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SELEÇÃO DE FAMÍLIAS DE CANA-DE-AÇÚCAR VIA MODELOS MISTOS SELECTION OF SUGARCANE FAMILIES BY MIXED MODELS

Ricardo Augusto, João Carlos Bespalhok Filho, José Luís, Camargo Zambon, Oswaldo Teruyo Ido, Marcos Deon, Vilela de Resende, Hugo Zeni-Neto

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Abstract

The objectives of this work were to select superior families and parents of sugarcane originated from biparental crosses, for biomass production using mixed models: REML/BLUP. The REML/BLUP methodology was adopted, with the REML used for estimation of the genetic variance, and the BLUP for the estimation of genetic values of families. For this study, 80 fullsib families from RB03 series were used, originated from crosses made on Serra do Ouro Station, County of Murici, Alagoas, in 2003. The experiment was installed in an experimental area, County of Sao Tome, Parana. The experimental design used was incomplete blocks, with five replications per family. Each replication was composed by ten plants. For selection of superior families, tons of canes per hectare (TCH) were considered. According to the obtained results, the analyzed characters showed individual heritabilities ( 2 ˆ a h ) from medium magnitudes (0.22), while the heritabilities from family means ( 2 ˆ mf h ) ranged from 0.73. The selection of families with genotypic values greater than the average trial, it is estimated significant profits of TCH. Based on TCH the best families were RB825336 e SP80-1816, RB825548 e RB855156, SP80-3280 e RB845257, RB83102 e RB855113, RB8495 e RB835089.

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What this paper is about

The objectives of this work were to select superior families and parents of sugarcane originated from biparental crosses, for biomass production using mixed models: REML/BLUP. The REML/BLUP methodology was adopted, with the REML used for estimation of the genetic variance, and the BLUP for the estimation of genetic values of families. For this study, 80 fullsib families from RB03 series were used, originated from crosses made on Serra do Ouro Station, County of Murici, Alagoas, in 2003. The experiment was installed in an experimental area, County of Sao Tome, Parana. The experimental design used was incomplete blocks, with five replications per family. Each replication was composed by ten plants. For selection of superior families, tons of canes per hectare (TCH) were considered. According to the obtained results, the analyzed characters showed individual heritabilities ( 2 ˆ a h ) from medium magnitudes (0.22), while the heritabilities from family means ( 2 ˆ mf h ) ranged from 0.73. The selection of families with genotypic values greater than the average trial, it is estimated significant profits of TCH. Based on TCH the best families were RB825336 e SP80-1816, RB825548 e RB855156, SP80-3280 e RB845257, RB83102 e RB855113, RB8495 e RB835089.

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Available abstract

The objectives of this work were to select superior families and parents of sugarcane originated from biparental crosses, for biomass production using mixed models: REML/BLUP. The REML/BLUP methodology was adopted, with the REML used for estimation of the genetic variance, and the BLUP for the estimation of genetic values of families. For this study, 80 fullsib families from RB03 series were used, originated from crosses made on Serra do Ouro Station, County of Murici, Alagoas, in 2003. The experiment was installed in an experimental area, County of Sao Tome, Parana. The experimental design used was incomplete blocks, with five replications per family. Each replication was composed by ten plants. For selection of superior families, tons of canes per hectare (TCH) were considered. According to the obtained results, the analyzed characters showed individual heritabilities ( 2 ˆ a h ) from medium magnitudes (0.22), while the heritabilities from family means ( 2 ˆ mf h ) ranged from 0.73. The selection of families with genotypic values greater than the average trial, it is estimated significant profits of TCH. Based on TCH the best families were RB825336 e SP80-1816, RB825548 e RB855156, SP80-3280 e RB845257, RB83102 e RB855113, RB8495 e RB835089.

Key concepts: Best linear unbiased prediction, Restricted maximum likelihood, Selection (genetic algorithm), Mixed model, Statistics, Hectare, Mathematics, Variance components

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