Prediction of direct and indirect genetic gains and genotypic correlations in rubber tree progenies

The objective of this work was to estimate the genetic parameters, genotypic and phenotypic correlations, and direct and indirect genetic gains among and within rubber tree (Hevea brasiliensis) progenies. The experiment was set up at the Municipality of Jaú, SP, Brazil. A randomized complete block design was used, with 22 treatments (progenies), 6 replicates, and 10 plants per plot at a spacing of 3x3 m. Three‑year‑old progenies were assessed for girth, rubber yield, and bark thickness by direct and indirect gains and genotypic correlations. The number of latex vessel rings showed the best correlations, correlating positively and significantly with girth and bark thickness. Selection gains among progenies were greater than within progeny for all the variables analyzed. Total gains obtained were high, especially for girth increase and rubber yield, which were 93.38 and 105.95%, respectively. Young progeny selection can maximize the expected genetic gains, reducing the rubber tree selection cycle.

Assessment of growth and yield performance of rubber tree clones of the IAC 500 series

The objective of this work was to evaluate the performance of 15 clones of the IAC 500 series of Hevea brasiliensis, developed at Instituto Agronômico (IAC), over a 12-year period, in the northwest region of São Paulo State, Brazil. The 15 new clones evaluated are primary clones obtained from selected ortets within half-sib progenies. The clone RRIM 600, of Malaysian origin, was used as the control. Dry rubber yield performance over a four-year period, mean girth at the tenth year, girth increment before and during tapping, thermal properties of the natural rubber produced and other characters of the laticiferous system were evaluated. Forty percent of the clones were superior in comparison to the control for yield. Clone IAC 500 recorded the highest yield (66.81 g per tree per tapping) over four years of tapping, followed by IAC 502 (62.37 g per tree per tapping), whereas the control recorded 48.71 g per tree per tapping. All selected clones were vigorous in growth. The natural rubber from this IAC clones showed thermal stability up to 300ºC. No differences were observed in the thermal behavior of rubber among the IAC series and the RRIM 600 clones. The clones IAC 500, IAC 501, IAC 502, IAC 503 and IAC 506 are the more promising for small-scale plantations, due to growth and yield potential.

Calibrating predicted tree diameter distributions in Catalonia, Spain

Abstract

Translocation of cyanogenic glycosides in rubber tree crown clones resistant to South American leaf blight

The objective of this work was to assess the possible transport of cyanogenic glycosides from leaves of rubber tree crown clones (Hevea spp.) resistant to South American leaf blight to the trunk of the panel clones in which they are grafted. The cyanogenic potential (HCNp) of the crown clones was determined in the trunk bark, at different distances from the cambium, and its gradient was evaluated along the trunk. The correlation between the HCNp of the crown leaves and that of the trunk bark was also evaluated. HCNp determined in leaves showed a wide range variation in the species studied as crown clones, with the lowest values registered in H. nitida clones, and the highest ones in H. rigidifolia. In the trunk bark, the tissue layer nearer the cambium showed higher HCNp values. A positive basipetal gradient was observed along the trunk, i.e., there was an increase in HCNp from the apex toward the base. Although the grafted crowns influence the cyanogenic potential of the trunk bark of panel clones, the absence of correlation between the HCNp of the leaves and trunk bark indicates that the crown is not the main source of the cyanogenic glycosides found in the trunk.

Prediction of hemodynamic severity of coarctation by magnetic resonance imaging.

