Theor Appl Genet (2009) 118:483–497DOI 10.1007/s00122-008-0915-z
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ORIGINAL PAPER
Identi W cation and veri W cation of QTLs for agronomic traits using wild barley introgression lines
Inga Schmalenbach · Jens Léon · Klaus Pillen
Received: 13 June 2008 / Accepted: 9 October 2008 / Published online: 1 November 2008? The Author(s) 2008. This article is published with open access at https://www.doczj.com/doc/5e10458503.html,
Abstract A set of 39 wild barley introgression lines (hereafter abbreviated with S42ILs) was subjected to a QTL study to verify genetic e V ects for agronomic traits,previously detected in the BC 2DH population S42 (von Kor V et al. 2006 in Theor Appl Genet 112:1221–1231) and,in addition, to identify new QTLs and favorable wild barley alleles. Each line within the S42IL set contains a single marker-de W ned chromosomal introgression from wild bar-ley (Hordeum vulgare ssp. spontaneum ), whereas the remaining part of the genome is exclusively derived from elite spring barley (H. vulgare ssp. vulgare ). Agronomic W eld data of the S42ILs were collected for seven traits from three di V erent environments during the 2007 growing sea-son. For detection of putative QTLs, a two-factorial mixed model ANOVA and, subsequently, a Dunnett test with the recurrent parent as a control were conducted. The presence of a QTL e V ect on a wild barley introgression was accepted, if the trait value of a particular S42IL was
signi W cantly (P <0.05) di V erent from the control, either across all environments and/or in a particular environment.A total of 47 QTLs were localized in the S42IL set, among which 39 QTLs were signi W cant across all tested environ-ments. For 19 QTLs (40.4%), the wild barley introgression was associated with a favorable e V ect on trait performance.Von Kor V et al. (2006 in Theor Appl Genet 112:1221–1231) mapped altogether 44 QTLs for six agronomic traits to genomic regions, which are represented by wild barley introgressions of the S42IL set. Here, 18 QTLs (40.9%)revealed a favorable wild barley e V ect on the trait perfor-mance. By means of the S42ILs, 20 out of the 44 QTLs (45.5%) and ten out of the 18 favorable e V ects (55.6%)were veri W ed. Most QTL e V ects were con W rmed for the traits days until heading and plant height. For the six corre-sponding traits, a total of 17 new QTLs were identi W ed,where at six QTLs (35.3%) the exotic introgression caused an improved trait performance. In addition, eight QTLs for the newly studied trait grains per ear were detected. Here,no QTL from wild barley exhibited a favorable e V ect. The introgression line S42IL-107, which carries an introgres-sion on chromosome 2H, 17–42cM is an example for S42ILs carrying several QTL e V ects simultaneously. This line exhibited improved performance across all tested envi-ronments for the traits days until heading, plant height and thousand grain weight. The line can be directly used to transfer valuable Hsp alleles into modern elite cultivars,and, thus, for breeding of improved varieties.
Introduction
Most agronomically important traits, such as yield and quality parameters, are quantitatively inherited. They are not conditioned by single genes, but polygenes or so called
Communicated by J.-L. Jannink.
I. Schmalenbach · K. Pillen
Max-Planck-Institute for Plant Breeding Research,
Barley Genetics Research Group, Carl-von-Linné-Weg 10, 50829 Cologne, Germany
J. Léon
Chair of Crop Science and Plant Breeding,
Institute of Crop Science and Resource Conservation,
University of Bonn, Katzenburgweg 5, 53115 Bonn, Germany Present Address:K. Pillen (&)
Chair of Plant Breeding, Institute of Agricultural
and Nutritional Sciences, University of Halle-Wittenberg, Ludwig-Wucherer-Str. 2, 06108 Halle, Germany e-mail: klaus.pillen@landw.uni-halle.de
“quantitative trait loci” (QTLs, Collard et al. 2005). Based on molecular linkage maps, many QTL studies were con-ducted since the late 1980s to identify and map the loci, which a V ect complex traits. In barley, such QTL studies focused on yield associated traits, as well as malting qual-ity, abiotic stress tolerance, and disease resistance (e.g. Tin-ker et al. 1996; Thomas et al. 1996; Je V eries et al. 1999; Kicherer et al. 2000).
Tanksley and Nelson (1996) proposed the advanced backcross (AB)-QTL analysis, which has several advanta-ges over classical QTL analyses. These are: (1) the detec-tion of QTLs and the development of improved varieties are conducted simultaneously. (2) Unadapted germplasm from wild species or land races is used to detect exotic alle-les superior to the elite alleles which might ultimately broaden the genetic variation of modern crop cultivars (Tanksley and McCouch 1997). (3) Since the AB-QTL strategy is based on BC2 or BC3 generations, the portion of the exotic donor genome, and thus linkage drag, is consid-erably reduced. The fact that wild species contain favorable alleles, which could be useful for the enhancement of quan-titative traits, was proven by many AB-QTL studies for several crop species, such as tomato (e.g. deVicente and Tanksley 1993; Fulton et al. 2002; Frary et al. 2004) and rice (Xiao et al. 1996; Li et al. 2002; Thomson et al. 2003; McCouch et al. 2007). In barley, several AB-QTL studies were conducted with regard to a multitude of characters, like agronomic traits, morphological traits, yield compo-nents, disease resistances, tolerance to abiotic stress and malting quality (Pillen et al. 2003, 2004; Talame et al. 2004; Li et al. 2005, 2006; Yun et al. 2006; Gyenis et al. 2007). Comprehensive studies were also performed by von Kor V et al. (2005, 2006, 2008), who generated a BC2DH population consisting of 301 lines based on an initial cross between the malting barley cultivar ‘Scarlett’ (Hordeum vulgare ssp. vulgare, hereafter abbreviated with Hv) and the Israeli wild barley accession ‘ISR 42-8’ (H. vulgare ssp. spontaneum, hereafter abbreviated with Hsp, von Kor V et al. 2004). The lines were genotyped with 98 SSR mark-ers, and subsequently evaluated under W eld conditions in up to eight environments. By a three-factorial mixed model analysis of variance (ANOVA), altogether 86 putative QTLs were identi W ed for nine agronomic traits, e.g. days until heading, plant height, thousand grain weight and grain yield, where 31 QTLs (36.0%) revealed a favorable e V ect of the exotic allele (von Kor V et al. 2006). In addition, 18 QTLs conferring resistance to diseases (von Kor V et al. 2005), and 48 QTLs for seven malting parameters (von Kor V et al. 2008), were detected. For these trait complexes, the performance was improved by the Hsp allele at 11 QTLs (61.1%) and 18 QTLs (37.5%), respectively.
As recommended by Zamir (2001), one step further towards the nearly simultaneous identi W cation and transfer of exotic QTL alleles associated with an improved trait per-formance, is the development and evaluation of introgres-sion lines (ILs). An IL set represents the complete genome of a wild species in the uniform background of an elite cul-tivar, where each single line solely contains a single marker-de W ned segment of the exotic parent. Due to the homozygosity of the ILs, they are a stable, and, thus, immortal, genetic resource which can be used with versatil-ity. Furthermore, the low proportion of exotic germplasm, present in each IL, is a great advantage compared to com-monly used QTL mapping populations, especially F2, BC1 and RI, but also AB populations. It allows the statistical veri W cation of small phenotypic e V ects, which are other-wise more di Y cult to detect (Zamir 2001). As an advance-ment compared to the AB-QTL analysis, the detection of QTLs and their simultaneous transfer into elite cultivars is carried out with ILs in one step. It does not require further steps of backcrossing or sel W ng. The usefulness of ILs for the detection of QTL e V ects and the identi W cation of favor-able exotic QTL alleles was demonstrated by numerous QTL studies for several di V erent crops, W rst of all for tomato. The Solanum pennellii IL library, which was initi-ated by Eshed and Zamir (1994) and currently consists of 76 ILs (Lippman et al. 2007), was used to identify nearly 3,000 putative QTLs for yield associated traits (Eshed and Zamir 1995; Hanson et al. 2007), morphological traits (Holtan and Hake 2003; Semel et al. 2006) and metabolites (Baxter et al. 2005; Overy et al. 2005; Schauer et al. 2006). With regard to quantitative traits, QTL studies using ILs were also conducted for rice (e.g. Mei et al. 2006; Zheng et al. 2007; Siangliw et al. 2007), wheat (Liu et al. 2006, 2007; Pestsova et al. 2006), maize (Szalma et al. 2007), melon (Eduardo et al. 2007; Fernandez-Trujillo et al. 2007; Moreno et al. 2008; Obando et al. 2008) and Arabidopsis (Keurentjes et al. 2007). In spring barley, Matus et al. (2003) conducted an association analysis to identify recom-binant chromosome substitution lines (RCSLs) showing positive transgressive segregation with respect to the elite parent for agronomic traits, domestication-related traits, and malting quality traits. Here, altogether 140 RCSLs, with a similar genetic structure as ILs, were evaluated in the W eld. A superior phenotype, compared to the elite par-ent, was exhibited by RCSLs for the traits number of grains per ear, ear length and thousand grain weight. A further barley QTL study using RCSLs was conducted by Hori et al. (2005). They developed a total of 134 RCSLs, each line carrying one or several Hsp introgressions, and con-taining on average 12.9% of the Hsp genome. By means of a core-set of 19 RCSLs and, in addition, 93 double-haploid lines (DHLs) originating from the same cross, altogether 18 and 24 QTLs could be identi W ed, respectively. Several QTLs revealed a coincident or very close localization in both populations (Hori et al. 2005).
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In the present study, we demonstrate the usefulness of wild barley introgression lines (S42ILs) for the detection of QTLs for important agronomic traits. The performance of a set of 39 S42ILs, each containing a single marker-de W ned Hsp introgression in the uniform genetic background of Hv, was evaluated with regard to seven traits in three di V erent W eld environments during 2007 growing season. Subse-quently, a line￡phenotype association study was conducted to verify QTL e V ects, which were previously identi W ed in the BC2DH population S42 (von Kor V et al. 2006), and, in addi-tion, to detect new QTLs. A further aim was to identify S42ILs, which exhibited an enhanced trait performance com-pared to the recurrent parent. These lines are a potentially valuable resource for the development of new elite cultivars. Materials and methods
Plant material
A set of 39 S42ILs (S42IL-101 to S42IL-139) were evalu-ated with regard to seven agronomic traits. The lines di V er among each other in only one single marker-de W ned chro-mosomal segment, introgressed from the Israeli wild barley accession ‘ISR 42-8’ (Hsp), whereas the remaining genome is consistently derived from the German spring barley culti-var ‘Scarlett’ (Hv). Based on 40 BC2DH lines, previously selected from spring barley population S42 (von Kor V et al. 2004), the S42ILs were developed by a further round of backcrossing with the recurrent parent ‘Scarlett’, several rounds of sel W ng and in parallel SSR marker-assisted selec-tion. Finally, the 39 S42ILs were selected in BC3S2 or BC3S4 generation. The approach and the genetic character-ization of the 39 S42ILs, as well as the veri W cation of QTLs for powdery mildew and leaf rust, are described in detail in Schmalenbach et al. (2008).
