Maize
Genetics Cooperation Newsletter 80. 2006.
New Delhi, India
Indian Agricultural Research Institute
Heritability and correlation studies in sweet corn for quality traits, field emergence and grain yield
--Kumari, J; Gadag, RN; Jha, GK
Ten sweet corn and seven field corn genotypes were studied for estimating components of genetic variance and combining ability for ear-related and biochemical traits using diallel and Òline-X-testerÓ mating designs. The study was carried out at the Division of Genetics and Division of Environmental Science, Indian Agricultural Research Institute, during 2003-2004. Diallel crosses were made among six inbred lines, including three each of sugary and shrunken genotypes, while in later crosses seven field corn inbreds were crossed as female lines with four sweet corn inbreds as tester parents. The details regarding pedigree, source of origin and endosperm mutants are given in Table 1.
Analyses
of variance by diallel shows the mean sum of squares is highly significant for
all nine traits except reducing sugar (Table 2). In the line-X-tester analysis (Table 3), parents as a whole
are significant at 1% for all characters, while the partitioned source of
variance for female parents indicated significance for starch, carbohydrate,
grain weight, field emergence and TSS.
This meant that field corn lines have significant variability for these
traits while significant for sugar components and phytoglycogen. As far as male parents or sugary lines
are concerned, these were significant for all sugar components, phytoglycogen
and total carbohydrate components.
As it is well known that field and sweet corn populations are
genotypically and phenotypically different, the female vs. male source of
variation is significant for all traits.
Simi-
Table 1.
Pedigree and source of origin of inbred lines.
|
Inbreds (Code #) |
Pedigree |
Source population |
Endosperm mutation |
|
DMB321 |
IPA40-f-17-1-1-4-1-1-1-f |
AD-609 |
Normal |
|
DMB322 |
TCA-22-3-1-1-2-f-#-f-1-1 |
A-64 |
Normal |
|
DMB323 |
IPA-1-f-16-2-#-f-1 |
A-64 |
Normal |
|
DMB324 |
IPA-34-5-f-1-1 |
MDR-1 |
Normal |
|
DMB325 |
PC2HS-31-f |
PC2composite |
Normal |
|
DMB326 |
IPA-3-6-10-3-1-1-1-2-1 |
A-64 |
Normal |
|
DMB327 |
TCA-21-1-b-1-1-1-3-1 |
AD-609 |
Normal |
|
SCI301 |
SCMD90 (01R)-2-1-3-1 |
Madhuri |
su |
|
SCI302 |
SCMD90 (01R)-3-1-2-1 |
Madhuri |
su |
|
SCI303 |
SCMD90 (01R)- 4-2-1-2 |
Madhuri |
su |
|
SCI304 |
SCMD90 (01R)- 4-3-2-1 |
Madhuri |
su |
|
SCI305 |
SCMD90 (01R)-5-4-1-1 |
Madhuri |
su |
|
SCI306 |
SCPRHY85 (01R)-2-1-2-3 |
SOOK SH137 |
sh |
|
SCI307 |
SCPRHY85 (01R)-6-3-1-2 |
SOOK SH137 |
sh |
|
SCI308 |
SCPRHY85 (01R)-7-3-2-1 |
SOOK SH137 |
sh |
|
SCI309 |
SCPRHY90 (01R)-2-2-1-2 |
SOOK SH138 |
sh |
|
SCI310 |
SCPRHY90 (01R)-3-1-3-1 |
SOOK SH138 |
sh |
larly, hybrid and parent vs. hybrid mean sum of squares are
significant for most of the traits.
This suggests the utilization of non-sweet germplasm in the improvement
of sugary genotypes through hybridization and introgression, followed by
backcrossing for characters such as field emergence, plant stand and yield.
The correlation coefficients were calculated to determine the degree of association of characters among the kernel quality components total soluble solids (TSS), grain yield and field emergence. Phenotypic correlations were computed using the formula given below. Pearson product-moment correlation coefficients were calculated using inbred line means from replicated trials of diallel and line-X-tester analysis using the SPSS 10.0 package.
|
|
Where,
|
rp |
= Phenotypic correlation |
|
Cov (XY) p |
= Phenotypic covariance between the characters X and Y |
|
X2p
and Y2p |
= Phenotypic variance of the characters X and Y, respectively |
Phenotypic correlation coefficients were compared against ÔrÕ values at (n-2) d.f. at the probability levels of 0.05 and 0.01 to test their significance. The results of correlation analysis for the traits studied in this experiment are presented in Table 4.
The main objective associated with this study was to understand the relationship between field emergence, grain weight and kernel quality traits, including total soluble solids (TSS). The correlation analysis revealed that total sugar is positively correlated with reducing sugar and non-reducing sugar with a high level of significance (p< 0.001). Phytoglycogen and total soluble solids had significant correlation with total sugar, with p values equal to 0.011 and 0.007, respectively. However it had negative significant correlation with starch, carbohydrate, grain weight and field emergence. The same trend was exhibited by reducing sugar as well as non-reducing sugar. Starch concentration in dry mature kernels was most highly correlated with total carbohydrate (r = 0.78), followed by field emergence (r = 0.69) and grain weight (r = 0.52) while it was negatively correlated with all other characters. The phytoglycogen content had a highly negative correlation coefficient with