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Soybean

Iron Acquisition of Three Soybean Varieties Grown at Five Seeding Densities and Five Rates of Fe–EDDHA

University of Minnesota, Northwest Research and Outreach Center, Crookston, MN 56716

^* Corresponding author (wiers003{at}umn.edu)

Received for publication September 25, 2006.

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Iron deficiency is a major, yield-limiting factor for large areas of soybean [Glycine max (L.) Merr.] production in the North Central USA. Our objective was to evaluate the effectiveness of increasing both seeding density and rate of Fe–EDDHA in reducing early season (V2–V3) visual chlorosis scores (VCSs) and increasing seed number and grain yield. These measures were judged to reflect differences in Fe acquisition, manifest at maturity as seed Fe concentration (seed [Fe]). Three varieties (Vs), five seeding densities (SDs), and five seed-applied Fe–EDDHA rates (IRs) were evaluated during 2000, 2001, and 2002. With mild to moderate Fe deficiency, applying Fe–EDDHA at planting markedly reduced early season VCSs, slightly increased seed number and grain yield, and had a similarly small influence on seed Fe concentration (seed [Fe]). In contrast, increasing SD had little influence on early season VCSs, but increased seed [Fe] as well as seed number and grain yield. Resistant and susceptible varieties differed in their response to increasing SDs and indicated that the more susceptible varieties (‘Daksoy’ and ‘Jim’) responded to increasing SD to a greater extent than the more resistant variety, ‘Corona’. Nonetheless, Corona's seed [Fe] usually exceeded that of Daksoy and Jim, whether in the near absence of Fe deficiency or in the presence of mild to moderate Fe deficiency. Fe acquisition, measured as seed [Fe], appeared to be regulated primarily by genotype, yet Fe acquisition of less Fe-efficient varieties could be increased by increasing SD or reducing the severity of Fe deficiency.

Abbreviations: IDC, iron deficiency chlorosis • IR, iron rate • SD, seeding density • Seed [Fe], seed iron concentration • V, variety • VCS, visual chlorosis score

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
PLANTS require a continuous supply of Fe to maintain proper growth, since very little Fe is mobilized from older to younger tissues (Karlen et al., 1982; Sojka et al., 1986; Sadler et al., 1991). Because Fe is necessary for several metabolic processes, yet potentially toxic, a plant's Fe uptake and homeostasis are tightly controlled (Hell and Stephan, 2003). Thus, in Strategy 1 plants such as soybean, Fe stress response mechanisms are turned on or off as needed to maintain adequate Fe concentrations in plant tissues. These Strategy 1 Fe stress response mechanisms are chemically reducing processes that occur within the root and generally include: (i) release of H⁺ from roots; (ii) exudation of reductants; (iii) increased reduction of Fe³⁺ to Fe²⁺ at the root plasmalemma; and (iv) accumulation of organic acids (primarily citrate) in the roots (Marschner et al., 1989; Brown and Jolley, 1989; Terry and Jolley, 1994; Rogers and Guerinot, 2002). The magnitude of these response mechanisms vary among genotypes, leading to differences in the reductive capacity of the rhizosphere and, therefore, to differences in resistance ratings among varieties grown on Fe chlorosis-prone soils.

Selecting resistant varieties has been promoted as the best strategy to reduce or alleviate Fe deficiency on soils where soybean has historically exhibited mild to severe Fe deficiency. Alternatively, only a limited number of management tactics designed to improve the availability of Fe have been studied with soybean. These primarily have included applying various seed, soil, or foliar Fe chelates or fertilizers and increasing plant populations. Few reports (Goos and Johnson, 2001) have involved both Fe chelates and increasing plant populations.

Results of research involving the application of Fe chelates or Fe fertilizers to soybean to reduce Fe deficiency have been variable. In several reports (Karkosh et al., 1988; Goos and Johnson, 2000, 2001; Heitholt et al., 2003; Lingenfelser et al., 2005) low rates of Fe have been applied primarily to ensure economic feasibility. Inconsistent results preclude precise recommendations, but small amounts of Fe usually provide small reductions in chlorosis and small increases in grain yield. Larger responses have been observed with higher rates (Penas et al., 1990; Wiersma, 2005). Results of research involving increasing plant populations to reduce Fe deficiency have been only somewhat less variable.

