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a Dep. of Experimental Pathology, Mayo Clinic, Rochester, MN 55905
b Dep. of Crop, Soil, and Environmental Sciences, Univ. of Arkansas, Fayetteville, AR 72701
c Dep. of Crop and Soil Environmental Sciences, Virginia Tech, Blacksburg, VA 24061
* Corresponding author (pchen{at}uark.edu)
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Abbreviations: HPLC, high performance liquid chromatography • QTL, quantitative trait loci • RIL, recombinant inbred lines
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Soybean is the second most valuable crop in the USA and has been used primarily as a source of protein and oil. Today, there is a sizable market for soy food products, for which seed traits such as seed size, sucrose, raffinose and stachyose contents, and seed coat and hilum color are considered important attributes affecting the taste and quality of the end product (Taira, 1990). For example, it is highly desired to have very large seed size (>200 mg seed–1) with high protein and sugar content for the production of tofu, soymilk, and miso, whereas natto production requires very small seed size (<80 mg seed–1) with high protein and sugar content. The increasing interest in adapted soybean cultivars that fit into specific soyfood markets has made selection for these seed traits a major objective for many breeding programs. Understanding of the interrelationships among the seed quality attributes and agronomic traits will help breeders improve selection efficiency and accelerate the breeding process.
Correlations among protein, oil, sucrose content, and seed size have been investigated and reported previously (Maughan, 1994; Lee et al., 1996; Brummer et al., 1997; Chandler and Fehr, 2000; Chandler et al., 2000). Seed size and oil content were correlated positively (r = 0.42), whereas protein content was negatively correlated with seed sucrose content (r = –0.46) (Maughan, 1994). Mansur et al. (1996) reported correlation coefficients among many agronomic traits. Seed yield was strongly positively correlated with seed size (r = 0.92); leaf length and leaf width were highly correlated (r = 0.58). In another report, maturity was not correlated with plant height (Lee et al., 1996). Studies on content of sugars in soybean showed that sucrose content was positively correlated with raffinose content (r = 0.27) and negatively correlated with stachyose content (r = –0.35), and stachyose content was negatively correlated with raffinose content (r = –0.29) (Hymowitz et al., 1972).
Wilcox and Shibles (2001) evaluated 43 random breeding lines to determine the interrelationships among seed traits and found no association between carbohydrate and seed yield. However, protein content was associated with sulfur (b = 0.008), oil (b = –0.156), total carbohydrate (b = –0.171), and sucrose content (b = –0.151). In a recent study, Neus et al. (2005) compared a set of breeding lines with normal or reduced stachyose derived from a high yield x low stachyose cross and found no significant difference in the mean performance between high and low stachyose lines for agronomic characteristics (field emergence, maturity, plant height, lodging, and seed yield) and other seed quality attributes (protein, oil, palmitate, sterate, oleate, linoleate, and linolenate). In most of these studies, adapted soybean genotypes with regular seed size and a narrow range of variation in seed quality traits were used in determining correlations among traits. Similar research information is limited for specialty soybeans with extreme differences in seed size and diverse genetic backgrounds.
The objectives of this study were to use a RIL population derived from a wide cross to (i) determine if any relationships exist between agronomic traits and seed contents of sucrose, raffinose and stachyose, (ii) estimate the heritabilities of the three sugars, and (iii) determine if any of the agronomic and/or morphological traits could be used as predictors of sugar content in soybean seeds.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The 308 RILs, both parents, and one check cultivar, Chesapeake, were arranged in a randomized complete block design with two replications at each of two locations: Kentland Research Farm near Blacksburg, VA, and the Eastern Virginia Agricultural Research and Extension Center (EVAREC) near Warsaw, VA. Each entry was planted in a single 1.2 m long row, at 30 seeds per row with 2.3 m between rows. Each parent and the check cultivar were entered three times in each block at each location. The tests were planted 24 June 1999 at Warsaw and 29 May 1999 at Blacksburg.
The following traits were evaluated at both locations: (i) maturity, the number of days after August 31 when 90% of the pods had reached mature color, (ii) plant height, the average height of the plants above the soil surface measured at maturity, (iii) canopy width, the average width of the canopy coverage in each row at maturity, (iv) leaflet length, the length of the terminal leaflet on the leaf attached to the third top node at the R1 stage, (v) leaflet width, the width of the terminal leaflet on the leaf attached to the third from the top node at the R1 stage, (vi) seed yield, the weight of the seeds harvested in bulk from each untrimmed plot, (vii) sucrose content, amount of sucrose (g kg–1) in the seed, (viii) raffinose content, amount of raffinose (g kg–1) in the seed, (ix) stachyose content, amount of stachyose (g kg–1) in the seed, and (x) seed size, weight of 100 seeds and expressed in mg seed–1. All length measurements were recorded in centimeters and all weights in grams. All content of sugars were calculated on a dry matter basis. All plants in each plot were harvested in bulk when the plants reached maturity and were stored at room temperature. The seeds were ground a month after harvest for sugar content analysis.
