We identified QTL associated with protein and amino acids in a soybean mapping population that was grown in five environments. These QTL could be used in MAS to improve these traits. Soybean, rather than nitrogen-containing forages, is the primary source of quality protein in feed formulations for domestic swine, poultry, and dairy industries. As a sole dietary source of protein, soybean is deficient in the amino acids lysine (Lys), threonine (Thr), methionine (Met), and cysteine (Cys). Increasing these amino acids would benefit the feed industry. The objective of the present study was to identify quantitative trait loci (QTL) associated with crude protein (cp) and amino acids in the 'Benning' × 'Danbaekkong' population. The population was grown in five southern USA environments. Amino acid concentrations as a fraction of cp (Lys/cp, Thr/cp, Met/cp, Cys/cp, and Met + Cys/cp) were determined by near-infrared reflectance spectroscopy. Four QTL associated with the variation in crude protein were detected on chromosomes (Chr) 14, 15, 17, and 20, of which, a QTL on Chr 20 explained 55 % of the phenotypic variation. In the same chromosomal region, QTL for Lys/cp, Thr/cp, Met/cp, Cys/cp and Met + Cys/cp were detected. At these QTL, the Danbaekkong allele resulted in reduced levels of these amino acids and increased protein concentration. Two additional QTL for Lys/cp were detected on Chr 08 and 20, and three QTL for Thr/cp on Chr 01, 09, and 17. Three QTL were identified on Chr 06, 09 and 10 for Met/cp, and one QTL was found for Cys/cp on Chr 10. The study provides information concerning the relationship between crude protein and levels of essential amino acids and may allow for the improvement of these traits in soybean using marker-assisted selection.

Deployment of salt tolerant cultivars is an effective approach to minimize yield loss in a saline soil. In soybean, Glycine max (L.) Merr., substantial genetic variation exists for salt response. However, breeding for salt tolerance is hampered because no economically viable screening method has been developed for practical breeding. To facilitate the development of an effective screening method for salt tolerance in soybean, the present study was conducted to determine the heritability of salt tolerance and to identify associated quantitative trait loci (QTL). F2:5 lines from the cross of 'S-100' (salt tolerant) x 'Tokyo' (salt sensitive) were evaluated in a saline field in Hyde County, N.C., USA, in 1999 and in a greenhouse located in Raleigh, N.C., USA, in 2001. S-100 and Tokyo are ancestors of popular soybean cultivars released for the southern USA. The visual salt tolerance ratings of the F2:5 lines ranged from 0 (complete death) to 5 (normal healthy appearance). The entry-mean heritability for salt tolerance was 0.85, 0.48, and 0.57 in the field (four replications), greenhouse (two replications), and combined environments, respectively. The genotypic correlation between field and greenhouse ratings was 0.55, indicating reasonably good agreement between the two screening environments. To identify QTL associated with salt tolerance, each line was characterized with RFLP markers and an initial QTL single-factor analysis was completed. These results were used to identify genomic regions associated with the trait and to saturate the selected genomic regions with SSR markers to improve mapping precision. Subsequently, a major QTL for salt tolerance was discovered near the Sat_091 SSR marker on linkage group (LG) N, accounting for 41, 60, and 79% of the total genetic variation for salt tolerance in the field, greenhouse, and combined environments, respectively. The QTL allele associated with tolerance was derived from S-100. Pedigree tracking was used to examine the association between the salt tolerance QTL and flanking SSR marker alleles in U.S. cultivars descended from S-100 or Tokyo through 60 years of breeding. The presence of alleles from S-100 at the Sat_091 and Satt237 marker loci was always associated with salt tolerance in descendants. Alleles from Tokyo for these same markers were generally associated with salt sensitivity in descendent cultivars. The strong relationship between the SSR marker alleles and salt tolerance suggests that these markers could be used for marker-assisted selection in commercial breeding.

