Late‐season N fertilization effects on soybean seed protein and biological N₂ fixation

Abstract

Soybean [Glycine max (L.) Merr.] seed protein concentration has been declining over the past decades with protein values falling below the ∼40% (dry weight base) required for optimal industrial processing. Further refinement of management practices is needed to help maintain concentrations above market standards. The objective of this work was to evaluate the impact of N fertilization during late reproductive stage on soybean seed protein on two cultivars differing in seed protein concentration in order to untangle the role of biological nitrogen fixation (BNF) to mediate seed protein responses. In experiments at two planting dates, late N fertilization was applied as either a foliar or soil-applied fertilizer and consisted of applying 80 kg ha -1 of N from R3 to R6 with four 20 kg ha -1 N applications. Both cultivar and planting date affected seed yield and protein concentration, ranging from 3,242 to 3,949 kg ha -1 and 34.8 to 38.4 g 100 g -1 , respectively. Soil and foliar N fertilizations had no effect on yield or N uptake but had positive effects on seed protein concentration (+2 g 100 g -1 ) only in the late-planted experiments. Applying N in the soil inhibited BNF. The amount of N 2 fixed during the seed-filling period, expressed per unit seed, is a relatively good predictor of the response of seed protein to N fertilization suggesting a critical role of BNF during this stage for securing a high concentration of seed protein.

Regional analysis of planting date and cultivar maturity recommendations that improve soybean oil yield and meal protein concentration

“…Lastly, seed and meal protein concentration showed the largest percentage of variability associated to random factors and to unaccounted sources of variation in our analysis ( Figure 2 ). Low repeatability in seed protein concentration is consistent with results by Dardanelli et al (2006) and suggests that other site-specific factors may be driving variation in seed and meal protein concentrations, such as soil fertility and management practices that affect crop N availability ( Bosaz et al, 2021 ; Chiluwal et al, 2021 ). However, we did find some significant effects and clear trends that provide new understanding on the interactive effect of planting date and cultivar maturity that can help increase oil yield and manage risk of deficient meal protein concentration.…”

Sowing date affects soybean biological nitrogen fixation

“…These contrasting results could be attributed to the moment in which the crop was fertilized and the rates, but Bosaz et al. (2021) also showed no yield improvements even with late N applications when BNF is declining.…”

“…These contradictory results might be associated with these studies not being specifically designed to test sowing date effects without other confounding factors that are common when sowing date is a covariable associated to a location. In a field experiment, where sowing date was purposely manipulated, Bosaz et al (2021) showed BNF was reduced in 6% (from 52.4 to 46.6% in early and late sowing dates, respectively) when the sowing was delayed by 33 d (an average decline of 0.15% d −1 ). This result, from a narrow sowing window of 54 d, is consistent with our results showing declines in the percentage of the total canopy N uptake that is coming from BNF across years, genotypes, and N fertilization levels, at an average rate of 0.22% d −1 when delaying the sowing date from mid-September to mid-December.…”

“…Our findings support these observations, showing yield was not limited by N availability, as N fertilization did not present significant yield changes. These contrasting results could be attributed to the moment in which the crop was fertilized and the rates, but Bosaz et al (2021) also showed no yield improvements even with late N applications when BNF is declining.…”

“…The model with the lowest AIC was selected as the best model. This approach has been applied elsewhere (Bosaz et al., 2021; Coyos et al., 2018; Madias et al., 2021). For percentage BNF the same approach was implemented using a linear mixed‐effect model ( lme4 package, lmer function) (Bates et al., 2015).…”