Determination of Sugar Content in Soybean Seeds by High Performance Liquid Chromatography (HPLC)
Fifty grams of seed from each plot were ground in a mill using a 0.08 mm mesh sieve. One gram of ground soybean seed was used to analyze the content of sugars (sucrose, stachyose, and raffinose). The sample was thoroughly mixed with 10 mL of double distilled water and shaken on a horizontal shaker at 200 rpm for 15 min. The sample was then centrifuged at 1800 g for 10 min. The soluble proteins from 5 mL supernatant were precipitated in 7 mL acetonitrile (100% HPLC-grade). The supernatant (1.5 mL) was then centrifuged at 12 200 g for 15 min. An aliquot of the supernatant (1 mL) was evaporated to dryness with compressed air using a Reactitherm heating/evaporation unit set at 98°C. The resulting dried material was dissolved in 400 µL of water–acetonitrile (35:65, v/v) solution and loaded to the HPLC.
The calibration standards were prepared for each sugar in three different concentrations: 1.25, 2.5, and 5.0 mg/mL. They were included with each group of samples loaded to the HPLC as controls on detector response.
The liquid chromatograph used was Hewlett-Packard series 1100 equipped with refractive index detector model HP 1047A. The separation was achieved on a polyamine-bonded silica-base polymeric gel column (25 cm x 4.6 mm; Astec, Advanced Separation Technologies, Inc., Whippany, NJ). The elution solvent was acetonitrile:water (65:35, v/v) with a pump rate of 1.0 mL/min. A 10 µL sugar extract from each sample was injected. The retention times for sugars and standards were detected at: (i) sucrose, 6.0 min, (ii) raffinose, 8.0 min, and (iii) stachyose, 12.0 min.
Peak area was calculated to determine the concentration of each sugar by ESTD (external standard) quantification procedure. The results from each sample were then compared with those of the calibration samples to calculate the amount of sugar in the extracted sample. To compensate for any instrumental drift over time, check sample (Chesapeake) was run every 20 samples in sequence and the calibration curve was repeated for each batch of samples. The final percent concentration of each sugar was calculated on a dry weight basis.
Statistical Analysis
Trait means, ranges, standard deviation, and Shapiro-Wilk test for distribution normality were determined for the RILs at each location. Parental means and standard deviations were also calculated by the SAS UNIVARIATE procedure (SAS Institute, 1998). Parental and check cultivar data were removed from the RIL data set for ANOVA (except for the Dunnett's comparison procedure) and heritability analyses. Analysis of variance was conducted by the GLM procedure. Genotype, location, block (location), and genotype x location were the main effects. Pearson's correlation coefficients between traits were computed by the CORR procedure for both locations. Simple correlations among the independent variables were reported in a Pearson correlation matrix. Frequency distributions of entry means over replications and locations were plotted for agronomic and seed quality traits. The Dunnett's procedure in SAS was used to compare the means of the transgressive segregants to the means for the parents. Broad sense heritability estimates on entry-mean basis were calculated from the ANOVA table (Agrobase, 2000).
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Significant (P < 0.05) transgressive segregation was observed for both high and low parents for all the traits except seed size at the Warsaw location and leaflet length, leaflet width, seed yield, and seed size at the Blacksburg location (Tables 1 and 2). Seed size was the only trait that did not show any transgressive segregation at either location. The most notable transgressive segregations for the RILs were early maturity and increased canopy width. Transgressive segregation was present for low sucrose but not for high sucrose. Transgressive segregation was not significant for leaflet length and width above the high parent and for yield below the low parent when data were combined across two locations.
Frequency Distributions of the RILs
Figure 1
presents the frequency distributions of the overall means of RILs for agronomic and seed quality traits. Continuous distribution was observed for all the traits as expected for quantitative inheritance. Shapiro-Wilk tests for normality showed that none of the traits were normally distributed except for sucrose content at both locations and plant height in Warsaw (Tables 1 and 2). The distribution of RILs for most of the traits was skewed toward the low parent PI 407162 except for maturity, plant height, raffinose content, and stachyose content. The means and distribution of the RILs were significantly closer to the value of the small-seeded wild parent for canopy spread, leaflet length and width, seed size and yield, and sucrose content than the domestic parent at both locations (Tables 1 and 2; Fig. 1).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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If any of the agronomic traits were highly correlated with seed quality traits, that information would be useful in selection for desired genes for a specific trait. We did not detect any significant correlations with quality traits that can be used in selection. However, some correlations, such as the positive correlation between seed yield and sucrose content and between seed size and sucrose content were encouraging, since we would not be dealing with a negative correlation in selecting to increase both traits. Seed yield was positively correlated with maturity, plant height, canopy width, and seed size as expected. In two other studies of agronomic and seed quality characteristics of soybean breeding lines (Neus et al., 2005; Wilcox and Shibles, 2001), the concentrations of carbohydrates (sucrose, stachyose, and total) were shown to be independent of seed yield, which is not completely in agreement with our results due to different genotypes used. We have identified a positive association between sucrose content and seed yield, but no correlation between seed yield and raffinose or stachyose content. Nevertheless, all three studies demonstrate that selection for high sucrose or low oligosaccharides will not adversely affect seed yield.
