Agronomic performance and genetic dissimilarity of second-harvest soybean cultivars using REML/BLUP and Gower’s algorithm

Follmann, Diego Nicolau; Souza, Velci Queiróz de; Filho, Alberto Cargnelutti; Demari, Gustavo Henrique; Nardino, Maicon; Olivoto, Tiago; Carvalho, Ivan Ricardo; Silva, Antonio David Bortoluzzi; Meira, Daniela; Meier, Carine

doi:10.1590/1678-4499.20180194

Cited by 11 publications

(3 citation statements)

References 28 publications

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“…BLUPs for proteins, lipids, fiber, mineral material and carbohydrates revealed positive and negative genotypic effects for the genotypes under study. Follmann et al (2019), emphasize that the genotypic effect is the difference between the point and the vertical line (demonstrating the general mean of the trait).…”

Section: Results and Discusionmentioning

confidence: 99%

Strategic Positioning of the Nutritional Profile of Wheat Grains Based on Genetic Parameters

Carvalho

Kehl²,

Pradebon

et al. 2022

Trop Subtrop Agroecosyst

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Background. Wheat is a staple food crop and easily accessible to the population, so the biofortification of wheat grains is substantial to mitigate malnutrition. Objective. To evidence and select wheat genotypes based on nutritional multi-characters of grains based on genetic parameters. Methodology. Experiments were carried out in the 2019 agricultural season in five wheat areas of the state of Rio Grande do Sul, in two sowing seasons, in the municipalities of Cachoeira do Sul, Cruz Alta, Santo Augusto, São Gabriel and Vacaria. The experimental design was randomized blocks, organized in a factorial scheme with 10 cultivation environments (5 sites by two sowing dates) and 30 genotypes, with three replications. To carry out the selection of genotypes, the WAASB, AMMI, GGE and BLUP methodologies were applied. Results. In terms of lipids and fibers, three mega environments were formed, highlighting the genotypes BRS 327, CD 1550, Ametista, CD 1303 and BRS 331, respectively. For mineral material, there was the formation of two mega environments and the genotypes that stood out were Quartz and Tbio Toruk, while for carbohydrate there was the formation of a mega environment and the genotype that stood out was CD 1550. The Tbio Mestre and LG Prisma genotypes were the ideal genotypes, with high performance in the Cachoeira do Sul environment – Sowing 2nd fortnight. Tbio Iguaçú expressed high levels of lipids in Santo Augusto – Seeding 1st fortnight, São Gabriel – Seeding 2nd fortnight and Vacaria – Seeding 2nd fortnight. ORS 1405 and Tbio Iguaçú expressed high levels of carbohydrates in the Vacaria - Seeding 2nd fortnight environment. Heritabilities without interaction effects were high, which characterizes high genotypic additive variance. Implications. The current results indicate that there is genetic variability, making it possible to select genotypes with greater expression of nutrients in the grains. Conclusion. The TBio Mestre, CD 1440, LG Prisma and Marfim genotypes expressed greater performance and stability of the evaluated traits.

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Section: Results and Discusionmentioning

confidence: 99%

Strategic Positioning of the Nutritional Profile of Wheat Grains Based on Genetic Parameters

Carvalho

Kehl²,

Pradebon

et al. 2022

Trop Subtrop Agroecosyst

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“…In this context, one of the most appropriate selection procedures involves the estimation of variance components (i.e., restricted maximum likelihood -REML) and the prediction of genotypic values (i.e., best linear unbiased prediction -BLUP) (Resende 2007). Accordingly, plant breeding studies use these methods, such as for white oat (Avena sativa L.; Olivoto et al 2019), soybean (Glycine max L.; Follmann et al 2019), bean (Phaseolus vulgaris L.; Santos et al 2019) and corn (Zea mays L.; Olivoto et al 2017), as well as in early-segregating generations of wheat (Pimentel et al 2014, Woyann et al 2019b.…”

Section: Parâmetros Genéticos E Seleção De Múltiplas Características ...mentioning

confidence: 99%

Genetic parameters and multiple-trait selection in wheat genotypes

Meier¹,

Marchioro

Meira

et al. 2021

Pesqui. Agropecu. Trop.

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Mixed models and multivariate analysis are powerful tools for selecting superior genotypes in plant breeding programs. The BLUP (best linear unbiased prediction) method has been used to predict genetic values without environmental effects. Furthermore, the FAI-BLUP (ideotype-design index) procedure is especially valuable for plant breeding because of multiple-trait selection. This study aimed to determine the genetic potential of advanced wheat generations using REML/BLUP in combination with multivariate techniques for the selection of superior genotypes. The experiment consisted of eleven wheat (Triticum aestivum L.) genotypes. The experimental design was randomized blocks, with three replications. Plant height, spike insertion height, number of tillers, number of spikelets, kernel width, hectoliter weight and kernel weight per plant were determined. The genetic parameters were estimated using the REML/BLUP methodology, and the FAI-BLUP index was calculated using predicted genetic values. The genotypes UFSMFW 1-02, UFSMFW 1-05 and UFSMFW 1-04 show potential to increase the grain yield. The selection gains for number of tillers (14.63 %) and kernel weight per plant (22.35 %) indicate the potential to select superior genotypes.

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“…The restricted maximum likelihood (REML) and the best linear unbiased prediction (BLUP) have been utilized as efficient selection procedures for the estimation of variance components and prediction of genotypic values (random effect), respectively [ 9 ]. These techniques have been utilized in various crop breeding programs such as white Guinea yam [ 5 ], white oat [ 10 ], soybean [ 11 ], bean [ 12 ], maize [ 13 ], etc.…”

Section: Introductionmentioning

confidence: 99%

Multiple-Traits Selection in White Guinea Yam (Dioscorea rotundata) Genotypes

Norman

Agre

Asiedu

et al. 2022

Plants

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Choosing superior parents with complementary trait values for hybridization and selecting variants with desired product profiles to release as a new cultivar are important breeding activities to progress genetic improvement in crops. This study assessed the genetic potential of 36 parental lines of white Guinea yam (Dioscorea rotundata) genotypes using multi-trait index-based factor analysis and ideotype design (FAI-BLUP). The experiment utilized 36 white yam genotypes laid out in a 6 × 6 triple lattice design with three replications and phenotyped for 18 agronomic and food quality traits. Findings showed significant differences among genotypes for all assessed traits. Fifteen traits had desired genetic gains, whereas stem diameter (−1.34%), and two starch property traits ((holding strength (−26.31%) and final paste viscosity (−3.33%)) had undesired selection gain. The FAI-BLUP index provided total genetic gains of 148.91% for traits desired for increase and –29.26% for those desired for decrease. Genotypes TDr08-21-2, TDr9518544, TDr9501932, TDr8902665 and Pampars were identified as top best candidate for simultaneous improvement of the measured traits in white yam breeding. The findings indicate the effectiveness of the FAI-BLUP index in identifying and selecting genotypes.

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Agronomic performance and genetic dissimilarity of second-harvest soybean cultivars using REML/BLUP and Gower’s algorithm

Cited by 11 publications

References 28 publications

Strategic Positioning of the Nutritional Profile of Wheat Grains Based on Genetic Parameters

Strategic Positioning of the Nutritional Profile of Wheat Grains Based on Genetic Parameters

Genetic parameters and multiple-trait selection in wheat genotypes

Multiple-Traits Selection in White Guinea Yam (Dioscorea rotundata) Genotypes

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