Phenotypic evaluation of agronomic traits
In order to evaluate the agronomic performance of the 39 S42ILs with regard to seven traits, W eld tests at three di V er-ent locations in Germany were conducted in the 2007 grow-ing season. The locations were the experimental W eld station Dikopshof (D07, University of Bonn, West Ger-many), and the breeders’ experimental W eld stations in Gudow (G07, Nordsaat Saatzucht, North Germany) and Herzogenaurach (H07, Saatzucht Josef Breun, South East Germany). The W eld tests were designed in three random-ized complete blocks (i.e. replications). The recurrent par-ent ‘Scarlett’ was tested as a control in four replications per block. In addition, the spring barley malting cultivar ‘Barke’ was tested in three replications per block to com-pare the performance of the S42ILs with a current https://www.doczj.com/doc/5e10458503.html, plot sizes (4.5–6.0m2), seed density (300–390kernels/ m2), nitrogen fertilization (30–80kg N/ha) taking into account the N min content of the soil, and W eld management were in accordance with the local practice. The grain was harvested with a plot harvester at total maturity (EC 92). The investigated traits and methods of measurement are listed in Table1.
Statistical analyses
Statistical analyses were carried out with SAS Enterprise Guide 4.1 (SAS Institute 2006). Genetic correlations between trait values were calculated with the least squares means (LSMEANS) for each of the 39 S42ILs averaged across all replications and environments. The LSMEANS were com-puted with the GLM procedure and used for calculating Pear-son’s correlation coe Y cient (r) with the CORR procedure.
For the detection of QTLs and identi W cation of favorable Hsp introgressions, a two-factorial mixed model ANOVA was carried out. The GLM model includes the line as a W xed factor, and the environment and line￡environment interac-tion as random factors: Y ijk= +L i+E j+LxE ij+ k(ij), where is the general mean, L i the W xed e V ect of the i th line, E j the random e V ect of the j th environment, L￡E ij is the random interaction e V ect of the i th line and the j th environ-ment, k(ij) is the error of Y ijk. When the analysis revealed sig-ni W cant di V erences between lines or line￡environment interactions, a Dunnett multiple comparison of LSMEANS di V erences between the ILs with the recurrent parent ‘Scar-lett’ as the control was conducted (Dunnett 1955). The pres-ence of a QTL in an Hsp introgression was accepted, when the trait value of a particular IL was signi W cantly (P<0.05) di V erent from ‘Scarlett’ across all environments (line main e V ect) and/or in a particular environment (line￡environment interaction e V ect). If several lines, which contained overlapping or X anking introgressions, showed a signi W cant e V ect of the same direction (increase or reduction of trait performance), it was assumed that these ILs carried the same QTL. Introgressions do overlap, if they pos-sess at least one common Hsp allele. They X ank each other, if they have adjacent Hsp alleles. The relative performance of an introgression line [RP (IL)] was calculated as follows: RP (IL)=[LSMEANS (IL)?LSMEANS (‘Scarlett’)]￡100/ LSMEANS (‘Scarlett’), where for each trait the LSMEANS were calculated across all replications and environments. Results
Trait performances of ‘Scarlett’ compared to the S42IL set
In Table2, the trait performances of the recurrent parent ‘Scarlett’ and the S42ILs are described per environment
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and across all tested environments by the parameters mean,minimum and maximum, and coe Y cient of variation.Across all three environments, both ‘Scarlett’ and the S42IL set revealed the highest coe Y cient of variation for the traits lodging at harvest (73.7 and 82.3%, respectively)and grain yield (34.8 and 35.0%, respectively). In contrast,a low variation of trait performance was measured for the traits grains per ear, days until heading, and plant height.As expected, ‘Scarlett’ exhibited a lower coe Y cient of vari-ation than the S42ILs for all traits and environments. Aver-aged across all environments and in G07, ‘Scarlett’ showed a slightly higher performance in grain yield than the S42IL set (50.8 and 60.0dt/ha, compared to 50.3 and 57.7dt/ha,respectively). In D07 and H07, an opposite e V ect was mea-sured (Table 2).Trait correlations
A total of 17 signi W cant correlations were detected between the seven investigated traits (Table 3). The strongest posi-tive correlations were found between days until heading and the traits grains per ear (r =0.74) and thousand grain weight (r =0.73), as well as between plant height and lodg-ing at harvest (r =0.73). In addition, days until heading exhibited strong negative correlations with lodging at har-vest (r =?0.84) and plant height (r =?0.61). Grain yield revealed signi W cant correlations with all traits. Whereas negative correlations were found with days until heading and grains per ear (r =?0.52 and r =?0.27, respectively),the other four traits showed positive correlations with grain yield ranging from 0.37 for plant height to 0.68 for thou-sand grain weight.QTL detection
In order to verify QTL e V ects, which were previously detected within the BC 2DH population S42, and to identify new QTLs, the 39 S42ILs were subjected to a line ￡phenotype association study. The initial two-facto-rial mixed model ANOVA exhibited signi W cant line e V ects (P <0.05) for all seven evaluated traits except ears per square meter. Signi W cant line ￡environment interaction e V ects (P <0.05) were detected for all traits (data not shown).
The subsequent Dunnett test revealed altogether 65 sig-ni W cant line ￡phenotype associations with four line main e V ects and 18 line ￡environment interaction e V ects. For 43 associations, the line main e V ect and the line ￡environment interaction e V ect, were signi W cant,simultaneously (Table 4). For 29 associations (44.6%),the respective IL showed an improved trait performance in comparison to the recurrent parent ‘Scarlett’. Taking into account that several ILs do overlap or are X anked, a
T a b l e 1L i s t o f s e v e n a g r o n o m i c t r a i t s e v a l u a t e d f o r 39 S 42I L s i n u p t o t h r e e e n v i r o n m e n t s
a
T h e b r e e d i n g g o a l s f o r t h e e v a l u a t e d t r a i t s w e r e d e W n e d a c c o r d i n g t o b r e e d i n g p r o g r a m s f o r s p r i n g m a l t i n g b a r l e y , w h e r e (?) i n d i c a t e s t h a t a r e d u c t i o n , a n d (+) t h a t a n i n c r e a s e o f t h e t r a i t v a l u e s i s d e s i r a b l e b T h e e n v i r o n m e n t n a m e s a r e c o m b i n a t i o n s o f t h e l o c a t i o n [D i k o p s h o f (D ), G u d o w (G ), H e r z o g e n a u r a c h (H )] a n d t h e y e a r 2007 (07)
A b b r .T r a i t
U n i t s
M e t h o d o f m e a s u r e m e n t
B r e e d i n g g o a l a
E n v i r o n m e n t t e s t e d b E A R
E a r s p e r s q u a r e m e t e r
N o . o f e a r s /m 2
N u m b e r o f e a r s c o u n t e d f r o m a r o w o f 50c m (D 07) o r 100c m (H 07)
+
D 07, H 07
G E A
G r a i n s p e r e a r
N o . o f g r a i n s /e a r
N u m b e r o f g r a i n s p e r e a r c a l c u l a t e d f r o m a r o w o f 50c m (D 07) o r 20 a v e r a g e e a r s (G 07 a n d H 07)
+
D 07, G 07, H 07
H E A
D a y s u n t i l h e a d i n g
d
N u m b e r o f d a y s f r o m s o w i n g u n t i l e m e r g e n c e o f 50% o f e a r s o n m a i n t i l l e r s
?D 07, G 07
H E I
P l a n t h e i g h t
c m
A v e r a g e p l a n t h e i g h t (i n c m ) m e a s u r e d f r o m s o i l s u r f a c e t o t i p o f s p i k e (i n c l u d i n g a w n s ) 2w e e k s a f t e r X o w e r i n g
?
D 07, G 07, H 07
L A H
L o d g i n g a t h a r v e s t
S c o r e s 1–9
V i s u a l r a t i n g o f t h e s e v e r i t y o f l o d g i n g a t h a r v e s t , w h e r e o n e r e p r e s e n t s n o l o d g i n g a n d n i n e r e p r e s e n t s t o t a l l o d g i n g o f p l o t
?
D 07, G 07, H 07
T G W
T h o u s a n d g r a i n w e i g h t g /1,000 g r a i n s A v e r a g e w e i g h t (i n g ) o f 1,000 g r a i n s c a l c u l a t e d f r o m t w o s a m p l e s o f 250 g r a i n s
+D 07, G 07, H 07
Y L D
G r a i n y i e l d d t /h a
W e i g h t o f b a r l e y g r a i n (i n d t /h a ), h a r v e s t e d f r o m 6.0m 2 (D 07), 4.5m 2 (G 07), 5.0/5.5m 2 (H 07), a f t e r d r y i n g f o r 1–2d a y s
+
D 07, G 07, H 07
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total of 47 putative QTLs were identi W ed. Here, one QTL (QTgw.S42IL-2H.b) was detected solely as line main e V ect and eight QTLs solely as line ￡environment inter-action e V ect. For the remaining 38 QTLs both the line main e V ect and the line ￡environment interaction e V ect,were signi W cant. Nineteen QTLs (40.4%) showed a favor-able e V ect of the Hsp introgression. In the following para-
graphs, the QTL e V ects are described for each trait separately.
Ears per square meter (EAR)
For EAR, altogether four S42ILs revealed a signi W cant line ￡phenotype association. Taking into account that
Table 2Parameters describing the trait performance of the recurrent parent ‘Scarlett’ and the S42ILs per environment and across all tested envi-ronments
a The trait and environment abbreviations are given in Table 1
b Number of observations
c Average trait performance
d Minimum and maximum trait performanc
e e
Coe Y cient of variation (in %)=SD/mean
Trait and environment a
‘Scarlett’S42ILs
N b
Mean c
Min d
Max d
CV (in %)e
N b
Mean c
Min d
Max d
CV (in %)e
EAR D0712968.0673.11250.018.01171033.7576.91634.622.2H07
12946.7840.01088.010.2117903.9616.01216.014.3Across all env.24957.3673.11250.014.4234968.8576.91634.620.3GEA D071222.319.024.0 6.411719.913.023.011.4G07423.022.024.0 3.53922.517.026.07.8H07
1223.520.027.08.411722.213.026.010.0Across all env.28 2.919.027.07.427321.213.026.011.7HEA D071260.360.061.00.811759.147.064.0 5.4G07
1272.370.075.0 2.011771.062.076.0 4.7Across all env.2466.360.075.09.423465.147.076.010.4HEI D071290.983.0101.0 5.711789.370.0100.0 6.3G071275.472.080.0 3.611778.663.0103.012.3H07
876.070.082.0 5.37877.564.098.08.6Across all env.3281.470.0101.010.431282.363.0103.011.3LAH D07127.4 5.08.012.11177.3 3.09.016.5G0712 3.2 1.0 5.050.1117 2.6 1.09.086.4H07
12 1.1 1.0 2.026.6117 1.3 1.08.092.4Across all env.36 3.9 1.08.073.7351 3.7 1.09.082.3TGW D071239.737.143.0 4.811739.334.647.0 5.8G071244.238.647.8 5.811744.936.452.0 6.9H07
1233.732.236.2 4.211733.526.941.88.7Across all env.3639.232.247.812.335139.226.952.013.8YLD D071265.761.872.4 5.011766.252.478.7 6.9G071260.054.764.9 5.011757.738.067.39.4H07
1226.820.430.411.911726.913.935.916.6Across all env.
