environments=8
genotypes=45
replications=2
blocks=5/rep
pooled ANOVA of G*E interaction in Alpha Lattice Design and ANOVA for each location is needed. Kindly guide me in this regard.
source of variation will be:
environment
reps with in environment rep(env)
blocks (rep*env)
genotypes
gen*env
See the link: https://www.bing.com/search?q=alpha+lattice+experimental+design+SAS&qs=n&form=QBRE&sp=-1&pq=alpha+lattice+experimental+design+sas&sc=1-37&sk=&cvid=B7DFE28FE3904A98A9C1EBBB9D7983D1
Best, D. Booth
Hi Muhammad,
https://www.researchgate.net/post/What_is_the_SAS_code_in_SAS_ver_92_for_analysing_an_alpha_lattice_design
https://www.researchgate.net/post/Is_it_an_alpha-Lattice_Design_Whats_the_SAS_code
https://www4.stat.ncsu.edu/~dickey/courses/st711/notes/Notes_pdf/Alpha%20Lattice%20designs.pdf
https://support.sas.com/documentation/onlinedoc/stat/121/lattice.pdf
http://halweb.uc3m.es/esp/Personal/personas/jmmarin/esp/Disenno/CursoDisExpSAS.pdf
https://pbgworks.org/sites/pbgworks.org/files/user/4/Lattice_seminar.pdf
The use of incomplete block designs has gained wider acceptability among researchers in developing countries as a tool to control random variation, particularly for evaluation trials of many genotypes. In the CIMMYT Maize Program, alpha (0,1) lattice designs have been used since 1986 for evaluating groups of more than 200 genotypes, generally planted in single row plots. Relative efficiencies of 1.0-2.0 have been observed, but the use of the alpha-lattice designs has thus far been restricted mainly to genotype evaluation trials. There is little information on the use of these designs in agronomic experiments, although they could be useful where there is no factorial type relationship among treatments, where the number of treatments is relatively large (e.g., 16), and where soil heterogeneity at the test site is high. Among the most important constraints to the use of these designs are: the lack of an appropriate language-independent software interface for entering and transforming data files, the difficulty of handling information in a common format, and the lack of integration with other analytical tools (graphing applications, selection algorithms, regression, etc.). A software module in English and Spanish that facilitates and integrates the use of the ALPHANAL and LATANOVA programs (Scottish Agricultural Statistics Service, Edinburgh)for the design and analysis of alpha (0,1) lattices is described. The software also allows for the processing of lattice
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