Generally, increasing seeding rates will reduce visual chlorosis ratings (early and/or mid-season) and often will increase grain yield when soybean is grown where Fe deficiency is moderate to severe (Uvalle-Bueno and Romero, 1988; Penas et al., 1990; Goos and Johnson, 2001; Lingenfelser et al., 2005). This generalization summarizes a limited number of studies that have investigated a small number (3) of genotypes and/or a small number (3) of seeding rates. These studies also indicate that not all varieties respond similarly to increases in seeding rate. Although grain yield is routinely regarded as an integrated measure of soybean response to treatments designed to reduce Fe deficiency, other parameters—for example [Fe] in aboveground dry matter at harvest, seed [Fe], or total Fe accumulated—may provide better measures of treatment response.

Applying Fe chelate and increasing seeding density (seeds unit^–1 of row) both strive to improve the availability and acquisition of Fe sufficient to satisfy plant requirements. In their review, Rengel and Marschner (2005) underscore the importance of increasing exploitation of soil volume and the conversion of unavailable nutrient forms into available forms as methods of increasing nutrient acquisition. Root systems of soybean plants within a row have been reported to intermingle (Bohm, 1977), that is, roots penetrate soil that is occupied by roots of neighboring plants. A larger root mass per unit volume of soil, along with the chemically reducing processes that occur in response to Fe stress in soybean (release of H⁺ and exudation of reductants) may increase the reductive capacity of the rhizosphere and promote Fe availability. Support for this reasoning was provided by Brown et al. (1967), who reported that an Fe-efficient soybean, when grown in the same container with an Fe-inefficient variety, was able to increase the availability of Fe at the root of the inefficient variety.

The objective of this study was to evaluate the effectiveness of increasing both seeding density and rate of Fe–EDDHA in reducing Fe deficiency of three soybean varieties reported to differ in IDC score. Questions we sought to address included: (i) is there an interaction between seeding density and rate of Fe chelate, that is, do higher seeding densities respond less to increases in rate of Fe chelate; (ii) do less tolerant varieties respond differently than a more tolerant variety; (iii) are there important two- or three-way interactions; and (iv) are the responses to SD and IR similar for VCS, seed number, grain yield and seed [Fe]?

	MATERIALS AND METHODS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Experiments were conducted during 2000, 2001, and 2002 at the Northwest Research and Outreach Center at Crookston, MN, on soils where soybean has historically exhibited mild to severe Fe deficiency. Soil samples were collected from each experimental area and analyzed by Agvise Laboratories, Northwood, ND (Table 1). Each year trials were done using calcareous, high pH soils. With the exception of 2001, trial areas received additional N fertilizer to reduce nodulation and enhance Fe deficiency (Aktas and van Egmond, 1979; Lucena, 2000; Terry et al., 1991). Urea fertilizer (103 kg N ha^–1, 2000; 167 kg N ha^–1, 2002) was broadcast and incorporated before planting. Weeds were controlled by hand weeding and application of selected herbicides at rates recommended locally for control of specific weed species and intensities. Insect pests and diseases were either absent or considered inconsequential. Weather variables were recorded at an official National Weather Service station located within 2 km of the experimental areas (Table 2).

View this table: [in this window] [in a new window]   Table 1. Selected properties of soils from three experimental areas.

Initial plant populations were recorded for each plot at 2 to 3 wk after planting by counting the number of seedlings in 1 m of each of the two center rows. Increasing seeding densities resulted primarily in linear increases in initial plant populations (data not shown). Although self-thinning (Cooper,1971; Ethredge et al., 1989) may have differentially influenced final plant densities, we did not record plant stands at harvest. Our results apply only to the initial seeding densities used at planting.

