Prediction of grain yield, adaptability, and stability in landrace varieties of lima bean (Phaseolus lunatus L.)

Sousa, Antônia M. de C. Batista de; Silva, Verônica Brito da; Lopes, Ângela Célis de Almeida; Gomes, Regina Lúcia Ferreira; Carvalho, Leonardo Castelo Branco

doi:10.1590/1984-70332020v20n1a15

Cited by 12 publications

(16 citation statements)

References 15 publications

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“…In Brazil, landraces are the main type of lima bean used by farmers and, usually, these landraces have high adaptation and rusticity. These features are important to be used in a plant breeding program since they provide a large source of genetic variability (PATERNIANI; NASS; SANTOS, 2000;SOUSA et al, 2020;SILVA et al, 2019a). Interestingly, lima bean landraces can grow under different environmental conditions and show a large variation in seeds traits, such as different sizes, shapes and colors (SILVA et al, 2015;SÁNCHEZ-NAVARRO et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Selection of Superior Genotypes of Lima Bean Landraces by Multivariate Approach

et al. 2022

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The knowledge of genetic diversity in plant population is essential to the success of plant breeding programs. Thus, previous characterization of landraces is one of the first steps before the indication of genotypes to these plant breeding programs. This study aimed to characterize, through morphological traits, and estimate the genetic diversity in landraces of lima bean (Phaseolus lunatus L.). Genetic diversity was estimated by using multivariate methods that selected individual landraces to be indicated for farmers and consumers. According to morphological traits proposed by Biodiversity International, the genotypes UFPI-667 and UFPI- 682 showed higher dissimilarity and high potential to be used in crosses since they are genetically distant and complementary. The principal component analysis identified positive and significant phenotypic associations between variables: pod length, pod width, and grain production. According to the multivariate methods used, the landraces UFPI-666, UFPI-650, UFPI-651, UFPI-687, UFPI-658, UFPI-673, UFPI-667, and UFPI-674 are potential candidates for selection since they have relevant features for lima bean breeding, such as shorter cycles and higher grain production. This study showed that multivariate analysis can be used as an effective tool to find potential traits in lima bean and can assist the lima bean breeders in the selection of potential landraces. Accessions UFPI-667 and UFPI-682 can be indicated as genitors for breeding programs, as they are genetically distant and complementary in their characteristics.

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Section: Introductionmentioning

confidence: 99%

Selection of Superior Genotypes of Lima Bean Landraces by Multivariate Approach

et al. 2022

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“…Numerous methods have been reported in the literature for studying adaptability and stability in multi-environment trials. The methods proposed may be based on the components of analysis of variance, on the regression method, on non-parametric methods, on multivariate methods, on mixed models, and on new methods, such as factor analytic models (Van Eeuwijk et al 2016, Carvalho et al 2016, Li et al 2017, Sousa et al 2020.…”

Section: Introductionmentioning

confidence: 99%

Adaptability and yield stability of soybean genotypes by REML/BLUP and GGE Biplot

Gonçalves

Ferreira-Gomes

Lopes

et al. 2020

Crop Breed. Appl. Biotechnol.

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The aim of this study was to ascertain the association between the REML/BLUP and GGE Biplot methodologies for selection of superior genotypes in regard to adaptability and yield stability for various regions of the Middle North region of Brazil. Sixteen soybean genotypes were evaluated in eight environments during the 2015/2016 and 2016/2017 crop seasons, analyzing the following traits: number of days to maturity, plant height, one hundred seed weight, and grain yield. In this study, the REML/BLUP and the GGE Biplot methods are highly correlated in terms of genotype ranking for selection and recommendation purposes. The genotypes BRASBT13-0528, M8372 IPRO, and BRASBT13-0621 most approximate a hypothetical ideal genotype.

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“…Several methodologies have been reported for studying adaptability and stability in multi-environment trials. The methods proposed may be based on the components of an analysis of variance, the regression method, non-parametric methods, multivariate methods, mixed models, and recent methods based on factor analytic models [ 14 , 15 , 16 , 17 , 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Adaptability and Stability of Safflower Genotypes for Oil Production

Neto

Zeffa

Freiria

et al. 2022

Plants

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The study aimed to analyze the agronomic performance of 11 safflower genotypes using adaptability and stability methods, while identifying safflower genotypes with stable behavior and a high grain yield in different environments of the Brazilian Cerrado. Ten lines and a cultivar of safflower were evaluated in four environments in the Brazilian conditions. Our results revealed the genotypes P30, P35, P9, P11, and P31 to be superior for grain yield and P43, P7, P11, and P31 to be superior for oil content. The lowest Wricke index, an indication of genotype stability, was observed for P9 (0.41%), which is considered the most stable genotype, followed by P35 (1.29%) and P31 (1.98%). For the predictability of the behavior of genotypes in the environments, P7 (80.85%), P35 (86.10%), P31 (85.90%), and P9 (97.42%) were considered predictable genotypes. The genotypes P11 (1045.6 kg ha−1 and 19.7%) and P21 (952.7 kg ha−1 and 20.6%) are recommended for cultivation in this region, considering both their grain yield and oil content. Safflower is viable to use out of season in the Brazilian Cerrado. The crop can generate profits for farmers and be used for oil production in periods of uncertain corn production.

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Prediction of grain yield, adaptability, and stability in landrace varieties of lima bean (Phaseolus lunatus L.)

Cited by 12 publications

References 15 publications

Selection of Superior Genotypes of Lima Bean Landraces by Multivariate Approach

Selection of Superior Genotypes of Lima Bean Landraces by Multivariate Approach

Adaptability and yield stability of soybean genotypes by REML/BLUP and GGE Biplot

Adaptability and Stability of Safflower Genotypes for Oil Production

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