As reported earlier, seed size was positively correlated with sucrose content (Maughan, 1994). In addition, we found a low positive correlation between seed size and raffinose content in Blacksburg. Among 60 soybean lines evaluated, Hymowitz et al. (1972) reported sucrose content to be positively correlated with raffinose (r = 0.27) and negatively correlated with stachyose (r = –0.35); raffinose and stachyose were also negatively correlated (r = –0.29). In our population, we did not see any negative correlations among the three sugars. The important difference between these two studies was that the genotypes we used in our study were from a single population whereas Hymowitz et al. (1972) used 60 unrelated genotypes. The correlations reported by Hymowitz et al. (1972) might be an artifact of selection of specific lines and therefore have little value in assessing genetic relationships. Our study was based on a large population of random lines from a single cross; therefore, the correlations reported in the present paper should reflect genetic relationships among the three sugars. It is likely that a broad range of genes affecting sugar content were present in the two separate sets of genotypes, so it might not be contradictory to find different relationships in the two studies.
The traits maturity, plant height, canopy width, seed yield, seed size, leaflet length, and leaflet width, showed significant location effect as well as genotype x location interaction as expected and has been shown in a similar study (Chandler et al., 2000). However, seed quality traits such as sucrose, raffinose and stachyose content were consistent across locations and did not show a significant genotype x location interaction, suggesting that they can be genetically manipulated in a wide range of environments for cultivar development (Table 5).
Choosing the correct parents to develop a population in a breeding study depends on the traits of interest. The results from our study showed that the ranges in stachyose and raffinose content were narrow compared with the range for sucrose content. This would be expected, since the parents were selected to be divergent in sucrose content but not for stachyose and raffinose content. The narrow ranges of stachyose and raffinose content among the RIL indicate that genes controlling these traits are similar in both parents. It has been reported that the variation in raffinose content ranges from 4 to 11 and 3 to 9 g kg–1 and stachyose ranges from 6 to 32 and 11 to 42 g kg–1 in G. soja and G. max, respectively (Hymowitz and Collins, 1974). Wider ranges between soybean genotypes and negative correlations between stachyose and raffinose content reported previously indicate that the results of our study do not apply to the whole species. There is a strong possibility that there are other genes controlling these traits.
In a breeding program, the first priority trait is yield. Any cultivar with good quality traits will not be successful if it has low yield potential. The positive correlation between seed yield and sucrose content would be useful if we are selecting for high levels of both traits. However, the positive correlation between seed size and yield and sucrose content would be helpful when selecting for large seededness, high seed yield, and high sucrose content for tofu and soymilk beans but would be disadvantageous when selecting for small seededness, high seed yield, and high sucrose content for natto beans. It is important to note that even though the correlations between the traits were statistically significant, we did not determine any high correlations (r > 0.4) between agronomic traits and seed quality traits to be useful in effectively selecting for high sucrose and low stachyose and raffinose content using agronomic traits. Nevertheless, the negative correlation between maturity and raffinose content would indicate that low raffinose content might be more difficult to obtain in a late maturing line.
One of the important results of this research was the lack of genotype x location effect for sugar traits. In agriculture, the main interest is in the applicability of the research findings over different environmental conditions. The RILs showed stable phenotypic ranking for sugar traits. Even though location effects were significant, relative ranking of lines with low and high sugar content remained consistent across locations. This information is important in considering environments for specialty soybean variety development and production.
The relatively high heritability for sucrose content is encouraging from the standpoint of breeding for high sucrose. The low heritability of raffinose and stachyose content would indicate that selection for lower content could be more difficult unless sources of greater genetic variation were found. On the other hand, the lack of strong correlations among any of the sugar traits indicates that it should be possible to obtain lines that are high in sucrose but low in raffinose and stachyose. However, seed protein might be sacrificed with increases in sucrose content (Wilcox and Shibles, 2001). It appeared that selection for low oligosaccharides would not affect the concentrations of seed protein, oil, and various fatty acids (Neus et al., 2005). It is important to note that these conclusions are very much dependent on specific parents, population, or genotypes used in a study.
Received for publication June 27, 2005.
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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This article has been cited by other articles:
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  E. R. Cober and H. D. Voldeng Mass Selection for Small Seed Size in Natto Soybean Populations and the Resulting Effect on Seed Yield Crop Sci., July 1, 2008; 48(4): 1337 - 1340. [Abstract] [Full Text] [PDF]
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