At the 2 to 3 trifoliolate stage (Ritchie et al., 1988), one observer recorded visual chlorosis ratings using the procedure described by Goos and Johnson (2000). Grain yields were determined after harvesting 5.17 m of the two center rows (5.79 m²). Moisture concentration of plot samples was recorded and used to adjust grain yields to a moisture concentration of 130 g kg^–1. Mass seed^–1 was determined by counting and weighing 2000 seeds from samples of grain from each plot and seed number was calculated from yield and mass seed^–1. After grinding [Tecator Cyclotec mill (Fisher Scientific, Itasca, IL) 0.048 mm (32 mesh) screen], 1-g subsamples of grain were dry-ashed (Miller, 1998) and assayed for Fe concentration as described by Wiersma (2005).

Experimental units were consistent with a split-split-plot arrangement of a randomized complete block design (Gomez and Gomez, 1984). Preliminary analyses of variance were done for each year using PROC GLM procedures of SAS (SAS Institute, 1999) to derive estimates of error mean squares. Bartlett's test was used to assess homogeneity of error variances derived using PROC GLM and results of nearly all of these tests were highly significant (P < 0.001). Although trials were done using calcareous, high pH soils each year, the severity of Fe deficiency and error variances differed substantially across years and, thus, combined analyses were not computed. Because of the complexity of a three-factor experiment, our approach to data analysis began with tests of main effects and interactions (Schabenberger and Pierce, 2002). Treatment responses were analyzed with a mixed linear model using PROC MIXED procedures of SAS (Littell et al., 1996). Separate analyses were done for each year, considering varieties (V), seeding densities (SD), and seed-applied Fe–EDDHA rates (IR) as fixed effects. Blocks and all terms involving blocks were considered random effects. Orthogonal, single degrees of freedom contrasts were formulated for comparisons among varieties. Variety contrasts were (V1) moderately tolerant vs. the mean of moderately susceptible and susceptible; and (V2) moderately susceptible vs. susceptible. Seeding densities and seed-applied Fe chelate rates are quantitative factors and were investigated using regression contrasts. Seeding density contrasts were (SD1) linear and (SD2) quadratic and, similarly, Fe–EDDHA rate contrasts were (IR1) linear and (IR2) quadratic. If linear or quadratic contrasts were significant (P < 0.05), equations were derived for the highest significant order using least square means of the appropriate regression variables. Where statistically significant (P < 0.05), and with the guidance of the SLICE option of LSMEANS in PROC MIXED (Schabenberger and Pierce, 2002), interactions were partitioned using products of contrasts for appropriate combinations of variety, seeding density, and/or Fe–EDDHA rate. Our approach to presenting and discussing measures of seed number, grain yield, and seed [Fe] is to first describe the overall responses to the main effects of SD and IR. Although we acknowledge that there are consequential interactions, especially those involving more and less resistant varieties, presenting the overall response first provides a foundation for later incorporation of important interactions.

	RESULTS AND DISCUSSION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
With soils having low availability of Fe (high pH, highly calcareous soils), planting an Fe-deficiency tolerant variety, increasing seeding density (and, presumably, the volume of roots unit^–1 volume of soil) and/or applying chelated Fe could be characterized as treatments designed to improve nutrient acquisition (Rengel and Marschner, 2005). The severity of Fe deficiency and the plant characters used to measure treatment response are both crucial to the determination of the suitability of various treatments for improving Fe acquisition. For example, in this study responses to both SD and IR were greater as the severity of Fe deficiency increased, whereas responses to IR, compared with responses to SD, were larger for characters measured early in plant development, but smaller for characters measured at harvest. Planting date, monthly precipitation, average daily temperature, DTPA-extractable Fe, severity of Fe deficiency, and error variances differed across years. Nonetheless, increasing SD and IR promoted relatively consistent increases in Fe acquisition in the presence of mild to moderate Fe deficiency.

