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Univ. of Georgia, Center for Applied Genetic Technologies, 111 Riverbend Rd., Athens, GA 30602-6810
* Corresponding author (rboerma{at}uga.edu)
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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Seed weight, measured as mass per seed, is an important yield component of soybean and is generally positively correlated with seed yield (Burton, 1987). Seed weight is an important trait for the production of soyfood products and plant breeders select for improved yield and other agronomic traits to develop cultivars with different seed weights for specialty uses. Spherical seed is often desirable for food-type soybean with seed weight ranging from large to small. Large seed is a desirable trait for soybean used in the production of soymilk, miso, and tofu, whereas small seed weight is an important characteristic for the production of natto (Wilson, 1995). The increasing market for soyfoods indicates the necessity of identifying and developing high-yielding soybean cultivars suitable for food processing and human consumption.
Flowering and maturity in soybean are generally influenced by photoperiod. This photoperiodic sensitivity limits adaptability of soybean as a full-season crop to relatively narrow latitudinal belts (Burton, 1997). In North America, cultivars adapted for each belt are designated a maturity grouping (MG). Maturity group selection for soybean production becomes important if we consider that farmers exploit cultivars belonging to different maturity groups according to the production systems they utilize. For example, some farmers may prefer late-maturity cultivars in double-cropping production areas. Others may adopt the early soybean production system that has a positive impact on soybean integrated pest management in the southern region since this system escapes serious crop injury from some annual insect pests (McPherson et al., 2001). The main plant characteristic that soybean cultivars need to have is resistance to lodging because an erect growth habit reduces mechanical harvest loss (Burton, 1997).
Evidence from selection experiments within fairly homogeneous genetic pools suggests that the genome is more flexible and plastic than once assumed. McClintock (1984) suggested that the genome is dynamic and that it can modify itself in response to environmental stresses. In soybean, Byth and Weber (1968) found genetic variability for various agronomic traits within F5–derived lines that are considered to be relatively homozygous. Gordon and Byth (1972) reported significant variation for several agronomic traits within the predominantly self-pollinated tobacco (Nicotiana tabacum L.) cultivar Hicks.
Fasoula and Boerma (2005) reported that single-plant selection at very low plant density successfully identified significant intra-cultivar variation for seed protein and oil within three soybean cultivars.
In the maize (Zea mays L.) long-term selection studies for modified oil and protein at the Univ. of Illinois, selection has been practiced effectively for more than 90 generations and variation is still sufficient to achieve progress (Dudley and Lambert, 2004). Sprague et al. (1960) and Russell et al. (1963) reported that doubled haploid lines and long-time inbred lines of maize accumulated considerable variation in agronomic traits that could not be accounted for only by the commonly reported rates of mutation. Higgs and Russell (1968) found significant variation among sublines of long-time inbred lines for all the agronomic traits studied.
Rasmusson and Phillips (1997) reported that elite gene pools have inherent mechanisms to provide a continuing source of new genetic variation and hypothesized that selection gain occurs because of variation present in the original gene pool as well de novo generated variation.
In flax (Linum usitatissimum L.), rapid modifications of the genome, correlated with changes in gene expression, have been observed during plant development and under stress conditions (Cullis, 2005). Mechanisms that could generate variation are intragenic recombination, unequal crossing over, DNA methylation, excision or insertion of transposable elements, and gene duplication (Cullis, 1990; Rasmusson and Phillips, 1997; Peterson, 1997; Morgante et al., 2005).
Accordingly, although elite cultivars are considered fairly homogeneous, latent genetic variation among the single plants of a cultivar exists and mechanisms that generate de novo variation may also be present. Intra-cultivar variation has been reported in crops such as wheat (Triticum aestivum L.), cotton (Gossypium hirsutum L.), rice (Oryza sativa L.), maize, and soybean (Fasoula, 1990; Fasoula and Fasoula, 2000; Tokatlidis, 2000; Fasoulas, 2000; Tokatlidis et al., 2004, 2006; Fasoula and Boerma, 2005).
Despite its importance, exploitation of intra-cultivar variation has not been widely investigated due to the belief that elite cultivars are highly homogeneous. The release of cultivars is a time consuming task, thus, it is desirable to exploit any latent or newly created genetic variation and remove any unwanted variation to constantly improve them. Furthermore, food-grade developed cultivars need to maintain higher standards of uniformity than commodity soybeans. The exploitation of intra-cultivar variation can be very useful for maintaining uniformity in the long term and improving desirable agronomic or seed-trait characteristics of these highly adapted gene pools.
The main objective of this study was to investigate the presence of variation for seed weight, maturity, and other agronomic traits within elite soybean cultivars released for their superior productivity and resistance to various diseases.
