Dataset Information

High Potassium Application Rate Increased Grain Yield of Shading-Stressed Winter Wheat by Improving Photosynthesis and Photosynthate Translocation.

ABSTRACT: Wheat (Triticum aestivum L) production on the Huang-Huai Plain of China has substantially affected in the past 50 years as a result of the decreasing total solar radiation and sunshine hours. Potassium has a significant effect on improving leaf photosynthesis ability under stress conditions. Five potassium application rates (K), 0 (K0), 50 (K50), 100 (K100), 150 (K150), and 250 (K250) mg K2O kg-1 soil, combined with two shading levels, no shading (NS) and shading at early filling stage for 10 days (SE), were used to investigate the effects of K application on winter wheat growth under SE condition. Under NS condition, the parameters related to chlorophyll fluorescence characteristics, dry matter productivity and grain yields reached the maximum values at a middle K application rate (100 mg K2O kg-1 soil). Shading stress significantly reduced leaf SPAD value, showed negative effects on chlorophyll fluorescence characteristics and reduced grain yield of winter wheat. However, as the result of the interaction of K×S, compared to NS condition, higher K application rate (150 mg and 250 K2O kg-1 soil) was beneficial in terms of achieving a higher grain yield of winter wheat under SE by improving leaf SPAD value, alleviating the damage of SE on the winter wheat photosynthetic system, and increasing fructan content and dry matter translocation percentage.

SUBMITTER: Wang Y

PROVIDER: S-EPMC7058633 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

High Potassium Application Rate Increased Grain Yield of Shading-Stressed Winter Wheat by Improving Photosynthesis and Photosynthate Translocation.

Wang Yi Y Zhang Zhongkui Z Liang Yuanyuan Y Han Yulong Y Han Yanlai Y Tan Jinfang J

Frontiers in plant science 20200228

Wheat (Triticum aestivum L) production on the Huang-Huai Plain of China has substantially affected in the past 50 years as a result of the decreasing total solar radiation and sunshine hours. Potassium has a significant effect on improving leaf photosynthesis ability under stress conditions. Five potassium application rates (K), 0 (K0), 50 (K50), 100 (K100), 150 (K150), and 250 (K250) mg K2O kg-1 soil, combined with two shading levels, no shading (NS) and shading at ...[more]

PMID: 32184793

Similar Datasets

Project description:Genomic selection (GS) is a strategy to predict the genetic merits of individuals using genome-wide markers. However, GS prediction accuracy is affected by many factors, including missing rate and minor allele frequency (MAF) of genotypic data, GS models, trait features, etc. In this study, we used one wheat population to investigate prediction accuracies of various GS models on yield and yield-related traits from various quality control (QC) scenarios, missing genotype imputation, and genome-wide association studies (GWAS)-derived markers. Missing rate and MAF of single nucleotide polymorphism (SNP) markers were two major factors in QC. Five missing rate levels (0%, 20%, 40%, 60%, and 80%) and three MAF levels (0%, 5%, and 10%) were considered and the five-fold cross validation was used to estimate the prediction accuracy. The results indicated that a moderate missing rate level (20% to 40%) and MAF (5%) threshold provided better prediction accuracy. Under this QC scenario, prediction accuracies were further calculated for imputed and GWAS-derived markers. It was observed that the accuracies of the six traits were related to their heritability and genetic architecture, as well as the GS prediction model. Moore-Penrose generalized inverse (GenInv), ridge regression (RidgeReg), and random forest (RForest) resulted in higher prediction accuracies than other GS models across traits. Imputation of missing genotypic data had marginal effect on prediction accuracy, while GWAS-derived markers improved the prediction accuracy in most cases. These results demonstrate that QC on missing rate and MAF had positive impact on the predictability of GS models. We failed to identify one single combination of QC scenarios that could outperform the others for all traits and GS models. However, the balance between marker number and marker quality is important for the deployment of GS in wheat breeding. GWAS is able to select markers which are mostly related to traits, and therefore can be used to improve the prediction accuracy of GS.

Project description:Increased genetic gain for complex traits in plant breeding programs can be achieved through different selection strategies. The objective of this study was to compare potential gains for grain yield in a winter wheat breeding program through estimating response to selection R values across several selection approaches including phenotypic (PS), marker-based (MS), genomic (GS), and a combination of PS and GS (PS+GS). Ten populations of Washington State University (WSU) winter wheat breeding lines including a diversity panel and F5 and double haploid lines evaluated from 2015 to 2019 growing seasons for grain yield in Lind and Pullman, WA, USA were used in the study. Selection was conducted by selecting the top 20% of lines based on observed yield (PS strategy), genomic estimated breeding values (GS), presence of yield "enhancing" alleles of the most significant single nucleotide polymorphism (SNP) markers identified from genome-wide association mapping (MS), and high observed yield and estimated breeding values (PS+GS). Overall, PS compared to other individual selection strategies (MS and GS) showed the highest mean response (R = 0.61) within the same environment. When combined with GS, a 23% improvement in R for yield was observed, indicating that gains could be improved by complementing traditional PS with GS within the same environment. Validating selection strategies in different environments resulted in low to negative R values indicating the effects of genotype-by-environment interactions for grain yield. MS was not successful in terms of R relative to the other selection approaches; using this strategy resulted in a significant (P < 0.05) decrease in response to selection compared with the other approaches. An integrated PS+GS approach could result in optimal genetic gain within the same environment, whereas a PS strategy might be a viable option for grain yield validated in different environments. Altogether, we demonstrated that gains through increased response to selection for yield could be achieved in the WSU winter wheat breeding program by implementing different selection strategies either exclusively or in combination.

Dataset Information

High Potassium Application Rate Increased Grain Yield of Shading-Stressed Winter Wheat by Improving Photosynthesis and Photosynthate Translocation.

Publications

High Potassium Application Rate Increased Grain Yield of Shading-Stressed Winter Wheat by Improving Photosynthesis and Photosynthate Translocation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets