Abstract
Papaya is one of the most important fruit crops worldwide and its production depends on the availability of varieties that meet the consumer market demands. This study aimed to evaluate papaya inbred lines and select the best lines for fruit quality. A population of 97 lines of F5 generation, that was conducted via Single Seed Descent method from the F2 generation and derived from the crossing between Sekati and JS-12 genotypes of the heterotic group Formosa, were evaluated for nine morphoagronomic traits related to fruit quality. The data set was submitted to GT biplot and Pearson’s correlation analyzes using the R software. According to the results, the lines 96, 61, 39, 1 and 88 were indicated as favorable allele sources for the traits of average fruit weight, pulp volume, fruit firmness, pulp yield, and soluble solids, respectively. Lines 107, 19, 61 and 63 were indicated as ideotypes for per se use. Effectively, the application of the multivariate graphical approach GT biplot provides a practical and efficient new way to identify superior genotypes in papaya breeding programs.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ahmad A, Ali ZM, Zainal Z (2013) Delayed softening of papaya (Carica papaya L. cv. Sekaki) fruit by 1-methylcyclopropene (1-MCP) during ripening at ambient and low temperature storage conditions. Aust J Crop Sci 7:750–757
Barragán-Iglesias J, Méndez-Lagunas LL, Rodríguez-Ramírez J (2018) Ripeness indexes and physicochemical changes of papaya (Carica papaya L. cv. Maradol) during ripening on-tree. Sci Hortic (amsterdam) 236:272–278. https://doi.org/10.1016/j.scienta.2017.12.012
Bhosale AA, Sundaram KK (2015) Nondestructive method for ripening prediction of papaya. Procedia Technol 19:623–630. https://doi.org/10.1016/J.PROTCY.2015.02.088
Borém A, Miranda GV, Fritsche-Neto R (2017) Melhoramento de Plantas, 7a Edição. Editora UFV
Bueraheng N, Promma S, Eksomtramage T (2017) Biplot analysis of agronomic and yield trait relations in Tenera oil palm (Elaeis guineensis Jacq.). J Sci Technol 39:709–714
Cardoso DL, Vivas M, Pinto FO et al (2017) Diallel mixed-model analysis of papaya fruit deformities. Ciência Rural 47:1–4. https://doi.org/10.1590/0103-8478cr20151553
Cortes DFM, Santa-Catarina R, Azevedo AON et al (2018) Papaya recombinant inbred lines selection by image-based phenotyping. Sci Agric 75:208–215. https://doi.org/10.1590/1678-992X-2016-0482
Cruz CD (2013) GENES - a software package for analysis in experimental statistics and quantitative genetics. Acta Sci 35:271–276. https://doi.org/10.4025/actasciagron.v35i3.21251
de Barros FLS, Kuhlcamp KT, Arantes SD, Moreira SO (2017) Productivity and quality of Formosa and Solo papaya over two harvest seasons. Pesqui Agropecu Bras 52:599–606. https://doi.org/10.1590/S0100-204X2017000800005
dos Santos A, do Amaral Júnior AT, do Kurosawa R NF et al (2017) GGE biplot projection in discriminating the efficiency of popcorn lines to use nitrogen. Ciência e Agrotecnologia 41:22–31. https://doi.org/10.1590/1413-70542017411030816
Dehghani H, Omidi H, Sabaghnia N (2008) Graphic analysis of trait relations of rapeseed using the biplot method. Agron J 100:1443–1449. https://doi.org/10.2134/agronj2007.0275
Dehghani H, Dvorak J, Sabaghnia N (2012) Biplot analysis of salinity related traits in beard wheat (Triticum aestivum L.). Ann Biol Res 3:3723–3731
de Oliveira TRA, de A Gravina G, de Oliveira GHF et al (2018a) The GT biplot analysis of green bean traits. Ciência Rural 48:e20170757. https://doi.org/10.1590/0103-8478cr20170757
de Oliveira TRA, de A Gravina G, de Oliveira GHF et al (2018b) Multivariate analysis used as a tool to select snap bean (Phaseolus vulgaris L.) genotypes. Aust J Crop Sci 12:67–73. https://doi.org/10.2147/ajcs.18.12.01.pne661
