Population Construction and Super-high Yield Characteristics of Japonica Super Rice in Cold Regions

[Objective] This study was conducted to construct a super-high yield population of Japnica rice in cold regions of North China and to explore its characteristics. [Method] The super rice variety Longjing 21 was selected as the experimental material. Different row spacing（two levels）, plant spacing（three levels） and seedling number per hill（three levels） were designed in field trials. Then, the growth stages,dry matter accumulation, leaf area, yield and yield components of these different treatments were measured. [Result] Rice yield had significantly negative correlation with plant spacing and row spacing, but no significant correlation with seedling number per hill. Rice yield was mainly affected by plant spacing, and less affected by seedling number per hill. The best recommended specifications for plant spacing of super rice variety Longjing 21 were 24 cm for row spacing, 12 cm for plant spacing and five seedlings per hill, and the expected yield was 10 473.0 kg/hm^2.The increased number of total spikelets（4.5×108hm2or more） in populations was the major reason for high yield. Super-high yield populations had fewer tillers at the early growth stage and achieved the expected number of productive tillers at critical leaf-age（June 25）, and tiller number peaked at jointing stage（July 6） and was about 1.2 times of the expected number. The percentage of productive tillers in total tillers of super-high yield population was more than 85% at heading stage. At middle growth stage（from jointing to heading stage）, the dry matter accumulation, leaf area index（LAI） at heading stage, effective leaf area, spikelet number of population,spikelet number per leaf area unit（cm2）, and culm-sheath weight per stem of super-high yield population were significantly higher than those of other populations.At late growth stage（from heading to maturity stage）, the leaf area decreasing rate of super-high yield population was significantly smaller than that of other populations. At late growth stage（from heading to maturity stage）, the leaf area decreasing rate, crop growth rate, net assimilation rate, biomass accumulation, number of filled grains per leaf area unit（cm^2） and grain weight per leaf area unit（cm^2） of high-yield population were significantly higher than those of other populations. Output and translocation of dry matter（weight per stem and sheath and total filling rate at maturity） from heading to milky stage of super-high yield population were significantly higher than those of other populations. [Conclusion] The characteristics of superhigh yield rice in cold region of North China are enriching the amount of actual filling of sink through improving photosynthetic efficiency from heading to maturity stage on the basis of enough panicle numbers.

Evaluating the performance of genomic selection on purebred population by incorporating crossbred data in pigs

Genomic selection(GS)has been widely used in livestock,which greatly accelerated the genetic progress of complex traits.The population size was one of the significant factors affecting the prediction accuracy,while it was limited by the purebred population.Compared to directly combining two uncorrelated purebred populations to extend the reference population size,it might be more meaningful to incorporate the correlated crossbreds into reference population for genomic prediction.In this study,we simulated purebred offspring(PAS and PBS)and crossbred offspring(CAB)base on real genotype data of two base purebred populations(PA and PB),to evaluate the performance of genomic selection on purebred while incorporating crossbred information.The results showed that selecting key crossbred individuals via maximizing the expected genetic relationship(REL)was better than the other methods(individuals closet or farthest to the purebred population,CP/FP)in term of the prediction accuracy.Furthermore,the prediction accuracy of reference populations combining PA and CAB was significantly better only based on PA,which was similar to combine PA and PAS.Moreover,the rank correlation between the multiple of the increased relationship(MIR)and reliability improvement was 0.60-0.70.But for individuals with low correlation(Cor(Pi,PA or B),the reliability improvement was significantly lower than other individuals.Our findings suggested that incorporating crossbred into purebred population could improve the performance of genetic prediction compared with using the purebred population only.The genetic relationship between purebred and crossbred population is a key factor determining the increased reliability while incorporating crossbred population in the genomic prediction on pure bred individuals.