Central nervous system signs in chickens caused by a new avian reovirus strain: a pathogenesis study

The present study describes the pathogenesis of infection of chicks with a new avian reovirus strain, belonging to the so-called enteric reovirus strains (ERS) that is capable of causing central nervous system signs in SPF white leghorns. After intramuscular (IM) or oral inoculation birds were either observed for clinical signs or sacrificed for macroscopic, histological and virological examination for 21 days. Virus isolation was performed on the brain, leg muscle, hock joint, liver and spleen. For the detection of viral antigen the immunohistochemistry (IHC) technique was performed on the caudal part of the cerebrum, spinal cord including spinal ganglia and right N. Ischiadicus. High mortality (79% in 7 days) was seen in birds that were inoculated IM. Survivors were depressed and stayed small until the end of the experiment. One bird had tremor and showed torticollis at 9 days after IM inoculation. Birds that were inoculated orally were depressed from day 4 and stayed small until the end of the experiment. One bird showed a torticollis at 10 days after inoculation. After both IM and oral inoculation ERS was isolated from the brain between 3 and 10 days after inoculation. Other examined organs were positive for virus isolation from day 1 or 5 until day 21. IHC revealed viral antigen positive cells in the Plexus chorioideus (plexus epithelial cells or cells within the underlying connective tissue) and in a spinal ganglion. The results indicate that the pathogenesis of ERS infection in chickens bears some resemblance with that of the mammalian reoviruses serotype 1 in mice.     

First report of Seville root-knot nematode (Meloidogyne hispanica) infecting tobacco in the Brazil

Journal of Plant Diseases and Protection - Tobacco (Nicotiana tabacum L.) is one of the major nonfood crops in the Southern of Brazil. During 2019/2020 and 2020/2021 crop seasons, Root Knot...     

The effect of over-irrigation on the growth and production of Gossypium hirsutum

Summary A field experiment was conducted to determine the effect of overirrigation on the growth characteristics and production of cotton. Over-irrigation, resulting in saturated soil conditions, was achieved by flood irrigation at different levels of soil water depletion on a soil with a low percolation rate. The highest seedcotton and lint yields were obtained from plants that did not experience over-irrigation at any time during the growing season; similar yields were obtained from plants that only experienced moderate over-irrigation after the onset of flowering (Table 9). The yield response could be related to branch growth, flowering rate and length of growing season (Tables 3, 4, 5, 6, 7, and 8).     

Finding niches for whole-farm design models – contradictio in terminis?

Whole-farm design models quantitatively analyze the effects of a variety of potential changes at the farm system level. Science-driven technical information is confronted with value-driven objectives of farmers or other social groupings under explicit assumptions with respect to exogenous variables that are important drivers of agricultural systems (e.g., market conditions). Hence, farm design is an outcome of objective specification and the potential of a system. In recent publications, whole-farm design modelling has been proposed to enhance (farm) innovation processes. A number of operational modelling tools now offers the opportunity to assess the true potential of whole-farm design modelling to enhance innovation. In this paper, we demonstrate that it is not trivial to find niches for the application of goal-based farm models. Model outcomes appeared not to match questions of farm managers monitoring and learning from their own and other farmers’ practices. However, our research indicates that whole-farm design modelling possesses the capabilities to make a valuable contribution to reframing. Reframing is the phenomenon that people feel an urge to discuss and reconsider current objectives and perspectives on a problem. Reframing might take place in a situation (i) of mutually felt dependency between stakeholders, (ii) in which there is sufficient pressure and urgency for stakeholders to explore new problem definitions and make progress. Furthermore, our research suggests that the way the researcher enters a likely niche to introduce a model and/or his or her position in this niche may have significant implications for the potential of models to enhance an innovation process. Therefore, we hypothesize that the chances of capitalizing on modelling expertise are likely to be higher when researchers with such expertise are a logical and more or less permanent component of ongoing trajectories than when these researchers come from outside to purposefully search for a niche.     

Bentazone Leaching in Spanish Soils

Adsorption, incubation and soil-column experiments with bentazone [3-isopropyl-1H-2,1,3-benzothiadiazin-4(3H)-one 2,2-dioxide] were carried out in ten different soils from the marches surrounding the Doñana National Park (Huelva, SW Spain). Adsorption isotherms for the different soils showed a good fit with the Freundlich equation. Bentazone was poorly adsorbed in all the soils studied, with no significant relationship between theK_f values and soil characteristics. A significant correlation was obtained between the soil organic matter content and the distribution constant values (K_d) calculated at an equilibrium concentration of 200 μg cm⁻³. The low adsorption and non-degradation of bentazone on these soils suggest that the herbicide readily percolates through soils to reach the surface and ground waters. The mobility of bentazone through three soil columns was also studied. The mass balances carried out showed that bentazone was totally eluted from the soil columns. The theoretical model applied to explain bentazone leaching under our experimental conditions seems to be suitable for soil columns with a uniform water-flow rate.     

