Chemical composition of Lippia spp. essential oil and antimicrobial activity against Aeromonas hydrophila

Phytotherapy can replace antibiotic administration as an alternative to control Aeromonas hydrophila, one of the main bacteria involved in the aetiology of farmed fish diseases. Given that plants of the Lippia spp. genus show biological potential for antimicrobial activity, this study evaluated the chemical composition of essential oils extracted from Lippia alba, Lippia origanoides and Lippia sidoides and their activity against A. hydrophila. The oils were obtained by steam distillation in a Clevenger‐type apparatus and their composition determined by gas chromatography and mass spectrometry (CG/MS). Antibacterial activity was assessed by calculating the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) using broth microdilution method. The main compounds identified were geranial (25.4%) and neral (16.6%) in L. alba oil, carvacrol (40.4%) and p‐cymene (11.4%) in L. origanoides oil and thymol (76.6%) and ortho‐cymene (6.3%) in L. sidoides oil. The three Lippia species showed bacteriostatic and bactericidal action against A. hydrophila, with MICs and MBCs ranging from 1250 to 5000 μg mL^?1. Of the species tested, the best performance was obtained with essential oil of L. sidoides.     

Effects of biofloc technology on reproduction and ovarian recrudescence in Nile tilapia

The objectives of this study were to evaluate the reproductive cycle, morphological changes of ovary and mobilization of energy reserves in Nile tilapia reared with biofloc technology (BFT). In general, the growth and reproductive performance were highly similar between BFT and Control system (clear water). Difference between the systems was found in the hepatosomatic index (using mixed‐effects models), which suggested that BFT can alter the energy mobilization in the post‐spawning period. The absolute and relative fecundity, fertilization rate, number of larvae produced per female, gonadosomatic index, proportion of oogenesis cells, number of post‐ovulatory and atretic follicles were similar between the two systems. We also did not detect a reduction in the reproductive cycle length in Nile tilapia reared in BFT. Because there was no evidence of the negative effects of BFT on Nile tilapia reproduction, we concluded that BFT might be used for breeder stocking of this species.     

Simulation of over-exploitation of ornamental fish and its consequences for the functional structure of assemblages of Amazonian streams

The consequences of over-exploitation may seriously impair the integrity and functioning of ecosystems. When loss of species is accompanied by the loss of ecological processes, the effects are no longer just taxonomic and may affect the stability of the environments. Ornamental fishing is one of the main economic activities of the middle Negro River. Such activity is directed to a small number of species and has the Cardinal Tetra (Paracheirodon axelrodi) as the main target species. Given the potential effects this pressure and the lack of information on its consequences, the present study analysed, through simulations, the possible effects of depletion of ornamental fish populations on the functional structure of fish assemblages, represented by functional diversity (FD) and functional redundancy (FR) indexes. We sampled 13 streams exploited by the ornamental fishery, where we collected 4,286 specimens of 110 species, of which 22 were targeted as ornamental fishing. We found that the ornamental species corresponded, on average, to 27.8% of the species and 33.3% of the FD of the assemblages. In a scenario of complete exclusion of ornamental species, local communities would lose 24.6% of the FD and reduce up to 12% of the FR. With these results, it is possible to infer that the local extinction of exploited species would cause negative impacts on the multifunctionality and the resilience of the streams ecosystems. In this way, we emphasise the need for proper management of the ornamental fisheries aiming to the sustainability of the activity and to the conservation of ecosystem functionality.     

Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm

This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner–Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale.     

