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Published online 17 August 2005
Published in Agron J 97:1314-1321 (2005)
DOI: 10.2134/agronj2004.0316
© 2005 American Society of Agronomy
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Production Papers

Relationships of Isoflavone, Oil, and Protein in Seed with Yield of Soybean

Xinhua Yina and Tony J. Vynb,*

a Mid-Columbia Agric. Res. and Ext. Cent., Oregon State Univ., Hood River, OR 97031-9512
b Dep. of Agron., Purdue Univ., West Lafayette, IN 47907-2054

* Corresponding author (tvyn{at}purdue.edu)

Received for publication December 21, 2004.

   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Ideal soybean [Glycine max (L.) Merr.] production systems achieve both high seed yield and high concentrations of desired seed quality components. However, the relationships between seed quality and yield of soybean are largely unknown. This study sought to determine the relationships of isoflavone, oil, and protein with seed yield of soybean across a wide range of yield levels. Field experiments involving soybean response to K fertilizer applications in alternate tillage and soybean row-width treatments were conducted at five locations in Ontario, Canada, from 1998 through 2000. Soybean yield and the concentrations and yields of oil, protein, daidzein, genistein, glycitein, and total isoflavone in seed were determined from a total of 13 trials. Oil concentration in seed decreased 4.2 g kg–1 with each megagram per hectare of increased seed yield. The relationship between protein concentration and seed yield was not significant. Concentrations of daidzein, glycitein, genistein, and total isoflavone increased by 249, 11, 164, and 427 mg kg–1 with each megagram per hectare of increased seed yield. Overall, oil and protein concentrations were much less responsive to seed yield increases compared with individual and total isoflavone concentrations. Daidzein was the most variable and glycitein the most stable isoflavone component. In addition, yields of individual and total isoflavones, and yields of oil and protein, were all positively related to seed yield. Our results suggest that high soybean seed yield can be accompanied by high concentrations of isoflavones without any substantial declines in oil and protein concentrations.

Abbreviations: HPLC, high-performance liquid chromatography • MG, maturity group • RT, retention time


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
SOYBEAN IS TRADITIONALLY produced for oil and protein in the seed, which are the economically important seed quality components of the crop. Seed of current U.S. soybean cultivars contains approximately 41% protein and 21% oil on average on a dry weight basis (Hartwig and Kilen, 1991). Smith (1991) summarized American Soybean Association recommendations for the ideal soybean to include high protein, high oil, and very high yield. Because of the positive potential role of isoflavones in prevention of cancer, heart disease, osteoporosis, and menopausal symptoms (Caragay, 1992; Messina, 1995; Hasler, 1998) due to their functions as antiestrogens (Kitts et al., 1980; Adlercreutz et al., 1986), antioxidants (Naim et al., 1976), and tyrosine protein kinase inhibitors (Akiyama et al., 1987), some soybean production area may be devoted to contract production for isoflavone extraction. If a premium/discount value marketing structure is implemented for these soybean seed quality components, producers will need information about how to produce soybean with high concentrations of these seed quality components.

Composition of soybean seed can be affected by cultivar, planting date, and environmental factors. Previous investigations have shown that differences in seed composition are inherent among cultivars (Simpson and Wilcox, 1983; Hartwig and Kilen, 1991; Helms and Orf, 1998). But it has also been frequently observed that the same cultivar, when grown in different years or under different environments in the same year, varies significantly in seed composition. For example, Helms et al. (1990) found that protein concentration of soybean increases as planting date is delayed. Applications of N, P, and K fertilizers and lime are among the most important factors affecting the seed composition of soybean (Stark, 1924; Yin and Vyn, 2003). Shannon et al. (1972) and Burton (1985) have reported a negative correlation between soybean seed yield and seed protein concentration.