36
50.8
20.4
72.4
34.8
351
50.3
13.9
78.7
35.0
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several lines contain overlapping or X anking introgressions,these associations were summarized to two QTLs on chromo-some 2H and 6H, respectively. At QEar.S42IL-2H.a, the line main e V ect and the line ￡environment interaction e V ect were signi W cant, whereas for QEar.S42IL-6H.a a signi W cant e V ect was only found in environment D07. For both QTLs, the Hsp introgression was associated with an increased number of ears per square meter relative to ‘Scarlett’. The strongest e V ect was exhibited by S42IL-107, containing an Hsp segment in the region 2H, 17-42cM. This line showed a signi W cantly higher trait performance than the recurrent parent only in the environment D07. Here, the number of ears per square meter was increased by 397.4 (41.1%) relative to ‘Scarlett’.Grains per ear (GEA)
A total of 14 signi W cant line ￡phenotype associations were identi W ed for the trait GEA on all chromosomes except 5H and 6H. These associations were summarized to eight QTLs, where W ve QTLs showed both a signi W cant line main e V ect and a line ￡environment interaction e V ect. Two QTLs each were localized on chromosomes 2H, 4H and 7H. At all eight QTLs, the Hsp introgressions were associ-ated with a reduced number of GEA by up to ?6.1(?26.8%) for S42IL-107 at QGea.S42IL-2H.a.Days until heading (HEA)
Altogether 19 signi W cant line ￡phenotype associations,summarized to 14 putative QTLs, were identi W ed for HEA on all seven barley chromosomes. For 12 QTLs both the line main e V ect and the line ￡environment interaction e V ect, were signi W cant, whereas two QTLs on chromosome 6H revealed an interaction e V ect solely for D07. For 13line ￡phenotype associations, and according to this, for nine QTLs, the exotic introgression was associated with a reduced number of days until heading relative to ‘Scarlett’.The strongest favorable e V ect was mapped to the region 2H, 17–42cM by S42ILs ?107 and ?108. Here, the num-ber of days until heading was reduced by 10.4 (15.7%) and
10.3 (15.5%), respectively. Strong reduction e V ects of ?6.6days (?9.9%) and ?6.1days (?9.2%) caused by Hsp introgressions were mapped to the regions 4H, 80–95cM and 7H, 146–166cM by the S42ILs ?121 and ?137,respectively.Plant height (HEI)
For HEI, eight signi W cant line ￡phenotype associations were localized on all chromosomes except 6H. Due to the X anking introgressions of S42ILs ?107 and ?109, a total of seven QTLs were detected. At all loci, the line main e V ect and the line ￡environment interaction e V ect were signi W-cant. At QHei.S42IL-2H.a, the Hsp segment, located within the region 2H, 17–42cM, caused a plant height reduced by 11.8cm (14.6%) relative to the control ‘Scarlett’. At the remaining six QTLs, the Hsp introgression increased the plant height by up to 15.9cm (19.7%) at QHei.S42IL-7H.b.Lodging at harvest (LAH)
Seven signi W cant line ￡phenotype associations were local-ized for LAH on chromosomes 1H, 2H, 4H and 7H. Taking into account that two S42ILs on chromosome 2H do over-lap, altogether six QTLs were detected. For W ve QTLs both the line main e V ect and the line ￡environment interaction e V ect, were signi W cant, whereas for one QTL solely an interaction e V ect was signi W cant in environment G07. At QLah.S42IL-2H.a, the exotic introgression caused a maxi-mum reduction of lodging severity at harvest by 1.6 scores (40.0%) relative to ‘Scarlett’ within the region 2H, 67–92cM. In addition, S42IL-138 containing an exotic intro-gression on chromosome 7H, 166–181cM, revealed a LAH reduced by 1.4 scores (37.1%) at QLah.S42IL-7H.b.Thousand grain weight (TGW)
For TGW, eight signi W cant line ￡phenotype associations were localized on chromosomes 2H, 4H and 6H. These e V ects were summarized to six QTLs. For one QTL the line
Table 3Pearsons correlation coe Y cient (r ) between seven agronomic traits in 39 S42ILs The agronomic traits are de W ned in Table 1. For calculating correlation coe Y cients, the least squares means of the trait performance of each IL were averaged across replications and environments. The r values are signi W cant with *P <0.05, **P <0.01 or ***P <0.001
Traits GEA HEA HEI LAH TGW YLD EAR ?0.51***
?0.36*0.030.39***0.25*0.47***GEA 0.74***
?0.19*?0.46***?0.02?0.27**HEA ?0.61***
?0.84***0.73***?0.52***HEI 0.73***
0.030.37***LAH 0.13
0.67***TGW
0.68***
Table4List of 65 signi W cant line￡phenotype associations for seven agronomic traits detected with 39 S42ILs
Trait a QTL in S42IL Chr.b Introgression
(in cM)c Introgression
line
E V ect d LSMEANS
(IL)e
Di V.f RP (IL) %g QTL in BC2DH
(von Kor V et al.
2006)
Candidate
genes h
EAR QEar.S42IL-2H.a2H17–42S42IL-107I1365.4D07397.441.1QEar.S42-2H.a Ppd-H11 2H17–92S42IL-108L+I1243.4286.129.9QEar.S42-2H.a,
QEar.S42-2H.b
2H67–92S42IL-109L+I1237.9280.629.3QEar.S42-2H.b QEar.S42IL-6H.a6H145–155S42IL-132I1359.0D07391.040.4QEar.S42-6H.a
GEA QGea.S42IL-1H.a1H39–70S42IL-103I19.7H07?3.8?16.3
QGea.S42IL-2H.a2H17–42S42IL-107L+I16.8?6.1?26.8Ppd-H11 2H17–92S42IL-108L+I19.7?3.3?14.2
QGea.S42IL-2H.b2H67–92S42IL-109L+I18.4?4.5?19.5
2H80–86S42IL-110L+I18.2?4.7?20.5
QGea.S42IL-3H.a3H65–70S42IL-111L+I19.1?3.8?16.6
QGea.S42IL-4H.a4H80–95S42IL-121L+I20.4?2.5?10.8
4H125–132S42IL-122I19.0D07?3.3?14.6
4H125–170S42IL-123L+I20.6?2.4?10.3
QGea.S42IL-4H.b4H170–190S42IL-124I18.3D07?3.3?17.6
QGea.S42IL-7H.a7H50S42IL-133I18.3D07?3.9?17.6
7H62–75S42IL-134L+I20.7?2.3?9.8
QGea.S42IL-7H.b7H146–155S42IL-136I19.0D07?3.3?14.6
7H146–166S42IL-137I17.7D07?4.6?20.6
HEA QHea.S42IL-1H.a1H0–85S42IL-102L+I68.2 1.9 2.9
1H39–70S42IL-103L+I68.3 2.1 3.1
QHea.S42IL-1H.b1H70–85S42IL-105L+I62.0?4.2?6.4
QHea.S42IL-2H.a2H17–42S42IL-107L+I55.8?10.4?15.7QHea.S42-2H.a Ppd-H11 2H17–92S42IL-108L+I56.0?10.3?15.5
QHea.S42IL-2H.b2H67–92S42IL-109I59.0D07?1.3?2.1
2H80–86S42IL-110L+I62.3?3.9?5.9
QHea.S42IL-3H.a3H130–175S42IL-114L+I62.8?3.4?5.2QHea.S42-3H.b sdw1(denso)2 3H155–190S42IL-115I59.0D07?1.3?2.1
QHea.S42IL-4H.a4H31–57S42IL-120L+I68.0 1.8 2.6
QHea.S42IL-4H.b4H80–95S42IL-121L+I59.7?6.6?9.9
QHea.S42IL-4H.c4H170–190S42IL-124L+I68.2 1.9 2.9QHea.S42-4H.a Vrn-H23
QHea.S42IL-5H.a5H43–69S42IL-125L+I62.2?4.1?6.2
QHea.S42IL-6H.a6H96–112S42IL-129I59.0D07?1.3?2.1QHea.S42-6H.b eps6L.12
QHea.S42IL-6H.b6H145–155S42IL-132I61.7D07 1.4 2.4
QHea.S42IL-7H.a7H50S42IL-133L+I69.0 2.8 4.2Vrn-H34
QHea.S42IL-7H.b7H62–75S42IL-134L+I63.2?3.1?4.7HvCO15 7H75–155S42IL-135I59.0D07?1.3?2.1QHea.S42-7H.b HvCO15, eps7L2 QHea.S42IL-7H.c7H146–166S42IL-137L+I60.2?6.1?9.2eps7L2
HEI QHei.S42IL-1H.a1H70–85S42IL-105L+I89.99.111.3
QHei.S42IL-2H.a2H17–42S42IL-107L+I69.0?11.8?14.6QHei.S42-2H.a Ppd-H11 2H67–92S42IL-109L+I73.1?7.7?9.6QHei.S42-2H.b sdw36 QHei.S42IL-3H.a3H130–175S42IL-114L+I94.914.117.5QHei.S42-3H.b sdw1 (denso)2 QHei.S42IL-4H.a4H80–95S42IL-121L+I95.414.618.1
QHei.S42IL-5H.a5H43–69S42IL-125L+I92.912.215.1QHei.S42-5H.a
QHei.S42IL-7H.a7H62–75S42IL-134L+I90.09.211.4QHei.S42-7H.b HvCO15
QHei.S42IL-7H.b7H146–166S42IL-137L+I96.715.919.7QHei.S42-7H.c
123
123
main e V ect and for three QTLs the line main e V ect plus the line ￡environment interaction e V ect were signi W cant. At the remaining QTLs a line plus a line ￡environment inter-action and a sole interaction e V ect was detected for the two linked ILs ?107 and ?108 whereas a line and a sole inter-action e V ect was detected for the two linked ILs ?119 and ?121. Four QTLs revealed a favorable e V ect of the exotic introgression on TGW. The highest increase in trait perfor-mance was measured at QTgw.S42IL ?2H.a in S42IL-108,which harbors a Hsp segment in the region 2H, 17–92cM.Here, the thousand grain weight was increased by 4.4g (13.1%) relative to ‘Scarlett’. This e V ect was solely signi W-cant in environment H07. The strongest favorable Hsp e V ect, which was signi W cant across all three environments,was mapped to 4H, 31–95cM. Here, S42IL-119 revealed a TGW increased by 3.4g (8.7%) relative to ‘Scarlett’.
Grain yield (YLD)
Altogether W ve signi W cant line ￡phenotype associations were identi W ed for YLD. Due to two X anking S42ILs on chromosome 7H, these e V ects were summarized to four QTLs on chromosomes 4H and 7H. Three QTLs were detected both as line main e V ect and line ￡environment interaction e V ect. At all three loci, the exotic segment was associated with a grain yield reduced by up to 10.8dt/ha (18.0%) in S42IL-134 at QYld.S42IL-7H.a. The QTL QYld.S42IL-4H.a was assessed solely as line ￡ environ-ment interaction e V ect, and revealed an improved trait per-formance compared to the recurrent parent for S42IL-118.Here, the introgression within region 4H, 31–57cM caused an increase in grain yield by 7.8dt/ha (11.8%) relative to ‘Scarlett’ in environment D07.
