Broad-sense heritabilities, genetic correlations, and selection indices for sugarcane borer resistance evaluation traits and their relation to yield loss.

MILLIGAN S; BALZARINI M

LAES/HAES

Louisiana State University, Agricultural Center

Lugar: Baton Rouge, USA; Año: 1999 p. 106 - 117

0101-0522

<!-- /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-parent:""; margin:0cm; margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman";} @page Section1 {size:612.0pt 792.0pt; margin:70.85pt 3.0cm 70.85pt 3.0cm; mso-header-margin:36.0pt; mso-footer-margin:36.0pt; mso-paper-source:0;} div.Section1 {page:Section1;} --> The sugarcane borer, Diatraea saccharalis, causes the majority of insect related damage to Louisiana sugarcane. Cultivar resistance potentially provides the most economic and environmentally effective means of control available to the production industry. Entomologists evaluate a number of variables (percent borer internodes, percent exited internodes, pupation success, moth production per area, and a damage rating) to assess cultivar resistance, but genetic knowledge concerning these traits and their interrelationships among each other and to yield loss is limited. Breeders are faced with the job of integrating the multiple trait evaluations of the cultivars. Selection indices are a method to quantitatively integrate the data. The optimum selection index procedure simultaneously weights the genetic confidence and interrelationships of the traits together with the relative economic value to provide phenotypic index values for evaluating the cultivars. When based on  accurate parameter estimates, the indices will provide the best solution to maximize genetic improvement for the selection goal. The study was performed to estimate the genetic parameters of common traits and their relationship to yield loss. The goal was to develop selection indices so that the breeder can best collate the range of borer damage variables into one index and then make the most effective selection decision.