Significant genetic and environmental impacts on isoflavone concentration in soybean seed have been reported. Wang et al. (2000) observed that total isoflavone concentration ranged from 1161 to 2743 µg g–1 in 210 soybean cultivars grown in South Dakota. Hoeck et al. (2000) showed that the genotype, genotype x year, genotype x location, and genotype x year x location interactions were all significant for both total and individual isoflavone concentrations. Eldridge and Kwolek (1983) reported that total isoflavone concentration in soybean seed varied from 1160 to 3090 µg g–1 among four soybean cultivars grown in the same environment and from 460 to 1950 µg g–1 among four locations with the same cultivar. Wang and Murphy (1994) observed that total isoflavone concentration of Vinton 81 soybean ranged from 1176 to 3309 µg g–1 among years at the same location and from 1176 to 1749 µg g–1 among locations within the same year; thus, year seemed to influence isoflavone concentration more than location. Kitamura et al. (1991) and Tsukamoto et al. (1995) showed that isoflavone concentration was significantly lower in soybean seed that developed in high temperatures during seed filling than in seed exposed to low temperatures during the filling period.

Further understanding of the relationships of the concentrations and yields of isoflavones, oil, and protein with seed yield of soybean is essential to soybean growers who may be given financial incentives to produce high-oil, high-protein, and (or) high-isoflavone soybean and to soybean breeders for the selection of soybean cultivars that have genetic potential for high concentrations of oil, protein, and (or) isoflavones. The primary objective of this study was to determine the relationships of the concentrations and yields of isoflavones, oil, and protein with seed yield of soybean simultaneously across a wide variety of production environments.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Plant Material
Soybean cultivars OAC Bayfield, First Line (FL) 2801R, NK S08-80 and NK S19-90 were used in this study. All were conventional glyphosate-susceptible soybean cultivars except FL 2801R, which is a glyphosate-tolerant cultivar. The cultivars were selected to represent a range of maturity groups (MGs) of soybean commonly grown in southwestern Ontario. The MGs of these cultivars are listed as follows: OAC Bayfield, MG 0.4; FL 2801R, MG 0.8; NK S08-80, MG 0.8; and NK S19-90, MG 1.9.

Field Experiments
Soybean seed samples used for this study were collected from four field experiments conducted in Ontario, Canada with various statistical designs but which all involved the determination of soybean responses to K fertilizer application and placement. There were five experimental locations in total, which will be referred to as Paris direct, Strathroy direct, Kirkton direct, Paris residual, and Kirkton residual, respectively. In these site names, "direct" infers that K fertilization treatments were imposed directly to the soybean crop while "residual" implies that K fertilizers were applied to the corn (Zea mays L.) preceding the soybean crop and no K fertilizer was applied after corn or during the soybean season. Soybean seed samples were collected from 1998 through 2000 in the three direct K experiments but only from 1998 through 1999 for the residual K tests. At each location, experiments were conducted at adjacent sites in the same field or in adjacent fields for successive seasons. The daily air temperatures and rainfall were recorded on site or collected from the closest weather station during the entire growing season for each experiment. Primary physical and chemical properties of the soils at each location are presented in Table 1. The K fertilization and other management treatments for each experiment are described below.


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  		Table 1. Initial soil properties of Ap horizon (0–15 cm) and soybean planting dates for the experimental sites (1998–2000).

 
Paris Direct
This field experiment was conducted on a private farm near Paris, Brant County, Ontario from 1998 through 2000. A randomized complete block split-plot design was used with four replicates. Potassium placement methods were randomly assigned to the whole plots, and soybean row widths were assigned to the subplots. Four K placement methods were applied in the spring as follows: (i) surface broadcast: fertilizer was uniformly broadcasted on the soil surface; (ii) 76-cm band: K was placed 10 cm deep in bands spaced 76 cm apart; (iii) 38-cm band: K was placed 10 cm deep in bands at 38-cm centers; and (iv) zero K: no K fertilizer was applied. When K was applied, the rate was 100 kg K ha–1 as muriate of potash (0–0–50). This K fertilizer rate was chosen based on Ontario recommendations for highest K fertilizer rates when soil-test K ranges between 0 and 60 mg L–1 (Ontario Ministry of Agriculture, Food and Rural Affairs, 1997). Soybean row widths included 76, 38, and 19 cm so that row spacings corresponded to fertilizer bands as well as the narrow-row production practices typical for soybean in the region. Soybean was planted in 4, 8, and 16 rows 21 m long with 76-, 38-, and 19-cm row widths, respectively, in each plot. Soybean cultivar OAC Bayfield was planted no-till in each season. Soybean was planted with an effort to obtain the maximum number of soybean rows located on the top of K fertilizer bands. Further details on site characteristics, soil K stratification, and soybean yield and quality responses to the K placement and row width treatments are available in Yin and Vyn (2003).