Table 4continued a Abbreviations of traits see Table 1
b
Chromosomal location of the target introgression c
Chromosomal extent of the target introgression in centiMorgans d
In the two-factorial ANOVA, signi W cant line ￡phenotype associations (P <0.05) were detected as line main e V ect (L) or line ￡environment interaction e V ect (I)e
If line main e V ects (L), or line main e V ects and a line ￡environment interaction e V ects (L +I) were detected, the LSMEANS[IL] across all envi-ronments are listed. If solely a line ￡environment interaction (I) was identi W ed, the LSMEANS[IL] in the particular environment (D07, G07 or H07) is given f
Score di V erence =LSMEANS[IL]?LSMEANS [Scarlett]g
Relative performance: RP[IL]=(LSMEANS[IL] – LSMEANS [Scarlett])￡100/LSMEANS[Scarlett]h
References: 1Turner et al. (2005), 2Laurie et al. (1995), 3Yan et al. (2004), 4Yan et al. (2006), 5Gri Y ths et al. (2003), 6Gottwald et al. (2004)
Trait a QTL in S42IL
Chr.b Introgression (in cM)c Introgression line E V ect d LSMEANS (IL)e
Di V .f
RP (IL) %g QTL in BC2DH (von Kor V et al. 2006)Candidate
genes h LAH QLah.S42IL-1H.a 1H
70–85S42IL-105I 6.3G07 3.2100.0QLah.S42IL-2H.a 2H
67–92S42IL-109L +I 2.3?1.6?40.0QLof.S42-2H.a
sdw36
2H
80–86S42IL-110L 2.6?1.3?34.3QLah.S42IL-4H.a 4H 80–95S42IL-121L +I 6.8 2.974.3QLah.S42IL-4H.b 4H 125–170S42IL-123L +I 5.4 1.640.0QLah.S42IL-7H.a 7H 146–166S42IL-137L +I 7.3 3.488.6QLof.S42-7H.b QLah.S42IL-7H.b 7H 166–181S42IL-138L +I 2.4?1.4?37.1TGW QTgw.S42IL-2H.a 2H
17–42S42IL-107L +I 42.3 3.17.9QTgw.S42-2H.a Ppd-H112H
17–92S42IL-108I 38.1H07 4.413.1QTgw.S42IL-2H.b 2H 80–86S42IL-110L 41.9 2.77.0QTgw.S42-2H.a QTgw.S42IL-4H.a 4H
31–95S42IL-119L 42.6 3.48.7QTgw.S42-4H.a
4H
80–95S42IL-121I 44.6D07 4.912.3QTgw.S42IL-4H.b 4H 125–132S42IL-122L +I 35.0?4.2?10.8QTgw.S42-4H.b QTgw.S42IL-4H.c 4H 170–190S42IL-124L +I 35.7?3.5?8.8QTgw.S42IL-6H.a 6H 112–155S42IL-130L +I 42.2 3.07.7YLD QYld.S42IL-4H.a
4H 31–57S42IL-118I 73.5D077.811.8QYld.S42IL-4H.b 4H 80–95S42IL-121L +I 41.9?9.0?17.7QYld.S42IL-7H.a 7H 50S42IL-133L 45.2?5.6?11.17H 62–75S42IL-134I 49.2G07
?10.8?18.0
QYld.S42IL-7H.b
7H
146–166
S42IL-137
L +I
41.8
?9.1
?17.9
QYld.S42-7H.b
Discussion
Identi W cation and veri W cation of QTLs
During the 2007 growing season, a set of 39 wild barley introgression lines (S42ILs) were evaluated in the W eld with regard to seven agronomic traits, and subsequently sub-jected to a line￡phenotype association study. The aim of the experiment was to verify QTL e V ects, previously detected with 301 double haploid lines of the population S42, and to identify new QTLs. It was furthermore intended to identify Hsp introgressions which cause an improvement of several traits simultaneously. The S42ILs carrying these introgressions could be used directly for the development of new elite cultivars. For the W ve traits EAR, HEA, HEI, TGW and YLD, both the S42ILs and the population S42, were evaluated. In addition, lodging was investigated at harvest (LAH) in the S42IL set, but at X owering (LOF) in the S42 population. The QTLs for LAH and LOF are directly comparable since both traits are closely linked. Von Kor V et al. (2006) identi W ed altogether 63 putative QTLs for the six traits in the S42 population, where 23 QTLs (36.5%) showed a favorable e V ect of the Hsp allele. Forty-four QTLs, among which 18 QTLs revealed a favor-able Hsp e V ect, are located in chromosomal regions which are already represented by Hsp introgressions in S42ILs, and are therefore comparable with the QTLs detected in the S42ILs. As illustrated in Table4, 20 out of 44 QTLs (45.5%) and ten out of 18 QTLs with a favorable Hsp e V ect (55.6%) were veri W ed by the evaluated S42ILs. Altogether, 18 out of 20 corresponding QTLs (90.0%) showed an e V ect of the same direction in both populations.
As underlined by Bernacchi et al. (1998b), the veri W ca-tion of a QTL can be characterized by the stability of its e V ect across environments. In the present study, 18 QTLs were stable across all tested environments in the S42 pop-ulation as well as in the S42ILs. A further important crite-rion for the evaluation of QTL veri W cation results is the magnitude of the e V ect measured in both populations. For all corresponding QTLs, with the exception of QHei.S42IL-7H.a and QHei.S42-7H.b, at least one S42IL exhibited a higher relative performance in comparison to ‘Scarlett’ than measured for the corresponding QTL in the S42 population. These di V erences as well as the non-con-W rmation of QTL e V ects from population S42 might be explained by the reduction of epistatic Hsp e V ects which are still active in the S42ILs. Since the S42ILs contain sin-gle exotic introgressions, whereas the BC2DH lines in the S42 population carry multiple independent introgressions, potential interactions between non-linked Hsp alleles are expected to be reduced in the S42IL set. Furthermore, the QTL data of the S42 population were based on W eld tests at up to eight di V erent environments, and thus o V ered a high reliability, whereas the S42ILs were only tested in three environments.
For the six traits analyzed in both populations, altogether 17 new QTLs, previously not identi W ed in the S42 popula-tion, were detected in the S42IL set. Here, six QTLs (35.3%) revealed a favorable Hsp e V ect. Furthermore, eight QTLs for the newly identi W ed trait GEA were mapped by S42ILs, among which no QTL showed a favorable Hsp e V ect.
A similar approach to verify QTLs was conducted in tomato by Bernacchi et al. (1998b). The authors generated a set of 23 near isogenic lines (NILs), which harbored QTLs with a favorable e V ect on one or several agronomic traits. Each NIL contained a single introgression of the wild spe-cies S. hirsutum or S. pimpinellifolium, whereas the remain-ing part of the genetic background was consistently derived from the elite parent S. esculentum. The aim of the study was to verify 25 QTLs for seven traits, previously mapped to 15 di V erent genomic regions in two A
B populations (Bernacchi et al. 1998a). The agronomic performance of the NILs was tested in W ve di V erent environments, and a total of 22 QTLs (88%) could be con W rmed by the NILs in at least one environment.
In the following paragraphs, the QTL results of the pres-ent study are discussed for each trait or trait complex sepa-rately. They are compared to the QTL e V ects, previously identi W ed in population S42 (von Kor V et al. 2006), and to di V erent candidate genes which map to the same chromo-somal region.
Days until heading
For HEA, von Kor V et al. (2006) detected a total of ten QTLs, half of them were located in genomic regions, which are already represented by Hsp introgressions of S42ILs. These W ve QTLs were veri W ed by QTL e V ects detected in the S42IL set, and exhibited an e V ect with the same direc-tion in both populations (Table4). Four QTLs were signi W-cant across all environments in the S42 population as well as in the S42ILs. In both populations, the strongest favor-able Hsp e V ect, associated with a reduction of HEA, was mapped to the top of chromosome 2H (QHea.S42-2H.a and QHea.S42IL-2H.a, respectively). Here, the number of days until heading was reduced by up to 10.4 (15.7%) in S42IL-107, compared to ‘Scarlett’. In the same region, Ppd-H1, the major photoperiod response gene of barley, whose day-length sensitive alleles promote X owering under long day conditions, is located (Turner et al. 2005). HvCO1, another barley photoperiod response gene of the circadian clock (Gri Y ths et al. 2003), coincides with the QTL QHea.S42IL-7H.b, which was detected in the S42ILs ?134 and ?135 on chromosome 7H. The barley vernalization response genes Vrn-H2 and Vrn-H3, which regulate X ower-
123
ing depending on low temperature (Laurie et al. 1995; Yan et al. 2004, 2006), are located on chromosomes 4H and 7H. These loci correspond to the QTLs QHea.S42IL-4H.c and QHea.S42-4H.a, and the newly identi W ed QTL QHea.S42IL-7H.a, respectively (Table4). All three QTLs exhibited an increased Hsp e V ect on number of days until heading. This is consistent with the fact that wild barley requires a period of low temperature as impulse for X ower-ing (Laurie 1997). Several ‘earliness per se’ genes, which are relatively independent from photoperiod and vernaliza-tion conditions, were mapped by Laurie et al. (1995). The genes eps6L.1 and eps7L coincide with the QTLs QHea.S42IL-6H.a and QHea.S42-6H.b, and QHea.S42IL-7H.c and QHea.S42-7H.b on chromosome 6H and 7H, respectively. Laurie et al. (1995) demonstrated a delay in X owering time in barley caused by the dwar W ng gene sdw1 (previously named denso). The gene location on chromo-some 3H corresponds to the localization of the QTLs QHea.S42IL-3H.a and QHea.S42-3H.b, which both exhib-ited an enhanced Hsp e V ect on HEA. Altogether eight new QTLs, which were not detected in the S42 population, were revealed by S42ILs. Half of them showed a reducing Hsp e V ect on HEA.
Plant height and lodging at harvest
In population S42, altogether 11 QTLs were detected for HEI (von Kor V et al. 2006), at which seven QTLs were localized in regions which are so far represented by S42ILs. Six out of these seven QTLs (85.7%) were con W rmed by QTL e V ects detected in S42ILs, exhibiting e V ects with the same direction in both populations (Table4). Furthermore, W ve veri W ed QTLs revealed signi W cant e V ects across all environments, both in S42 population and in the S42ILs. In both populations, the strongest favorable Hsp e V ect on HEI was mapped to region 2H, 17–42cM. Here, plant height was reduced in S42IL-107 by 14.6%, relative to ‘Scarlett’, whereas the Hsp allele in the S42 population caused a reduction e V ect of 11.7%. As described by Laurie et al. (1994), this localization corresponds to the Ppd-H1 locus which, in addition to X owering regulation, exerts a strong e V ect on plant height (Turner et al. 2005). A possible candi-date gene for QHei.S42-2H.b and the e V ect of QHei.S42IL-2H.a in S42IL-109 is the gibberellic-acid insensitive dwar-W ng gene sdw3 of barley (Gottwald et al. 2004). It might also be causal for the strong reduction of LAH in S42ILs ?109 and ?110 at QLah.S42IL-2H.a. As illustrated in Fig.1, further co-localizations of QTLs for HEI and LAH are present in the chromosomal regions 1H, 70–85cM, 4H, 80–95cM, and 7H, 146–166cM. For all three QTLs, the Hsp introgression caused an increasing e V ect on both traits, which coincides with their strong positive correlation of 0.73 (Table3). The dwar W ng gene sdw1, which reduces plant height and lodging (Bezant et al. 1996), maps to the same genomic region as QHei.S42IL-3H.a and QHei.S42-3H.b. However, no QTL e V ect on LAH was detected by S42ILs in this region. The QTLs QHei.S42IL-7H.a and QHei.S42-7H.b, which both revealed an increasing Hsp e V ect on HEI, coincide with HvCO1 (Gri Y ths et al. 2003). As described above, the number of days until heading is reduced by Hsp introgressions in the same region. These opposed e V ects on HEA and HEI correspond to their nega-tive correlation (r=?0.61). In addition to the veri W ed QTLs, two new unfavorable Hsp e V ects on HEI were iden-ti W ed in S42ILs on chromosome 1H and 4H.
