Family selection and evaluation of Larix gmelinii var.principis-rupprechtii(Mayr.)Pilger based on stem analysis data at multiple sites

Larix gmelinii var.principis-rupprechtii(Mayr.)Pilger is an important native tree species in North China with advantages of fast growth,straight trunk,and good wood properties.The multi-year and multi-site breeding research of families of the species has not been reported previously.Based on diameter at breast height(DBH),height and volume of 25 families on four experimental sites,we calculated variance components,genetic parameters,juvenile and mature trait correlations and made genotype main effect plus genotype×environment interaction effect(GGE)biplot based on the breeding values estimated using the method of best linear unbiased prediction(BLUP).Compared with height,DBH and volume had higher heritability and larger variation coefficients,making them the more suitable traits for family selection and evaluation.Based on these,GGE biplots containing 20 combinations of site×age were drawn using data at 13 to 17 years when the interactions between family and location were strong.Test sites classifications based on DBH,and volume were inconsistent,with two categories for DBH and one for volume.The Guyuan site was the most suitable with strong discriminating ability,high representativeness and stability among tree ages.Integrating the ranking results of DBH and volume,families 66,76,82 and 111 were high-yielding and stable,families 78 and96 were high-yielding with above average stability,families72 and 79 were high-yielding with below average stability,whereas stability of family 100 was inconsistent between DBH and volume.Early selection based on DBH was convenient and reliable,and can be made at seven years.This study provides support for the selection of Larix gmelinii var.principis-rupprechtii families in Hebei province and an example for the application of stem analysis data from multiple sites in tree breeding.

Mixed Model, AMMI and Eberhart-Russel Comparison via Simulation on Genotype ×Environment Interaction Study in Sugarcane

Brazil is the world leader in sugarcane production and the largest sugar exporter. Developing new varieties is one of the main factors that contribute to yield increase. In order to select the best genotypes, during the final selection stage, varieties are tested in different environments (locations and years), and breeders need to estimate the phenotypic performance for main traits such as tons of cane yield per hectare (TCH) considering the genotype × environment interaction (GEI) effect. Geneticists and biometricians have used different methods and there is no clear consensus of the best method. In this study, we present a comparison of three methods, viz. Eberhart-Russel (ER), additive main effects and multiplicative interaction (AMMI) and mixed model (REML/BLUP), in a simulation study performed in the R computing environment to verify the effectiveness of each method in detecting GEI, and assess the particularities of each method from a statistical standpoint. In total, 63 cases representing different conditions were simulated, generating more than 34 million data points for analysis by each of the three methods. The results show that each method detects GEI differently in a different way, and each has some limitations. All three methods detected GEI effectively, but the mixed model showed higher sensitivity. When applying the GEI analysis, firstly it is important to verify the assumptions inherent in each method and these limitations should be taken into account when choosing the method to be used.

Stability of Soybean Genotypes and Their Classification into Relative Maturity Groups in Brazil

The stability of soybean genotypes is very important in breeding programs for not only the evaluation, selection, and production of cultivars but also the establishment of parameters required for the classification of genotypes into relative maturity groups (RMG). The aim of this study was to define stable genotypes for traits, such as days to flowering, days to maturity, and length of the reproductive period, and to classify them into RMG. For this purpose, 20 commercial soybean cultivars were evaluated in 12 environments distributed in the major producing regions of Brazil. Assessments according to the Eberhart and Russell method and the additive main effects and multiplicative interaction (AMMI) method were effective in the identification of stable genotypes and their classification into RMG. These methods can also be used collectively for this purpose. Our results showed that the AMMI method led to a better interpretation of genotype-environment interactions. Thus, RMG obtained on the basis of stable genotypes represented a good estimate of the relative maturity of soybean crops throughout Brazil. *Corresponding author.

Use of genotype-environment interactions to elucidate the pattern of maize root plasticity to nitrogen deficiency

Maize（Zea mays L.） root morphology exhibits a high degree of phenotypic plasticity to nitrogen（N） de ficiency,but the underlying genetic architecture remains to be investigated Using an advanced BC_4F_3 population,we investigated the root growth plasticity under two contrasted N levels and identi fied the quantitative trait loci（QTLs） with QTL-environment（Q×E）interaction effects. Principal components analysis（PCA） on changes of root traits to N de ficiency（D LN-HN） showed that root length and biomass contributed for 45.8% in the same magnitude and direction on the first PC,while root traits scattered highly on PC_2 and PC_3. Hierarchical cluster analysis on traits for D LN-HN further assigned the BC_4F_3 lines into six groups,in which the special phenotypic responses to N de ficiency was presented These results revealed the complicated root plasticity of maize in response to N de ficiency that can be caused by genotype environment（G×E） interactions. Furthermore,QTL mapping using a multi-environment analysis identi fied 35 QTLs for root traits. Nine of these QTLs exhibited signi ficant Q×E interaction effects. Taken together,our findings contribute to understanding the phenotypic and genotypic pattern of root plasticity to N de ficiency,which will be useful for developing maize tolerance cultivars to N de ficiency.

Genetic interrogation of phenotypic plasticity informs genome-enabled breeding in cotton

Phenotypic plasticity, or the ability to adapt to and thrive in changing climates and variable environments, is essential for developmental programs in plants. Despite its importance, the genetic underpinnings of phenotypic plasticity for key agronomic traits remain poorly understood in many crops. In this study, we aim to fill this gap by using genome-wide association studies to identify genetic variations associated with phenotypic plasticity in upland cotton (Gossypium hirsutum L.). We identified 73 additive quantitative trait loci (QTLs), 32 dominant QTLs, and 6799 epistatic QTLs associated with 20 traits. We also identified 117 additive QTLs, 28 dominant QTLs, and 4691 epistatic QTLs associated with phenotypic plasticity in 19 traits. Our findings reveal new genetic factors, including additive, dominant, and epistatic QTLs, that are linked to phenotypic plasticity and agronomic traits. Meanwhile, we find that the genetic factors controlling the mean phenotype and phenotypic plasticity are largely independent in upland cotton, indicating the potential for simultaneous improvement. Additionally, we envision a genomic design strategy by utilizing the identified QTLs to facilitate cotton breeding. Taken together, our study provides new insights into the genetic basis of phenotypic plasticity in cotton, which should be valuable for future breeding.

Advances in crop phenotyping and multi-environment trials

Efficient evaluation of crop phenotypes is a prerequisite for breeding, cultivar adoption, genomics and phenomics study. Plant genotyping is developing rapidly through the use of high-throughput sequencing techniques,while plant phenotyping has lagged far behind and it has become the rate-limiting factor in genetics, large-scale breeding and development of new cultivars. In this paper,we consider crop phenotyping technology under three categories. The first is high-throughput phenotyping techniques in controlled environments such as greenhouses or specifically designed platforms. The second is a phenotypic strengthening test in semi-controlled environments, especially for traits that are difficult to be tested in multi-environment trials(MET), such as lodging, drought and disease resistance. The third is MET in uncontrolled environments, in which crop plants are managed according to farmer's cultural practices. Research and application of these phenotyping techniques are reviewed and methods for MET improvement proposed.