Strathroy Direct and Kirkton Direct
This field test was conducted near both Strathroy and Kirkton, Ontario from 1998 through 2000. A randomized complete block experimental design was used in each season at both locations. There were three replicates for Strathroy in 1998 and for Kirkton in 2000; all other site-years had four replications. There were 13 treatments in total including K application timing and methods, conservation tillage systems, and soybean row widths. The rate of K applied was 100 kg K ha–1 for both locations. Soybean cultivar NK S19-90 was used in 1998, and NK S08-80 was grown in 1999 and 2000 at Strathroy. Soybean cultivar OAC Bayfield was planted in 1998, and FL 2801R was grown in 1999 and 2000 at Kirkton. Soybean was planted in four rows spaced 76 cm apart, or eight rows spaced 38 cm apart, in a 21-m length for each plot at both locations. Details about soil characteristics, treatment designs, and soybean responses were described in Yin and Vyn (2002b). Because of resource limitations, only no-till soybean planted at a row width of 38 cm in the four K treatments of fall band, spring band, fall broadcast, and zero K was evaluated for this study.

Paris Residual
This field experiment involving a corn–soybean rotation was conducted near Paris, Brant County, Ontario from 1997 through 1999. For the corn season, the experiment was conducted using a randomized complete block design with four replicates in both 1997 and 1998. Spring K placement methods included deep band, surface broadcast, and zero K. Where K was applied, it was at a rate of 100 kg K ha–1 as muriate of potash (0–0–50). Corn was planted in 76-cm rows.

The same plots were used for subsequent no-till soybean in 1998 and 1999. Soybean cultivar FL 2801R was planted in 19-cm rows in both seasons. Each plot consisted of 16 rows in 21-m length. The soybean crop received no K treatments other than the residual fertilization from the previous year's no-till corn. Detailed information about soil characteristics and soybean responses to K treatments was presented in Yin and Vyn (2004).

Kirkton Residual
This field test was conducted on a private farm from 1997 through 1999 near Kirkton, Perth County, Ontario. For the prior corn season, a randomized complete block split-split-plot design with four replications was used. Tillage systems including no-till, fall zone-till, and fall moldboard plow were randomly assigned to the whole plots; fall K application rates of 0, 42, and 84 kg K ha–1 were assigned to the subplots; and spring K rates of 0 and 42 kg K ha–1 were assigned to the sub-subplots. Additional information about treatments and crop management practices associated with the previous corn was communicated previously (Vyn and Janovicek, 2001).

The identical experimental design and plot arrangement as the previous corn year were used for the subsequent no-till soybean in each season. No K fertilizer was applied after corn or during the soybean season. Soybean was planted no-till in the same direction as the previous corn rows. Soybean cultivar FL 2801R was used in both 1998 and 1999. Soybean was planted in eight rows 21 m long spaced 38 cm apart for each plot in both seasons. More information about treatments and soybean management practices was presented previously in Yin and Vyn (2002a). Only the plots receiving either zero K or 84 kg K ha–1 of fall K plus 42 kg K ha–1 of spring K in each tillage system were evaluated in this study.

Seed Evaluation
After soybean reached maturity, seed yield was determined using a plot combine to harvest a central strip of soybean 1.0 m wide for the entire plot length from each plot and adjusting yield to a moisture content of 130 g kg–1. Seed samples were taken at harvest for the determination of oil, protein, and isoflavone concentrations. Seed oil concentration was determined using GrainSpec (FOSS Electric, Warrington, Great Britain) near infrared reflectance spectroscopy calibrated with a gravimetric method. Seed protein concentration was measured using the same equipment as for seed oil calibrated by Kjeldahl (N x 6.25). All these samples that were stored under the identical conditions and contained 80 to 85 g kg–1 moisture were ground for isoflavone analysis.

Concentrations of daidzein, genistein, and glycitein were determined using a high-performance liquid chromatography (HPLC) method modified from Franke et al. (1995) after acid hydrolysis of the endogenous 12 isoflavones to their aglycone forms (daidzein, genistein, and glycitein), which were summed to obtain total isoflavone concentration. The aglycone weight corresponded to approximately 55% of the weight in the naturally occurring glycosylated forms.

