Description Usage Arguments Details Value Note Author(s) References See Also Examples
Analysis of Line x Tester data containing only Crosses laid out in RCBD or Alpha Lattice design.
1 |
data |
dataframe containing following variables |
replication |
replication |
line |
line |
tester |
tester |
y |
trait of interest |
block |
block (for alpha lattice design only) |
Analyzing the line by tester data only using the data from crosses which are evaluated in alpha lattice design. All the factors are considered as fixed.
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ANOVA with all the factors. |
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ANOVA with all the factors. |
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Phenotypic and Genotypic variance for the given trait. |
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Phenotypic coefficient of variability and Genotypic coefficient of variability and Environmental coefficient of Variation. |
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Propotional contribution of Lines, Tester and Line x Tester interaction. |
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Combining ability effects of lines. |
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Combining ability effects of testers. |
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Combining ability effects of crosses |
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ANOVA with all the factors. |
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Genetic component of Variance as per Singh and Chaudhary, 1977. |
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Standard error for combining ability effects. |
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Critical Difference at 5 pecent for combining ability effects. |
The block variable is inserted at the last if the experimental design is Alpha Lattice. For RCBD no need to have block factor.
Nandan Patil tryanother609@gmail.com
Kempthorne, O. (1957), Introduction to Genetic Statistics. John Wiley and Sons, New York. , 468-472. Singh, R. K. and Chaudhary, B. D. (1977). Biometrical Methods in Quantitative Genetic Analysis. Kalyani Publishers, New Delhi.
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## Not run: #Line Tester analysis data with only crosses in RCBD
library(gpbStat)
data(rcbdltc)
result1 = ltc(rcbdltc, replication, line, tester, yield)
result1
#Line Tester analysis data with only crosses in Alpha Lattice
library(gpbStat)
data(alphaltc)
result2 = ltc(alphaltc, replication, line, tester, yield, block)
result2
## End(Not run)
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