Visual Chlorosis Scores
Average VCS recorded at V2–V3 in chlorosis screening nurseries of potential or current varieties, and in management trials involving various treatments, are commonly accepted as reasonable estimates of the severity of Fe deficiency. Using the mean VCS of the lowest rate of Fe–EDDHA (0 mg m^–1) across Vs and SDs, the severity of Fe deficiency in our study ranged from almost no chlorosis (VCS = 1.2, 2001) to mild chlorosis (VCS = 2.3, 2002) to moderate chlorosis (VCS = 3.0, 2000). Differences in severity of Fe deficiency among years were reasonably consistent with differences in soil test results (Table 1), with less deficiency associated with higher DTPA-extractable Fe and lower calcium carbonate equivalent values. All main effects and several interactions were significant in 2001 (Table 3); however, differences in VCS observed in the near absence of chlorosis have little meaning.

View larger version (23K): [in this window] [in a new window]   Fig. 1. Decline in visual chlorosis score at V2–V3 stages of development in response to (A) the main effects of seeding density (SD) and (B) Fe–EDDHA rate (IR) in trials with nil (2001), mild (2002), and moderate (2000) Fe deficiency.

Consequential differences in VCS with increasing IRs were observed with moderate (2000) and mild (2002) Fe deficiency, but not in its absence (2001; Fig. 1B). With moderate (2000) Fe deficiency, rates of Fe–EDDHA higher than those we used (>251 mg m^–1) would have been required to reduce VCS to values (1.0) thought to represent nondeficient plant growth. Other researchers have also noted that higher rates (>251 mg m^–1) may be required with more severe Fe deficiency (Penas et al., 1990; Wiersma, 2005). With mild (2002) Fe deficiency, nondeficient plant growth was approached at the higher rates of Fe–EDDHA (188 and 251 mg m^–1) used in this study. Rates of Fe–EDDHA used by other researchers have varied from 8.5 mg m^–1 (Goos and Johnson, 2000) to 43 mg m^–1 (Karkosh et al., 1988; Goos and Johnson, 2001) to 168 mg m^–1 (Lingenfelser et al., 2005) to 213 and 426 mg m^–1 (Penas et al., 1990) and from 125 to 625 mg m^–1 (Wiersma, 2005). With one exception (Lingenfelser et al., 2005), rates of 43 mg m^–1 and higher have reduced early season VCS across a wide range of susceptible and resistant varieties as well as environments. It is noteworthy that researchers reporting reductions in early season VCSs all used SDs >28 seeds m^–1. In this study (Table 3), the general lack of significant V x IR and SD x IR interactions suggests that maintaining the same rate of Fe–EDDHA m^–1 of row will reduce VCS at V2–V3 regardless of V or SD. However, it is important to remember that these results will not necessarily apply to all circumstances.

Seed Number, Grain Yield, and Seed [Fe]
Numerous studies have investigated soybean yield response to increasing plant populations and have reported that yield tends to increase in a quadratic fashion, increasing as population increases to a certain level, then exhibiting little response or declining somewhat as populations are increased further (Elmore, 1998; Purcell et al., 2002; Kratochvil et al., 2004; Cober et al., 2005; and references therein). Yield increases are commonly associated with increases in seed number per unit area, seldom with increases in seed weight, and variety x population interactions are not uncommon (Ball et al., 2000; Cober et al., 2005; Kumudini et al., 2001; and references therein). Nonetheless, when grown on Fe chlorosis-prone soils, linear responses to increasing seeding density have been observed, with yield continuing to increase at higher seeding rates (Goos and Johnson, 2001; Penas et al., 1990). Resistant and susceptible varieties also may differ in their response to increasing seeding densities, as well as increasing rates of Fe chelate (Penas et al., 1990). In this study, significant (P < 0.05) differences in seed number and grain yield, due to the main effects of V, SD, and/or IR, occurred in each environment (Table 3). Significant linear and quadratic SD and IR responses also were detected in most environments; however, the SD x IR interaction was not significant in any environment (Table 3). Thus, responses to SD were similar at all IRs and responses to IR were similar at all SDs. The V x SD interactions were frequently significant and were evaluated using products of V and SD contrasts. The V x IR interaction was never statistically significant and results of partitioning the interaction rarely were significant. The lack of significant interactions involving IRs in our study may have occurred because the IRs used were too low.

