Abstract
A population that consisted of F1 half-sibs and their parents was replicated in field plantings to generate roots to identify AFLP molecular markers and compare statistical models for selection of trait-linked markers using β-carotene content as the grouping variable. Genotypes were grouped into high and low β-carotene classes based on hierarchical cluster analysis. Association parameters between the high and low phenotypic classes of β-carotene and molecular marker profiles were made using logistic regression and discriminant analysis. Logistic regression selected 8 markers less that were associated with β-carotene content compared to discriminant analysis. Further analysis showed that logistic regression achieved 100% correct classification with the 9 markers selected compared to 17 markers that were required by discriminant analysis thus making logistic regression more efficient than discriminant analysis. Logistic regression based on Frequentist hypothesis testing differs from Bayesian based discriminant analysis. This difference may account for the percent correct classification observed.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alwala S, Kimbeng CA, Williams WP, Kang MS (2008) Molecular markers associated with resistance to Aspergillus flavus in maize grain: QTL and discriminant analyses. J New Seeds 9:1–18
Ameny MA, Wilson PW (1997) Relationship between Hunter color and β-carotene content in white-fleshed African sweetpotato. J Sci Food Agric 73:301–306
Anderson P, Kapinga R, Zhang D, Hermann M (2007) Vitamin A for Africa (VITAA): an entry point for promoting orange-fleshed sweetpotato to combat vitamin A-deficiency in sub-Saharan Africa. In: Proceedings of the 13th ISTRC symposium, pp 711–720
Andrade M, Barker I, Cole D, Dapaah H, Elliott H, Fuentes S, Grüneberg W, Kapinga R, Kroschel J, Labarta R, Lemaga B, Loechl C, Low J, Lynam J, Mwanga R, Ortiz O, Oswald A, Thiele G (2009) Unleashing the potential of sweetpotato in sub-Saharan Africa: current challenges and way forward. International Potato Center (CIP), Lima, Peru. Working Paper 2009-1, 197 pp
Arcade A, Anselin F, Faivre Rampant P, Lesage MC, Pâques LE, Prat D (2000) Application of AFLP, RAPD and ISSR markers to genetic mapping of European and Japanese Larch. Theor Appl Genet 100:299–307
Boudreaux JE (1994) Commercial vegetable production recommendations. La. Coop. Ext. Serv. Publ. 2433
Clark CA, Hoy MW (2006) Effects of common viruses on yield and quality of Beauregard sweetpotato in Louisiana. Plant Dis 90:83–88
Du XY, Zhang QL, Zheng-Rong L (2009) Comparison of four molecular markers for genetic analysis in Diospyros L. (Ebenaceae). Plant Syst Evol 281:171–181
Fajardo DS (2000) Genetic diversity in Papua New Guinea sweetpotato [Ipomoea batatas (L.) Poir] germplasm. MSc thesis, Louisiana State University, Baton Rouge
Fernández-Cáceres PL, Martín MJ, Pablos F, Gonzáles AG (2001) Differentiation of tea (Camellia sinensis) varieties and their geographical origin according to their metal content. J Agric Food Chem 49:4775–4779
Fregene M, Bernal A, Duque M, Dixon A, Tohme J (2000) AFLP analysis of African Cassava (Manihot esculenta Crantz) germplasm resistant to the cassava mosaic disease (CMD). Theor Appl Genet 100:678–685
Grüneberg WJ, Manrique K, Zhang D, Hermann M (2005) Genotype X environment interactions for a diverse set of sweetpotato clones evaluated across varying ecogeographic conditions in Peru. Crop Sci 45:2160–2171
Hagenimana V, K’Osambo LM, Carey EE (1998) Potential of sweetpotato in reducing vitamin A deficiency in Africa. CIP Program Report, Lima, Peru, pp 287–294
Hunter PS (1958) Photoelectric color difference meter. J Opt Soc Am 48:485–995
Karyeija RF, Gibson RW, Valkonen JPT (1998) The significance of sweet potato feathery mottle virus in subsistence sweet potato production in Africa. Plant Dis 82:4–15
