Litcius/Paper detail

Do lower nitrogen fertilization levels require breeding of different types of cultivars in triticale?

Jan E. Neuweiler, Johannes Trini, Hans Peter Maurer, Tobias Würschum

2021Theoretical and Applied Genetics12 citationsDOIOpen Access PDF

Abstract

KEY MESSAGE: The comparably low genotype-by-nitrogen level interaction suggests that selection in early generations can be done under high-input conditions followed by selection under different nitrogen levels to identify genotypes ideally suited for the target environment. Breeding high-yielding, nitrogen-efficient crops is of utmost importance to achieve greater agricultural sustainability. The aim of this study was to evaluate nitrogen use efficiency (NUE) of triticale, investigate long-term genetic trends and the genetic architecture, and develop strategies for NUE improvement by breeding. For this, we evaluated 450 different triticale genotypes under four nitrogen fertilization levels in multi-environment field trials for grain yield, protein content, starch content and derived indices. Analysis of temporal trends revealed that modern cultivars are better in exploiting the available nitrogen. Genome-wide association mapping revealed a complex genetic architecture with many small-effect QTL and a high level of pleiotropy for NUE-related traits, in line with phenotypic correlations. Furthermore, the effect of some QTL was dependent on the nitrogen fertilization level. High correlations of each trait between N levels and the rather low genotype-by-N-level interaction variance showed that generally the same genotypes perform well over different N levels. Nevertheless, the best performing genotype was always a different one. Thus, selection in early generations can be done under high nitrogen fertilizer conditions as these provide a stronger differentiation, but the final selection in later generations should be conducted with a nitrogen fertilization as in the target environment.

Topics & Concepts

TriticaleBiologyAgronomyGenetic architectureCultivarTraitSelection (genetic algorithm)Gene–environment interactionQuantitative trait locusHuman fertilizationPlant breedingNitrogenGenotypeBiotechnologyGeneticsProgramming languageComputer scienceQuantum mechanicsArtificial intelligencePhysicsGeneWheat and Barley Genetics and PathologyPlant nutrient uptake and metabolismGenetic Mapping and Diversity in Plants and Animals