An easy,accurate and efficient procedure to create forest fire risk maps using the SEXTANTE plugin Modeler

To prevent, detect, and protect against forest fires, forest personnel need to define rules for determining forest fire risk. In Portugal, all municipalities must annually produce forest fire risk(FFR) maps. To produce more reliable FFR maps more easily, we developed an open source model using the Modeler plugin of SEXTANTE in the program QGIS version 2.0 Dufour. The model provides all the maps involved in the FFR model(susceptibility map, hazard map, vulnerability map, economic value map,and potential loss map) and was produced according to Portuguese Forest Authority's(AFN, Autoridade Florestal Nacional) rules for determining the FFR. This model was tested for the Portuguese municipality Santa Maria da Feira, where 40 % of the total municipality area falls in the category ‘‘very high' or ‘‘high' fire risk. The ‘‘very high'fire risk area is mainly classified as broad-leaved forest and has the steepest slopes(15 %). The distance of burned areas to roads was also analyzed; the proportion of burned areas increased with increasing distance to the main roads.In addition, 92.6 % of the ‘‘high' and ‘‘very high' risk zones were located in areas with lower elevation. These results confirmed that forest fire is strongly influenced not only by environmental factors but also by anthropogenic factors. The procedure implemented here was compared with our open source application already available in QGIS and also to the same procedure implemented in GIS proprietary software. Although the results were obviously the same, the model developed here presents several advantages over the other two approaches. Besides being faster,it is easy to change the model parameters according to user needs(i.e., to the rules of different countries), and can be modified and adapted to other variables and other areas to create risk maps for different natural phenomena(e.g.,floods, earthquakes, landslides). The model is easy to use and to create risk and hazard maps rapidly in a free, open source environment that does not require any programming knowledge.     

A new standard area diagram set for assessment of severity of soybean rust improves accuracy of estimates and optimizes resource use

Soybean rust (SBR), caused by Phakopsora pachyrhizi, is the most important yield-damaging fungal disease of soybean due to severe reduction in healthy leaf area and acceleration of leaf fall. In experimental research, SBR severity is estimated visually aided/trained by a standard area diagram (SAD) developed and validated during the mid-2000s (Old SAD). In this study, we propose a new SAD set for SBR with six true-colour diagrams following linear increments (c. 15% increments) amended with four additional diagrams at low (<10%) severities, totalling 10 diagrams (0.2%, 1%, 3%, 5%, 10%, 25%, 40%, 55%, 70%, and 84%). For evaluation, 37 raters were split into two groups. Each assessed severity in a 50-image sample (0.25%–84%), first unaided and then using either the Old SAD or the New SAD. Accuracy, precision, and reliability of estimates improved significantly relative to unaided estimates only when aided by the New SAD (accuracy >0.95). Low precision (<0.78) and a trend of underestimation with an increase in severity were the main issues with the Old SAD, which did not differ from unaided estimates. Simulation to evaluate the impact of the errors by different methods on hypothesis tests, showed that the new SAD was more powerful for detecting the smallest difference in mean control (e.g., 70% vs. 65% disease reduction) than the Old SAD; the latter required a 2-fold increase in sample size to achieve the same power. There is a need to improve some SADs, taking advantage of new knowledge and technology to increase accuracy of the estimates, and to optimize both resource use efficiency and management decisions.     

Use of genomic and phenotypic selection in lines for prediction of testcrosses in maize II: grain yield and plant traits

Plant breeders have been trying to predict the performance of hybrids based on their parental performance. One application of molecular markers is its use in selection. The objectives were to map quantitative trait loci (QTL) and verify its congruence in maize lines and in their testcrosses and verify the possibility to select testcrosses from the predicted means of the lines by using information from markers. Two-hundred and fifty six lines and the testcrosses of these lines with two testers were evaluated in six environments, considering grain yield, plant lodging, days to anthesis and silking, anthesis-silking interval, plant and ear height and ear placement. QTL were mapped in the lines and in testcrosses and the predicted means of the lines were computed based on QTL effects and in all markers of the genome. The congruence of QTL detected in the lines and testcrosses were small for all traits. The correlations between the predicted means of the lines and the phenotypic means of the testcrosses ranged from low for grain yield to moderate for cycle and stature traits. The highest coincidences of the lines and selected testcrosses were observed for cycle and stature traits and the lowest for grain yield. Even by using molecular markers information, it is only possible to predict the testcrosses performance from the lines information to less complex traits and with reduced dominance effect. For complex traits and with pronounced dominance effect, information of markers must be obtained directly in the testcrosses, so they can be used for selection.