K’Osambo LM, Carey EE, Misra AK, Wilkes J, Hagenimana V (1998) Influence of age, farming site and boiling on pro-vitamin A content in sweetpotato [Ipomoea batatas (L.) Lam.] storage roots. J Food Compos Anal 11:305–321
LaBonte DR, Buteler MI, Villordon AQ (1997) Molecular markers in sweetpotato. In: La Bonte DR, Yamashita M, Mochida H (eds) Proceedings of international workshop on sweetpotato production systems towards the 21st century, Miyakonojo, Miyazaki, Japan, pp 181–191
LaBonte DR, Picha DH, Johnson HA (2000) Carbohydrate-related changes in sweetpotato storage roots during development. J Am Soc Hortic Sci 125:200–204
Low J, Kinyae P, Gichuki S, Oyunga MA, Hagenimana V, Kabira J (1997) Combating vitamin A deficiency through the use of sweetpotato. Results from phase I of an action research project in South Nyanza, Kenya. International Potato Center, Lima, 110 pp
Mcharo TM (2005) Associating molecular markers with phenotypes in sweetpotatoes and liriopogons using multivariate statistical modeling. PhD dissertation (ETD-03142005-155707), Louisiana State University, Baton Rouge
Mcharo M, LaBonte DR, Oard JH, Kays SJ, McLaurin WJ (2004) Linking quantitative traits with AFLP markers in sweetpotatoes using discriminant analysis. Acta Hortic 637:285–293
Mcharo M, Labonte DR, Clark C, Hoy M, Oard J (2005) Molecular marker variability for southern root-knot nematode resistance in sweetpotato. Euphytica 144:125–132
Miano D, LaBonte DR, Clark CA (2008) Identification of molecular markers associated with sweetpotato resistance to sweetpotato virus disease in Kenya. Euphytica 160:15–24
Mwanga ROM, Kreigner A, Cervantes-Flores JC, Zhang DP, Moyer JW, Yencho GC (2002) Resistance to sweetpotato chlorotic stunt virus and sweetpotato mottle virus is mediated by two separate recessive genes in sweetpotato. J Am Soc Hortic Sci 127:798–806
Mwanga ROM, Odongo B, Niringiye C, Alajo A, Abidin PE, Kapinga R, Tumwegamire S, Lemaga B, Nsumba J, Carey EE (2007) Release of two orange-fleshed sweetpotato cultivars, ‘SPK004’ (‘Kakamega’) and ‘Ejumula’, in Uganda. HortScience 42(7):1728–1730
Pohar M, Mateja B, Turk S (2004) Comparison of logistic regression and linear discriminant analysis: a simulation study. Metodološki zvezki 1:143–161
Rohlf FJ (1993) NTSYS-pc numerical taxonomy and multivariate analysis system. Version 1.8. Exeter Publications, Setauket
SAS Institute Inc (1999) SAS/STAT user’s guide. SAS Institute Inc., Cary
SAS Institute Inc (2002) The SAS system for windows v9.1. SAS Institute Inc., Cary
Sneath PHA, Sokal RR (1973) Numerical taxonomy. The principles and practice of numerical classification. W.H. Freeman, San Francisco
Takahata Y, Noda T, Nagata T (1993) HPLC determination of β-carotene of sweetpotato cultivars and its relationship with color values. Jpn J Breed 43:421–427
Uen Y, Lin S, Wu D, Su Y, Wu J, Cheng T, Chi C, Wang J (2007) Prognostic significance of multiple molecular markers for patients with stage II colorectal cancer undergoing curative resection. Ann Surg 246:1040–1046
Zhang N, Xu Y, Akash M, McCouch S, Oard JH (2005) Identification of candidate markers associated with agronomic traits in rice using discriminant analysis. Theor Appl Genet 110:721–729
Acknowledgements
This research was supported by funds from The McKnight Foundation Collaborative Crop Research Program, state and matching funds allocated to the Louisiana State University AgCenter. Dr. Peter Ojiambo of North Carolina State University, Raleigh, is greatly acknowledged for facilitating SAS data analysis.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mcharo, M., LaBonte, D.R. Multivariate selection of AFLP markers associated with β-carotene in sweetpotatoes. Euphytica 175, 123–132 (2010). https://doi.org/10.1007/s10681-010-0193-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10681-010-0193-0