Maize Genetics Cooperation Newsletter vol 84 2010
Please Note: Notes submitted to the Maize Genetics
Cooperation Newsletter may be cited only with consent of authors.
Ya�an, Sichuan, China
Sichuan Agricultural University
Ottawa, Ontario, Canada
Eastern Cereal and Oilseed Research Centre
Genetic Diversity and Combining Ability of Maize Landraces from China�s Sichuan Basin
K. Xiang, K. C. Yang, G. T. Pan, L. M. Reid and X. Y. Zhu
Maize
landraces are adapted to the specific environmental
conditions of their habitats and selection by humans. It is important to
systemically evaluate landraces for desired traits and to maintain this genetic
diversity for future plant breeding. The objective of this research was to characterize the
agronomic and quality traits of 22 maize landraces and select the landraces with important traits and the most
potential for future breeding programs.
The 22 landraces
selected, on the basis of
their origin, agronomic performance and other important characteristics as determined
by The Institute of Variety Resources Research, CAAS (1988), for this study
included:. Hanyuanhongbaogu, Baibaogu, Jinhuanghou, Wenchuanerbai, Rongzhaiyumi, Nuoyumi, Dadudu, Yuzuibaogu, Qiuzi, Daguangyuan, Lengfengwu, Dabaimaya, Junlianhongbaogu, Wuer, Xuesi, Dahuang, Xiaobai, Dababai, Dazhaibaogu, Dabanya, Ganzierbai, and Dazihuang.
In the fall of 2006, the 22 landraces were planted in Yuanjiang, Yunnan. Data was recorded on plant height, ear height, total leaf number, ear length, barren-tip length,number of rows per ear, kernels per row, kernel depth, grain yield, kernel weight, oil composition, protein and starch content. During flowering, 13 of these races with medium to late maturity ratings and five testers (478, Mo17, 48-2, 9636 and Huangzao4) were chosen to create a diallel cross to examine combining abilities. For each of the landraces, pollen was combined from 30 plants and used to pollinate the five testers in the diallel method of North Carolina Design II (NCII). In the spring of 2007, the resulting 65 F1 crosses were evaluated in Duoying, Ya�an, and grain yield per plant was recorded.
Analysis of variance (ANOVA) was carried out by the DPS2000 method (http://www.chinadps.net).
Coefficient of variation (CV) was analyzed among populations by
using Microsoft Excel (2003) to determine which had significantly different
traits. The CV was computed as:,
where was mean of a trait, �s� was standard deviation. General
combining ability (GCA) and specific combining ability (SCA) of grain yield in the
13 landraces were calculated by using the incomplete diallel
cross model (Ming et al. 1994; Rong et al. 2003). Heterosis was investigated by analyzing the SCA for grain
yield per plant.
ANOVA revealed that
significant genotypic variation existed among the 22 landraces for many of the
agronomic and quality traits measured (Table 1). CV of the 12 agronomic traits measured ranged from 5.59% to
32.42%, with an average of 15.78%. Grain yield per plant and traits directly
related with grain yield, such as rows per ear, kernels per row, kernel depth
etc., had some of the highest CVs, indicating that the landraces differed more on
these traits rather than others such as plant height, leaf number and flowering
time. In contrast, the CV of the three quality traits (oil, protein and starch
ratio) ranged from 0.91% to 5.64%,with an average of 4.06%,
which suggested that variation for quality traits was lower than that for
agronomic traits. For each trait, we determined which landrace had the most
desired or optimum data for that trait (Table 1). Three
landraces, Dazhaibaogu, Dahuang and Yuzuibaogu, exhibited the best agronomic performance while another
three, Nuoyumi, Rongzhaiyumi
and Dadudu, had highest oil, protein and starch
content, respectively.
Individual ANOVA for grain
yield of 65 crosses between 13 landraces and five testers showed that differences in grain yield per plant were significant.
The results of the combining ability analysis showed that GCA and SCA effects on
grain yield per plant were highly significant among landraces as well as among crosses
(Table 2). Five landraces (Hanyuanhongbaogu, Dabaimaya, Xuesi, Dahuang and Dazhaibaogu) had the
highest GCA effects (Table 2), which suggested that these landraces had the
greatest potential for future breeding. The CV of GCA effects on grain yield
per plant was 48.85%, which indicated that there are more selecting options in
future breeding. Several SCA effects on grain yield per plant were also
significant (Table 2). The SCA
effects ranged from -18.21 (Dabanya×478) to 27.41 (Xuesi×9636).