de Oliveira TRA, Gravina GA, da Cruz DP et al (2019) The performance of bean pod lineage inoculated with Gluconacetobacter diazotrophicus PAL5. Sci Hortic (amsterdam) 249:65–70. https://doi.org/10.1016/j.scienta.2019.01.044
Dias NLP, de Oliveira EJ, Dantas JLL (2011) Avaliação de genótipos de mamoeiro com uso de descritores agronômicos e estimação de parâmetros genéticos. Evaluation of papaya genotypes using agronomic descriptors and estimation of genetic parameters. Pesq Agropec Bras 46:1471–1479. https://doi.org/10.1590/S0100-204X2011001100008
FAO (2016) Food and Agriculture Organization of the United Nations. http://faostat.fao.org.in. Accessed 10 Aug 2019
Gabriel KR (1971) The biplot graphic display of matrices with application to principal component analysis. Biometrika 58:453–467
Hongyu K, Sandanielo VLM, de Oliveira Junior GJ (2015a) Análise de Componentes Principais: resumo teórico, aplicação e interpretação. EE&S Eng Sci 1:83–90. https://doi.org/10.18607/ES20165053
Hongyu K, de L Silva F, de L Oliveira ACS et al (2015b) Comparação entre os modelos Ammi e GGe biplot para os dados de ensaios multi-ambientais. Rev Bras Biom 33:139–155
Kaplan M, Arslan M, Kale H, Kokten K (2017) GT biplot analysis for silage potential, nutritive value, gas and methane production of stay-green grain sorghum shoots. Cienc e Investig Agrar 44:230–238. https://doi.org/10.7764/rcia.v44i3.1802
Khadivi-Khub A, Sarooghi F, Abbasi F (2016) Phenotypic variation of Prunus scoparia germplasm: implications for breeding. Sci Hortic (amsterdam) 207:193–202. https://doi.org/10.1016/j.scienta.2016.05.023
Koc AB (2007) Determination of watermelon volume using ellipsoid approximation and image processing. Postharvest Biol Technol 45:366–371. https://doi.org/10.1016/J.POSTHARVBIO.2007.03.010
Maia MCC, de Araújo LB, dos S Dias CT et al (2016) Selection of mango rosa genotypes in a breeding population using the multivariate-biplot method. Ciência Rural 46:1689–1694. https://doi.org/10.1590/0103-8478cr20130722
Mohammadi R, Amri A (2011) Graphic analysis of trait relations and genotype evaluation in durum wheat. J Crop Improv 25:680–696. https://doi.org/10.1080/15427528.2011.601437
Nguyen TTT, Shaw PN, Parat MO, Hewavitharana AK (2013) Anticancer activity of Carica papaya: A review. Mol Nutr Food Res 57:153–164. https://doi.org/10.1002/mnfr.201200388
Odewale JO, Collins A, Ataga CD et al (2014) Genotype by trait relations between yield and some morphological traits of coconut (Cocos nucifera L.) hybrid varieties based on GT biplot. Int J Plant Soil Sci 3:270–280. https://doi.org/10.9734/IJPSS/2014/7083
de Oliveira JG, Vitória AP (2011) Papaya: nutritional and pharmacological characterization, and quality loss due to physiological disorders. An overview. Food Res Int 44:1306–1313. https://doi.org/10.1016/j.foodres.2010.12.035
Ovando-Martinez M, López-Teros VM, Tortoledo-Ortiz O et al (2018) Effect of ripening on physico-chemical properties and bioactive compounds in papaya pulp, skin and seeds. Indian J Nat Prod Resour 9:47–59
Paramesh M, Reddy DM, Priya MS et al (2016) GT biplot analysis for yield and drought related traits in mung bean (Vigna radiata L. Wilczek). Eletron J Plant Breed 7:538–543. https://doi.org/10.5958/0975-928X.2016.00069.7
Rasmusson DC (1987) An evaluation of ideotype breeding. Crop Sci 27:1140–1146
Reis RC, de S Viana E, de Jesus JL et al (2015) Caracterização físico-química de frutos de novos híbridos e linhagens de mamoeiro. Pesqui Agropecu Bras 50:210–217. https://doi.org/10.1590/S0100-204X2015000300004