For this purpose, single-plant progeny lines, selected at the low plant density of 1.4 plants/m2 from within these cultivars, were evaluated across locations and years for seed weight, maturity, plant height, lodging resistance, and seed yield.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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Single plants from Benning, Haskell, and Cook were grown in a replicated-3 honeycomb design (Fasoulas and Fasoula, 1995) using a plant spacing of 0.9 m (1.4 plants/m2) to eliminate the unfavorable effect of competition on response to selection (Fasoula and Fasoula, 1997, 2002; Fasoula and Tollenaar, 2005). The seed source of the cultivars was foundation seed produced in 1994. A total of 333 plants from Benning, 392 plants from Haskell, and 371 plants from Cook were evaluated (Fasoula and Boerma, 2005).
The individual plants from Benning averaged 125 g, the Haskell plants 173 g, and the Cook plants 168 g yield per plant. At maturity, each plant was harvested by hand and threshed in a plot combine because of the large number of seeds per plant. Single-plant selection was performed as reported by Fasoula and Boerma (2005). The single-plant progeny lines selected from within these cultivars were evaluated across locations and years for seed yield, seed weight, maturity, plant height, and lodging resistance. The seed composition of the progeny lines was assessed in a previous study (Fasoula and Boerma, 2005).
In 1996, three field experiments were conducted; one for the selected plants of each cultivar, and each experiment included a total of 44 entries (40 selected plants from the honeycomb trial and four entries of the original cultivar as a check). The three experiments were planted on 13 June 1996 at the Univ. of Georgia Plant Sciences Farm near Athens GA, in randomized complete block designs with three replications. Seeds from the selected single plants were planted in one-row plots with a row spacing of 0.76 m and a row length of 3.5 m. The soil type was Appling coarse sandy loam (fine, kaolinitic, thermic Typic Kanhapludults). Each plot was harvested and data on seed weight and maturity were collected.
For the collection of the phenotypic data the same procedure was followed for all the row-plot experiments (1996–1998). For the seed weight determination, the weight of 100 seeds from each row plot was measured. Maturity was recorded as the number of days after 31 August when 95% of the pods had reached mature pod color. Plant height was measured as the average length of plants from the ground to the top extremity at maturity. Three plants were measured and the average plant height was recorded. For taking the lodging scores, a scale of 1 to 5 was used, where a rating of 1 denoted that all plants were erect and a rating of 5 denoted that more than 80% of the plants were prostrate.
Based on the 1996 analysis of data for seed weight and other agronomic traits, the most divergent single-plant selections (P < 0.05) for each trait were evaluated in 1997. For each cultivar, the lines with large and small seed weight were grown in a randomized complete block experiment along with some other lines of the same cultivar selected for various agronomic and seed traits. Three separate field experiments were established for the progeny lines of each cultivar. Each experiment consisted of 36 lines with three replications, including four entries of the original soybean cultivar as a check. The experiments were planted on 6 June 1997 at the Univ. of Georgia Plant Sciences Farm near Athens, GA and on 10 June 1997 at the Univ. of Georgia Southwest Branch Experiment Station near Plains, GA. At both locations, the experimental unit for each entry was two 4-m rows spaced 0.76 m apart. The soil type at Athens was a Cecil coarse sandy loam (fine, kaolinitic, thermic Typic Kanhapludults) and the one at Plains was a Greenville sandy clay loam (fine, kaolinitic, thermic Rhodic Kandiudults). At maturity, each plot was harvested and threshed with a plot combine. Data were collected on seed yield, seed weight, maturity, lodging, and plant height.
Based on the 1997 analysis of data for seed weight, maturity, and other agronomic traits, the most divergent lines (P < 0.05) for each trait were evaluated in 1998. For Benning-derived lines, eight lines were evaluated for seed weight (four large- and four small-seeded) and five for maturity (two late- and three early-maturing). For Cook, six lines were evaluated for seed weight (three large- and three small-seeded) and five lines were evaluated for maturity (two late- and three-early maturing). For Haskell, seven lines were evaluated for seed weight (five large- and two small-seeded) and five lines were evaluated for maturity (four late- and one early-maturing). In addition, some Cook-derived and Haskell-derived progeny lines were evaluated for plant height and lodging resistance.
For each cultivar, the single-plant progeny lines were grown in a randomized complete block design with four replications. Three separate field experiments were established in 1998 for the progeny lines of each cultivar. Each experiment consisted of 30 lines, including four entries of the original soybean cultivar as a check. The experiments were planted on 1 June 1998 at the Univ. of Georgia Plant Sciences Farm and on 9 June 1998 at the Univ. of Georgia Southwest Branch Experiment Station. The soil type at Athens was an Appling coarse sandy loam and the one at Plains was a Greenville sandy clay loam. At both locations, the experimental unit for each entry was two 4-m rows spaced 0.76 m apart. Data were collected on seed yield, seed weight, maturity, lodging, and plant height.