Altogether seven QTLs for lodging at X owering which mapped to regions covered by exotic introgressions in the S42IL set, were identi W ed by von Kor V et al. (2006). As shown in Table4, the QTLs QLof.S42-2H.a and QLof.S42-7H.b were veri W ed by QLah.S42IL-2H.a and QLah.S42IL-7H.a, detected by the S42ILs -109 and ?110, and ?137, respectively. In the S42 population as well as in the S42ILs, both QTLs were detected as signi W cant e V ects of the same direction across all environments. In the present study, four new QTLs for LAH were localized on chromosomes 1H, 4H and 7H. Here, QLah.S42IL-7H.b exhibited a favorable Hsp e V ect.
Yield components
In the present study, the S42IL set was evaluated with regard to the three yield components EAR, GEA and TGW. Von Kor V et al. (2006) detected altogether 11 and nine QTLs for EAR and TGW, respectively. Nine and eight QTLs are localized in chromosomal regions which are also represented by S42ILs. For both traits, three QTLs could be con W rmed in the S42IL study (Table4). For EAR as well as for TGW, one QTL revealed an unfa-vorable Hsp e V ect in the S42 population, but a favorable exotic e V ect in the S42ILs. Furthermore, one new QTL e V ect for TGW with an enhanced trait performance of S42IL-130 was mapped to the genomic region 6H, 112–155cM. For EAR and GEA, the S42ILs ?107, ?108 and ?109 revealed co-localizations of signi W cant line￡phenotype associations in the region 2H, 17–92cM. All three S42ILs showed an increased EAR and simultaneously a reduced GEA, compared to ‘Scarlett’(Fig.1). These e V ects with an opposed direction coincide with a negative correlation of ?0.51 between both traits. For all three yield components, QTL e V ects were detected by the S42ILs ?107 and ?109 on the top of chromosome 2H. As described by Laurie et al. (1994), the Ppd-H1 locus, which mapped to the same region, also has an e V ect on yield components, probably as a direct result of the e V ect on X owering time. Also on chromosome 2H, but not directly at the Ppd-H1 locus, Li et al. (2005, 2006)
123
123
detected altogether eight QTLs for the W ve yield compo-nents ear length, spikelet number per spike, grain number per spike, spike number per plant, and thousand grain mass. At one QTL each for spike number per plant and thousand grain mass, the Hsp allele was associated with an improved trait performance.
Grain yield
For YLD, von Kor V et al. (2006) detected 13 QTLs on all chromosomes. At three QTLs the Hsp allele caused an increased grain yield compared to the recurrent parent.Nine QTLs could theoretically be veri W ed by the 39
Fig.1
SSR map with 65 signi W -cant (P <0.05)
line ￡phenotype associations for 39 S42ILs and seven agro-nomic traits. The chromosomes are shown as black bars with centiMorgan values for SSR loci following the order of von Kor V et al. (2004). The extent of Hsp introgressions are given in grey bars right to the chromosomes. The associations are illustrated as symbols below the S42ILs. They either reveal a favorable (W lled symbols ) or unfavorable (empty symbols ) Hsp e V ect. Associations solely detected as line ￡environment interaction e V ect are marked by an asterisk right to the symbol
S42ILs since they are located in genomic regions which are covered by Hsp introgressions. Solely the QTL QYld.S42-7H.b, showing an unfavorable Hsp e V ect in the S42 population, was veri W ed by QYld.S42IL-7H.b. The latter revealed a reduced grain yield in S42IL-137, com-pared to ‘Scarlett’. In addition, three new QTLs for YLD were mapped to chromosomes 4H and 7H present in four di V erent S42ILs (Table4). A potentially valuable intro-gression line for breeding of cultivars with enhanced grain yield might be S42IL-118 where yield was increased by 11.8% relative to ‘Scarlett’. However, the stability of this favorable e V ect has to be veri W ed since the YLD e V ect was only detected as a line￡environment interaction active in D07.
Several times, co-localizations of QTLs for YLD and yield associated traits were detected which were consis-tent with the genetic correlations, for example, for HEA and TGW (Fig.1). In the region 4H, 31–57cM, a QTL e V ect for YLD as well as for TGW was detected. For both traits, the Hsp introgression caused an enhanced perfor-mance compared to the recurrent parent. This coincides with the strong positive correlation (r=0.68) between YLD and TGW (Table3). One coincidence of QTLs for YLD and HEA was identi W ed in the genomic region 7H, 50cM. Here, an opposite Hsp e V ect was in accordance with the negative trait correlation of ?0.52. For YLD and LAH, two QTL co-localizations were detected in the regions 4H, 80–95cM and 7H, 146–166cM. On both QTLs the exotic introgression was associated with a reducing e V ect on YLD and an increasing e V ect on LAH. This is contrary to the positive genetic correlation between both traits. Due to the fact that a strong severity of lodging is assumed to be associated with a loss of grains, and, thus, a reduced grain yield, a negative trait correlation would be expected. For instance, von Kor V et al. (2006) measured a genetic correlation of ?0.55 between the traits grain yield and lodging at X owering. In the present study, the unexpected positive correlation between YLD and LAH might be due to the fact, that both traits di V ered substantially between the three examined environments. Whereas LAH was extremely high in D07, YLD was extremely low in H07 (Table2). We assume that the observed positive correlation might be arti W cial since it disappeared when the calculation was based on single plot entries per environment (data not shown). Despite a positive genetic correlation (r=0.47) between YLD and EAR, no co-localizations of QTLs could be revealed. In contrast, three co-localizations for YLD and GEA were detected on chromosomes 4H and 7H (Fig.1). In all cases, an unfavorable Hsp e V ect on both traits was observed. Here, the negative correlation of ?0.27 was contradictory.Examples of S42ILs harboring QTL e V ects
for several traits simultaneously
As illustrated in Fig.1, several chromosomal regions revealed clusters of QTLs for di V erent traits. Among the set of 39 S42ILs, altogether seven lines on chromosomes 2H, 4H and 7H exhibited at least four QTLs simultaneously. Four of these lines carry introgressions on chromosome 2H, among which the S42ILs ?107 and ?109 exhibited a favorable Hsp e V ect on four di V erent traits. S42IL-107, car-rying a Hsp segment in the region 2H, 17–42cM, showed a signi W cant improved performance relative to the recurrent parent for the traits HEA, HEI and TGW across all tested environments. In addition, one favorable Hsp e V ect on EAR, only signi W cant in environment D07 was measured (Table4). In S42IL-109, the exotic introgression in the region 2H, 67–92cM was associated with an improved per-formance for EAR, HEI and LAH. All three e V ects were stable across environments, whereas an additional favor-able e V ect on HEA was only signi W cant in environment D07 (Fig.1). Amongst others, S42ILs ?107 and ?109 rep-resent valuable genetic resources for the development of new elite cultivars with enhanced agronomic performance. The relatively small portion of the Hsp genome present in most of the 39 S42ILs facilitates and accelerates the direct transfer of favorable exotic alleles into modern cultivars through backcrossing and marker-assisted selection. How-ever, during the selection of favorable introgressions for a particular trait, it is worthwhile to assure the complete absence of unfavorable e V ects on other traits. ILs, exhibit-ing negative side e V ects, should not be transferred directly into new cultivars without selection of recombination events. It is, thus, advisable to select ILs with small Hsp introgressions, only exhibiting favorable exotic QTL e V ects.
Future prospects
The present study describes the application of wild barley introgression lines for the identi W cation and veri W cation of QTL e V ects. Altogether, 45.5% of the QTLs for six agro-nomic traits, previously identi W ed in population S42 by von Kor V et al. (2006), were veri W ed by S42ILs. In future, promising Hsp e V ects will be subjected to map-based clon-ing. These e V ort will focus on e V ects chosen by the follow-ing criteria: the QTL e V ects are (1) veri W ed, (2) signi W cant across all environments and (3) strong, i.e. the elite and the exotic allele di V er substantially in their phenotypic perfor-mance. Appropriate S42ILs for map-based cloning projects are the S42ILs ?110 and ?137 carrying an exotic segment in the region 2H, 80?86cM and 7H, 146–166cM, respec-tively. Both S42ILs exhibit signi W cant and veri W ed QTL
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e V ects for multiple traits. A high-resolution mapping approach will eventually help to distinguish between gene linkage and true pleiotropy as the alternative hypotheses to explain the e V ects on multiple traits which are observed in these S42ILs. The required high-resolution mapping popu-lations for chosen S42ILs are currently under construction. For this reason, all 39 S42ILs are currently backcrossed again with ‘Scarlett’. In subsequent generations, recombi-nation events and SUB-ILs with smaller introgressions will be selected. This material can serve as a starting point for both high-resolution mapping and molecular breeding.
In future, the S42IL set will also be characterized in detail through genotyping with Illumina SNPs (Rostoks et al. 2006) or Diversity Arrays Technology (DArT) mark-ers (Wenzl et al. 2006), which will facilitate the W ne-map-ping of QTL e V ects. Currently, the S42ILs are also extensively tested with regard to malting quality and abiotic stress tolerance. All genotype and phenotype data of the S42ILs will be archived in the public IL data base ‘Phenom Networks’ (http://phn.huji.ac.il/RTQ/).
Acknowledgments We are grateful to Drs. E. Laubach (Nordsaat Saatzucht), J. Breun and H. Kempe (Saatzucht Josef Breun), and W. Bungert and H. Rehkopf (Dikopshof, University of Bonn) and their teams for conducting W eld experiments. The excellent technical assis-tance of M. Noschinski is appreciated. This work was funded by the German Plant Genome Research Initiative (GABI) of the Federal Min-istry of Education and Research (BMBF, project 0313125B).
