Genetic improvement of silage maize: predicting genetic gain using selection
            indexes and best linear unbiased prediction

Crevelari, Jocarla Ambrosim; Pereira, Messias Gonzaga; Azevedo, Flávio Henrique Vidal; Vieira, Ricardo Augusto Mendonça

doi:10.5935/1806-6690.20190023

Cited by 8 publications

(12 citation statements)

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“…We observed a significant genetic variation about the potential DM digestibility of the studied corn hybrids, as revealed by the in vitro gas production technique and the need for a nonlinear model that accounted for the hybrid × location interaction effect for a better description of gas production profiles. This result may be attributable to the corn variability studied by our research group (Crevelari et al, 2017(Crevelari et al, , 2018(Crevelari et al, , 2019. The variable digestibility relates to the quality of the fibrous fraction because of somewhat different environmental conditions, as mentioned before (Van Soest, 1994).…”

Section: Discussionmentioning

confidence: 83%

“…Corn genetic improvement can enhance its agronomic performance and nutritional qualities for silage production (Roth et al, 1970;Deinum and Bakker, 1981;Crevelari et al, 2019;Pereira et al, 2020). Some results indicate that environmental factors, such as agronomic factors that change grain:stover ratio, do not greatly influence the final digestibility of the corn silage, nor improve ensiling characteristics, but the factors affecting yields and economic returns may be worth investigating (Russell et al, 1992).…”

Section: Discussionmentioning

confidence: 99%

“…In addition, environmental constraints affect the forage yield of corn hybrids, which demand specific recommendations to corn forage cropping by region to predict the effect of environmental factors (e.g., altitude and temperature) on silage quantity and quality (Buxton, 1996;Crevelari et al, 2017Crevelari et al, , 2018Crevelari et al, , 2019. Therefore, our goal was to evaluate the forage and nutritional potential of dented corn hybrids for silage production in two locations of low altitudes above sea level (a.s.l.)…”

Section: Laila Cecília Ramos Bendiamentioning

confidence: 99%

“…We determined the ASH contents in porcelain crucibles (method 942.05; AOAC, 2019), fitted with porcelain covers to avoid spillages during incineration and manipulation of crucibles. However, (Crevelari et al, 2017(Crevelari et al, , 2019.…”

Section: Sampling and Processing Of Corn Plantsmentioning

confidence: 99%

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A two-location trial for selecting corn silage hybrids for the humid tropic: forage and grain yields and in vitro fermentation characteristics

Bendia¹,

Oliveira²,

Azevedo³

et al. 2021

Revista Brasileira De Zootecnia

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The goal of our study was to evaluate the nutritional potential of dented corn hybrids for silage production. We performed a two-location trial in which 19 dented corn hybrids and five corn controls grew in four randomized blocks within two experimental areas located in the Northern (Campos dos Goytacazes) and Northwestern (Itaocara) Rio de Janeiro State, Brazil. We recorded yields of fresh and dry forage matter and yields of fresh and dry grain matter, as well as chemical composition variables. We interpreted variables by assuming a Normal distribution for yield variables and a Beta distribution for chemical composition and ratios. The SAS GLIMMIX procedure fitted the linear model under those assumptions. Dual-pool models fitted the gas production profiles generated by in vitro anaerobic fermentations. We used the nlme of R software to fit the dual-pool models and the information-theoretic approach to evaluate their quality of fit. We did a cluster analysis (NbClust of R) to group corn hybrids based on fresh and DM yields and kinetic parameters of in vitro gas production. Three clusters of corn hybrids stood out, their basic differences relied on fresh and DM yields. Nonetheless, the least-squares means for gas production characteristics among groups did not present disjoint confidence intervals. Therefore, we can infer that dented corn hybrids rank by forage yield, but not by forage quality, and recommend the most productive ones that consistently outstand in both locations (hybrids UENF-2203, UENF-2192, UENF-2193, and UENF-506-11).