Three physiological traits that may affect performance of soybean [Glycine max (L.) Merr.] when soil water availability is limiting are (i) water use efficiency (WUE), (ii) regulation of whole plant water use in response to soil water content, and (iii) leaf epidermal conductance (ge) when stomata are closed. Six soybean plant introductions (PIs), eight breeding lines derived from them, and nine cultivars were compared for variability in these three traits during vegetative growth in two greenhouse studies. In the first experiment, whole plant water use, normalized both to plant size and evaporative demand (the normalized transpiration ratio, NTR), was monitored during a 10‐d cycle of gradually increasing drought stress and then for an additional 2 d following rewatering. The critical soil water content at which each plant began to reduce its water use (FTSWC), was determined. The WUE was estimated as the ratio of total plant dry weight to total water used. In the second experiment, ge was determined for these same 23 genotypes by measuring leaf water vapor exchange after a 36‐h dark adaptation. Substantial variation was found among genotypes for WUE, FTSWC, ge, and also the extent to which NTR recovered on rewatering. Generally, adapted cultivars had greater WUE and lower ge than did PIs. However, PI 471938 and its progeny N98‐7264 were clear exceptions to this trend. An unexpected finding was that WUE was significantly negatively correlated with ge across genotypes.

Asian soybean rust (ASR), caused by Phakopsora pachyrhizi Syd., is a widespread disease of soybean [Glycine max (L.) Merr.] with the potential to cause serious economic losses. The objective of this study was to genetically map red‐brown lesion type resistance from the cultivar Hyuuga. A population of 117 recombinant inbred lines (RILs) from the cross of Dillon (tan lesion) × Hyuuga (red‐brown [RB] lesion) was rated for ASR lesion type in the field and inoculated with P. pachyrhizi in the greenhouse. The RB resistance gene mapped between Satt460 and Satt307 on linkage group (LG)‐C2. When field severity and lesion density in the greenhouse were mapped, the Rpp?(Hyuuga) locus explained 22 and 15% of the variation, respectively (P < 0.0001). The RB lesion type was associated with lower severity, fewer lesions, and reduced sporulation when compared to the tan lesion type. A population from the cross of Benning × Hyuuga was screened with simple sequence repeat (SSR) markers in the region on LG‐C2 flanked by Satt134 and Satt460. Genotype at these markers was used to predict lesion type when the plants were exposed to P. pachyrhizi All the lines selected for the Hyuuga markers in this interval had the RB lesion type and they averaged approximately 50% fewer lesions compared to lines with tan lesions. Sporulation was only detected in 6% of the RB lines compared with 100% of the tan lines. Marker‐assisted selection can be used to develop soybean cultivars with the Rpp?(Hyuuga) gene for resistance to ASR.

Molecular markers provide the opportunity to identify marker-quantitative trait locus (QTL) associations in different environments and populations. Two soybean [Glycine max (L.) Merr.] populations, 'Young' x PI 416 937 and PI 97100 x 'Coker 237', were evaluated with restriction fragment length polymorphism (RFLP) markers to identify additional QTLs related to seed protein and oil. For the Young x PI 416937 population, 120 F4-derived lines were secored for segregation at 155 RFLP loci. The F4-derived lines and two parents were grown at Plains, G.a., and Windblow and Plymouth, N.C. in 1994, and evaluated for seed protein and oil. For the PI 97100 x Coker 237 population, 111 F2-derived lines were evaluated for segregation at 153 RFLP loci. Phenotypic data for seed protein and oil were obtained in two different locations (Athens, G.a., and Blackville, S.C.) in 1994. Based on single-factor analysis of variance (ANOVA) for the Young x PI 416937 population, five of seven independent markers associated with seed protein, and all four independent markers associated with seed oil in the combined analysis over locations were detected at all three locations. For the PI 97 100 x Coker 237 population, both single-factor ANOVA and interval mapping were used to detect QTLs. Using single-factor ANOVA, three of four independent markers for seed protein and two of three independent markers for seed oil were detected at both locations. In both populations, singlefactor ANOVA, revealed the consistency of QTLs across locations, which might be due to the high heritability and the relatively few QTLs with large effects conditioning these traits. However, interval mapping of the PI 97100 x Coker 237 population indicated that QTLs identified at Athens for seed protein and oil were different from those at Blackville. This might result from the power of QTL mapping being dependent on the level of saturation of the genetic map. Increased seed protein was associated with decreased seed oil in the PI 97100 x Coker 237 population (r = -0.61). There were various common markers (P[Symbol: see text]0.05) on linkage groups (LG) E, G,H,K, and UNK2 identified for both seed protein and oil. One QTL on LG E was associated with seed protein in both populations. The other QTLs for protein and oil were population specific.