Dataset Information

Biostimulant Effects of Glutacetine® and Its Derived Formulations Mixed With N Fertilizer on Post-heading N Uptake and Remobilization, Seed Yield, and Grain Quality in Winter Wheat.

ABSTRACT: Biostimulants could play an important role in agriculture particularly for increasing N fertilizer use efficiency that is essential for maintaining both yield and grain quality in bread wheat, which is a major global crop. In the present study, we examined the effects of mixing urea-ammonium-nitrate fertilizer (UAN) or urea with five new biostimulants containing Glutacetine® or its derivative formulations (VNT1, 2, 3, and 4) on the physiological responses, agronomic traits, and grain quality of winter wheat. A first experiment under greenhouse conditions showed that VNT1, VNT3, and VNT4 significantly increased the seed yield and grain numbers per ear. VNT4 also enhanced total plant nitrogen (N) and total grain N, which induced a higher N Harvest Index (NHI). The higher post-heading N uptake (for VNT1 and VNT4) and the acceleration of senescence speed with all formulations enabled better nutrient remobilization efficiency, especially in terms of N mobilization from roots and straw toward the grain with VNT4. The grain ionome was changed by the formulations with the bioavailability of iron improved with the addition of VNT4, and the phytate concentrations in flour were reduced by VNT1 and VNT4. A second experiment in three contrasting field trials confirmed that VNT4 increased seed yield and N use efficiency. Our investigation reveals the important role of these new formulations in achieving significant increases in seed yield and grain quality.

SUBMITTER: Maignan V

PROVIDER: S-EPMC7691253 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Biostimulant Effects of Glutacetine® and Its Derived Formulations Mixed With N Fertilizer on Post-heading N Uptake and Remobilization, Seed Yield, and Grain Quality in Winter Wheat.

Maignan Victor V Bernay Benoit B Géliot Patrick P Avice Jean-Christophe JC

Frontiers in plant science 20201113

Biostimulants could play an important role in agriculture particularly for increasing N fertilizer use efficiency that is essential for maintaining both yield and grain quality in bread wheat, which is a major global crop. In the present study, we examined the effects of mixing urea-ammonium-nitrate fertilizer (UAN) or urea with five new biostimulants containing Glutacetine® or its derivative formulations (VNT1, 2, 3, and 4) on the physiological responses, agronomic traits, and grain quality of ...[more]

PMID: 33281859

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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.

Dataset Information

Biostimulant Effects of Glutacetine® and Its Derived Formulations Mixed With N Fertilizer on Post-heading N Uptake and Remobilization, Seed Yield, and Grain Quality in Winter Wheat.

Publications

Biostimulant Effects of Glutacetine® and Its Derived Formulations Mixed With N Fertilizer on Post-heading N Uptake and Remobilization, Seed Yield, and Grain Quality in Winter Wheat.

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