Biometric analysis of protein and oil contents of soybean genotypes in different environments

Rodrigues, Josiane Isabela da Silva; Arruda, Klever Márcio Antunes; Cruz, Cosme Damião; Piovesan, Newton Deniz; Barros, Everaldo Gonçalves de; Moreira, Maurílio Alves

doi:10.1590/s0100-204x2014000600009

Cited by 17 publications

(13 citation statements)

References 21 publications

(28 reference statements)

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“…On average for all six environments, PC was negatively correlated with GY (r = −0.74**), whereas the association between OC and GY (r = 0.34), and between oil and protein contents (r = −0.09) were not significant. These associations are present in wheat, but also in other crops [37,[49][50][51] which makes it difficult to develop productive cultivars with high contents of protein and oil [52]. In our study, cvs.…”

Section: Genotypic Variationsmentioning

confidence: 74%

“…Rodrigues et al [52] reported that water stress and high temperatures reduce both protein and oil contents in soybean seeds, while Rotundo and Westgate [57] concluded that temperature has a more pronounced effect on oil content, but it also affects protein content. Barbosa et al [58] found that higher temperatures during grain filling favored oil accumulation in soybean.…”

Section: Ge Effects On Oc Pc and Gymentioning

confidence: 99%

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Biometric Analyses of Yield, Oil and Protein Contents of Wheat (Triticum aestivum L.) Genotypes in Different Environments

et al. 2019

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The objectives of this study were to investigate: (1) the effects of genotype, environment, and their interactions on the oil content (OC), protein content (PC) and grain yield (GY) of 25 varieties of winter wheat, (2) the correlations among these traits in different environments, and (3) the effects of different climatic variables and their interactions with wheat genotypes for the examined traits. The field experiments were performed on three experimental sites in Serbia in 2009/10 and 2010/11. The most variable traits were GY and PC, while the variations of OC were lower. A significant positive correlation between wheat bran OC and GY was found in one, while highly significant negative correlations between PC and GY were found in three out of six environments. The partial least square regression (PLSR) triplots for protein content, oil content and grain yield enabled us to identify favorable and limiting climatic conditions for each trait and explained 31.9%, 32.6%, and 30.4% of the total variance, respectively. Cvs. Renesansa and Zvezdana were identified as genotypes with high average values for all traits, while cvs. Bankuty 1205 and Banatka were identified as potential sources of high protein content.

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Section: Genotypic Variationsmentioning

confidence: 74%

Section: Ge Effects On Oc Pc and Gymentioning

confidence: 99%

Biometric Analyses of Yield, Oil and Protein Contents of Wheat (Triticum aestivum L.) Genotypes in Different Environments

et al. 2019

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“…The parameters of adaptability and stability contribute to management adjustments and better recommendation of cultivars. This is observed in species of agricultural interest, such as corn for grain production (Cargnelutti Filho et al, 2007), oat for the content of betaglucan (Crestani et al, 2010) and soybean for oil and protein contents in the seeds (Rodrigues et al, 2014). Table 3.…”

Section: Resultsmentioning

confidence: 94%

Rapeseed population arrangement defined by adaptability and stability parameters

Krüger

Medeiros

Silva

et al. 2016

Rev. bras. eng. agríc. ambient.

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A B S T R A C TThe objective of this study was to identify the plant arrangement that allows greater grain yield with adaptability and stability of rapeseed hybrids. The experiments were conducted in randomized block design with four replicates and the 12 treatments consisted of combination of inter-row spacings (0.20, 0.40, and 0.60 m) and plant densities (20, 40, 60 and 80 plants m -2 ). The hybrids Hyola 432 (early cycle) and Hyola 61 (medium cycle) were cultivated in three growing seasons (2008, 2009 and 2010).

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“…Outros autores também relatam variabilidade do teor de proteína e óleo em soja. Rodrigues et al (2014), em estudo com 49 genótipos, relatam teores de proteína entre 32,07 e 48,57% e, de óleo, entre 14,40 e 24,20%. Quanto à divergência genética, as distâncias genéticas estimadas entre os 29 genótipos do Grupo 1 variaram entre 0,04 e 0,85 e apresentaram média de 0,57.…”

Section: Resultsunclassified

Divergência em QTLs e variância genética para teores de proteína e óleo em soja

Rodrigues

Arruda

Cruz

et al. 2015

Pesq. agropec. bras.

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Resumo -O objetivo deste trabalho foi avaliar a relação entre os parâmetros de divergência em regiões de QTLs e a variância genética em genótipos de soja, quanto aos teores de proteína e óleo nos grãos. Dois grupos de genótipos foram avaliados, em diferentes ambientes, quanto aos teores de proteína e óleo e genotipados com marcadores moleculares de regiões de QTLs. A partir de cada grupo, estabeleceram-se subgrupos por critérios pré-definidos e avaliou-se a relação entre os parâmetros, tendo-se comparado a divergência média e a variância genética entre os subgrupos. Os subgrupos foram definidos com base nos critérios de diferença em divergência média, homogeneidade e heterogeneidade nos subgrupos e proximidade em uma projeção tridimensional da matriz de distância. As percentagens de concordância entre maiores valores de divergência média e de variância genética para o total de subgrupos de cada grupo inicial foram de 72,5 e de 73,4%, respectivamente. Portanto, nestes genótipos, há relação positiva entre as estimativas de divergência em regiões de QTL e variância genética para os teores de proteína e de óleo dos grãos. As distâncias genéticas com base nos marcadores moleculares de regiões de QTLs são eficientes para a predição da variabilidade genética em genótipos de soja para os teores de proteína e de óleo dos grãos.Termos para indexação: Glycine max, distância genética, marcadores moleculares, variabilidade genética. Divergence on QTLs and genetic variance for protein and oil contents in soybeanAbstract -The objective of this work was to evaluate the relationship between the parameters of divergence on QTL regions and the genetic variance in soybean genotypes for protein and oil contents. Two groups of genotypes were evaluated for protein and oil contents in different environments, and genotyped with molecular markers of QTL regions. Subgroups were established by predefined criteria from each group, and the relationship between the parameters was evaluated by comparing mean divergence and genetic variance between the subgroups. The subgroups were defined based on the criteria of difference of mean divergence, homogeneity and heterogeneity in the subgroups, and proximity in a three-dimensional projection of the distance matrix. Percentage agreement between the greater values for mean divergence and genetic divergence for the subgroup total of each initial group was 72.5 and 73.4%, respectively. Therefore, there is a positive relationship between the estimates on QTL regions and genetic variance for protein and oil contents in grains in these genotypes. The genetic distances based on molecular markers of QTL regions are efficient to predict the genetic variability in soybean genotypes, for protein and oil contents.

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Biometric analysis of protein and oil contents of soybean genotypes in different environments

Cited by 17 publications

References 21 publications

Biometric Analyses of Yield, Oil and Protein Contents of Wheat (Triticum aestivum L.) Genotypes in Different Environments

Biometric Analyses of Yield, Oil and Protein Contents of Wheat (Triticum aestivum L.) Genotypes in Different Environments

Rapeseed population arrangement defined by adaptability and stability parameters

Divergência em QTLs e variância genética para teores de proteína e óleo em soja

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