Improving wood volume predictions in dry tropical forest in the semi-arid Brazil

The volumetric variability of dry tropical forests in Brazil and the scarcity of studies on the subject show the need for the development of techniques that make it possible to obtain adequate and accurate wood volume estimates. In this study, we analyzed a database of thinning trees from a forest management plan in the Contendas de Sincorá National Forest, southwestern Bahia State, Brazil. The data set included a total of 300 trees with a trunk diameter ranging from 5 to 52 cm. Adjustments, validation and statistical selection of four volumetric models were performed. Due to the difference in height values for the same diameter and the low correlation between both variables, we do not suggest models which only use the diameter at breast height (DBH) variable as a predictor because they accommodate the largest estimation errors. In comparing the best single entry model (Hohenald-Krenn) with the Spurr model (best fit model), it is noted that the exclusion of height as a predictor causes the values of 136.44 and 0.93 for Akaike information criterion (AIC) and adjusted determination coefficient (R2 adj), which are poorer than the second best model (Schumacher-Hall). Regarding the minimum sample size, errors in estimation (root mean square error (RMSE) and bias) of the best model decrease as the sample size increases, especially when a larger number of trees with DBH≥15.0 cm are randomly sampled. Stratified sampling by diameter class produces smaller volume prediction errors than random sampling, especially when considering all trees. In summary, the Spurr and Schumacher-Hall models perform better. These models suggest that the total variance explained in the estimates is not less than 95%, producing reliable forecasts of the total volume with shell. Our estimates indicate that the bias around the average is not greater than 7%. Our results support the decision to use regression methods to build models and estimate their parameters, seeking stratification strategies in diameter classes for the sample trees. Volume estimates with valid confidence intervals can be obtained using the Spurr model for the studied dry forest. Stratified sampling of the data set for model adjustment and selection is necessary, since we find significant results with mean error square root values and bias of up to 70% of the total database.     

Comparison between vegetation indices for detecting spatial and temporal variabilities in soybean crop using canopy sensors

Precision Agriculture - Crop monitoring through remote sensing techniques enable greater knowledge of average variability in crop growth. Canopy sensors help provide information on the variability...     

Genome-wide in silico analysis of SOD genes in common bean (Phaseolus vulgaris L.)

Journal of Crop Science and Biotechnology - Superoxide dismutases (SODs) are a group of enzymes that play essential roles in catalyzing the dismutation of superoxide radicals to protect cells from...     

Meta-analysis of fungicide efficacy on soybean target spot and cost–benefit assessment

Target spot of soybean has spread in Brazil, the southeastern United States and Argentina in the last decade. A collaborative network of field Uniform Fungicide Trials (UFT) in Brazil was created in 2011 to study the target spot control efficacy of fungicides, including azoxystrobin + benzovindiflupyr (AZ_BF), carbendazim (CZM), fluxapyroxad + pyraclostrobin (FLUX_PYRA), epoxiconazole + FLUX_PYRA (EPO_FLUX_PYRA), mancozeb (MZB) and prothioconazole + trifloxystrobin (PROT_TRIF). Network meta-analysis was used to conduct a quantitative synthesis of UFT data collected from 2012 to 2016 and to evaluate the effects of disease pressure (DP, low ≤ 35% target spot severity in the nontreated control < high) and year of experiment on the overall mean efficacy and yield response to each of the tested fungicides. Based on mean percentage control of target spot severity, the tested fungicides fall into three efficacy groups (EG): high EG, FLUX_PYRA (76.2% control relative to the nontreated control) and EPO_FLUX_PYRA (75.7% control); intermediate EG, PROT_TRIF (66.5% control) and low EG, MZB (49.6% control), AZ_BF (46.7% control) and CZM (32.4% control). DP had a significant effect on yield response. At DP_Low, the highest response was due to PROT_TRIF (+342 kg ha⁻¹, +12.8%) and EPO_FLUX_PYRA (+295.5 kg ha⁻¹, +11.2%), whereas at DP_High, EPO_FLUX_PYRA and FLUX_PYRA outperformed the other treatments, with yield responses of 503 kg ha⁻¹ (+20.2%) and 469 kg ha⁻¹ (+19.1%), respectively. The probability of a positive return on fungicide investment ranged from 0.26 to 0.56 at DP_Low and from 0.34 to 0.66 at DP_High.