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Jaime Sahagún-Castellanos ; Juan Enrique Rodríguez-Pérez ; Margarita Gisela Peña-Ortega ;REVISTA CHAPINGO SERIE HORTICULTURA 2017, XXIII (1)

Autor: Lucas Hernández-Ibáñez

Fuente: http://www.redalyc.org/


Introducción



REVISTA CHAPINGO SERIE HORTICULTURA ISSN: 1027-152X chapingo.horticultura@gmail.com Universidad Autónoma Chapingo México Hernández-Ibáñez, Lucas; Sahagún-Castellanos, Jaime; Rodríguez-Pérez, Juan Enrique; Peña-Ortega, Margarita Gisela Prediction of fruit yield and firmness of tomato hybrids with BLUP and RR-BLUP using ISSR molecular markers REVISTA CHAPINGO SERIE HORTICULTURA, vol.
XXIII, núm.
1, enero-abril, 2017, pp. 21-33 Universidad Autónoma Chapingo Chapingo, México Available in: http:--www.redalyc.org-articulo.oa?id=60949768002 How to cite Complete issue More information about this article Journals homepage in redalyc.org Scientific Information System Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Non-profit academic project, developed under the open access initiative Scientific article doi: 10.5154-r.rchsh.2016.06.021 Prediction of fruit yield and firmness of tomato hybrids with BLUP and RR-BLUP using ISSR molecular markers Predicción de rendimiento y firmeza de fruto de híbridos de tomate con BLUP y RR-BLUP mediante marcadores moleculares ISSR Lucas Hernández-Ibáñez; Jaime Sahagún-Castellanos*; Juan Enrique Rodríguez-Pérez; Margarita Gisela Peña-Ortega Universidad Autónoma Chapingo, Instituto de Horticultura, Departamento de Fitotecnia. Carretera México-Texcoco km 38.5, Chapingo, Estado de México, C.
P.
56230, MÉXICO. jsahagunc@yahoo.com.mx, tel.: (595) 952 1500, ext.
6185 (*Corresponding author) Abstract I Keywords: Solanum lycopersicum L., best linear unbiased prediction, ridge regression BLUP, fruit yield components. n the development of tomato hybrids, a large number of parental lines involves an excessively high number of possible hybrids, making their formation and evaluation problematic.
The magnitude of this can be reduced to manageable levels with the use of hybrid performance prediction methods.
In this study we compared two methods based on genomic fingerprints, mixed model...





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