Linear relationships between root and above-ground traits in common bean segregant generations




path analysis, correlation, selection gains, plant breeding


The correlation estimation and its partition into cause and effect is seen as a valuable tool in obtaining gains from selection in plant breeding. This allows the anticipation of choosing the best genotypes. Thus, the objective of this study was to consider indirect selection for simultaneous improvement of root and above-ground traits in segregating common bean populations. The experiment was carried out in the 2021/22 season, considering six common bean genotypes, two parents and four segregating generations (F2, F3, F4 and F5), under a lattice design. Root system traits were measured by two phenotyping methods, called Shovelomics and WinRHIZO. The aerial part traits evaluated were chlorophyll content, plant height, stem diameter, first pod height insertion and yield components (number of pods, number of grains and weight of grains per plant). Correlation analysis and cause and effect analysis (path analysis) were performed. Significant correlation estimates (τ) were found between root and aerial traits, with emphasis on chlorophyll B content with left horizontal length (τ = -0.22) and chlorophyll A content with total root length (τ = 0.24). The unfolding of these estimates by path analysis indicated that the chlorophyll A content has a correlation and a high direct effect on the total length of roots and that the total chlorophyll content indirectly influences the left and right horizontal root lengths. This fact makes it possible to obtain gains with the selection of improved common bean plants for root system based on the direct and indirect evaluation of chlorophyll contents, easily measured in the aerial part of the plants. This allows the optimization of time and resources in breeding programs, aiming at obtaining agronomically superior plants.


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Author Biographies

Paulo Henrique Cerutti, Universidade do Estado de Santa Catarina, Lages, SC, Brasil.

Departamento de Agronomia.

Luan Tiago dos Santos Carbonari, Universidade do Estado de Santa Catarina, Lages, SC, Brasil.


Carlos Zacarias Joaquim Junior, Universidade do Estado de Santa Catarina, Lages, SC, Brasil.


Altamir Frederico Guidolin, Universidade do Estado de Santa Catarina, Lages, SC, Brasil.


Jefferson Luís Meirelles Coimbra, Universidade do Estado de Santa Catarina, Lages, SC, Brasil.



APPIAH-KUBI D et al. 2022. Heat Stress Tolerance: A Prerequisite for the Selection of Drought- and Low Phosphorus-Tolerant Common Beans for Equatorial Tropical Regions Such as Ghana. Plants 11: 1-16.

BARILI LD et al. 2011. Correlação fenotípica entre componentes do rendimento de grãos de feijão comum (Phaseolus vulgaris L.). Semina:Ciencias Agrarias 32: 1263-1274.

BEEBE SE et al. 2013. Phenotyping common beans for adaptation to drought. Frontiers in Physiology 4: 1-20.

BISATO M et al. 2021. Early performance of common bean cultivars submitted to different sowing depths. Revista de Ciencias Agroveterinarias 20: 118 -127.

BULYABA R et al. 2020. Genotype by location effects on yield and seed nutrient composition of common bean. Agronomy 10: 1-16.

BURRIDGE JD et al. 2020. Comparative phenomics of annual grain legume root architecture. Crop Science 60: 2574 - 2593.

CARVALHO IF et al. 2004. Estimativas e implicações da correlação no melhoramento vegetal. Pelotas: UFPel. 142p.

CQFS-RS/SC. 2016. Manual de adubação e de calagem para os estados do Rio Grande do Sul e Santa Catarina. Núcleo Regional Sul: Comissão de química e fertilidade do solo. 376p.

CRUZ CD. 2013. GENES - A software package for analysis in experimental statistics and quantitative genetics. Acta Scientiarum 35: 271-276.

CRUZ CD et al. 2012. Modelos biométricos aplicados ao melhoramento genético. Viçosa: UFV. 512p.

DA ROCHA F et al. 2014. Análise dialélica como ferramenta na seleção de genitores em feijão. Revista Ciência Agronômica 45: 74 - 81.

DIANATMANESH M et al. 2022. Yield and yield components of common bean as influenced by wheat residue and nitrogen rates under water deficit conditions. Environmental Technology and Innovation 28: 102549.

EMBRAPA. 2018. Empresa Brasileira de Pesquisa Agropecuária. Sistema brasileiro de classificação de solos. 5.ed. Brasília: Embrapa. 355p.

