Stability analysis in R | Genotype X Environment interaction | Fixed effect models (AMMI) | GGE plot

This tutorial covers all the concepts of stability analysis in plant breeding which will be conducted on a multi environment data in order to know the different type of interaction between genotype and environments, here in this video i will show how to do the data analysis of a multi environment trail by using fixed effect models in which random effects will be ignored. The video starts from brief introduction followed by data structure or guidelines in entering data into excel later in the r studio i will suggest all the care and precautions which are taken by the beginners and this will be beginner friendly video because i wont read the script instead i go through step wise in order to make the video more desirable to follow on. The procedure starts with importing dataset into the environment followed by data manipulation and finally data inspection for detecting outliers and handling mess in the dataset, before getting into the data analysis part. In the analysis part i will talk about getting mean values in different combination for preparing two table along with some of the plots like heat map and line graph, next i will show you how to do individual anova with bartlett test and pooled anova based on fixed effect model, later we will get into the stability analysis part where i do cover up concepts like environmental index, ecovalence, shukla’s stability variance, regression based anova (Eberhart and Russell model) followed by some of the non parametric stability concepts like superiority by Linn and Bins, Fox top third criteria, Factor based analysis etc.. The most important aspect of the tutorial is AMMI model here i will fit ammi model and get all kinds of biplots, with that i do talk about weighted average absolute scores concept developed by the author of this package himself where we do fit a new model and get a different kind of plot. In the last part of the video i do cover GGE modelling and model options which are available in this package and talk about ten different kinds of biplots including which won where, basic biplot, ranking of environment, genotypes and evaluation of them etc….. 1) Statistical modelling - https://www.frontiersin.org/articles/... 2) Mixed models - https://onlinelibrary.wiley.com/doi/a... 3) Metan - https://besjournals.onlinelibrary.wil... 4) Supp. info - https://besjournals.onlinelibrary.wil... 5) Yan and Tinker - https://cdnsciencepub.com/doi/pdf/10.... Data set is there in TNAU stat example of stability analysis https://drive.google.com/file/d/1bjZW... Script https://docs.google.com/document/d/1M... 00:00 - Intro 00:37 Interactions 03:22 statistical models 04:31 metan 05:45 study materials 06:28 original paper 06:41 supplementary material 07:41 Yan and Tinker 08:46 Data structure 11:02 Beginners tips 12:15 packages required 14:24 setting up working directory 14:56 importing data set 17:52 factor conversion 20:37 data inspection 21:18 judging outliers 24:12 Data cleaning 26:07 Data analysis 26:18 Descriptive statistics 28:02 importing table 29:50 Mean performance 34:13 Plotting performance 37:08 Winners 38:24 Ranks 40:01 Ind anova and Bartlett test 45:59 Pooled anova 48:23 Stability analysis 48:45 Environmental index 50:44 Ecovalence 52:05 Shukla’s stability var. 52:57 Regression based model 54:01 Reg. anova 56:22 superiority 58:16 Fox top third criteria 59:28 Factorial 1:02:08 Wrapper function 1:03:20 Ranks based on stab. Ind. 1:05:53 Correlation b/w indexes 1:07:55 AMMI Model 1:11:11 AMMI Biplots 1:21:00 AMMI based stats 1:22:46 WAAS 1:25:43 Cross verify IPCA 1:26:46 GGE Modelling 1:26:51 Model options 1:27:09 svp 1:27:34 svp = environment 1:29:12 Basic biplot 1:30:38 Discriminative vs. representativeness 1:32:23 Ranking of environments 1:33:21 Relationship among environments 1:34:46 svp = genotype 1:36:29 Mean performance vs. stability 1:37:42 Examining a genotype 1:39:06 Ranking of Genotypes 1:40:12 svp = symmetrical 1:41:56 Which Won Where 1:43:11 Examine a environment 1:44:37 Comparison among genotypes 1:46:02 Getting a plot out 1:47:14 Genotypic and Phenotypic correlations