Genetic evaluation of micronutrient traits in diploid potato from a base population of Andean Landrace Cultivars

Crop Science

Volumn 54, Issue 5, 2014, Pages 1949-1959

  Paget, Mark ^a   Amoros, Walter ^b   Salas, Elisa ^b   Eyzaguirre, Raul ^b   Alspach, Peter ^a   Apiolaza, Luis ^c   Noble, Alasdair ^a   Bonierbale, Merideth ^b  

^a THE NEW ZEALAND INSTITUTE FOR PLANT AND FOOD RESEARCH LIMITED   (New Zealand)

^b INTERNATIONAL POTATO CENTER   (Peru)

^c UNIVERSITY OF CANTERBURY   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84906492480     PISSN: 0011183X     EISSN: 14350653     Source Type: Journal    
DOI: 10.2135/cropsci2013.12.0809     Document Type: Article

References (55)

1. Andre, C.M., M. Ghislain, P. Bertin, M. Oufir, M.d. Rosario Herrera, L. Hoffmann, J.F. Hausman, Y. Larondelle, and D. Evers. 2007. Andean potato cultivars (Solanum tuberosum L.) as a source of antioxidant and mineral micronutrients. J. Agric. Food Chem. 55:366-378. doi:10.1021/jf062740i
2. Apiolaza, L.A., S.S. Chauhan, and J.C.F. Walker. 2011. Genetic control of very early compression and opposite wood in Pinus radiata and its implications for selection. Tree Genet. Genomes 7:563-571. doi:10.1007/s11295-010-0356-0
3. Bernardo, R. 2002. Breeding for quantitative traits in plants. Stemma Press, Woodbury, M.N.
4. Blasco, A. 2001. The Bayesian controversy in animal breeding. J. Anim. Sci. 79:2023-2046.
5. Bonierbale, M., W. Amoros, G. Burgos, E. Salas, and H. Juarez. 2007. Prospects for enhancing the nutritional value of potato by plant breeding. African Potato Conference Proceedings, Egypt. p. 26-46.
6. Bouis, H.E., and R.M. Welch. 2010. Biofortification: A sustainable agricultural strategy for reducing micronutrient malnutrition in the global South. Crop Sci. 50:S20-S32. doi:10.2135/cropsci2009.09.0531
7. Brown, C.R., K.G. Haynes, M. Moore, M.J. Pavek, D.C. Hane, S.L. Love, R.G. Novy, and J.C. Miller. 2010. Stability and broad-sense heritability of mineral content in potato. Iron. Am. J. Potato Res. 87:390-396. doi:10.1007/s12230-010-9145-4
8. Brown, C.R., K.G. Haynes, M. Moore, M.J. Pavek, D.C. Hane, S.L. Love, R.G. Novy, and J.C. Miller. 2011. Stability and broad-sense heritability of mineral content in potato. Zinc. Am. J. Potato Res. 88:238-244. doi:10.1007/s12230-011-9188-1
9. Brown, C.R., K.G. Haynes, M. Moore, M.J. Pavek, D.C. Hane, S.L. Love, R.G. Novy, and J.C. Miller, Jr. 2012. Stability and broad-sense heritability of mineral content in potato: Calcium and magnesium. Am. J. Potato Res. 89:255-261. doi:10.1007/s12230-012-9240-9
10. Burgos, G., W. Amoros, M. Morote, J. Stangoulis, and M. Bonierbale. 2007. Iron and zinc concentration of native Andean potato cultivars from a human nutrition perspective. J. Sci. Food Agric. 87:668-675 10.1002/jsfa.2765. doi:10.1002/jsfa.2765
11. Butler, D.G., B.R. Cullis, A.R. Gilmour, and B.J. Gogel. 2009. ASReml-R reference manual. v. 3. Queensland Department of Primary Industries & Fisheries, Brisbane, QLD, Australia.
12. Cakmak, I. 2008. Enrichment of cereal grains with zinc: Agronomic or genetic biofortification? Plant Soil 302:1-17. doi:10.1007/s11104-007-9466-3
13. Egoville, M.J., J.F. Sullivan, M.F. Kozempel, and W.J. Jones. 1988. Ascorbic acid determination in processed potatoes. Am. Potato J. 65:91-97. doi:10.1007/BF02867457
14. Falconer, D.S., and T.F.C. Mackay. 1996. Introduction to quantitative genetics. Longman Group Limited, Harlow, U.K.
15. Gelman, A. 2006. Prior distributions for variance parameters in hierarchical models. Bayesian Anal. 1:515-533. doi:10.1214/06-BA117A
16. Gilmour, A.R., B.R. Cullis, A.P. Verbyla, and A.C. Gleeson. 1997. Accounting for natural and extraneous variation in the analysis of field experiments. J. Agric. Biol. Environ. Stat. 2:269-293. doi:10.2307/1400446
