Scientific Reports · 2020 · 46 citations · 40 references
AgricultureAgronomyPlant SciencesCrop ProductionPlant GeneticsPlant NutritionAmino Acid CompositionAmino Acid NutritionCrop NutritionProtein NutritionProtein QualitySeed Nutritional CompositionGrain Amino Acid CompositionHigh-yielding VarietiesNitrogen Effects On YieldNon-essential Amino AcidsSeed Amino Acid ProfileSeed Essential Amino AcidsSeed Protein Amino Acid CompositionTryptophan Content
Abstract Soybean [ Glycine max (L.) Merr.] is the most important oilseed crop for animal industry due to its high protein concentration and high relative abundance of essential and non-essential amino acids (AAs). However, the selection for high-yielding genotypes has reduced seed protein concentration over time, and little is known about its impact on AAs. The aim of this research was to determine the genetic shifts of seed composition for 18 AAs in 13 soybean genotypes released between 1980 and 2014. Additionally, we tested the effect of nitrogen (N) fertilization on protein and AAs trends. Soybean genotypes were grown in field conditions during two seasons under a control (0 N) and a N-fertilized treatment receiving 670 kg N ha −1 . Seed yield increased 50% and protein decreased 1.2% comparing the oldest and newest genotypes. The application of N fertilizer did not significantly affect protein and AAs concentrations. Leucine, proline, cysteine, and tryptophan concentrations were not influenced by genotype. The other AAs concentrations showed linear rates of decrease over time ranging from − 0.021 to − 0.001 g kg −1 year −1 . The shifts of 11 AAs (some essentials such as lysine, tryptophan, and threonine) displayed a relative-to-protein increasing concentration. These results provide a quantitative assessment of the trade-off between yield improvement and seed AAs concentrations and will enable future genetic yield gain without overlooking seed nutritional value.
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Fitting Linear Mixed-Effects Models Using <b>lme4</b>
Douglas M. Bates, Martin Mächler, Benjamin M. Bolker et al. · Journal of Statistical Software · 2015 · 85.6K citations · Full text
Official Methods of Analysis of
Analytical Chemistry · 1980 · 59.6K citations
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