Open Access This article is distributed under the terms of the Crea-tive Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. References
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课程设计报告 通讯录管理系的设计与实现 姓名：钟婷英 班级：计122 学号：1213023039 时间：2014年1月10日 1，问题描述 通讯录是用来记载和查询联系人通讯信息的工具，电子通讯录已经为手机，电子词典等设备中不可缺少的工具软件，请设计一个能够满足这种需求的软件，基本功能模块如下图所示。 输入：记录的录入。 显示：通讯录的显示。 查找：按指定方式，输入关键字，查找指定记录。 插入：实现记录的添加或在指定位置插入记录。 保存：将内存中正在被操作的通讯录以文件形式保存到磁盘。 读入：保存的逆操作，讲存在磁盘中的通讯录文件读到内存中。 排序：按指定关键字对通讯录数据进行排序。 修改：提供修改某条记录的功能。 移动：移动记录在通讯录中的存储位子，使其被查找或显示时的位序前移或后移。 退出：结束程序运行。 2，设计要求 （1）设计通讯录数据的逻辑结构和物理结构。 （2）通讯录至少包括下列数据信息：姓名，电话，单位等。 （3）完成图示基本功能。 （4）软件易用，操作简单。 （5）根据自己使用通讯录体会扩充其他功能，如按姓名查找，按号码查找，按序号删除等。 （6）设计足够多的测试用例 主程序 输 入 显示 查找 插入 删除 保存 读入 排序 修改 移动 退出
（7）数据输入有效性检验：如姓名不能为空，号码中不能有非法字符等。（8）提供分组管理的相关功能，如：分组显示，加入组，组创建，组查询等。（9）可视化的界面设计。 3，概要设计 1，使用struct data struct addressList定义结构体类型，struct data结构体中包括年月日的定义，strcut addressList中包括联系人ID账号，名字，性别，名族，生日，手机号码，QQ号码和家庭地址等。 struct date { int year; int month; int day; }; struct addressList { char ID[10]; char name[10]; char gender[4]; char minzu[2]; date birthday; char shoujihao[14]; char QQ[11]; char address[40]; }; 2，程序设计过程中用到的函数有： int zhujiemian( ); void tianjia(fstream & ); void xiugai(fstream & ); void shanchu(fstream & ); void chazhao(fstream & ); void liulan(fstream & ); int findRecord(fstream &, const char *); int getAmount(fstream & ); 3，整个程序用的是面向对象的方法，在主函数中调用各种函数，来实现通讯录的功能。在主函数中，使用的是c++语言中的开关语句（switch）用来选择通讯录的各种功能。
学生通讯录管理系统的设计与实现
学生通讯录管理系统的设计与实现 问题描述： 纸质的通讯录已经不能满足实际需求，容易丢失，查找困难等问题是纸质通讯录所不能克服的缺点。“学生通讯录管理系统”是为了帮助老师、同学，或者其它一些需要使用的通讯录的人员进行管理和应用的一种应用程序。 需求分析： 1）输入数据建立通讯录。 2）查询通讯录中满足要求的信息。 3）插入新的通讯录信息。 4）删除不需要的通讯录信息。 5）查看所有的通讯录信息。 主界面设计要求： 1）通讯录的建立 2）插入通讯录记录 3）查询通讯录记录 4）删除通讯录记录 5）显示通讯录记录 6）退出系统 设计要求： A.建立通讯录时，每个学生的信息包括：学号，姓名，电话。
B.查找时，学号、姓名、电话均能够作为查询字段。 C.查看所有的通讯录信息时，所有记录需要时有序的（按学号排序，按姓名排序（字典序），按电话号码排序）。 D.存储结构：要求使用顺序存储结构。 E.数据使用：使用本班级的具体信息。 需求分析： 本次设计目的是学生信息管理系统，可存入每个学生的基本信息，所有学生信息都可根据名字、学号、电话、邮箱进行查询，也都能够根据这四个基本信息检索到一个学生并删除其数据。输入形式：student.txt，以文件形式进行输入。 输出形式：根据不同的输入进行不同的操作。 达到功能：能插入一个学生的信息，能删除一个学生的信息，能查询一个学生的信息。 测试数据：班上70个同学的基本数据。 概要设计： 数据类型：顺序链表 ArrayList类 学生数据结构：StuData类包含name、id、phone、email四个String基本类型。 所有操作写在Structure中，包含insert、remove、query、printAll。 Main函数用Java标准输入，循环输入，用switch判断输入进行
数据结构实验报告 实验名称：通讯录管理系统的设计与实现 试验时间：2011.1.13 班级：姓名 学号： 指导老师：1.问题描述： 通讯录是用来记录，查询联系人通讯信息的工具。电子通讯录已成为手机，电子词典等电子设备中不可缺少的工具软件。设计一个能够，满足这种需求的软件。 基本功能模块：输入，显示，查找，插入，删除，保存，读入，排序，修改，移动，退出。 2.设计要求： （1）基本要求 1.设计通讯录数据的逻辑结构和物理结构。 2.通讯录至少包含下列数据信息：姓名，电话，地址等。 3.完成图示基本功能。 4.软件易用，操作简单。 5.根据自己使用通讯录的体会，扩充其他功能，如按姓名查找，按学 号查找，按序号查找等。 （2）较高要求 1.数据输入有效性检验：如姓名不能为空，号码中不能有非法字符等。 2.提供分组管理的相关功能，如：分组显示，加入组，组创建，组查 询等。 3.可视化的界面设计。 3.测试案例：
请输入您的选择（0--6）: 1 分别输入编号,姓名,性别,电话,地址(输入0 结束通信录的建立): 编号：01 姓名：张三 电话：152****1919 地址：2-222 编号：0 请输入您的选择（0--6）: 2 编号：01 姓名：张三 电话：152****1919 地址：2-222
是否继续添加？（Y/N）：N 请输入您的选择（0--6）: 3 请选择查询的方式（1 编号，2 姓名）：1 请输入编号：01 编号：01 姓名：张三 电话：152****1919 地址：2-222 请问是否继续查询？（Y/N）:N
请输入您的选择（0--6）: 4 输入删除编号：01 删除学生信息如下： 编号：01 姓名：张三 电话：152****1919 地址：2-222 请输入您的选择（0--6）: 5 通讯录的全部信息如下： *****编号*****姓名*****性别*****电话*****地址*****
目录 摘要 (1) 关键词 (1) 第一章绪论 (2) 1.1课题背景 (2) 1.2 目的和意义 (2) 第二章需求分析 (3) 2.1 范围 (3) (1) 标识 (3) (2) 系统概述 (3) 2．2 需求概述 (3) (1) 系统目标 (3) (2) 运行环境 (3) ①设备 (3) ②支持程序 (3) ③用户的特点 (3) 2.3功能需求 (4) (1)功能介绍 (4) (2) 系统用例图 (4) 2.4实体关系图 (5) 第三章概要设计 (6) 3.1 范围 (6) (1) 标识 (6) (2) 系统概述 (6) 3.2 系统结构 (6) 3.3 通讯录界面设计 (7) 第四章系统详细设计 (8) 4.1 范围 (8) (1) 标识 (8)
(2) 系统概述 (8) 4.2 详细设计说明 (8) 第五章测试说明 (16) 5.1 范围 (16) (1) 标识 (16) (2) 系统概述 (16) 5.2 测试计划及预期结果 (16) 5.3 具体测试情况 (16) 第六章总结 (19) 参考文献 (20)
通讯录的设计与实现 摘要 随着互联网的不断发展，互联网对我们生活产生的影响越来越大。在日常的生活中，我们需要接触很多不同的人，如何运用互联网技术实现朋友圈通讯录的管理呢？这是我们日常生活中经常要面临的问题。本次毕业设计中设计的通讯录管理系统既可以实现对通讯录进行管理，在本地进行通讯录的增加、修改、删除、更新等操作。本次设计的通讯录管理系统主要是了解通讯录管理系统的业务逻辑，熟悉通讯录管理系统的实现方式，模拟了真实的通讯录管理软件，为后续相关内容的学习打下了坚实的基础。 通讯录管理系统是一个专门针对少用户的实用系统，它方便了大家对众多信息的储存和快速查询的功能，大大减少了查找过程的时间，是一个比较实用的通讯录管理系统，。对我们后续学习移动端的通讯录管理也会有很大的帮助。 本设计使用的计算机语言是C++，C++语言是在C语言的基础上作了进一步的强化。C语言是一种计算机程序设计语言，它既具有高级语言的特点，又具有汇编语言的特点。它的应用范围广泛，具备很强的数据处理能力。作为C语言家族的一种，C++也具备了C 语言所具有的优点，并对其进行了优化封装，是开发者更容易操作运用，所以本次课程设计采用了C++作为系统的开发语言。本通讯录管理系统的主要功能有：建立通讯录的链表、插入通讯录信息、查询通讯录信息、删除通讯录信息，输出通讯录信息，保存到通讯录信息。采用的是面向过程的方法，封装函数功能，调用各个功能函数来实现系统的各个功能。 关键词 通讯录；链表；类；
武汉理工大学 毕业设计（论文） 通讯录管理系统实现与设计 学院（系）： 专业班级： 学生姓名： 指导教师：
目录 第一章绪论 (2) 1．1课题简介 (2) 1．2开发的意义 (2) 1．3团队构成 (3) 第二章开发环境及实现技术 (4) 2．1开发环境 (4) 2．2开发工具简介 (4) 第三章系统设计 (6) 3．1概要设计 (6) 3．2详细设计 (7) 第四章数据库设计 (9) 4．1数据库A CCESS简介 (9) 4．2数据库需求分析 (10) 4．3数据库需求分析 (10) 第五章详细设计 (12) 5．1系统登录模块的设计与实现 (12) 5．2主界面的设计与实现 (16) 5．3单人资料模块的设计与实现 (19) 5．4模糊查询模块的设计与实现 (22) 5．5全体资料模块的设计与实现 (25) 5．6用户注册模块的设计与实现 (26) 5．7用户维护模块的设计与实现 (28) 5．8备忘提醒模块的设计与实现 (29) 第六章系统使用说明 (33) 6．1使用说明 (33) 6．2运行环境 (33) 第七章设计心得 (34) 参考文献 (35)
第一章绪论 1．1课题简介 通讯录管理系统是每一个用户管理通讯录的不可缺少的一个管理信息系统,它的内容对于用户的管理者来说是至关重要的,所以通讯录管理系统应该能够为每一个用户的管理者提供充足的信息和快捷的查询手段，大大的方便用户合理的管理通讯录。 随着科学技术的不断提高,计算机科学日渐成熟,网上通讯工具的迅速发展，其强大的功能已为人们深刻认识,它已进入人类社会的各个领域并发挥着越来越重要的作用。 作为计算机应用的一部分,使用计算机对通讯录进行管理,具有着手工管理所无法比拟的优点，如:检索迅速、查找方便、可靠性高、存储量大、保密性好、寿命长、成本低等。这些优点能够极大地提高通讯录管理的效率,也是用户理财的科学化、正规化管理,与先进科学技术接轨的重要条件。 因此，开发这样一套管理软件成为很有必要的事情，对于我们即将计算机专业毕业的学员来说，也是一次将计算机应用于现实管理的一次很有意义的实践活动。 1．2开发的意义 计算机已经成为我们学习和工作的得力助手，使用其可方便的管理通讯录 今天，计算机的价格已经十分低廉，性能却有了长足的进步。它已经被应用于许多领域。 现在我国的通讯录管理水平还停留在纸介质的基础上，这样的机制已经不能适应时代的发展，因为它浪费了许多人力和物力，在信息时代这种传统的管理方法必然被计算机为基础的信息管理所取代。 我作为一个计算机应用专业的毕业生，希望可以在这方面有所贡献。改革的总设计师邓小平同志说过“科学技术是第一生产力”，我希望能用我所学的知识编制出一个实用的程序来帮助用户进行财务管理。 开发这一系统的好处大约有以下几点： 第一、可以存储大量的通讯录信息，安全、高效；