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Section: Discussionmentioning

confidence: 83%

Section: Discussionmentioning

confidence: 99%

Section: Laila Cecília Ramos Bendiamentioning

confidence: 99%

Section: Sampling and Processing Of Corn Plantsmentioning

confidence: 99%

See 2 more Smart Citations

A two-location trial for selecting corn silage hybrids for the humid tropic: forage and grain yields and in vitro fermentation characteristics

Bendia¹,

Oliveira²,

Azevedo³

et al. 2021

Revista Brasileira De Zootecnia

Self Cite

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show abstract

“…The Mulamba & Mock sum of ranks index presented higher gains when compared to the Smith and Hazel index. The efficiency of using selection indexes has also been observed in silage maize (Crevelari et al, 2019), soybean (Teixeira et al, 2017), and wheat (Fellahi et al, 2018). Almeida et al (2019) showed concordance between indexes with regards to the ranking of the best genotypes; the magnitude of the expected gain must be considered.…”

Section: Discussionmentioning

confidence: 88%

Selection gain and interrelations between agronomic traits in wheat F5 genotypes

et al. 2019

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This work aimed to estimate the variance components and genetic parameters, the selection gain, and the cause and effect relationships among traits in order to identify important traits for direct and indirect selection of wheat (Triticum aestivum L.) lines. Three strategies were used to obtain selection gains: direct and indirect selection, an index based on "ranks," and the Smith and Hazel index. In the 2017 crop season in Brazil, 420 wheat lines from the F 5 generation were conducted in families with intercalary controls. High heritability of spike weight, number of kernels, and total kernel weight resulted in the best direct selection gains. The selection of plants with a high number of tillers resulted in grain yield improvement. The use of selection indexes is important in advanced wheat lines; they promote genetic gains distributed among agronomic traits.

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Adaptability and stability of corn hybrids for silage via genotype and genotype × environment interaction biplot

et al. 2023

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The occurrence of the genotype × environment (G × E) interaction is one of the main factors that hinder the selection of adapted and stable genotypes. The genotype and G × E interaction (GGE) biplot methodology is an efficient process to detect corn (Zea mays L.) hybrids for silage and, consequently, will help in the recommendation of new and more stable hybrids in different environments in breeding programs. In this sense, this study aimed to evaluate and select corn hybrids for silage that simultaneously combine high yield and stability in different environments in the state of Rio de Janeiro, Brazil, via GGE biplot. Eleven corn hybrids, eight precommercial topcrosses and three commercial controls, were evaluated at three sites (Campos dos Goytacazes, Cambuci, and Itaocara, Rio de Janeiro) during two seasons: the 2017-2018 season and 2018-2018 off-season. The experiments were designed in completely randomized blocks with three replications. Individual and joint analyses of variance were performed and, after detecting significant interaction between genotype and environment, the adaptability and phenotypic stability of corn genotypes for silage were analyzed using the GGE biplot methodology. The GGE biplot analysis was efficient in interpreting the data and represented 83.68% of the total variation in the first two principal components. The use of the GGE biplot method allowed the recommendation of more productive, stable, and responsive hybrids for the state of Rio de Janeiro. The hybrid UENF MS2208 is indicated for cultivation in the state of Rio de Janeiro for combining high green biomass yield and stability. INTRODUCTIONCorn (Zea mays L.) is a crop that has importance in the socioeconomic, environmental, and cultural spheres worldwide and also in Brazil. It mainly is due to its potential use in human and animal food and biofuel production among others AEC, average environment coordinate; G × E, genotype × environment interaction; GGE, genotype and genotype × environment interaction; GMY, green biomass yield.

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Genetic improvement of silage maize: predicting genetic gain using selection indexes and best linear unbiased prediction

Cited by 8 publications

References 0 publications

A two-location trial for selecting corn silage hybrids for the humid tropic: forage and grain yields and in vitro fermentation characteristics

A two-location trial for selecting corn silage hybrids for the humid tropic: forage and grain yields and in vitro fermentation characteristics

Selection gain and interrelations between agronomic traits in wheat F5 genotypes

Adaptability and stability of corn hybrids for silage via genotype and genotype × environment interaction biplot

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