02169naa a2200277 a 450000100080000000500110000800800410001902400380006010000230009824501040012126000090022552013590023465000130159365000260160665000140163265300260164665300290167265300180170165300210171970000150174070000180175570000190177370000230179270000190181577300570183421244072020-08-18       2019    bl uuuu     u00u1 u    #d7 a10.14393/BJ-v35n4a2019-421252DOI1 aABREU, H. K. A. de  aAdaptability and stability of cowpea genotypes via REML/BLUP and GGE BIPLOT.h[electronic resource]  c2019  aSeveral methodologies have been proposed in order t o measure the influence that genotype-by-environment interaction exerts on the v arious characters of interest. The mixed models usi ng REML/BLUP and GGE Biplot have been mentioned as adv antageous to identify superior genotypes. The use o f environmental information can be useful to find the factors that are in the real difference between th e genotypes. The objective of this study was to compa re statistical methodologies for the adaptability a nd stability analysis of cowpea genotypes in value for cultivation and use testings. The experiments were carried out from March to July 2016 and 2017, in the munici palities of Dourados and Aquidauana. A randomized complete block design was used, with 14 genotypes a nd four replicates, 12 advanced lines and two comme rcial cultivars. After detecting significant genotype-by- environment interaction, the adaptability and pheno typic stability of cowpea genotypes were analyzed by the GGE Biplot and REML/BLUP. Both methodologies were concordant in the identification of the best cowpea genotypes for the State of Mato Grosso do Sul. The genotypes 6 (Pingo-de-ouro 1-5-4), 10 (Pingo-de-our o 1-5-10) and 8 (Pingo-de-ouro 1-5-7) are the most suitable to be grown in the State, because they hav e gathered high grain yield, adaptability and stabi lity  aGenotype  aMultivariate analysis  aGenótipo  aAnálise multivariada  aEnvironments interaction  aFeijão caupi  aVigna unguiculat1 aCECCON, G.1 aCORREA, A. M.1 aFACHINELLI, R.1 aYAMAMOTO, E. L. M.1 aTEODORO, P. E.  tBioscience Journalgv. 35, n. 4, p. 1071-1082, 2019.