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Provedor de dados:  Acta Agron. (Palmira)
País:  Colombia
Título:  Genotype x envíronment ínteractíon for yield of rice hybrids and ínbred varíetíes ín Venezuela
Autores:  Acevedo Barona,Marco Antonio
Silva Díaz,Rubén José
Perdomo Rojas,Rosaura Desirée
Pérez Almeida,Iris Betzaida
Álvarez Parra,Rosa María
Torres Angarita,Orlando José
Data:  2022-03-01
Ano:  2022
Palavras-chave:  Adaptability
GGE biplot
Lin-Binns
Stability
Oryza sativa L
Resumo:  Abstract Performance tests in múltiple locations are essential to study the genotype x-environment interaction, as well as to identify superior genotypes and testing locations. The objective of this study was to evaluate the adaptability and stability of rice hybrids and inbred varieties for grain yield. Six experiments were conducted in rice-producing areas of Venezuela using a randomized complete block design during the dry season of 2015 2016. The ANOVA detected significant differences for genotype, location, and genotype-by-location interaction, highlighting the hybrid by location interaction. The Lin and Binns model identified the hybrids ‘RHA-180' and ‘HL23035H' and the ‘Soberana Fl' variety as adapted and stable. In the GGE biplot model, the first components were significant, and together explained 82 % of the total variability. The hybrids ‘RHA-180' and ‘HL23035H' were identified as adapted and stable, whereas the ‘RHA-180' hybrid was considered the “ideal genotype”. The varieties ‘Soberana Fl' and ‘SD-20A' displayed high performance and intermediate stability. The two mega-environments differed by having the best performing genotypes ‘RHA-180' and ‘Soberana Fl'. Plot 199 was the most representative locality to evaluate hybrids and varieties, whereas the INIA Guárico location discriminated better the rice genotypes. Both models coincided regarding the identification of adapted and stable hybrids and varieties in Venezuela. Nonetheless, while it was easy and efficient to apply the Lin and Binns model, the SREG model was more detailed, effective, and informative.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Identificador:  http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-28122022000100073
Editor:  Universidad Nacional de Colombia
Relação:  10.15446/acag.v71n1
Formato:  text/html
Fonte:  Acta Agronómica v.71 n.1 2022
Direitos:  info:eu-repo/semantics/openAccess
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