Seed Number
Similar, quadratic increases in seed number in response to increasing SD were observed in each environment, although the magnitude of response varied with severity of Fe deficiency and V (Table 3 and Fig. 2A ). Indeed, partitioning the V x SD interaction indicated that the response was more likely linear in the presence of Fe deficiency. In the near absence of Fe deficiency (2001), seed production of the less Fe-efficient varieties, Daksoy and Jim, exhibited almost no response to increasing SD, whereas seed production of the more Fe-efficient variety, Corona, showed a typical, quadratic response (Fig. 2C). On the other hand, with mild (2002; Fig. 2D) and moderate (2000; Fig. 2B) Fe deficiency, all varieties responded linearly to increasing SD and the less efficient varieties had rates of increase at least double those of the more efficient variety. The presumed synergism among roots and increase in reductive capacity of the rhizosphere that accompanies an increase in seeding density may have promoted Fe acquisition and seed production to a greater extent in less efficient varieties, although the more efficient variety benefited as well.

View larger version (21K): [in this window] [in a new window]   Fig. 2. Similar increases in seed number in response to (A) the main effect of seeding density (SD) in three environments often masked the important variety (V) x SD interactions observed in (B) 2000, (C) 2001, and (D) 2002.

View larger version (21K): [in this window] [in a new window]   Fig. 3. Significant increases in seed number were noted each of three environments in response to (A) the main effect of Fe–EDDHA rate (IR); the two-way V x IR interactions observed in (B) 2000, (C) 2001, and (D) 2002 were not significant.

View larger version (22K): [in this window] [in a new window]   Fig. 4. Increases in grain yield in response to (A) the main effect of seeding density (SD) varied among environments, as did the variety (V) x SD interactions observed in (B) 2000, (C) 2001, and (D) 2002.

The V x SD interactions we observed and others have reported indicate that not all varieties respond similarly to increasing SD when planted on soils prone to Fe deficiency. Whether or not these varietal differences are predicated on Fe-efficiency is uncertain. Nonetheless, the presence of V x SD interactions, especially with mild to moderate Fe deficiency, again suggests that the more resistant variety (Corona) responded less to the synergism among roots and increase in reductive capacity of the rhizosphere that accompanies an increase in seeding density. This may have been because Corona's Fe stress response mechanisms were capable of acquiring more Fe under less favorable rhizosphere conditions than Daksoy and Jim.

None of the interactions involving Vs and IRs were statistically significant (Table 3) and, overall, the response to increasing IR was substantially less (two- to threefold smaller) than the response to increasing SD (Fig. 5 ). For example, where Fe deficiency was judged to be moderate (2000), increasing SD from 13 to 39 seeds m^–1 increased grain yield (averaged across Vs and IRs) about 61%, whereas increasing IR from 0 to 251 mg m^–1 increased grain yield about 15%. Further, Vs exhibited essentially identical responses to increasing IRs (Fig. 5), but differed as much as fourfold in their response to SD (Fig. 4). Penas et al. (1990) also observed significant V x SD interactions, but not V x IR interactions. Although increasing seeding density and applying chelated Fe are both considered treatments that will improve Fe acquisition, they do not require the same plant responses. The lack of V x IR interactions, regardless of the severity of Fe deficiency, suggests that varietal differences in Fe stress response mechanisms were not expressed when a readily available form of Fe was supplied in relatively small amounts. Yet, in other research, involving much higher rates of Fe–EDDHA (125–625 mg m^–1) and four different varieties (2 IDC-resistant and 2 IDC-susceptible), susceptible varieties exhibited much larger responses to increasing IRs than resistant varieties in the presence of mild to moderate Fe deficiency, but similar responses with severe Fe deficiency (Wiersma, 2005). The smaller amounts of Fe chelate applied in this study and the lower levels of Fe deficiency encountered may have limited the expression of varietal differences, as well as the overall response to increasing IRs.

View larger version (20K): [in this window] [in a new window]   Fig. 5. Increases in grain yield in response to (A) the main effect of Fe–EDDHA rate (IR) in three environments and the similarity of variety (V) responses observed in (B) 2000, (C) 2001, and (D) 2002.

