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.     

LED-Induced Chlorophyll Fluorescence Spectral Analysis for the Early Detection and Monitoring of Cadmium Toxicity in Maize Plants

Chlorophyll fluorescence spectral analysis permits detection, monitoring, and evaluation of abiotic stresses upon healthy plants using illumination of a light source in the UV?CVIS spectral range. This technique indirectly assesses the amount of physiological stress caused by photosynthetic damage, specifically damage to photosystem II, in plants. The objective of this study was to detect the toxicity of cadmium in maize plants via spectral analysis of chlorophyll fluorescence. The analysis is noninvasive and nondestructive and is used to follow the temporal evolution of changes in the chlorophyll content and physiological state of Zea mays L. seedlings under cadmium stress. Conventional techniques were also used to evaluate the dry matter production and Cd accumulation in plant leaves. Plants exhibited a notable reduction in dry matter production and chlorophyll levels with the administration of increasing doses of Cd in the nutrient solution. The fluorescence analysis was sensitive to changes caused by Cd in maize plants, detecting damage caused by different treatments before visual symptoms were observed. This technique has a practical application and produces rapid results that can be used in the evaluation of Cd-induced stress in plants and the detection of areas contaminated by this element.     

Accumulation of phytoalexins in leaves of plane tree (Platanus spp.) expressing susceptibility or resistance toCeratocystis fimbriata f. sp.platani

Inoculation of leaves of resistantPlatanus occidentalis and susceptiblePlatanus acerifolia leaves withCeratocystis fimbriata f. sp.platani, the canker stain disease agent, induced foliar necrosis and biosynthesis of two phytoalexins, scopoletin and umbelliferone. Foliar symptoms keep localized and accumulation of coumarin phytoalexins was rapid for incompatible interactions. Necrosis spread widely and accumulation of these phenolic compounds was much later and lower for compatible interactions. The differential response could be used in a genetic improvement program for resistance against canker stain.     

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.     

Large-scale historical afforestation failure with Pinus cembra in the Swiss Prealps

New Forests - Between the nineteenth and early twentieth centuries, large-scale afforestation projects were undertaken in the Swiss Prealps. The Swiss stone pine (Pinus cembra L.), an emblematic...     

Litter production and nutrient deposition from native woody species in the Brazilian semi-arid region

Agroforestry Systems - The use of native trees in agroecosystems is a promising way to increase litter deposition and nutrient cycling and foster the recovery of degraded areas, especially in...