In a population of 57 wheat fixed lines genotyped with 7588 selected markers, usefulness of each biparental cross was calculated to evaluate the cross performance, a key target of breeding programs aimed at developing pure lines. It was observed that progeny mean was a major determinant of usefulness, but the usefulness ratings of quality traits were more influenced by their genetic variances in the progeny population. Near-zero or positive correlations between yield and major quality traits were found in some crosses, although they were negatively correlated in the population of parents. A selection index incorporating yield, extensibility, and maximum resistance was formed as a new trait and its usefulness for selecting the crosses with the best potential to improve yield and quality simultaneously was calculated. It was shown that applying the selection index improved both yield and quality while retaining more genetic variance in the selected progenies than the individual trait selection. It was concluded that combining genomic selection with simulation allows the prediction of cross performance in simulated progenies and thereby identifies candidate parents before crosses are made in the field for pure-line breeding programs.展开更多
基金supported by the Creative Foundation of the Chinese Academy of Sciences,China
文摘A first generation sodium Laser Guide Star Adaptive Optics System(LGS-AOS) was developed and integrated into the Lijiang 1.8 m telescope in 2013. The LGS-AOS has three sub-systems:(1) a 20 W long pulsed sodium laser,(2) a 300-millimeter-diameter laser launch telescope, and(3) a 37-element compact adaptive optics system. On 2014 January 25, we obtained high resolution images of an mV8.18 star,HIP 43963, during the first light of the LGS-AOS. In this paper, the sodium laser, the laser launch telescope,the compact adaptive optics system and the first light results will be presented.
基金supported by the National Key Basic Research Program of China(2014CB138105)the National Natural Science Foundation of China(31371623)
文摘In wheat breeding, it is a difficult task to select the most suitable parents for making crosses aimed at the improvement of both grain yield and grain quality. By quantitative genetics theory,the best cross should have high progeny mean and large genetic variance, and ideally yield and quality should be less negatively or positively correlated. Usefulness is built on population mean and genetic variance, which can be used to select the best crosses or populations to achieve the breeding objective. In this study, we first compared five models(RR-BLUP, Bayes A, Bayes B, Bayes ridge regression, and Bayes LASSO) for genomic selection(GS) with respect to prediction of usefulness of a biparental cross and two criteria for parental selection, using simulation. The two parental selection criteria were usefulness and midparent genomic estimated breeding value(GEBV). Marginal differences were observed among GS models. Parental selection with usefulness resulted in higher genetic gain than midparent GEBV. In a population of 57 wheat fixed lines genotyped with 7588 selected markers, usefulness of each biparental cross was calculated to evaluate the cross performance, a key target of breeding programs aimed at developing pure lines. It was observed that progeny mean was a major determinant of usefulness, but the usefulness ratings of quality traits were more influenced by their genetic variances in the progeny population. Near-zero or positive correlations between yield and major quality traits were found in some crosses, although they were negatively correlated in the population of parents. A selection index incorporating yield, extensibility, and maximum resistance was formed as a new trait and its usefulness for selecting the crosses with the best potential to improve yield and quality simultaneously was calculated. It was shown that applying the selection index improved both yield and quality while retaining more genetic variance in the selected progenies than the individual trait selection. It was concluded that combining genomic selection with simulation allows the prediction of cross performance in simulated progenies and thereby identifies candidate parents before crosses are made in the field for pure-line breeding programs.