17. Gonçalves-Vidigal, M.C., F. Mora, T.S. Bignotto, R.E.F. Munhoz, and L.D. de Souza. 2008. Heritability of quantitative traits in segregating common bean families using a Bayesian approach. Euphytica 164:551-560. doi:10.1007/s10681-008-9758-6
18. Graham, R., D. Senadhira, S. Beebe, C. Iglesias, and I. Monasterio. 1999. Breeding for micronutrient density in edible portions of staple food crops: Conventional approaches. Field Crops Res. 60:57-80. doi:10.1016/S0378-4290(98)00133-6
19. Gregorio, G.B. 2002. Progress in breeding for trace minerals in staple crops. J. Nutr. 132:500S-502S.
20. Hadfield, J.D. 2010. MCMC methods for multi-response generalized linear mixed models: The MCMCglmm R package. J. Stat. Softw. 33:1-22.
21. Haynes, K.G., G.C. Yencho, M.E. Clough, M.R. Henninger, and S.B. Sterrett. 2012. Genetic variation for potato tuber micronutrient content and implications for biofortification of potatoes to reduce micronutrient malnutrition. Am. J. Potato Res. 89:192-198. doi:10.1007/s12230-012-9242-7
22. Henderson, C.R. 1976. A simple method for computing the inverse of a numerator relationship matrix used in the prediction of breeding values. Biometrics 32:69-83. doi:10.2307/2529339
23. Hirschi, K.D. 2009. Nutrient biofortification of food crops. Annu. Rev. Nutr. 29:401-421. doi:10.1146/annurev-nutr-080508-141143
24. Horton, S., H. Alderman, and J.A. Rivera. 2009. Hunger and malnutrition. In: B. Lomborg, editor, Global crises, global solutions. Cambridge Univ. Press, New York.
25. Kutman, U.B., B. Yildiz, and I. Cakmak. 2011. Effect of nitrogen on uptake, remobilization and partitioning of zinc and iron throughout the development of durum wheat. Plant Soil 342:149-164. doi:10.1007/s11104-010-0679-5
26. Lunn, D.J., A. Thomas, N. Best, and D. Spiegelhalter. 2000. WinBUGS-A Bayesian modelling framework: Concepts, structure, and extensibility. Stat. Comput. 10:325-337. doi:10.1023/A:1008929526011
27. Lynch, M., and B. Walsh. 1998. Genetics and analysis of quantitative traits. Sinauer Assoc., Sunderland, M.A.
28. Nestel, P., H.E. Bouis, J.V. Meenakshi, and W. Pfeiffer. 2006. Biofortification of staple food crops. J. Nutr. 136:1064-1067.
29. Oakey, H., A.P. Verbyla, B.R. Cullis, X.M. Wei, and W.S. Pitchford. 2007. Joint modeling of additive and non-additive (genetic line) effects in multi-environment trials. Theor. Appl. Genet. 114:1319-1332. doi:10.1007/s00122-007-0515-3
30. Ortiz, R., S.J. Peloquin, R. Freyre, and M. Iwanaga. 1991. Efficiency of potato breeding using FDR 2n gametes for multitrait selection and progeny testing. Theor. Appl. Genet. 82:602-608. doi:10.1007/BF00226797
31. Palta, J. 1996. Recent advances in plant responses to stress: Bridging the gap between science and technology. HortScience 31:51-57.
32. Patterson, H.D., and R. Thompson. 1971. Recovery of block information when block sizes are unequal. Biometrika 31:100-109.
33. Pfeiffer, W., and B. McClafferty. 2007a. HarvestPlus: Breeding crops for better nutrition. Crop Sci. 47:S88-S105. doi:10.2135/cropsci2007.09.0020IPBS
34. Pfeiffer, W.H., and B. McClafferty. 2007b. Biofortification: Breeding micronutrient-dense crops. In: M.S. Kang and P.M. Priyadarshan, editors, Breeding major food staples. Blackwell Publ., p. 61-91.
35. Piepho, H.P., C. Richter, and E. Williams. 2008. Nearest neighbour adjustment and linear variance models in plant breeding trials. Biom. J. 50:164-189. doi:10.1002/bimj.200710414
36. Plummer, M. 2003. JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling, Proceedings of the 3rd International Workshop on Distributed Statistical Computing., Vienna, Austria.
37. Po, E.A., S.S. Snapp, and A. Kravchenko. 2010. Potato yield variability across the landscape. Agron. J. 102:885-894. doi:10.2134/agronj2009.0424