In
conclusion, Dazhaibaogu, Dahuang, Yuzuibaogu, Xuesi and Dabaimaya were the
landraces determined to have the most promising characteristics for further use
in maize breeding programs.
Acknowledgements We thank Junpin Yang in The Crop Research Institute of Sichuan Academy of Agricultural Sciences for providing the maize landraces.
Table 1 The mean, standard deviation (SD),
minimum-maximum (Min-Max), coefficient of variation (CV), and optimum
landrace for 12 agronomic and three quality traits measured on 22 maize
landraces from the Sichuan Basin of China
Trait |
Mean |
SD |
Min-Max |
CV (%) |
Optimum landrace |
Plant height (cm) |
258.54 |
22.51 |
213.23-305.65 |
8.71 |
Ganzierbai |
Ear height (cm) |
132.69 |
23.11 |
82.46-178.24 |
17.42 |
Rongzhaiyumi |
Total leaf number |
19.94 |
1.83 |
14.00-24.00 |
9.18 |
Wuer |
Growing period (d) |
127.27 |
7.21 |
117.00-142.00 |
5.59 |
Daguangyuan |
Ear length (cm) |
12.47 |
1.46 |
8.40-15.18 |
11.71 |
Lengfengwu |
Barren-tip length (cm) |
1.11 |
0.36 |
0.30-1.80 |
32.42 |
Dazhaibaogu |
Rows per ear |
12.54 |
1.80 |
8.70-17.05 |
14.36 |
Dazhaibaogu |
Kernels per row |
22.56 |
3.27 |
16.70-31.39 |
14.49 |
Dahuang |
Kernel depth (cm) |
1.52 |
0.23 |
0.79-1.84 |
15.15 |
Dahuang |
Grain yield per plant (g) |
74.99 |
19.05 |
26.57-108.91 |
25.40 |
Yuzuibaogu |
100-kernel weight (g) |
20.87 |
4.08 |
9.00-27.93 |
19.55 |
Qiuzi |
Test weight (g/L) |
632.79 |
97.57 |
245.00-705.00 |
15.42 |
Baibaogu |
Oil ratio (%) |
5.16 |
0.29 |
4.47-5.86 |
5.63 |
Nuoyumi |
Protein ratio (%) |
11.00 |
0.62 |
9.34-12.11 |
5.64 |
Rongzhaiyumi |
Starch ratio (%) |
69.37 |
0.63 |
67.74-70.60 |
0.91 |
Dadudu |
Table
2 General combining ability (GCA) and specific
combining ability (SCA) effects on grain yield per plant based on the analysis of combining ability
data of 13 maize landraces from the Sichuan Basin of China and five testers
Landrace |
GCA effects |
SCA effects |
||||
478 |
Mo17 |
48-2 |
9636 |
Huangzao4 |
||
Hanyuanhongbaogu |
6.75** |
15.51** |
-3.34 |
-1.78 |
-10.48** |
0.09 |
Nuoyumi |
-11.45** |
-2.24 |
-0.92 |
8.31** |
2.41 |
-7.56** |
Dadudu |
-2.59 |
-10.69** |
13.98** |
1.77 |
-15.31** |
10.25** |
Yuzuibaogu |
-5.87* |
5.79* |
-10.54** |
5.70* |
-5.18* |
4.23 |
Lengfengwu |
-6.86** |
0.22 |
-9.21** |
4.12 |
7.37** |
-2.50 |
Dabaimaya |
5.29* |
17.91** |
-6.03* |
-11.13** |
11.38** |
-12.13** |
Wuer |
-6.02* |
-17.95** |
9.67** |
10.91** |
-1.07 |
-1.56 |
Xuesi |
5.42* |
-5.86* |
-10.02** |
-15.83** |
27.41** |
4.31 |
Dahuang |
10.95** |
0.30 |
-4.39 |
8.50** |
4.87* |
-9.27** |
Xiaobai |
0.89 |
2.71 |
10.41** |
3.66 |
-13.66** |
-3.11 |
Dazhaibaogu |
8.22** |
7.52** |
-3.90 |
8.74** |
-14.79** |
2.43 |
Dabanya |
-2.92 |
-18.21** |
-7.99** |
-9.22** |
20.50** |
14.92** |
Dazihuang |
0.00 |
4.99* |
22.29** |
-13.75** |
-13.45** |
-0.08 |
*, **Significant at the 0.05 and 0.01 probability levels, respectively