SciELO - Scientific Electronic Library Online

 
vol.23 issue1Mexican plums (Spondias spp.): their current distribution and potential distribution under climate change scenarios for MexicoApplication of biol, inorganic fertilizer and superabsorbent polymers in the growth of heliconia (Heliconia psittacorum cv. Tropica) author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


Revista Chapingo. Serie horticultura

On-line version ISSN 2007-4034Print version ISSN 1027-152X

Abstract

HERNANDEZ-IBANEZ, Lucas; SAHAGUN-CASTELLANOS, Jaime; RODRIGUEZ-PEREZ, Juan Enrique  and  PENA-ORTEGA, Margarita Gisela. Prediction of fruit yield and firmness of tomato hybrids with BLUP and RR-BLUP using ISSR molecular markers. Rev. Chapingo Ser.Hortic [online]. 2017, vol.23, n.1, pp.21-34. ISSN 2007-4034.  https://doi.org/10.5154/r.rchsh.2016.06.021.

In 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 theory and the experimental evaluation of a sample of hybrids: 1) best linear unbiased prediction or BLUP and 2) ridge regression BLUP. Thirty-six single crosses were performed with the objective of determining the number, firmness and total and commercial yield of fruits. With 1,000 size-independent random samples, n = 6, 12, 18, 24 and 30, the behavior of the remaining 36-n hybrids was predicted. The correlation coefficients between predicted and observed values ranged between 0.25 and 0.83. BLUP consistently recorded the highest values. In both prediction methods when n increased the magnitude of the correlations also increased.

Keywords : Solanum lycopersicum L.; best linear unbiased prediction; ridge regression BLUP; fruit yield components.

        · abstract in Spanish     · text in English | Spanish     · English ( pdf ) | Spanish ( pdf )