题目：学生通讯录管理系统 任务说明： 主要利用c语言的文件操作能力设计开发一个小型的通讯录管理系统，至少具有如下功能： ①记录通讯录内的人员的学号、姓名、地址、电话号码。 ②显示所有人员的信息。 ③通过输入姓名查找人员信息。 ④通过输入姓名查找到要删除的人员信息，然后可以进行删除。 ⑤通过输入姓名查找到要修改的人员信息，然后可以进行修改。 ⑥添加人员信息。 系统功能描述： 本程序的功能是为用户提供简单的通讯录进行管理，通过该程序存储联系人信息，提供关键字（只能是英文关键字进行查找）查找功能，可以对数据进行修改、删除、添加等操作。 各按钮的功能如下： 查找记录：以姓名为关键字，查找并显示该记录。若查找不到，则显示“好象没有”； 添加记录：将当前记录按姓名序加入通讯录，然后显示第一条记录； 修改记录：修改当前记录，显示当前记录。姓名为关键字，
不允许修改； 删除记录：删除当前记录，然后显示第一条记录； 第一条记录：将当前记录指针移动至首节点，若已为首节点，则不移动； 前一条记录：将当前记录指针向前移动一个节点，若已为首节点，则不移动； 后一条记录：将当前记录指针向后移动一个节点，若已为尾节点，则不移动； 最后一条记录：将当前记录指针移动至尾节点，若已为尾节点，则不移动； 加载：从文件中掉入已保存的通讯录数据； 保存：保存通讯录数据； 退出：退出系统；
设计思路： 根据要求，电话录数据以文本文件存放在文件中，故需要提供文件的输入、输出等操作；还需要保存记录以进行修改，删除，查找等操作；另外还应提供键盘式选择菜单实现功能选择。 图1 系统功能模块图 软件中使用的结构体和结构体数组，如： struct callmember { char name[20]; char address[20]; char code[20]; char callnumber[20]; }; 对用户的信息进行保存，他们都以二进制的形式读写。 其中：
湖南涉外经济学院课程设计报告 课程名称数据库原理与应用课程设计 题目通讯录管理系统 组员 学院信息科学与工程学院 班级 指导教师 2015年12月30 日
任务分配表
摘要 随着社会的发展,人际关系变得越来越重要，为了保持良好的人际关系，必须经常与亲戚、朋友、同学、同事保持联系，但是有时候存在着许多的限制条件，比如怎样找到交流对象的各种信息？可能你会想到现实生活中的手机等通讯工具，由于这些工具的单一性，不可能在第一时间找到自己想要的信息资料，因此，为了能够快速查找到联系人的信息，节省查找时间，开发通讯录管理系统。 通讯录管理系统是一个基于SQL数据库储存和JAVA界面模式的个人通讯录管理系统。它是将自己的联系人的具体信息集中管理，成为一个方便人们使用的小软件。在开发过程中主要运用Java, SQL Server技术,由于开发工具和数据库之间的良好使用，可以为开发带来方便，使之成为一个可施行的系统。从而达到开发的目的-----实现对通讯录信息的管理。 通过采用相关技术，以及老师的辅导和同学们的帮助，将系统设计的功能全部实现。功能包括：用户的登录, 添加联系人信息，修改联系人信息，删除联系人信息，查询联系人信息，可以浏览全部通讯的联系人，并且可以根据数据表的各字段来查询你所要找的联系人等功能 关键词: SQL Server,JAVA。
目录 摘要 (3) 第一章绪论 (6) 1.1目的 (6) 1.2背景 (6) 1.3研究内容 (6) 第二章数据库需求分析 (7) 2.1 通讯录系统的功能 (7) 2.2通讯录系统的数据流 (7) 2.3 通讯录系统数据流程图 (8) 2.4通讯录的数据字典 (9) 第三章数据库概念结构设计 (12) 3.1实体 (12) 3.2实体间包括 (12) 3.3 实体属性图 (12) 3.4局部E-R图 (13) 第四章数据库逻辑设计 (15) 4.1 E-R图转化而得到的关系模式 (15) 4.2 由关系模式转换得到的函数依赖 (15) 4.3 关系模式优化 (15) 4.4 对优化后的关系模式的结构 (15) 第五章数据库实施 (17) 5.1数据库创建代码 (17) 5.2数据库表创建代码 (17) 5.2.1用户表 (17) 5.2.2联系人表 (17) 5.2.3分组表 (18) 5.3视图创建代码 (18) 5.4存储过程代码创建 (19) 第六章数据库运行和维护 (20) 6.1登陆模块 (20) 6.2联系人界面 (20) 6.3朋友分组界面及详细查询 (20) 6.4同学分组界面及详细查询 (21) 6.5同事分组界面及详细查询 (22) 6.6查询界面 (23) 6.7增加界面 (24) 6.8修改界面 (24) 6.9删除界面 (25) 第七章总结 (26) 参考文献 (27)
开放教育 课程设计报告书 课程名称：通讯录管理系统 班级：综合邮政07秋 学号：077240001 姓名：王芬 指导老师：高海东
通讯录管理系统 一．需求分析 设计题目及要求： ◆建立通讯录信息，信息至少包含编号、姓名、年龄、电话、通讯地址、电子 邮箱等； ◆能够提供添加、删除和修改通讯录信息的功能； ◆能够提供安不同方式查询的功能；如按姓名或年龄、电话等查询； ◆将通讯录保存在文件中； ◆能够按表格方式输出通讯录信息。 系统功能需求分析： 主要包含一下多种功能： 添加：添加通讯录记录 显示：显示通讯录记录 删除：删除通讯录记录 查询：查询通讯录记录 修改：修改通讯录记录 保存：将信息保存到文件 二．概要设计 系统功能模块图：
添加：可以添加通讯录记录，依次输入编号、姓名、年龄、电话号码、通讯地址、电子邮箱后，会提示是否继续添加。 显示：可以以表格形式输出所有通讯录里的记录 删除：输入欲删除的那个人的名字后，会自动删除他（她）的记录内容 查询：可以选择用姓名、电话、地址三种方式查询 修改：输入欲修改的那个人的名字后，再依次输入编号、姓名、年龄、电话号码、通讯地址、电子邮箱即可完成修改 保存：，输入文件名（带后缀名）后，即可将通讯录信息保存到文件 三．详细设计 (1).通讯录： typedef struct { char score; /*编号*/ char name[10]; /*姓名*/ char num[15]; /*号码*/ char email[20]; /*邮箱*/ char age[8]; /*年龄*/ char adds[20]; /*住址*/ }Person; void main() /*主函数*/ { int n=0; for(;;) {
通讯录管理系统设计说明书 系统概述： 随着毕业的来临，我们就将面临分离。为了能在毕业后，能够方便联系我们在大学其间的同学朋友，通讯录就是一个可以帮我们方便查找同学朋友的工具。 随着计算机的普及，人们的生活摆脱了传统式的记事本、电话簿，越来越多的靠计算机来帮助人们记住这些事情，极其简便。这就需要有一个使用的通讯录管理系统，用户可以方便的通过自己电脑的通讯录管理系统，来随时查阅自己所需要的信息，而不必再大费周折去翻开那繁琐的记事本。 通讯录管理系统是一个专门针对储存用户联系方式以及一些简单个人信息的实用管理系统，它方便了用户对众多客户、朋友、同事等个人信息的储存和快速查阅的功能，大大减少了查找过程的时间。 关键字：插入，删除，查找，输出。 需求分析： 调查用户需求： 随着同学们的即将毕业,蹋出社会,交际难免地逐渐扩大，与外界联系将更为广泛和密切，传统的手工通讯录、地址簿已经难以满足快节奏、高效率的现代生活的需求。经常发生要在几十甚至上百张名片中找出某一张名片的情况，若由手工完成效率十分低。当交际扩大后，传统的手工通讯录非常不方便，不易查询、修改、存放，不易保密，容易遗失。 由计算机带来管理庞大而繁杂的通讯录是非常合适的，不仅查询和修改方便，并且效率高，速度快，完全能够满足现代化交际活动的要求，同时也更方便同学们联系交往。 本系统专门用于个人通讯信息管理的小型应用软件，主要提供个人通讯信息的登记、修改、浏览、查询和打印等功能。
1．用户的主要信息需求： ①对个人通讯信息资料进行登记、修改、浏览。 ②对个人通讯信息资料进行按姓名和学号查询。 ③对个人通讯信息资料进行打印输出。 系统功能设计与分析： 1.功能模块图 2.功能设计 （1）新建通讯录功能 增加一个新的记录,并保存通讯录； （2）搜索通讯录功能
基于c语言的通讯录管理系统设计与实现 集团标准化小组：[VVOPPT-JOPP28-JPPTL98-LOPPNN]
《高级语言程序设计》 ——基于c语言的通讯录管理系统 的设计与实现 姓名：王炳旭 学号： 1216F0610119 指导老师：孟芸 系别：信息工程系 专业班级：计科F1201班
《高级语言程序设计》课程设计任务书 设计内容及要求： 1.设计内容 输入功能：记录信息并保存文件中。 显示功能：输出文件中所有信息。 查找功能：查询所需通讯信息。 删除功能：删除无用信息。 2.设计要求 建立通讯录信息，信息包含姓名、性别、班级、电话，保存在文件中； 能够输出文件中所有通讯录信息。 能够提供按姓名、班级或性别查询信息； 能够提供按姓名删除通讯录信息的功能； 时间安排： 九月：选择自己所要设计的程序，查阅书籍、网上查询，收集所需资料解决疑惑。 十月：开始编写程序，不断分析。 十一月：代码实现，程序能够运行。 十二月：写报告，完成课程设计。 《高级语言程序设计》课程设计教师评阅成绩表
《高级语言程序设计》课程设计承诺书
目录 1.引言-------------------------------------------------------- 2 1.1设计内容 ---------------------------------------------- 2 1.2设计任务及具体要求 ------------------------------------ 2 1.3系统环境 ---------------------------------------------- 3 2.总体设计---------------------------------------------------- 3 2.1系统功能简介 ------------------------------------------ 3 2.2总体程序框图 ------------------------------------------ 3 2.3各个模块之间的主要关系 -------------------------------- 4 3.详细设计---------------------------------------------------- 4 3.1各个模块的程序流程图及运行界面 ------------------------ 4 3.2关键代码分析说明 -------------------------------------- 8 3.3程序使用说明 ------------------------------------------ 9 4.总结-------------------------------------------------------- 9 致谢---------------------------------------------------------- 9 参考文献------------------------------------------------------ 9 附录--------------------------------------------------------- 10 1.引言 当今时代，计算机已经成为人们生活中不可或缺的一部分，它打破了地域时间限制，改变了人们的工作和生活方式。通讯录系统能方便用户的需求，满足用户迅速、准确的查找修改或者删除联系人信息，把各个联系人信息以文档保存。本文介绍了简易通讯录管理系统在VC++6.0环境下的实现过程：系统的分析，功能模块的设计，系统的流程图及运行界面。此系统的主要管理的信息
课程设计报告 课程设计名称：数据结构课程设计系：三系 学生姓名： 班级： 学号： 成绩： 指导教师： 开课时间：2011-2012学年一学期
宿迁学院 课程设计任务书 课程名称：数据结构 指导教师： 专业班级： 学生姓名： 起止日期：2012.12-2013.1
设计题目一：通讯录管理系统的设计与实现 1 概述 1.1 现状分析 课程设计是实践教学中的重要环节，它以某一门课程为基础，涉及和课程相关的各方面知识，是一门独立于课程外的特殊课程。课程设计就是让所有同学对课程更全面的应用。本次实验项目“通讯录管理”就是针对数据结构的一门应用较为广泛的系统管理方法。 1.2 实现意义 本次实验应用性能很好，结构清楚，能随时添加、删除、查找、修改、输出联系人；并且可以用姓名、编号两种方式；而且其中增加了排序功能，使得插入之后排序为接下来的操作提供便利，操作更精确，以人性化的方式展现出来，效果十分突出。 2 系统分析 编程完成通讯录的一般性管理工作如通讯录中记录的增加、修改、查找、删除、输出等功能。每个记录包含编号、姓名、性别、电话号码、住址个人基本信息。用《数据结构》中的链表做数据结构结合c语言基本知识编写一个通讯录管理系统。本程序相对简单，使用方便，几乎不用特殊的命令，只需按提示输入即可。对于建立通讯录管理系统，则需了解并掌握数据结构与算法的设计方法，尤其在算法方面，链表及结点的联系,提高综合运用所学的理论知识和方法独立分析和解决问题的能力。 3 概要设计 3.1算法的设计 本实验从整体上分为七大模块：（1）通讯录链表的建立；（2）通讯者结点的插入；（3）通讯者结点的查询；（4）通讯者结点的删除；（5）通讯者结点的修改；（6）通讯录链表的输出；（7）退出通讯录管理通讯者结点的删除系统。