The phenotypic data were analyzed by analysis of variance or nearest neighbor analysis when significant field trends were present (Stroup and Mulitze, 1991) using the Agrobase Software (Agronomix Software Inc., Winnipeg, Canada). For comparing the mean of a line with the mean of the check, the least significant difference (LSD) was calculated using the equation LSD = tdf 0.05 [EMS (1/n1 + 1/n2)]1/2, where EMS = error term used for estimating the significance, n1 = number of values used in computing the mean of a line, and n2 = number of values used in calculating the mean of the check.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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For the Haskell-derived lines, the five large-seeded lines (H-4243, H-1536, H-339, H-1452, and H-2007) produced larger seed weight (P < 0.05) than the two small-seeded lines (H-736 and H-3637) (Table 3). Across 3 yr, the five large-seeded lines averaged 30 mg seed–1 more seed weight compared to the two small-seeded lines. On average, the large-seeded lines had significantly larger seed (ranged 11–38 mg seed–1) compared to Haskell, whereas the small-seeded lines had significantly smaller seed (7 mg seed–1) than Haskell (Table 3). Evidently, intra-cultivar variation for seed weight within Haskell was much greater for large seed than for small seed weight. The largest-seeded line H-4243 averaged 194 mg seed–1 across years, producing 24% (38 mg seed–1) higher seed weight and 22% (601 kg ha–1) higher seed yield than Haskell. Across years, the intra-cultivar variation for seed weight was 45 mg seed–1 between the most divergent Haskell-derived lines (Table 3).
Intra-Cultivar Variation for Maturity
Haskell and Benning are Maturity Group VII cultivars (Boerma et al., 1994, 1997), whereas Cook is classified as Maturity Group VIII (Boerma et al., 1992). There were significant differences (P < 0.05) in maturity among the single-plant progeny lines derived from each of the elite cultivars tested (Table 4). For Benning, the intra-cultivar variation was greater in lines that matured earlier than Benning. Evaluated across years, two lines (B-1317 and B-1711) matured 1 d later and three lines (B-418, B-424, and B-2448) matured 2, 2, and 4 d earlier, respectively, compared to Benning (Table 4). There were no significant differences in seed yield among the progeny lines. Averaged across years, the most divergent single-plant progeny lines from Benning differed by 5 d in maturity.
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There were large differences (P < 0.05) in maturity among the single-plant progeny lines derived from Haskell and we found that the intra-cultivar variation was greater for later maturity (Table 4). Across years, two lines (H-4243 and H-1536) matured 6 d later and two other lines (H-1452 and H-2303) matured 5 and 4 d later, respectively, than Haskell. One line (H-240) matured 1 d earlier than Haskell. It is noticeable that H-4243, which matured 6 d later, averaged 22% (601 kg ha–1) higher seed yield than Haskell, whereas H-2303 yielded 12% (336 kg ha–1) less than Haskell. The most divergent lines derived from Haskell differed by 7 d in maturity. The 7-d difference in maturity represents the largest intra-cultivar variation found in the three cultivars tested.
Intra-Cultivar Variation for Plant Height and Lodging
There were significant differences (P < 0.05) in plant height among some of the single-plant progeny lines derived from Haskell and Cook (Fig. 1
and 2
), whereas no variation for plant height was found within the Benning-derived progeny lines. When evaluated across years, two Cook-derived selections (C-2734 and C-3402) had significantly (P < 0.05) greater plant height than two shorter selections (C-2014 and C-1420) (Fig. 1). The tall progeny lines averaged 108 cm and were 12 cm taller compared to the shorter lines that averaged 96 cm. Line C-2734 averaged 109 cm in plant height and was significantly different from Cook which averaged 102 cm in plant height. The shortest line averaged 94 cm which was also different (P < 0.05) from Cook. As a result, the intra-cultivar variation for plant height between the most divergent Cook-derived lines was 15 cm (Fig. 1).
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There was no significant variation (P > 0.05) in the Benning- or Cook-derived progeny lines evaluated for lodging. Genotypic variation in lodging can be evaluated only under environmental conditions that are conducive to lodging. Intra-cultivar variation for lodging score was found only in Haskell with the most lodging-resistant line (H-4243) averaging a 2.2 score compared to a score of 3.6 for the most lodging-susceptible line (H-2539) (Fig. 3 ). In these experiments, Haskell averaged a 3.1 score.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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There was no variation in the Benning-derived lines evaluated for plant height and lodging and no variation in the Cook-derived lines evaluated for lodging. Resistance to lodging can be evaluated only under environmental conditions that are conducive to the expression of the trait. Most of our trials were not conducive to lodging. It is evident that a much larger number of single-plant progeny lines have to be evaluated under specific environmental conditions to find variation for resistance to lodging. Intra-cultivar variation for lodging resistance was found only in Haskell with the most resistant line averaging a 2.2 score compared to the least resistant line averaging a 3.6 score (Fig. 3). Some exceptional lines were identified. For example, line H-4243 derived from Haskell averaged 38 mg seed–1 greater seed weight, 601 kg ha–1 higher seed yield, and had improved lodging-resistance than the original Haskell (Table 3, Fig. 3).
