Nitrogen uptake dynamics of high and low protein wheat genotypes

Abstract

Increasing wheat (Triticum aestivum L.) yield and grain protein concentration (GPC) without excessive nitrogen (N) inputs requires understanding the genotypic variations in N accumulation, partitioning, and utilization strategies. This study evaluated whether high protein genotypes exhibit increased N accumulation (herein also expressed as N nutrition index, NNI) and partitioning (including remobilization from vegetative organs) compared to low-protein genotypes under low and high N conditions. Four winter wheat genotypes with similar yields but contrasting GPC were examined under two N rates (0 and 120 kg N ha^-1) across two environments and four growing seasons in Oklahoma, US. As expected, the high-protein genotypes Doublestop CL+ (Dob) and Green Hammer (Grn) had greater GPC than the medium- (Gallagher, Gal) and low-protein genotypes (Iba), without any difference in grain yield. Total plant N accumulation at maturity showed diminishing increases for greater grain yield, and low-protein genotype showed greater N utilization efficiency (NUtE) than high-protein genotypes. The high-protein genotype Grn tended to achieve higher GPC by increasing total N uptake, while Dob exhibited a tendency towards higher N partitioning to grain (NHI). The allometric relationship between total N accumulation and biomass remained unchanged for both high- and low-protein genotypes. The N remobilization patterns differed between high- and low-protein genotypes. As N conditions improved, the proportional contributions of remobilized N from leaves tended to increase, while contributions from stems and chaff tended to decrease or remained unchanged for high-protein genotypes. This study highlights the importance of both N uptake capacity and efficient N partitioning to the grain as critical traits for realizing wheat's dual goals of higher yield and protein. Leaf N remobilization plays a critical role during grain filling, sustaining plant N status and contributing to protein levels. The higher NUtE observed in the low-protein genotype Iba likely contributed to its lower GPC, emphasizing the trade-off between NUtE and GPC. The physiological strategies employed by high-protein genotypes, such as genotype Grn's tendency for increased N uptake and Dob's efficient N partitioning, provide a foundation for future breeding efforts aimed at developing resource-efficient and nutritionally superior wheat genotypes capable of achieving both increased yield and protein.

Keywords: N remobilization patterns; agronomic practices; breeding strategies; crop physiology; genotype selection; nitrogen use efficiency; nutrient partitioning; plant nutrition.

Figure 1

Mean grain yield (A), grain protein concentration (B) for each genotype, N rate and site on average of four growing seasons, and the relationship between grain yield and total N accumulation at maturity (C) for each site across two N rates (0N and 120N), four genotypes, and four growing seasons (n=96 observations). The solid lines represent the selected models for this relationship (Perkins, y = 0.12x²+ 55x-130, R² = 0.83; Stillwater, y = -0.11x² + 62x -418, R²=0.84), and the dashed lines are the 5% and 95% quantiles (minimum and maximum N utilization efficiency (i.e., NUtE, grain yield to whole plant N uptake ratio), respectively. The statistical analysis shown in (B) indicates that mean values with different letters are statistically different at p<0.05.

Figure 2

Relationship between total N and biomass accumulation at maturity for each site across four genotypes, two N rates (0N and 120N), and three growing seasons (2020, 2021, 2023) (n=96 observations) (Perkins, y = 0.011x-3.98, R²= 0.83, p<0.01 and Stillwater, y = 0.012x-10.9, R²=0.77, p<0.01). The solid lines represent the selected models to describe this relationship, and the dashed lines are the 5% and 95% quantiles (minimum and maximum, respectively).

Figure 3

The relationship between grain N and total N accumulation (i.e., slope = N Harvest Index [NHI]) for each site across four genotypes, two N rates (0N and 120N) and three growing seasons (2020, 2021, 2023) (n=96) (Perkins, y = 0.64x+2.6, R² = 0.96; Stillwater, y = 0.77x+3.09, R²=0.98). The solid lines are best-fitted functions for this relationship, and the dashed lines are the 5% and 95% quantiles (minimum and maximum, respectively).

Figure 4

Nitrogen remobilization of each vegetative organ (Organs RemN, kg ha^-1) at two N rates (0N and 120N) and each site (Perkins and Stillwater) averaged across four genotypes and three growing seasons (2020, 2021, 2023) (n=96). Different letters represent statistical difference among plant organs on average of N rates, genotypes, and growing seasons at p< 0.05.

Figure 5

Relationship between contribution RemN_organ to Sum RemN_Veg and NNI for each site-year across two N rates (0N and 120N) and three growing seasons (2020, 2021, 2023) (n=96). For leaf, Perkins RemN_leaf vs NNI: 26.5 x + 19.3, R² = 0.12 and Stillwater RemN_leaf vs NNI: 22.4 x + 25.8, R² = 0.03. For stem, Perkins RemNstem vs NNI: 6.04 x – 44.5, R² < 0.02 and Stillwater RemN_stem vs NNI: 6.04 x – 44.5, R² < 0.01. For chaff, Perkins RemN_chaff vs NNI: 18.4 x – 38.9, R² = 0.07 and Stillwater RemN_chaff vs NNI: 32.1 x – 41.3, R² =0.07. The solid lines are best-fitted functions for this relationship, and the dashed lines are the 5% and 95% quantiles (minimum and maximum, respectively).