38. R Development Core Team. 2012. R: A language and environment for statistical computing. R foundation for statistical computing, Vienna, Austria.
39. Rengel, Z., G. Batten, and D. Crowley. 1999. Agronomic approaches for improving the micronutrient density in edible portions of field crops. Field Crops Res. 60:27-40. doi:10.1016/S0378-4290(98)00131-2
40. Rose, D., G. Burgos, M. Bonierbale, and G. Thiele. 2009. Understanding the role of potatoes in the Peruvian diet: An approach that combines food composition with household expenditure data. J. Food Compost. Anal. 22:525-532. doi:10.1016/j.jfca.2008.10.002
41. Sands, D.C., C.E. Morris, E.A. Dratz, and A.L. Pilgeram. 2009. Elevating optimal human nutrition to a central goal of plant breeding and production of plant-based foods. Plant Sci. 177:377-389. doi:10.1016/j.plantsci.2009.07.011
42. Sorensen, D., and D. Gianola. 2002. Likelihood, Bayesian, and MCMC methods in quantitative genetics. Springer, Berlin.
43. Spiegelhalter, D.J., N.G. Best, B.R. Carlin, and A. van der Linde. 2002. Bayesian measures of model complexity and fit. J. Roy. Stat. Soc. Ser. B. (Stat. Method.) 64:583-616. doi:10.1111/1467-9868.00353.
44. Šrek, P., M. Hejcman, and E. Kunzová. 2010. Multivariate analysis of relationship between potato (Solanum tuberosum L.) yield, amount of applied elements, their concentrations in tubers and uptake in a long-term fertilizer experiment. Field Crops Res. 118:183-193. doi:10.1016/j.fcr.2010.05.009
45. Stein, A.J. 2010. Global impacts of human mineral malnutrition. Plant Soil 335:133-154. doi:10.1007/s11104-009-0228-2
46. Stein, A.J., J.V. Meenakshi, M. Qaim, P. Nestel, H.P.S. Sachdev, and Z.A. Bhutta. 2005. Analyzing the health benefits of biofortified staple crops by means of the disability-adjusted life years approach: A handbook focusing on iron, zinc and vitamin A. HarvestPlus Technical Monograph No. 4. International Food Policy Research Institute, Washington, D.C.
47. Subramanian, N.K., P.J. White, M.R. Broadley, and G. Ramsay. 2011. The three-dimensional distribution of minerals in potato tubers. Ann. Bot. 107:681-691. doi:10.1093/aob/mcr009
48. Van Tassell, C.P., and L.D. Van Vleck. 1996. Multiple-trait Gibbs sampler for animal models: Flexible programs for Bayesian and likelihood-based (co)variance component inference. J. Anim. Sci. 74:2586-2597.
49. Waldmann, P. 2009. Easy and flexible Bayesian inference of quantitative genetic parameters. Evolution 63:1640-1643. doi:10.1111/j.1558-5646.2009.00645.x
50. Waldmann, P., and T. Ericsson. 2006. Comparison of REML and Gibbs sampling estimates of multi-trait genetic parameters in Scots pine. Theor. Appl. Genet. 112:1441-1451. doi:10.1007/s00122-006-0246-x
51. Waldmann, P., J. Hallander, F. Hoti, and M.J. Sillanpaa. 2008. Efficient Markov chain Monte Carlo implementation of Bayesian analysis of additive and dominance genetic variances in noninbred pedigrees. Genetics 179:1101-1112. doi:10.1534/genetics.107.084160
52. Welch, R.M., and R.D. Graham. 2004. Breeding for micronutrients in staple food crops from a human nutrition perspective. J. Exp. Bot. 55:353-364 10.1093/jxb/erh064.doi:10.1093/jxb/erh064
53. White, P., J. Bradshaw, M. Dale, G. Ramsay, J. Hammond, and M. Broadley. 2009. Relationships between yield and mineral concentrations in potato tubers. HortScience 44:6-11.
54. White, P.J., M.R. Broadley, J.P. Hammond, G. Ramsay, N.K. Subramanian, J. Thompson, and G. Wright. 2012. Bio-fortification of potato tubers using foliar zinc-fertiliser. J. Hortic. Sci. Biotechnol. 87:123-129.
55. White, J., and R. Zasoski. 1999. Mapping soil micronutrients. Field Crops Res. 60:11-26. doi:10.1016/S0378-4290(98)00130-0