All the chemicals and solvents used in isoflavone measurement (e.g., ethanol, methanol, and hydrochloric acid) were analytical grade or HPLC grade. "Nano Pure" or equivalent HPLC-grade water was used. The three standard aglycones of isoflavone (daidzein, genistein, and glycitein) were obtained from Indofine Chemical Company (Sommerville, NJ).

Finely ground soybean seed was weighed in duplicate samples of 0.5000 g each and dispersed in 10 mL of ethanol plus 2 mL of concentrated HCl. The resulting solutions were hydrolyzed by heating to 125°C for 2 h in a sand bath. After cooling, the samples were centrifuged at 3000 rpm for 10 min. The clear aliquot was filtered through a 0.45-µm PTFE filter. Individual hydrolyzed daidzein, genistein, and glycitein were separated on a HPLC equipped with a photodiode array (PDA) detector (200–300 nm) using the following instrumental conditions: HPLC = Waters 600E multisolvent delivery system with a 717 plus autosampler and a PDA detector set to collect spectra from 200–300 nm; HPLC column = Waters Nova Pak C18 column (3.9 by 150 mm, 5-µm particle size) with C18 guard column; HPLC mobile phases = Solvent A was 4% aqueous acetic acid and Solvent B was 100% HPLC grade methanol; flow rate = 1.5 mL min–1; and injection volume = 5 µL. The HPLC mobile phases were Solvent A (4% aqueous acetic acid) and Solvent B (100% methanol), and the solvent system was as follows (% solvent A/% solvent B): 0 min (70/30), 12.5 min (65/35), 13 min (50/50), 15 min (30/70), 22.5 min (25/75), and 23 min (70/30). Recovery was monitored by the addition of a recovery standard, flavone, to the sample before hydrolysis.

Using this program, daidzein [retention time (RT) = 13.09 min] and glycitein (RT = 16.16 min) were well separated near the beginning of the run while genistein (RT = 19.62 min) eluted later; the recovery standard (flavone) was eluted (RT = 22.89 min) within a 25-min run time.

The Millennium software (version 3.2) associated with the Waters HPLC instrument was used to generate linear calibration curves based on peak areas for the three isoflavone standards run with each sample batch. The software also computed the micrograms of isoflavone per gram sample for each of the calibrated isoflavones when sample weight and dilution volumes were entered. Peak areas were generally used to quantitatively analyze the isoflavone concentrations.

The yields of oil, protein, daidzein, genistein, glycitein, and total isoflavone were defined as the products of seed yield and the seed concentrations of oil, protein, daidzein, genistein, glycitein, and total isoflavone, respectively, and were calculated for each experiment.

Statistical Analysis
Data of the concentrations and yields of each of these seed quality components were combined across all the five locations and two to three growing seasons before any statistical analysis in this study.

To measure the differences in the concentrations and yields of these seed quality components among different seed yield levels, seed yield from each individual plot was grouped into low (<2.5 Mg ha–1), medium (2.5–3.0 Mg ha–1), high (3.0–3.5 Mg ha–1), and very high (>3.5 Mg ha–1) categories based on data distribution and common soybean yield standards. There were 87, 79, 77, and 61 individual plots for the low, medium, high, and very high categories, respectively. Although all the experiments were designed to evaluate K effects, in addition to K treatment influences at each experiment, variables such as location, year, replication, cultivar, tillage, and (or) row width could all have been contributing factors to the placement of an individual sample in one of these categories. However, each soybean cultivar in our experiments was almost equally represented in each of the four yield ranges.