Sabaghnia N, Janmohammadi M (2014) Graphic analysis of nano-silicon by salinity stress interaction on germination properties of lentil using the biplot method summary. Agric for 60:29–40. https://doi.org/10.1192/bjp.205.1.76a
Sabaghnia N, Janmohammadi M (2016) Biplot analysis of silicon dioxide on early growth of sunflower. Plant Breed Seed Sci 73:87–98. https://doi.org/10.1515/plass-2016-0008
Santa-Catarina R, Fernando D, Cortes M et al (2018) Image-based phenotyping of morpho-agronomic traits in papaya fruits (Carica papaya L. THB var.). Aust J Crop Sci 12:1750–1756. https://doi.org/10.21475/ajcs.18.12.11.p1437
Sharifi P, Ebadi AA (2018) Relationships of rice yield and quality based on genotype by trait (GT) biplot. An Acad Bras Cienc 90:343–356. https://doi.org/10.1590/0001-3765201820150852
Siddiqui MW (2018) Preharvest modulation of postharvest fruit and vegetable quality. Elsevier Science
Sousa MBE, Damasceno-Silva KJ, de Rocha M M et al (2018) Genotype by environment intraction in Cowpea lines using GGE biplot method. Rev Caatinga 31:64–71. https://doi.org/10.1590/1983-21252018v31n108rc
Souza JMA, Ataíde EM, Silva MDS (2014) Qualidade pós-colheita e correlação entre características físicas e químicas de frutos de mamoeiro comercializados em Serra Talhada—PE. Magistra 26:554–560
Team RDC (2018) R: a language and environment for statistical computing
Trevisan MJ, Jacomino AP, Cunha Junior LC, Alves RF (2013) Aplicação de 1-metilciclopropeno associado ao etileno para minimizar seus efeitos na inibição do amadurecimento do mamão “golden.” Rev Bras Frutic 35:384–390. https://doi.org/10.1590/S0100-29452013000200007
Vettorazzi JCF, Santa-catarina R, Pastana T et al (2021) Combining ability of recombined F4 papaya lines: a strategy to select hybrid combination. Sci Agric 78. https://doi.org/10.1590/1678-992X-2019-0191
Wall MM (2006) Ascorbic acid, vitamin A, and mineral composition of banana (Musa sp.) and papaya (Carica papaya) cultivars grown in Hawaii. J Food Compos Anal 19:434–445. https://doi.org/10.1016/j.jfca.2006.01.002
Wilker J, Navabi A, Rajcan I et al (2019) Agronomic performance and nitrogen fixation of heirloom and conventional dry bean varieties under low-nitrogen field conditions. Front Plant Sci 10:1–21. https://doi.org/10.3389/fpls.2019.00952
Yan W (2014) Crop variety trials: data management and analysis, pp 1–30
Yan W, Frégeau-Reid J (2018) Genotype by Yield∗Trait (GYT) biplot: a novel approach for genotype selection based on multiple traits. Sci Rep 8:1–10. https://doi.org/10.1038/s41598-018-26688-8
Yan W, Holland JB (2010) A heritability-adjusted GGE biplot for test environment evaluation. Euphytica 171:355–369. https://doi.org/10.1007/s10681-009-0030-5
Yan W, Rajcan I (2002) Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Sci 42:11–20. https://doi.org/10.2135/cropsci2002.0011
Yan W, Kang MS, Ma B et al (2007) GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Sci 47:641–653. https://doi.org/10.2135/cropsci2006.06.0374
Yang RC, Crossa J, Cornelius PL, Burgueño J (2009) Biplot analysis of genotype × environment interaction: proceed with caution. Crop Sci 49:1564–1576. https://doi.org/10.2135/cropsci2008.11.0665
Funding
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001.
Author information
Authors and Affiliations
Contributions
All authors contributed equally to the conceptualization, methodology and writing of the manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Santana, J.G.S., Ramos, H.C.C., Miranda, D.P. et al. Genotype analysis by trait is a practical and efficient approach on discrimination of inbred lines and identification of papaya (Carica papaya L.) ideotypes for fruit quality. Euphytica 217, 129 (2021). https://doi.org/10.1007/s10681-021-02850-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10681-021-02850-8