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Alteration in yield and oil quality traits of winter rapeseed by lodging at different planting density and nitrogen rates.

ABSTRACT: Lodging is a factor that negatively affects yield, seed quality, and harvest ability in winter rapeseed (Brassica napus L.). In this study, we quantified the lodging-induced yield losses, changes in fatty acid composition, and oil quality in rapeseed under different nitrogen application rates and planting densities. Field experiments were conducted in 2014-2017 for studying the effect of manually-induced lodging angles (0°, 30°, 60°, and 90°), 10, 20 and 30?d post-flowering at different densities and nitrogen application rates. The fertilization/planting density combination N270D45 produced the maximum observed yield and seed quality. Timing and angle of lodging had significant effects on yield. Lodging at 90° induced at 10?d post-flowering caused the maximum reduction in yield, biomass, and silique photosynthesis. Seed yield losses were higher at high N application rates, the maximum being at N360D45. Lodging decreased seed oil content and altered its fatty acid composition by increasing stearic and palmitic acid content, while decreasing linoleic and linolenic acid content, and deteriorating oil quality by increasing erucic acid and glucosinolate content. Therefore, lodging-induced yield loss and reduction in oil content might be reduced by selecting optimum N level and planting density.

SUBMITTER: Khan S

PROVIDER: S-EPMC5766575 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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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:BackgroundThe combination of mulch with N fertilizer application is a common agronomic technique used in the production of rainfed maize (Zea mays L.) to achieve higher yields under conditions of optimum planting density and adequate N supply. However, the combined effects of mulch, planting density, and N fertilizer application rate on plant N uptake and N translocation efficiency are not known. The objective of this study was to quantify the interaction effect of mulch, planting density, and N fertilizer application rate on maize grain yield, N uptake, N translocation, and N translocation efficiency. The experiment was arranged in a randomized complete block design with three factors (2 mulch levels × 2 planting densities × 4 N fertilizer application rates) replicated four times.ResultsThere was a significant interaction among mulch, plant density, and N fertilizer on maize grain yield, kernel number per cob, N uptake, N translocation, and N translocation efficiency. Averaged over the 3 years of the study, total plant N uptake at silking ranged from 79 to 149 kg N ha- 1 with no mulch and from 76 to 178 kg N ha- 1 with mulch. The N uptake at silking in different plant organs ranked as leaf > grain > stem > cob. Averaged across all factors, the highest N translocation was observed in leaves, which was 59.4 and 88.7% higher than observed in stems and ears, respectively. The mean vegetative organ N translocation efficiency averaged over mulch, planting density, and N fertilizer application rate treatments decreased in the order of leaf > stem > cob.ConclusionsMulch, planting density, and N fertilizer application rate not only have significant effects on improving maize grain yield and NUE, but also on N uptake, N translocation, and N translocation efficiency. Our results showed clearly that under high planting density, the combination of mulch and moderate N fertilizer application rate was the optimal strategy for increasing maize grain yield and N use efficiency.

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Alteration in yield and oil quality traits of winter rapeseed by lodging at different planting density and nitrogen rates.

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