A published formula containing minimal aortic cross-sectional area and the flow deceleration pattern in the descending aorta obtained by cardiovascular magnetic resonance predicts significant coarctation of the aorta (CoA). However, the existing formula is complicated to use in clinical practice and has not been externally validated. Consequently, its clinical utility has been limited. The aim of this study was to derive a simple and clinically practical algorithm to predict severe CoA from data obtained by cardiovascular magnetic resonance. Seventy-nine consecutive patients who underwent cardiovascular magnetic resonance and cardiac catheterization for the evaluation of native or recurrent CoA at Children's Hospital Boston (n = 30) and the University of California, San Francisco (n = 49), were retrospectively reviewed. The published formula derived from data obtained at Children's Hospital Boston was first validated from data obtained at the University of California, San Francisco. Next, pooled data from the 2 institutions were analyzed, and a refined model was created using logistic regression methods. Finally, recursive partitioning was used to develop a clinically practical prediction tree to predict transcatheter systolic pressure gradient ≥ 20 mm Hg. Severe CoA was present in 48 patients (61%). Indexed minimal aortic cross-sectional area and heart rate-corrected flow deceleration time in the descending aorta were independent predictors of CoA gradient ≥ 20 mm Hg (p <0.01 for both). A prediction tree combining these variables reached a sensitivity and specificity of 90% and 76%, respectively. In conclusion, the presented prediction tree on the basis of cutoff values is easy to use and may help guide the management of patients investigated for CoA.

Genetic diversity of cultivated accessions and wild species of rubber tree using EST‑SSR markers

The objective of this work was to evaluate the efficiency of EST‑SSR markers in the assessment of the genetic diversity of rubber tree genotypes (Hevea brasiliensis) and to verify the transferability of these markers for wild species of Hevea. Forty‑five rubber tree accessions from the Instituto Agronômico (Campinas, SP, Brazil) and six wild species were used. Information provided by modified Roger's genetic distance were used to analyze EST‑SSR data. UPGMA clustering divided the samples into two major groups with high genetic differentiation, while the software Structure distributed the 51 clones into eight groups. A parallel could be established between both clustering analyses. The 30 polymorphic EST‑SSRs showed from two to ten alleles and were efficient in amplifying the six wild species. Functional EST‑SSR microsatellites are efficient in evaluating the genetic diversity among rubber tree clones and can be used to translate the genetic differences among cultivars and to fingerprint closely related materials. The accessions from the Instituto Agronômico show high genetic diversity. The EST‑SSR markers, developed from Hevea brasiliensis, show transferability and are able to amplify other species of Hevea.

Stability and adaptability of runner peanut genotypes based on nonlinear regression and AMMI analysis

The objective of this work was to estimate the stability and adaptability of pod and seed yield in runner peanut genotypes based on the nonlinear regression and AMMI analysis. Yield data from 11 trials, distributed in six environments and three harvests, carried out in the Northeast region of Brazil during the rainy season were used. Significant effects of genotypes (G), environments (E), and GE interactions were detected in the analysis, indicating different behaviors among genotypes in favorable and unfavorable environmental conditions. The genotypes BRS Pérola Branca and LViPE‑06 are more stable and adapted to the semiarid environment, whereas LGoPE‑06 is a promising material for pod production, despite being highly dependent on favorable environments.

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

This paper presents the general regression neural networks (GRNN) as a nonlinear regression method for the interpolation of monthly wind speeds in complex Alpine orography. GRNN is trained using data coming from Swiss meteorological networks to learn the statistical relationship between topographic features and wind speed. The terrain convexity, slope and exposure are considered by extracting features from the digital elevation model at different spatial scales using specialised convolution filters. A database of gridded monthly wind speeds is then constructed by applying GRNN in prediction mode during the period 1968-2008. This study demonstrates that using topographic features as inputs in GRNN significantly reduces cross-validation errors with respect to low-dimensional models integrating only geographical coordinates and terrain height for the interpolation of wind speed. The spatial predictability of wind speed is found to be lower in summer than in winter due to more complex and weaker wind-topography relationships. The relevance of these relationships is studied using an adaptive version of the GRNN algorithm which allows to select the useful terrain features by eliminating the noisy ones. This research provides a framework for extending the low-dimensional interpolation models to high-dimensional spaces by integrating additional features accounting for the topographic conditions at multiple spatial scales. Copyright (c) 2012 Royal Meteorological Society.

