Correlations between characters and path analysis in sweet sorghum (Sorghum bicolor (L.) Moench) genotypes for juice production

Sweet sorghum presents stems with juice similar to that of sugar cane, rich in fermentable sugars, that may be used in off-season for sugar and ethanol production optimizing the sugar-ethanol sector. The objective of this work was to determine genetic correlations between characters and perform path analysis between juice volume and its components. Twenty-five sweet sorghum genotypes were evaluated in randomized blocks design with three repetitions and studied variables were: number of days to flowering; plant height; number of stems; weight of green mass; weight of dry mass; number of leaves; diameter of stems; volume of extracted juice and percentage of total soluble solids. In order to verify the existence of variability among the genotypes, data were subjected to variance analysis by F-test. Subsequently, genetic parameters were determined, as soon as genetic correlation estimator?s method, performed by t-test, to determine phenotypic correlation and bootstrap method for determining environmental and genetics correlation coefficient. Before performing path analysis a multicollinearity diagnosis was also conducted. The results of genetic correlation and path analysis point weight of green mass as the main variable influencing the juice volume, allowing these characters in indirect selection for increasing juice volume.

[1]  Cosme Damião Cruz,et al.  GENES - a software package for analysis in experimental statistics and quantitative genetics - doi: 10.4025/actasciagron.v35i3.21251 , 2013 .

[2]  Gustavo Henrique Gravatim Costa,et al.  Technological quality of sweet sorghum processed without panicles for ethanol production , 2016 .

[3]  Antonio Costa de Oliveira,et al.  Estimativas de correlações genotípicas e de ambiente em gerações com elevada freqüência de heterozigotos , 2005 .

[4]  E. E. Cunha,et al.  Caracterização de genótipos e estimativa de parâmetros genéticos de características produtivas de sorgo forrageiro , 2010 .

[5]  F. Mekbib,et al.  Estimation of genetic variability, heritability, and genetic advance in advanced lines for grain yield and yield components of sorghum [Sorghum bicolor (L.) Moench] at Humera, Western Tigray, Ethiopia , 2020 .

[6]  V. Sridhar,et al.  Studies on Genetic Variability, Correlation and Path Analysis in Yellow Pericarp Sorghum [Sorghum bicolor (L.) Moench] Genotypes , 2019 .

[7]  T. Mengiste,et al.  Identification of sorghum grain mold resistance loci through genome wide association mapping , 2019, Journal of Cereal Science.

[8]  C. D. Cruz,et al.  Utilização de bootstrap não-paramétrico para avaliação de correlações fenotípicas, genotípicas e ambientais - DOI: 10.4025/actasciagron.v30i5.5966 , 2008 .

[9]  C. Barcelos,et al.  Sweet sorghum as a whole-crop feedstock for ethanol production , 2016 .

[10]  G. V. Miranda,et al.  CORRELAÇÃO DE CARACTERES DE UMA POPULAÇÃO CRIOULA DE MILHO PARA SISTEMA TRADICIONAL DE CULTIVO , 2008 .

[11]  S. Sinha,et al.  Understanding Genetic Diversity of Sorghum Using Quantitative Traits , 2016, Scientifica.

[12]  A. T. Bruzi,et al.  Association among agro-industrial traits and simultaneous selection in sweet sorghum. , 2017, Genetics and molecular research : GMR.

[13]  F. Silva,et al.  Análise de trilha para os componentes de produção de cana-de-açúcar via blup , 2009 .

[14]  G. V. Miranda,et al.  Associações da produtividade com outras características agronômicas de café ( Coffea arábica L. “Catimor”) , 2008 .

[15]  R. Vencovsky,et al.  Correlações e análise de trilha de caracteres tecnológicos e a produtividade de fibra de algodão , 2007 .

[16]  D. A. Kenny,et al.  Correlation and Causation. , 1982 .

[17]  C. G. P. Carvalho,et al.  Correlações e análise de trilha em linhagens de soja semeadas em diferentes épocas , 2002 .

[18]  Breno Luciano de Araújo,et al.  Parâmetros genéticos em cultivares de sorgo granífero avaliados em safrinha , 2014 .

[19]  A. M. Junior,et al.  Análise de trilha dos componentes do rendimento de grãos em genótipos de canola , 2004 .

[20]  M. S. Oliveira,et al.  Correlações genéticas e análise de trilha para componentes da produção de frutos de açaizeiro , 2012 .

[21]  Ana Paula Oliveira Nogueira,et al.  Análise de trilha e correlações entre caracteres em soja cultivada em duas épocas de semeadura = Path analysis and correlations among traits in soybean grown in two dates sowing , 2012 .

[22]  Juliano Garcia Bertoldo,et al.  Correlação fenotípica entre componentes do rendimento de grãos de feijão comum (Phaseolus vulgaris L.) Phenotypic correlation between yield components of common bean (Phaseolus vulgaris L.) , 2011 .

[23]  L. P. M. Pires,et al.  Plants population and harvesting times influence in saccharine sorghum BRS 506 production , 2018 .

[24]  A. D. Lúcio,et al.  Análise de trilha entre as variáveis das análises de sementes de espécies florestais exóticas do Rio Grande do Sul , 2006 .

[25]  F. Tardin,et al.  Genetic divergence in biomass sorghum genotypes through agronomic and physical-chemical characters , 2020 .

[26]  M. Resende,et al.  Early selection in sugarcane family trials via BLUP and BLUPIS procedures - doi: 10.4025/actasciagron.v35i4.16430 , 2013 .

[27]  P. S. V. Filho,et al.  Divergência genética em germoplasma de feijoeiro comum coletado no estado do Paraná, Brasil , 2006 .

[28]  M. G. Pereira,et al.  Correlations between agronomic traits and path analysis for silage production in maize hybrids , 2018, Bragantia.

[29]  K. Tesfaye Genetic diversity study of sorghum (Sorghum bicolor (L.) Moenc) genotypes, Ethiopia , 2017 .

[30]  B. W. Zago,et al.  Correlation and path analysis of biomass sorghum production. , 2016, Genetics and molecular research : GMR.

[31]  M. Laing,et al.  Genetic variability, heritability and genetic gain for quantitative traits in South African sorghum genotypes , 2019, Australian Journal of Crop Science.

[32]  S. Rios,et al.  Análise de trilha para carotenoides em milho , 2012 .