Analysis of variance was conducted for each of these seed quality components using the ANOVA procedure in the SAS package (SAS Inst., 2002). Four seed yield categories were treated as the experimental treatments in this study. Mean separations were accomplished using Fisher's protected LSD test. Linear regression analysis was conduced using the REG procedure in the SAS package between the concentrations (or the yields) of each measured seed quality component and soybean seed yield on a plot basis. In addition, multiple-factor linear regression analysis was conducted between soybean seed yield and K application and placement, soybean cultivar, location, and growing seasons on a plot basis. A total of 304 plots were used in all the regression analyses. Probability levels less than 0.05 were designated as significant for all analyses.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
CONCLUSIONS
 REFERENCES
 
Oil, Protein, and Isoflavone Concentrations
Although oil concentrations in seed with high and very high seed yield categories were statistically lower than those under low and medium yield ratings (Fig. 1) , the differences among the four yield categories were quite small. For example, oil concentration decreased only 3.8% (8.3 g kg–1) when yield rating changed from low to very high. This was the largest difference in oil concentration observed among the four seed yield categories. The differences in oil concentration were not significant either between low and medium or between high and very high yield ratings. Protein concentration in seed did not differ significantly among the four yield categories (Fig. 1). Variations in both oil and protein concentrations with yield levels were thus relatively negligible even across a wide range of seed yield from less than 2.5 Mg ha–1 to greater than 3.5 Mg ha–1 from a field crop production perspective.



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  		Fig. 1. Variations in oil and protein concentrations among different seed yield categories. Bars within each seed component followed by the same letter are not significantly different at P = 0.05.

 
Daidzein, genistein, and total isoflavone concentrations in seed increased significantly as seed yield increased from the low up to the high category (Fig. 2) . But when seed yield increased even further, there were no significant increases in daidzein, genistein, or total isoflavone concentrations. Glycitein concentrations were significantly greater in the high and very high categories than in the low and medium yield ratings. The largest relative differences in daidzein, glycitein, genistein, and total isoflavone concentrations among the four yield categories were 67.0, 17.7, 39.6, and 49.1%, respectively. Therefore, the results of this study showed that daidzein had a greater increase in concentration as soybean yields climbed than either genistein or glycitein and, furthermore, that genistein increased more with yield than glycitein. This suggests that daidzein is the most variable and glycitein the most stable of the isoflavone components. Overall, on a concentration basis, both individual and total isoflavones varied with soybean yield level to a much greater magnitude than oil and protein (Fig. 1 and 2).



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  		Fig. 2. Variations in individual and total isoflavone concentrations among different seed yield categories. Bars within each seed component followed by the same letter are not significantly different at P = 0.05.

 
In general, our results are in agreement with those of Stark (1924), who reported that an increase in soybean seed yield was frequently associated with a statistically significant but small decrease in oil concentration. However, our results did not agree with his finding that soybean yield was positively associated with seed protein concentration. Other soybean studies have found a negative correlation between seed yield and seed protein concentration (Shannon et al., 1972; Burton, 1985). The differences among all these studies confirm that soybean seed composition can be affected by cultivar, management practices, and environmental factors. Vyn et al. (2002) observed that K fertilizer application significantly increased soybean seed yield and individual and total isoflavone concentrations simultaneously on low-testing K soils; this observation indirectly supports the finding in the current study that individual and total isoflavone concentrations increased as seed yield went up. Our results suggest that high soybean seed yield can be accompanied by high concentrations of isoflavones without any large declines in oil and protein concentrations.

Oil, Protein, and Isoflavone Yields
Unlike oil and protein concentrations, both oil and protein yields showed a significant increase as seed yield increased from low up to very high (Fig. 3) . The increases were 77 and 84%, respectively, for oil and protein yields when the seed yield category changed from low to very high. The increase in seed yield was the dominant contributing factor to the increases in oil and protein yields.



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  		Fig. 3. Variations in oil and protein yields among different seed yield categories. Bars within each seed component followed by the same letter are not significantly different at P = 0.05.

 
Similar to oil and protein yields, yields of individual and total isoflavones increased significantly as seed yield rating increased from low up to very high level (Fig. 4) . The increases were 203, 104, 151, and 169% for daidzein, glycitein, genistein, and total isoflavone yields, respectively, when seed yield category changed from low to very high. It was therefore obvious that the proportional increases in daidzein, genistein, and total isoflavone yields were much greater than those for oil and protein yields.



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  		Fig. 4. Variations in individual and total isoflavone yields among different seed yield categories. Bars within each seed component followed by the same letter are not significantly different at P = 0.05.