FANCELLI AL & NETO DD. 2007. Produção de feijão. Piracicaba: Esalq. 224p.

GEPTS P & FERNÁNDEZ F. 1982. Etapas de desarollo de la planta de frijol comum (Phaseolus vulgaris L.). Cali: CIAT.

GOLTSEV V et al. 2012. Drought-induced modifications of photosynthetic electron transport in intact leaves: Analysis and use of neural networks as a tool for a rapid non-invasive estimation. Biochimica et Biophysica Acta - Bioenergetics 1817: 1490-1498.

GOMEZ KA & GOMEZ AA. 1985. Statistical procedures for agricultural research. Philippines: International Rice Research Institute. 690p.

KARAVIDAS I et al. 2022. Agronomic Practices to Increase the Yield and Quality of Common Bean (Phaseolus vulgaris L.): A Systematic Review. Agronomy 12: 2.

KOWALSKI CJ. 1972. On the effects of non-normality on the distribution of the sample product-moment correlation coefficient. Journal of the Royal Statistical Society 21: 1-12.

MARSHALL AH et al. 2016. A new emphasis on root traits for perennial grass and legume varieties with environmental and ecological benefits. Food and Energy Security 5: 26 - 39.

MUKANKUSI C et al. 2019. Genomics, genetics and breeding of common bean in Africa: A review of tropical legume project. Plant Breeding 138: 401- 414.

NOGUEIRA APO et al. 2012. Análise de trilha e correlações entre caracteres em soja cultivada em duas épocas de semeadura. Bioscience Journal 28: 877-888.

PEREIRA FB et al. 2013. Relação entre os caracteres determinantes das eficiências no uso de nitrogênio e fósforo em milho. Revista Ceres 60: 636-645.

PORNARO C et al. 2017. WinRHIZO technology for measuring morphological traits of bermudagrass stolons. Agronomy Journal 109: 3007-3010.

ROCHA JR et al. 2019. Selection of superior inbred progenies toward the common bean ideotype. Agronomy Journal 111: 1181-1189.

SÁNCHEZ-REINOSO AD et al. 2019. Drought-tolerant common bush bean physiological parameters as indicators to identify susceptibility. Hort Science 54: 2091-2098.

SCHNEIDER HM et al. 2020. Should Root Plasticity Be a Crop Breeding Target? Frontiers in Plant Science 11: 1-16.

SPARKS AH. 2018. Nasapower: a NASA POWER global meteorology, surface solar energy and climatology data client for R. Journal of Open Source Software 3: 1-3.

STROCK CF et al. 2019. Field Crops Research Seedling root architecture and its relationship with seed yield across diverse environments in Phaseolus vulgaris. Field Crops Research 237: 53-64.

SUÁREZ JC et al. 2021. Influence of nitrogen supply on gas exchange, chlorophyll fluorescence and grain yield of breeding lines of common bean evaluated in the Amazon region of Colombia. Acta Physiologiae Plantarum 43: 1-15.

TRACHSEL S et al. 2011. Shovelomics: High throughput phenotyping of maize (Zea mays L.) root architecture in the field. Plant and Soil 341: 75-87.

VELHO LPS et al. 2017. Phenotypic correlation and direct and indirect effects of aerial part components with root distribution of common bean. Pesquisa Agropecuaria Brasileira 52: 5.

VENCOVISKY R & BARRIGA P. 1992. Genética biométrica no fitomelhoramento. Ribeirão Preto: SBG. 496p.

ZANDALINAS SI et al. 2018. Plant adaptations to the combination of drought and high temperatures. Physiologia Plantarum 162: 2-12.



How to Cite

CERUTTI, Paulo Henrique; CARBONARI, Luan Tiago dos Santos; JUNIOR, Carlos Zacarias Joaquim; GUIDOLIN, Altamir Frederico; COIMBRA, Jefferson Luís Meirelles. Linear relationships between root and above-ground traits in common bean segregant generations. Revista de Ciências Agroveterinárias, Lages, v. 23, n. 1, p. 43–52, 2024. DOI: 10.5965/223811712312024043. Disponível em: Acesso em: 13 jun. 2024.



Research Article - Science of Plants and Derived Products

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