Seed [Fe]
Averaged across Vs, SDs, and IRs, seed [Fe] reflected differences in the severity of Fe deficiency among environments and varied from 47 mg kg^–1 with moderate Fe deficiency, to 58 mg kg^–1 with mild deficiency, to 69 mg kg^–1 in the near absence of Fe deficiency (Table 3). These values are similar to those reported by Moraghan and Helms (2005) and Wiersma (2005) for calcareous, high pH soils, but substantially less than more common values of 100 to 120 mg kg^–1 often reported for soybean grown on noncalcareous, lower pH soils (Beeghly and Fehr, 1989; Spehar, 1994). In this study responses to SD and differences among varieties were associated with differences in the severity of Fe deficiency among environments. Although seed [Fe] appeared to be regulated primarily by genotype, genotypic expression could be modified by management practices and the environment. In the absence of Fe deficiency (2001), neither the V main effect nor any of the V contrasts, with one exception, were significantly different (Table 3) and Corona, Jim, and Daksoy had average seed [Fe] values of 71.0, 66.4, and 69.1 mg kg^–1, respectively. Expression of genetic differences in Fe stress response mechanisms may have been limited when adequate Fe was available. Nonetheless, increasing SD promoted small, linear increases in seed [Fe] and, although not statistically significant (P > 0.05), Corona continued to increase seed [Fe] as SD increased, whereas Daksoy and Jim did not (Table 3; Fig. 6C ). Corona may have an inherent, genetic ability to acquire, transport, and/or remobilize Fe to a greater extent than the less Fe-efficient Jim and Daksoy.

View larger version (21K): [in this window] [in a new window]   Fig. 6. Seed [Fe] increased similarly in response to (A) the main effect of seeding density (SD) in each environment, whereas the variety (V) x SD interactions observed in (B) 2000, (C) 2001, and (D) 2002, identify largely different responses between resistant and susceptible varieties.

Increasing IR had a much smaller impact on seed [Fe] than did increasing SD. Increasing IR from 0 to 251 mg m^–1 increased seed [Fe] <1%, about 1.5%, and 11.3% in 2002, 2001, and 2000, respectively (Fig. 7A ). The very small responses to IR in 2001 (Fig. 7C) and 2002 (Fig. 7D) precluded any meaningful discrimination among Vs, IRs, or V x IR interactions. On the other hand, with moderate Fe deficiency (2000), all three varieties exhibited small, linear increases in seed [Fe] as IR increased (Fig. 7B). Although higher rates of Fe–EDDHA may have been required to further promote seed Fe accumulation, similarly small (<12%) increases in seed [Fe] in response to rates as high as 625 mg m^–1 have been reported (Wiersma, 2005). The smaller amounts of Fe chelate applied in this study and their location near the soil surface, some distance from active root absorption sites later in plant development, may have failed to provide a continuous supply of Fe during seed filling.

View larger version (20K): [in this window] [in a new window]   Fig. 7. Increase in seed [Fe] in response to (A) the main effect of Fe–EDDHA rate (IR) in three environments and the nonsignificant variety V x IR interactions observed in (B) 2000, (C) 2001, and (D) 2002.

	CONCLUSIONS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

Measures of seed [Fe] provided indirect, but reasonable, evidence that increasing seeding density facilitates a synergism among roots that increases the reductive capacity of the rhizosphere and promotes Fe availability. Shoot demand (seed number, grain yield) for Fe was increased with increasing SD, yet seed [Fe] and content also increased, indicating that closer spacing of plants within the row increased Fe acquisition to supply the increased demand. Further, seed [Fe] continued to increase at SDs beyond those required for maximum grain yield and also increased as SD increased where yield was not maximized. Seed [Fe] appeared to be regulated primarily by genotype, yet seed [Fe] of less Fe-efficient varieties could be increased by increasing SD or reducing the severity of Fe deficiency.

	ACKNOWLEDGMENTS

 
The author acknowledges the excellent technical assistance of Robert J. Bouvette, Jr., Mark A. Hanson, and Eugene L. Peters, without whom this research would not have been possible.

	NOTES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Research supported in part by the Minnesota Soybean Research and Promotion Council and the Northwest Research and Outreach Center.

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