**3.2 Variety x Fe-EDDHA rate**

Four cultivars (two Fe deficiency resistant, two Fe deficiency susceptible) and six rates of Fe-EDDHA (0, 2.24, 4.48, 6.72, 8.96, and 11.2 kg ha-1) were evaluated at one location in 2002 and six cultivars (two Fe deficiency resistant, two moderately resistant, and two susceptible) were evaluated at two locations in 2003. Visual chlorosis scores recorded at V3 could distinguish resistant from susceptible cultivars only when no Fe-EDDHA was applied, whereas harvest seed [Fe] could discriminate among resistant and susceptible cultivars at all six rates of Fe-EDDHA and in exactly the same order at each level of added Fe chelate (Table 1). Although grain yield increased markedly with added Fe chelate (Fig. 1. C), seed [Fe] changed very little (approx. 11%) (Fig. 1. F). The rank order of cultivars for harvest seed [Fe] was also the same as that of the cultivars' initial or planting seed [Fe], providing some evidence that seed [Fe] reflects varietal differences in resistance to Fe deficiency. Similar results recorded for the two 2003 trials, where two additional cultivars were evaluated under different severities of Fe deficiency, extend the applicability of this concept to evaluations conducted on similar soils.

Importance of Seed [Fe] for

Improved Agronomic Performance and Efficient Genotype Selection 33

Fig. 5. Varietal differences in linear response to added N, averaged across three years, for

plant height, relative chlorophyll, and nodulation score.

Fig. 4. Results (observed and predicted values) from linear regression equations of harvest seed [Fe] on applied Fe-EDDHA were significant for each one-third of the canopy for resistant cultivars, but for none of the canopy thirds for susceptible cultivars, Crookston, MN and Fisher, MN, 2003. Rates of applied Fe-EDDHA were: 0, 125, 250, 375, 500, 625 mg Fe-EDDHA per m of a 0.56 m wide row.

Fig. 4. Results (observed and predicted values) from linear regression equations of harvest seed [Fe] on applied Fe-EDDHA were significant for each one-third of the canopy for resistant cultivars, but for none of the canopy thirds for susceptible cultivars, Crookston, MN and Fisher, MN, 2003. Rates of applied Fe-EDDHA were: 0, 125, 250, 375, 500, 625 mg

Fe-EDDHA per m of a 0.56 m wide row.

Fig. 5. Varietal differences in linear response to added N, averaged across three years, for plant height, relative chlorophyll, and nodulation score.

Importance of Seed [Fe] for

Improved Agronomic Performance and Efficient Genotype Selection 35

Fig. 7. Changes in means of visual chlorosis score and number of entries during the last

decade for three large-scale chlorosis nurseries.

Fig. 6. Varietal differences in linear response to added N, averaged across three years for seed number, seed weight, grain yield, and seed [Fe].

Fig. 6. Varietal differences in linear response to added N, averaged across three years for

seed number, seed weight, grain yield, and seed [Fe].

Fig. 7. Changes in means of visual chlorosis score and number of entries during the last decade for three large-scale chlorosis nurseries.

Importance of Seed [Fe] for

2008

2009

2010

2009, and 2010.

\*\* Significant at 1% level of probability.

utilization (Lin et al., 2000).

Improved Agronomic Performance and Efficient Genotype Selection 37

Year Amenia Ayr Colfax Galesburg Leonard

 Amenia 1 0.7902\*\* 0.8386\*\* 0.8118\*\* 0.6696\*\* Ayr 1 0.7676\*\* 0.7559\*\* 0.6368\*\* Colfax 1 0.7958\*\* 0.6832\*\* Galesburg 1 0.6372\*\* Leonard 1

 Ayr Colfax Galesburg Leonard Prosper Ayr 1 0.6932\*\* 0.7227\*\* 0.5606\*\* 0.6674\*\* Colfax 1 0.5829\*\* 0.5109\*\* 0.6168\*\* Galesburg 1 0.5151\*\* 0.5800\*\* Leonard 1 0.5270\*\* Prosper 1

Table 2. Genotypic rank correlations across several North Dakota locations during 2008,

Results from earlier research (Table 1; Figs.1, 2, and 3) provided preliminary, but convincing, evidence that grain yield and harvest seed [Fe] were closely related to planting seed [Fe] across several genotypes when conditions favorable for Fe deficiency prevailed. These studies, however, involved only 4 to 29 cultivars. To confirm this observation we evaluated 72 cultivars expressing a wide range of seed Fe concentrations. Our primary objective was to compare plant traits thought to represent measures of resistance to Fe deficiency. This collection of Maturity Group 00 (MG 00) genotypes had a range of planting seed Fe concentrations from 64 to 106 ug Fe g-1 seed. We assumed that the seed we obtained had been grown with adequate Fe availability. Plants were grown in nutrient solution as well as field nurseries. Nutrient solution culture procedures described by Chaney et al. (1992) were used to evaluate genotypes grown with moderate to severe Fe deficiency under controlled conditions. Other researchers have concluded that similar quantitative trait loci (QTL) are identified in nutrient solution and field tests and, therefore, both systems identify similar genetic mechanisms of iron uptake and/or

These seventy-two genotypes also were grown on high pH, highly calcareous soils at three locations in 2003 and one location in 2004. Measures of resistance to Fe deficiency were: harvest seed [Fe] (µg g-1 seed); harvest seed Fe content (µg 1000-1 seeds); and Fe removal (µg Fe m-2). Classification variables were: published visual chlorosis (VC); in-field visual chlorosis at V3 (V3); planting seed [Fe] (µg Fe g-1 seed) (FC); planting seed Fe content (µg Fe

1000-1 seeds) (FS); and relative chlorophyll concentration (SPAD values) (GC).

**3.3 Northwest Minnesota - seventy-two cultivars, 4 environments** 

 Ayr Hunter Leonard Ayr 1 0.7989\*\* 0.7817\*\* Hunter 1 0.7964\*\* Leonard 1

Fig. 8. Frequency (as a percentage of the total) of cultivars in increasing, field visual chlorosis categories at three North Dakota locations in 2009.


\*\* Significant at 1% level of probability.

36 Soybean – Genetics and Novel Techniques for Yield Enhancement

Fig. 8. Frequency (as a percentage of the total) of cultivars in increasing, field visual

chlorosis categories at three North Dakota locations in 2009.

Table 2. Genotypic rank correlations across several North Dakota locations during 2008, 2009, and 2010.