Among all the traits tested, the largest amount of intra-cultivar variation was discovered for seed weight and maturity. Among the 3 cultivars, Haskell had the largest intra-cultivar variation for seed weight and other agronomic traits (see Tables 1
–4 and Fig. 1–3). On the basis of genetic theory, there would be 50% less variation within a F5–derived (Haskell and Cook) than a F4–derived cultivar (Benning), but this does not account for other sources of variation that built up in each cultivar each generation.
In soybean, positive relationships between seed weight and seed yield have often been reported (Burton, 1987). In our results, there was no association between seed weight and seed yield in the Benning-derived, Cook-derived, or Haskell-derived progeny lines, though in some cases, there was a tendency of the large-seeded lines to produce higher seed yields than the small-seeded lines (Tables 1, 2, and 3).
Seed weight is an important trait for the production of soyfood products and plant breeders select for different seed weights for specialty uses. The increasing market for soyfoods indicates the necessity of developing and maintaining high-yielding soybean cultivars suitable for food processing and human consumption. Our results show that the large amount of intra-cultivar variation for seed weight can be utilized to select high-yielding progeny lines with larger or smaller seed. There is also distinct advantage in being able to discover lines with different maturity from within an elite and adapted soybean cultivar. Maturity group selection for soybean production becomes important if we consider that farmers exploit cultivars belonging to different maturity groups according to the production systems they utilize. For example, some may prefer late-maturity cultivars in double-cropping production areas or to plant a cultivar with a range of maturities to fit variable environmental conditions.
Elite cultivars have long been considered by plant breeders a relatively permanent record with nonexisting or very limited genetic variation. But increasingly, molecular biologists are finding that the genome undergoes constant remodeling and restructuring. Our results corroborate those of Rasmusson and Phillips (1997) who reported that in barley (Hordeum vulgare L.), incremental genetic gains were made for several traits in a very narrow gene pool. They hypothesized that selection gain in elite gene pools occurs due to variation present in the original gene pool as well as due to de novo generated variation. Evidence from long-term selection experiments and doubled haploid studies in maize (Sprague et al., 1960; Russell et al., 1963; Higgs and Russell, 1968; Dudley and Lambert, 2004) also corroborate our results and suggest that the genome is more flexible and plastic than previously assumed. The maize genome is in constant flux, as transposable elements continue to change both the genic and nongenic fractions of the genome, profoundly affecting genetic diversity (Morgante et al., 2005).
Additional data on the presence of intra-cultivar variation have been reported on various crops. In wheat, intra-cultivar selection at 1.2 plants/m2 within the cultivar Siete Cerros produced lines with 8% higher and 9% lower seed yield compared to Siete Cerros (Fasoula, 1990). In another study, intra-cultivar selection within the bread wheat cultivar Nestos identified lines that produced significantly higher seed yield, respectively, compared to the original Nestos (Tokatlidis et al., 2004, 2006). In cotton, intra-cultivar selection at 0.7 plants/m2 across years within the elite cultivar Sindos 80 led to the release of the cultivar Macedonia which exhibited a 10% yield superiority over Sindos 80 across 16 environments. Moreover, two cotton lines were discovered with tolerance to Verticillium wilt to which the original cultivar Sindos 80 is susceptible (Fasoulas, 2000). Significant variation within maize inbred lines has been reported for grain yield and other ear traits by Tokatlidis (2000). In soybean, Fasoula and Boerma (2005) discovered a significant amount of intra-cultivar variation for seed protein, seed oil, and fatty acid composition within elite cultivars. Molecular analysis of sunflower (Helianthus annuus L.) and rice cultivars also revealed the existence of intra-cultivar variation (Zhang et al., 1995; Olufowote et al., 1997).
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CONCLUSIONS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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Received for publication September 28, 2005.
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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V. A. Fasoula, H. R. Boerma, J. L. Yates, D. R. Walker, S. L. Finnerty, G. B. Rowan, and E. D. Wood Registration of Six Soybean Germplasm Lines Selected within the Cultivar 'Haskell' Differing in Seed and Agronomic Traits Journal of Plant Registrations, September 1, 2007; 1(2): 160 - 161. [Full Text] [PDF]
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