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Burgueño, J.

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Burgueño
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Burgueño, J.

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  • Chapter 11. RIndSel: selection Indices with R
    (Springer, 2018) Alvarado Beltrán, G.; Pacheco Gil, Rosa Angela; Pérez-Elizalde, S.; Burgueño, J.; Rodríguez, F.M.; Cerón-Rojas, J.J.; Crossa, J.
    RIndSel is a graphical unit interface that uses selection index theory to select individual candidates as parents for the next selection cycle. The index can be a linear combination of phenotypic values, genomic estimated breeding values, or a linear combination of phenotypic values and marker scores. Based on the restriction imposed on the expected genetic gain per trait, the index can be unrestricted, null restricted, or predetermined proportional gain indices. RIndSel is compatible with any of the following versions of Windows: XP, 7, 8, and 10. Furthermore, it can be installed on 32-bit and 64-bit computers. In the context of fixed and mixed models, RIndSel estimates the phenotypic and genetic covariance using two main experimental designs: randomized complete block design and lattice or alpha lattice design. In the following, we explain how RIndSel can be used to determine individual candidates as parents for the next cycle of improvement.
    Publication
  • Chapter 10. Stochastic simulation of four linear phenotypic selection indices
    (Springer, 2018) Crossa, J.; Burgueño, J.; Toledo, F.H.; Cerón-Rojas, J.J.
    Stochastic simulation can contribute to a better understanding of the problem, and has already been successfully applied to evaluate other breeding scenarios. Despite all the theories developed in this book concerning different types of indices, including phenotypic data and/or data on molecular markers, no examples have been presented showing the long-term behavior of different indices. The objective of this chapter is to present some results and insights into the in silico (computer simulation) performance comparison of over 50 selection cycles of a recurrent and generic population breeding program with different selection indices, restricted and unrestricted. The selection indices included in this stochastic simulation were the linear phenotypic selection index (LPSI), the eigen selection index method (ESIM), the restrictive LPSI, and the restrictive ESIM.
    Publication