Costs of female reproduction in a conifer tree: a whole-tree level assessment

1. Costs of reproduction lie at the core of basic ecological and evolutionary theories, and their existence is commonly invoked to explain adaptive processes. Despite their sheer importance, empirical evidence for the existence and quantification of costs of reproduction in tree species comes mostly from correlational studies, while more comprehensive approaches remain missing. Manipulative experiments are a preferred approach to study cost of reproduction, as they allow controlling for otherwise inherent confounding factors like size or genetic background. 2. Here, we conducted a manipulative experiment in a Pinus halepensis common garden, removing developing cones from a group of trees and comparing growth and reproduction after treatment with a control group. We also estimated phenotypic and genetic correlations between reproductive and vegetative traits. 3. Manipulated trees grew slightly more than control trees just after treatment, with just a transient, marginally non-significant difference. By contrast, larger differences were observed for the number of female cones initiated 1 year after treatment, with an increase of 70% more cones in the manipulated group. Phenotypic and genetic correlations showed that smaller trees invested a higher proportion of their resources in reproduction, compared with larger trees, which could be interpreted as an indirect evidence for costs of reproduction. 4. Synthesis. This research showed a high impact of current reproduction on reproductive potential, even when not significant on vegetative growth. This has strong implications for how we understand adaptive strategies in forest trees and should encourage further interest on their still poorly known reproductive life-history traits.

Genetic parameters and estimated genetic gains in young rubber tree progenies

The objective of this work was to assess the genetic parameters and to estimate genetic gains in young rubber tree progenies. The experiments were carried out during three years, in a randomized block design, with six replicates and ten plants per plot, in three representative Hevea crop regions of the state of São Paulo, Brazil. Twenty-two progenies were evaluated, from three to five years old, for rubber yield and annual girth growth. Genetic gain was estimated with the multi-effect index (MEI). Selection by progenies means provided greater estimated genetic gain than selection based on individuals, since heritability values of progeny means were greater than the ones of individual heritability, for both evaluated variables, in all the assessment years. The selection of the three best progenies for rubber yield provided a selection gain of 1.28 g per plant. The genetic gains estimated with MEI using data from early assessments (from 3 to 5-year-old) were generally high for annual girth growth and rubber yield. The high genetic gains for annual girth growth in the first year of assessment indicate that progenies can be selected at the beginning of the breeding program. Population effective size was consistent with the three progenies selected, showing that they were not related and that the population genetic variability is ensured. Early selection with the genetic gains estimated by MEI can be made on rubber tree progenies.

High capacity robust audio watermarking scheme based on FFT and linear regression

Peer-reviewed

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

Identification and characterization of pathogenic Pestalotiopsis species to pecan tree in Brazil

The objective of this work was to characterize and cluster isolates of Pestalotiopsis species and to identify those that are pathogenic to pecan, based on morphological and molecular characters. Pestalotiopsis spp. isolates were identified by sequencing the internal transcribed spacer (ITS) and β?tubulin regions. Identification methods were compared to indicate the key morphological characters for species characterization. Thirteen isolates were used for the pathogenicity tests. Morphological characterization was performed using the following variables: mycelial growth rate, sporulation, colony pigmentation, and conidial length and width. Ten pathogenic isolates were identified, three as -tubulin regions. Identification methods were compared to indicate the key morphological characters for species characterization. Thirteen isolates were used for the pathogenicity tests. Morphological characterization was performed using the following variables: mycelial growth rate, sporulation, colony pigmentation, and conidial length and width. Ten pathogenic isolates were identified, three as Pestalotiopsis clavispora and three as P. cocculi. The other isolates remained as an undefined species. The morphological characters were efficient for an initial separation of the isolates, which were grouped according to differences at species level, mainly colony diameter, which was identified as an important morphological describer. Beta-tubulin gene sequencing was less informative than the ITS region sequencing for species identification.