Keywords:Vernacular architecture Life-cycle assessment Environmental impacts Rammed earth Compressed earth block (CEB) Earthen architecture a b s t r a c tIn the Portuguese context, the life cycle assessment of building materials is still in its infancy. So far, there is only a small number of Environmental Product Declarations (EPDs) available, all target for industriallybased materials. Although vernacular earthen materials are seen as ecological materials, with low potential environmental impacts, there are no studies that allow to quantitatively compare these materials with conventional ones, according to the applicable standards. In the case of Portugal, there are no EPDs or studies for these materials and the studies available worldwide are hard to compare, since they not follow the same life-cycle assessment methodology. This paper aims at contributing to a better understanding about the environmental performance of earthen materials by presenting results from the life cycle assessment of Compressed Earth Blocks (CEBs) and Rammed earth, based on specific life cycle inventory values obtained from a producer company, following the guidance provided by the standard EN15804. Among other conclusions, results show that CEB and Rammed earth have a total Embodied Energy of 3.94 MJ/block and 596 MJ/1 m 3 and a Global Warming Potential of 0.39 kg CO 2 eq/block and 47.5 kg CO 2 eq./1 m 3 , respectively. In a cradle-to-gate analysis of different walls, the use of earthen building elements can result in reducing the potential environmental impacts in about 50%, when compared to the use of conventional ones. Additionally, the advantages of using earthen materials are also discussed for the different building life-cycle stages, focusing on the possibility to recycle these materials in a closed-loop approach.

Based on morphological, bioacoustics, and morphological traits, the genus Scinax has been subdivided into two major clades: S. catharinae and S. ruber. The first clade includes S. catharinae and S. perpusillus groups, whereas the second clade includes S. rostratus and S. uruguayus groups. Chromosome morphology, NOR and C-banding patterns of variation support these clades. This study aims the cytogenetic characterization of five species currently included in the S. perpusillus group: Scinax sp. (gr. perpusillus), S. arduous, S. belloni, S. cosenzai, and S. v-signatus, including standard cytogenetic techniques and repetitive DNA FISH probes. All species had 2n = 24 chromosomes. Nucleolar organizing regions occurred in chromosome pair 6 in all species, but differed in their locations among some species, suggesting a putative synaponomastic character for the clade. In S. belloni, the first chromosome pair was a metacentric, contrasting with the submetacentric first pair reported in all other species of the genus. Scinax sp. (gr. perpusillus) and S. v-signatus had similar karyotypic formulae, suggesting they are related species. Scinax cosenzai had a divergent C-banding pattern. Repetitive DNA probes hybridized more frequently in chromosomal subtelomeric regions in all species indicating recent cladogenesis in these species. Karyotypic evidence indicates unreported high levels of stabilization within S. perpusillus and in S. catharinae clade, resulting in a wealth of characters potentially informative for higher phylogenetic analyses.

No abstract

No abstract

To increase the number of cytogenetic characters used in Ololygon tripui systematics, we applied some cytogenetic techniques such as Giemsa, C- and NOR-banding, and (FISH)fluorescence in situ hybridization with 18S rDNA and repetitive microsatellite DNA probes to the study of four populations from Minas Gerais State (southeastern Brazil). All populations showed 2n = 24 and FN = 48, and chromosomal formula 8m + 10sm + 6st. (NORs)Nucleolar organizing regions were located on chromosome pair 6 in all populations, although in the Tripuí locality additional markings were observed on one homologue of chromosome pair 3. These patterns were partially congruent with results obtained using the 18S rDNA FISH probe. The microsatellites repetitive DNA (GA)15 and (CAT)10 probes accumulated predominantly in the terminal region of all chromosomes. Chromosome morphology and Ag-NOR were conserved among populations, a conserved pattern in Ololygon Fitzinger, 1843. Repetitive DNA FISH probes patterns were similar among populations, but they revealed species-specific differences when compared with other species of the genus Ololygon, suggesting that molecular cytogenetics are potentially more informative in karyologically conservative taxa.

Multiple-trait model tends to be the best alternative for the analysis of repeated measures, since they consider the genetic and residual correlations between measures and improve the selective accuracy. Thus, the objective of this study was to propose a multiple-trait Bayesian model for repeated measures analysis in Jatropha curcas breeding for bioenergy. To this end, the grain yield trait of 730 individuals of 73 half-sib families was evaluated over six harvests. The Markov Chain Monte Carlo algorithm was used to estimate genetic parameters and genetic values. Genetic correlation between pairs of measures were estimated and four selective intensities (27.4%, 20.5%, 13.7%, and 6.9%) were used to compute the selection gains. The full model was selected based on deviance information criterion. Genetic correlations of low (ρg ≤ 0.33), moderate (0.34 ≤ ρg ≤ 0.66), and high magnitude (ρg ≥ 0.67) were observed between pairs of harvests. Bayesian analyses provide robust inference of genetic parameters and genetic values, with high selective accuracies. In summary, the multiple-trait Bayesian model allowed the reliable selection of superior Jatropha curcas progenies. Therefore, we recommend this model to genetic evaluation of Jatropha curcas genotypes, and its generalization, in other perennials.

Reaction norms fitted through random regression models (RRM) have been widely used in animal and plant breeding for analyses of genotype × environment (G × E) interaction. However, in annual crops, they remain unexplored. Thus, this study aimed to evaluate the applicability and efficiency of RRM fitted through Legendre polynomials as a tool to recommend cotton (Gossypium hirsutum L.) genotypes. To this end, a data set with 12 genotypes of cotton evaluated in 10 environments for fiber length (FL) and fiber fineness was used. The restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) procedure was used to estimate the variance components and to predict the genetic values. Results showed that there was genetic variability among cotton genotypes and that the reaction norms over the environmental gradient illustrated the G × E interaction. Very high selective accuracies (̂> 0.90) were found for both traits in all environments, which indicates high reliability in the genotype's recommendation. The areas under the reaction norms were calculated for the recommendation of genotypes for unfavorable, favorable, and overall environments. Regarding genotypes recommendation, areas under reaction norms allow recommending genotypes for unfavorable and favorable environments, as well as for overall recommendation, for both traits. This study is the first considering reaction norms fitted through RRM for the recommendation of cotton genotypes and demonstrated the potential of this technique in cotton breeding, besides its great potential to deal with G × E interactions.

In multi-environment trials (MET), large networks are assessed for results improvement. However, genotype by environment interaction plays an important role in the selection of the most adaptable and stable genotypes in MET framework. In this study, we tested different residual variances and measure the selection gain of cotton genotypes accounting for adaptability and stability, simultaneously. Twelve genotypes of cotton were bred in 10 environments, and fiber length (FL), fiber strength (FS), micronaire (MIC), and fiber yield (FY) were determined. Model selection for different residual variance structures (homogeneous and heterogeneous) was tested using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The variance components were estimated through restricted maximum likelihood and genotypic values were predicted through best linear unbiased prediction. The harmonic mean of relative performance of genetic values (HMRPGV) were applied for simultaneous selection for adaptability, stability, and yield. According to BIC heterogeneous residual variance was the best model fit for FY, whereas homogeneous residual variance was the best model fit for FL, FS, and MIC traits. The selective accuracy was high, indicating reliability of the prediction. The HMRPGV was capable to select for stability, adaptability and yield simultaneously, with remarkable selection gain for each trait.