 
Regressions of Oil, Protein, and Isoflavone Concentrations with Seed Yield
Although regression analysis showed that seed oil concentration was negatively and linearly related to seed yield when the data were combined across locations and years (Fig. 5) , the decrease was quite small (about 4 g kg–1) when seed yield increased by over 1 Mg ha–1. The relationship between protein concentration and seed yield was not significant (Fig. 5). However, concentrations of daidzein, glycitein, genistein, and total isoflavone were all positively and linearly related with seed yield (Fig. 6) . The isoflavone concentration increases were much larger than the oil concentration increment when seed yield increased by 1 Mg ha–1. Low R2 values for these regression equations were probably due to the fact that only a single factor (seed yield) was used in these analyses. There are likely to be other factors contributing to the changes in these seed quality components.



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  		Fig. 5. Regression of oil and protein concentrations with seed yield.

 


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  		Fig. 6. Regression of individual and total isoflavone concentrations with seed yield.

 
Our results do not support a very high positive correlation between soybean yield and oil concentration over a wide range of soil K regimes (Gaydou and Arrivets, 1983; Sale and Campbell, 1986). This was probably because they had very low seed yield and a relatively narrow range of yield levels. However, our observations on isoflavone over a wide range of production environments were supported by those of Vyn et al. (2002), who found that total isoflavone concentration in soybean seed was positively related to seed yield using a linear regression model on soils with low exchangeable K status.

In a recent genetic mapping study, Meksem et al. (2001) observed that one quantitative trait locus (QTL) for genistein concentration was closely linked to a seed yield QTL in the mapping population of Essex x Forrest. Although the genetic material used in our study is of different origin and MG from that used by Meksem et al. (2001), the effects of the two linked QTLs for genistein concentration and yield may be a more universal genetic phenomenon in soybean.

In summary, the strong positive relationship of total isoflavone concentration with seed yield and the weak association of oil and protein concentrations with seed yield suggests that there was no big trade-off of seed yield or oil and protein concentrations for isoflavone concentration in soybean; rather, isoflavone concentration significantly increased as seed yield went up without substantial decreases in oil and protein concentrations. This positive relationship between total isoflavone concentration and seed yield is very encouraging, as it suggests that high soybean yield could be compatible with high quality from an isoflavone-based functional food perspective. Furthermore, high total isoflavone concentration in seed could be achieved without large decreases in oil and protein concentrations.

Regressions of Oil, Protein, and Isoflavone Yields with Seed Yield
Unlike the variable constituent-specific responses for concentrations, the yields of oil, protein, daidzein, glycitein, genistein, and total isoflavone were consistently both significantly and positively related to seed yield (Fig. 7 and 8) . However, individual and total isoflavone yields had greater relative increases than oil and protein yields. Because there were no significant increases in either oil or protein concentrations as seed yield went up, the increases in oil and protein yields were primarily attributed to the increases in seed yield.



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  		Fig. 7. Regression of oil and protein yields with seed yield.

 


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  		Fig. 8. Regression of individual and total isoflavone yields with seed yield.

 
This study was based on a data set collected from field experiments designed to evaluate both direct and residual effects of K application and placement on soybean yield and seed composition in various tillage systems and soybean row widths. According to a multiple-factor linear regression analysis that included K application and placement, cultivar, location, and growing season as the independent factors, we found that the soybean yield differences used in this study were not only attributed to the K application and placement effects, but were also attributable to cultivars, locations, and growing seasons (data not presented). Therefore, the significant relationships of seed quality components with seed yield observed in this study were conceivably influenced by all of the stated factors above, rather than by K application and placement alone.


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
REFERENCES
 
Oil concentration in seed decreased very slowly, and protein concentration remained almost constant, as soybean yield increased. Concentrations and yields of individual and total isoflavones, and yields of oil and protein, were all positively related to seed yield. Daidzein was the most variable and glycitein the most stable isoflavone component. Our results suggest that even when soybean farmers plant cultivars that were not selected based on having high isoflavone concentrations, and even when seed oil and protein concentrations are little affected by yield level, high soybean seed yield can be accompanied by high seed isoflavone concentrations.


   ACKNOWLEDGMENTS
 
Research was supported by Purdue Research Foundation, Agricultural Adaptation Council of Canada, Ontario Soybean Growers' Marketing Board, Potash and Phosphate Institute of Canada, and Ontario Ministry of Agriculture, Food, and Rural Affairs.


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




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