C语言课程设计：通讯录管理系统
目录 一、需求分析 (2) 二、概要设计 (2) 三、详细设计 (3) 四、上机操作 (14) 五、实习心得 (19) 六、源程序 (20)
一、需求分析 具有数据的插入、修改、删除、显示和查询功能的电话簿管理程序。 （1）数据包括：人名、工作单位、电话号码和E-MAIL地址。（2）可对记录中的姓名和电话号码进行修改。 （3）可增加和删除记录。 （4）可显示所有的保存记录。 （5）可按人名或电话号码进行查询。 [提示] 建议采用结构体数组和文件系统实现。结构体成员包括人名、工作单位、电话号码和E-MAIL地址。 根据题目的要求程序应该采用结构体数组和文件系统实现。应该有文件的操作功能；在程序中应该包括输入、显示、删除、查询、添加、修改、保存、加载和退出的功能。 二、概要设计 根据上面的分析，可以将程序系统的设计分为如下几个模块：插入、显示、删除、查询、修改、保存和退出。
三、详细设计 1、主函数； 主函数一般设计得比较简洁，只提供输入，处理和输出部分的 函数调用。其中各功能模块用菜单方式选择。 流程图 N 【程序】 int main()
***********\n"); printf("\t\t**********************************************\n"); scanf("%d",&n); for(i=0;i 通讯录管理系统的设计与实现源代码 #include } } } iCount=t; } infile.close(); } void Print(Student *h)//打印记录 { if(h==NULL) { cout<<"\n****************************************\n\n"; cout<<"没有学生记录！\n"; cout<<"\n****************************************\n"; return; } cout<<"\n************************************************************ ********************\n\n"; cout<<"所有的学生：\n\n"; cout<<" ------------------------------------------\n"; cout<<"| "< 通讯录管理软件系统设计方案 目录 第一章项目开发计划书 (3) 1.1 引言 (3) 1.1.1 编写目的 (3) 1.1.2 背景 (3) 1.2 项目概述 (3) 1.2.1 工作内容 (3) 1.2.2 主要参加人员 (3) 1.2.3 产品 (4) 1.2.4 服务 (4) 1.2.5 验收标准 (4) 1.2.6 本计划的批准者和批准日期 (4) 1.3 实施计划 (4) 1.3.1 工作任务的分配与人员分工 (4) 1.3.2 进度 (5) 1.4 支持条件 (5) 1.4.1 计算机系统支持 (5) 第二章可行性分析 (6) 2.1 可行性研究前提 (6) 2.2 对现有系统的分析 (6) 2.3 建议新系统 (6) 2.3.1 新系统说明 (6) 2.3.2 新系统的流程图 (7) 2.4 经济上可行性 (7) 2.5 技术可行性 (7) 2.6 开发工具的选择 (8) 2.7 新系统的影响 (8) 2.8 结论 (8) 第三章需求分析 (9) 3.1 市场需求分析 (9) 3.2 系统功能性需求分析 (9) 3.2.1 功能划分 (9) 3.2.2 功能描述 (9) 3.3 系统非功能性需求 (9) 3.3.1 可用性 (9) 3.3.2 可靠性 (10) 3.4 数据字典 (10) 3.5 实体-联系图 (11) 第四章系统设计 (12) 4.1 总体设计 (12) 4.1.1 需求概述 (12) 4.1.2 联系人管理系统功能设计 (12) 4.2 功能模块的设计与实现 (13) 4.2.1 用户注册模块 (13) 4.2.2 用户登录模块 (13) 4.2.3 用户管理自己联系人信息模块 (14) 第五章系统测试 (17) 5.1 测试的作用和意义 (17) 5.2 测试方法 (17) 5.3 测试内容 (17) 5.4 测试结果 (18) 5.4.1 注册和登录模块测试 (18) 5.4.2 查询模块测试 (18) 5.4.3 联系人信息添加、修改和删除模块测试 (19) 5.5 结论 (19) 第六章总结 (20) 参考文献 (21) 附录：程序主要部分源代码 (21) 学院 计算机科学与技术系 课程设计报告 2013～2014学年第二学期 课程面向对象课程设计 课程设计名称通讯录程序 学生XXX 学号 专业班级XXXXX 指导教师XXX 20 年月 目录 一、设计题目 (1) 二、设计要求 (1) 三、总体设计 (1) 3.1系统功能框架 (1) 3.2系统功能说明 (3) 四、详细设计 (3) 1．数据结构设计 (3) 2．系统模块设计 (10) 五、运行结果 (13) 一．设计题目 随着社会的进步与发展，通讯越来越密切。希望能通过对java课程设计的学习和掌握来编写一个通讯录管理系统。 二．设计要求 （1）只能使用Java语言，采用面向对象方法进行设计，要求源程序要有适当的注释，使程序容易阅读。 （2）程序必须与数据库进行通信。 （3）系统必须是图形用户界面的形式并连接数据库 三. 总体设计 3.1系统总体功能框架图 3.2 系统功能说明 （1）具有新用户注册功能。 （2）具有注册用户登录功能。 （3）具有数据的录入功能。 （4）具有数据查询功能，可以实现查询全部信息和按条件执行查询。（5）具有按条件删除数据功能。 （6）具有统计功能 4. 详细设计 4.1数据结构设计（java程序设计） //登录系统 package .ibm.etp.addressbook.action; import java.util.HashMap; import java.util.List; import https://www.doczj.com/doc/5e10458503.html,er; import .ibm.etp.addressbook.service.LoginService; import .opensymphony.xwork2.ActionSupport; public class LoginAction extends ActionSupport { private static final long serialVersionUID = 1L; public String username; public String password; private String message; Override public String execute() throws Exception { HashMap 南通大学 二○一一～二○一二学年第一学期 计算机科学与技术学院 课程设计报告书 课程名称：数据结构课程设计 班级：计101 学号：1013022015 姓名：徐鹏 指导教师：顾颀 二○一二年一月 设计题目:通讯录管理系统的设计与实现 1. 需求分析 1.1 描述要求编程解决的问题，给出程序要达到的具体要求 1.1.1基本要求 ①设计通讯录数据的逻辑结构和物理结构 ②通讯录至少包括下列数据信息：姓名、电话、单位等。 ③完成图示基本功能。 ④软件易用，操作简单。 ⑤根据自己使用通讯录的体会，扩充其他功能，如按姓名查找、按号码查找、按序 号删除等。 ⑥设计足够多的测试用例。 1.1.2较高要求 ①数据输入有效性的检验：如姓名不能为空、号码中不能有非法字符等。 ②提供分组管理的相关功能，如：分组显示、加入组、组创建、组查询等。 ③可视化的界面设计。 1.2 测试案例设计，包括以下两方面案例： 1.2.1 合理的输入，给出的合理的输出 输入：1 张三12345678 计101 2-102 输出：输入成功! 1.2.2 不合理的输入，给出的输出 输入：2 李四12**5678 计101 2-102 输出：电话号码中出现非法输入 请重新输入: 2. 概要设计 2.1 功能划分与定义，功能结构图 基本功能模块如下图所示： 输入：记录的输入。 显示：通讯录显示。 查找：按指定的方式，输入关键字，查找指定记录。 插入：实现记录的添加或在指定位置插入新纪录。 删除：提供指定记录的删除功能。 保存：将内存中正在被操作的通讯录以文件形式保存到磁盘。 读入：保存的逆操作，将存在磁盘里的通讯录文件读取到内存中。 排序：按指定关键字对通讯录进行排序。 修改：提供修改某条记录的功能。 移动：移动记录在通讯录中的存储位置，使其被查找或显示时的位序前移或后移。 退出：结束程序运行。 2.2 给出数据的逻辑设计、抽象的数据类型描述 （1）数据域描述通讯录的相关信息，每个人的基本信息含有多个属性，其中包括姓名、电话、单位等，为此可根据人员信息建立结构体，类型定义如下： struct Datatype{ int id; //编号 char name[10]; //姓名 char phone[12]; //电话 char class[10]; //单位 }; 3. 详细设计 3.1 数据的存储设计 根据通讯录的设计要求，可使用单链表实现该通讯系统的功能，链表节点只含一个 数据域和一个指针，线性表的链式存储结构如下： struct Node { Datatype data; //数据域，存放表元素 Node *next; //指针域，指向下一个结点}; 3.2 界面设计，包括菜单、数据输入输出格式等 主菜单：查找联系人子菜单：显示通讯录子菜单： 1-添加联系人1-按序号查找1-按序号显示 2-查找联系人2-按姓名查找2-按姓名显示 3-修改联系人3-按号码查找3-按号码显示 4-删除联系人 5-移动联系人 6-显示通讯录 7-退出 C课程设计通讯录管理 系统 文件排版存档编号：[UYTR-OUPT28-KBNTL98-UYNN208] 课程设计说明书（论文）课程名称 C++程序设计实践 题目通信录管理系统 专业软件工程班级 学号姓名 xx 起止日期 指导教师赵新慧成绩 辽宁石油化工大学计算机与通信工程学院 摘要 本次课程设计任务是通过编写一个通信录管理系统，学习用VisualC++开发简单的管理系统。采用VisualC++软件为主要开发工具。巩固和加深学生对C++课程的基本知识的理解和掌握，掌握C++编程和程序调试的基本技能，利用C++进行简单软件设计的基本思路和方法，提高运用C++解决实际问题的能力，掌握书写程序设计说明文档的能力使用计算机进行信息管理。实现通信录的管理功能（添加、删除、排序）、按姓名查询的功能，以及把联系人资料保存在文件中，将文件中内容读出来。使用计算机进行系统管理，不仅提高了工作效率，而且大大提高了其安全性，尤其对于复杂的信息管理，计算机能充分地发挥它的优越性，通信录管理系统是每个人不可缺少的部分，在课程设计中，系统开发平台为Windows XP,程序设计语言采用Visual C++，在程序设计中，运用了面向对象解决问题的方法。程序通过调试运行，初步实现了设计目标。 Abstract The curriculum design task is through the preparation of a student achievement ranking management system, learning management system with Visual C++ 6 to develop simple. Using Visual C++ 6 software as the main development tool. To consolidate and deepen the students the basic knowledge of C++ course of understanding and master, master the basic通讯录管理系统的设计与实现c++源代码
通讯录管理软件系统设计方案
java课程设计(通讯录管理系统)
通讯录管理系统的设计和实现
C课程设计通讯录管理系统
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