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. 2016 Sep 13:4:e2452.
doi: 10.7717/peerj.2452. eCollection 2016.

Canopy position has a profound effect on soybean seed composition

Steven C Huber #  1   2   3 , Kunzhi Li #  1   2   4 , Randall Nelson #  3   5 , Alexander Ulanov  6 , Catherine M DeMuro  1 , Ivan Baxter  7   8
Affiliations

Canopy position has a profound effect on soybean seed composition

Steven C Huber et al. PeerJ. .

Abstract

Although soybean seeds appear homogeneous, their composition (protein, oil and mineral concentrations) can vary significantly with the canopy position where they were produced. In studies with 10 cultivars grown over a 3-yr period, we found that seeds produced at the top of the canopy have higher concentrations of protein but less oil and lower concentrations of minerals such as Mg, Fe, and Cu compared to seeds produced at the bottom of the canopy. Among cultivars, mean protein concentration (average of different positions) correlated positively with mean concentrations of S, Zn and Fe, but not other minerals. Therefore, on a whole plant basis, the uptake and allocation of S, Zn and Fe to seeds correlated with the production and allocation of reduced N to seed protein; however, the reduced N and correlated minerals (S, Zn and Fe) showed different patterns of allocation among node positions. For example, while mean concentrations of protein and Fe correlated positively, the two parameters correlated negatively in terms of variation with canopy position. Altering the microenvironment within the soybean canopy by removing neighboring plants at flowering increased protein concentration in particular at lower node positions and thus altered the node-position gradient in protein (and oil) without altering the distribution of Mg, Fe and Cu, suggesting different underlying control mechanisms. Metabolomic analysis of developing seeds at different positions in the canopy suggests that availability of free asparagine may be a positive determinant of storage protein accumulation in seeds and may explain the increased protein accumulation in seeds produced at the top of the canopy. Our results establish node-position variation in seed constituents and provide a new experimental system to identify genes controlling key aspects of seed composition. In addition, our results provide an unexpected and simple approach to link agronomic practices to improve human nutrition and health in developing countries because food products produced from seeds at the bottom of the canopy contained higher Fe concentrations than products from the top of the canopy. Therefore, using seeds produced in the lower canopy for production of iron-rich soy foods for human consumption could be important when plants are the major source of protein and human diets can be chronically deficient in Fe and other minerals.

Keywords: Canopy; Elemental composition; Ionome; Nutrition; Physiology; Soybean.

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Conflict of interest statement

The authors declare there are no competing interests.

Figures

Figure 1
Figure 1. Quadrants of a soybean plant.
The mature plant is divided up into quadrants upon harvest and each quadrant is analyzed separately. Plat normalized data uses the average of all four quadrants to normalize year, plot and line affects.
Figure 2
Figure 2. Canopy gradients of seed composition traits before normalization and line and year effects on total accumulation.
(A) Composition gradients from the bottom to the top of the canopy for cultivar ‘Chamberlain’. The plots display the quadrant average as a line with the 95% confidence interval calculated using standard error as the ribbon. Units are mg (Single seed weight), PPM (Fe) and percentage for Protein and Oil (B) Year and line effects for each compositional trait, represented as boxplots. Units are PPM.
Figure 3
Figure 3. Canopy gradients of seed composition traits.
For each trait, the data was normalized to the plot average to remove the effect of environment and genotype. The plots display the quadrant average as a line with the 95% confidence interval calculated using standard error as the ribbon. (A) Percentage protein, percentage oil and single seed weight. (B) Elements with a significant (p < 1e − 10) effect of gradient in an ANOVA analysis that included Entry, Year and Position.
Figure 4
Figure 4. Correlation plot among composition traits.
Pearson correlation values between compositional traits. (A) Correlation across 832 quadrants normalized to the plot average. (B) Correlation across 208 plot means.
Figure 5
Figure 5. Effect of thinning on compositional traits.
For each trait, the data was normalized to the plot average to remove the effect of environment and genotype. The plots display the quadrant average as a line with the 95% confidence interval calculated using standard error as the ribbon. (A) Percentage protein and percentage oil in 2010. (B) Elements (from 2010 to 2012) with a significant (p < 1e − 10) effect of gradient in an ANOVA analysis that included Entry, Year, Position and thinning.
Figure 6
Figure 6. Difference in top/bottom composition traits is not correlated with seed fill period.
The difference in plot normalized composition between the top quad and the bottom quad for protein, oil and iron plotted versus the difference in seed fill period for 51 plots in 2012.
Figure 7
Figure 7. Canopy differences in iron are reflected in food products.
Fe content of the products from 3 replicates of seven lines (flour) and four lines (Milk and Okara). Boxplots display the five number summary (median, 25, and 75% percentile define the box, with whiskers extending to 1.5 × interquartile range).
Figure 8
Figure 8. Canopy gradients of leaf composition traits.
For each trait, the data was normalized to the plot average to remove the effect of environment and genotype. The plots display the quadrant average as a line with the 95% confidence interval calculated using standard error as the ribbon. Elements with a significant (p < 1e − 10) effect of gradient in an ANOVA analysis that included Entry, Collection Date and Position.
Figure 9
Figure 9. Concentrations of selected primary metabolites in developing seeds of cultivar ‘Williams 82’.
A, Suc; B, citrate; and C, Asn. Boxplots display the five number summary (median, 25, and 75% percentile define the box, with whiskers extending to 1.5 × interquartile range) for three replicates at each sampling time: 7 AM (7) , 12N (12) , 7 PM (19) and the following morning at 7 AM (31). The black vertical bars represent the intervening night period. Values are µg (g DW).
Figure 10
Figure 10. Concentrations of free amino acids in developing seeds.
Boxplots display the five number summary (median, 25, and 75% percentile define the box, with whiskers extending to 1.5 × interquartile range) for values from each sampling interval (3 replicates and 4 time points are merged within each box) and nodal position. Ornithine levels reflect both ornithine and arginine as arginine is converted to ornithine during sample prep for GC-MS. D1.bot, D1.top and D7.top refer to the samples collected on day one top and bottom quadrants and the day seven top quadrant respectively.
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Grants and funding

Funding was provided by the United Soybean Board and the US Department of Agriculture—Agricultural Research Service. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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