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OALib Journal期刊
ISSN: 2333-9721
费用:99美元
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匹配条件: “Mekonene Ayana Gebul” ,找到相关结果约96条。
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Heritability and Correlation among Sugarcane (Saccharum spp.) Yield and Some Agronomic and Sugar Quality Traits in Ethiopia
[PDF]
Esayas Tena, Firew Mekbib, Amsalu Ayana
American Journal of Plant Sciences (AJPS)
,
2016,
DOI: 10.4236/ajps.2016.710139
broad sense heritability and phenotypic and genetic
correlations among sugarcane yield components, an experiment was
conducted at Wonji and Metehara Sugar Estates of Sugar Corporation of Ethiopia
during 2012/2013. High broad sense heritability (h2) was detected for stalk
diameter (0.730), single cane weight (0.672), millable cane number
(0.624), stalk height (0.624) and pol % (0.608), indicating that these traits could be selected
for easily. Expected genetic gain of the yield components was moderate to high. All traits had
low to high genetic correlations (rg = -0.005 to 0.884) with cane
yield and (rg = 0.027 to 0.999) with sugar yield. On average genetic
correlations were higher than phenotypic correlations. High Genotypic
Coefficient of Variation (GCV), broad sense heritability and expected genetic
advance were recorded for stalk diameter, single cane weight
and millable cane number. A selection strategy based on these traits could lead to
improvement in cane and sugar yield.
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Correlation and Path Coefficient Analyses in Sugarcane Genotypes of Ethiopia
[PDF]
Esayas Tena, Firew Mekbib, Amsalu Ayana
American Journal of Plant Sciences (AJPS)
,
2016,
DOI: 10.4236/ajps.2016.710141
experiment was
conducted at Wonji and Metehara Sugar Estates, Ethiopia between March 2012 and October 2013. The experiment,
comprising of 400 sugarcane genotypes
of which 174 were local that
were collected from different regional states of Ethiopia and 226
introduced, was laid out in partial balanced lattice design with two
replications. Data was collected on
cane yield and its components, sugar yield and sugar quality traits. ANOVA,
correlation and path coefficient analysis were done. Analysis of variance revealed significant
differences (P < 0.01) for all the
characters studied. Cane yield showed strong positive and highly significant (P < 0.01) correlation with millable
cane number (r = 0.832), single cane weight (r = 0.528), stalk height (r = 0.517) and sugar yield (r = 0.987). There was also positive significant (P = 0.05)
correlation of tiller count and cane diameter with cane yield. Path analysis
revealed the highest positive direct effect of millable cane number (0.812) on cane yield followed by single cane weight (0.682) and pol percent (0.550). However, stalk diameter and brix percent had
considerable negative direct effects and indirect positive
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Genetic Diversity of Quantitative Traits of Sugarcane Genotypes in Ethiopia
[PDF]
Esayas Tena, Firew Mekbib, Amsalu Ayana
American Journal of Plant Sciences (AJPS)
,
2016,
DOI: 10.4236/ajps.2016.710142
March 2012 and October 2013 at Wonji and
Metehara Sugar Estates using partial balanced lattice design with two
replications. Data was recorded on
21 quantitative characters which included
cane yield and its components, sugar yield and sugar quality traits. ANOVA
portrayed highly significant
differences (P < 0.01) among the genotypes for 21 quantitative traits.
Cluster analysis revealed intra cluster D2 values ranging from 2.16
- 10.60 and inter cluster from 7.24 - 5864. There were six principal components
accounting for 79.26% of the total variation in the tested materials. Millable
stalk count, single cane weight, stalk diameter, cane yield, sugar yield and
sugar quality traits showed high positive loading on the first two PCs and
accounted for most of the variation observed among the genotypes. Therefore, this
study suggested that the important characters responsible for diversity in the
sugarcane genotypes could be grouped in two principal components namely “Yield”
and “Quality” with “Yield” traits being comparatively more important than “Quality”.
Genotypes clustered for high mean values of various traits could be exploited
for further improvement of the crop either through selection or through hybridization.
The clusters having high mean value for yield could be selected for yield per
se as well.
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