Dynamics of biochemical and morphophysiological changes during zygotic embryogenesis in Acca sellowiana (Berg.) Burr.

Acca sellowiana (Berg.) Burr. is a native Myrtaceae from southern Brazil and Uruguay, now the subject of a domestication and breeding program. Biotechnological tools have been used to assist in this program. The establishment of a reliable protocol of somatic embryogenesis has been pursued, with a view to capturing and fixing genetic gains. The rationale behind this work relies on the fact that deepening comprehension of the general metabolism of zygotic embryogenesis may certainly improve the protocol for somatic embryogenesis. Thus, in the present work we studied the accumulation of protein, total sugars, starch, amino acids, polyamines (PAs), IAA and ABA, in different stages of A. sellowiana zygotic embryogenesis. Starch is the predominant storage compound during zygotic embryo development. Increased synthesis of amino acids in the cotyledonary stage, mainly of asparagine, was observed throughout development. Total free PAs showed increased synthesis, whereas total conjugated PAs were mainly observed in the early developmental stages. IAA decreased and ABA increased with the progression from early to late embryogenesis. Besides providing basic information on the morphophysiological and biochemical changes of zygotic embryogenesis, the results here obtained may provide adequate strategies towards the modulation of somatic embryogenesis in this species as well as in other woody angiosperms.

Log-Burr XII regression models with censored data

In survival analysis applications, the failure rate function may frequently present a unimodal shape. In such case, the log-normal or log-logistic distributions are used. In this paper, we shall be concerned only with parametric forms, so a location-scale regression model based on the Burr XII distribution is proposed for modeling data with a unimodal failure rate function as an alternative to the log-logistic regression model. Assuming censored data, we consider a classic analysis, a Bayesian analysis and a jackknife estimator for the parameters of the proposed model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the log-logistic and log-Burr XII regression models. Besides, we use sensitivity analysis to detect influential or outlying observations, and residual analysis is used to check the assumptions in the model. Finally, we analyze a real data set under log-Buff XII regression models. (C) 2008 Published by Elsevier B.V.