A broad diversity survey of Rhizoctonia species from the Brazilian Amazon reveals the prevalence of R. solani AG-1 IA on signal grass and the new record of AG-1 IF on cowpea and soybeans

Leaf blight, sheath blight, and web blight are major diseases caused by Rhizoctonia species on both Fabaceae and Poaceae plant hosts in the Brazilian Amazon agroecosystem. To determine the diversity of Rhizoctonia species associated with foliar diseases on fabaceous (cowpea and soybean) and poaceous (rice and signal grass [Urochloa brizantha]) hosts, a broad survey was conducted in Pará, Rondônia, Roraima, and Mato Grosso, in the Amazon, from 2012 to 2013. We extended our survey to Cerrado areas of Mato Grosso, and the lowlands of Paraíba Valley, in São Paulo, where these Rhizoctonia foliar diseases have not been reported so far. Our findings revealed that these diseases are caused by a diversity of Rhizoctonia solani AG-1 complex. We detected that R. solani AG-1 IA (sexual phase Thanatephorus cucumeris) was the predominant pathogen associated with signal grass leaf blight and collar rot diseases in the Amazon, especially in Rondônia and northern Mato Grosso. In addition, a subgroup of R. solani (AG-1 IF), not previously reported in Brazil, was associated with leaf blight on cowpea and soybean, in Roraima. Another subgroup (AG-1 ID) was also detected in Roraima. In Mato Grosso Cerrados we did not find any of the major Rhizoctonia foliar pathogens. Instead, R. oryzae (Waitea circinata) was the predominant species associated with a collar rot on U. brizantha. In the lowlands of São Paulo, R. oryzae-sativae (Ceratobasidium oryzae-sativae) was the predominant pathogen detected causing the rice sheath spot disease.     

Evaluation of cytochrome b as a sensitive target for PCR based detection of T. annulata carrier animals

Bovine tropical theileriosis, caused by the tick-borne protozoan Theileria annulata, imposes a serious constraint upon breed improvement programmes and livestock production in tropical and sub-tropical regions of the world. Animals that recover from primary infection serve as carriers and play a critical role in the epidemiology of the disease, acting as reservoirs of infection. However, conclusive identification of carrier animals can be problematic. This study describes assessment of candidate target genes for PCR assay-based detection of T. annulata infected carrier animals. Following in silico screening and rejection of three major multi-copy gene families, an assay based on PCR amplification of a 312 bp segment of the T. annulata gene for cytochrome b (Cytob1 assay) was established. Sensitivity was evaluated using serial dilutions of blood obtained from experimentally infected calves, while specificity was confirmed by testing DNA representing twelve different T. annulata stocks and other Theileria and Babesia species. Direct comparison with other target genes and published data indicated that Cytob1 PCR-based assays provide the greatest level of sensitivity, combined with a high level of specificity and the ability to detect different T. annulata genotypes. It can be concluded that the cytochrome b gene is the optimal target for PCR amplification and its incorporation in a Reverse Line Blot Assay offers the most sensitive method yet devised to detect the parasite in carrier animals. The use of this assay will increase the accuracy of epidemiological studies aimed at improving disease control in endemically unstable regions.     

External quality assurance system for antibiotic resistance in bacteria of animal origin in Europe (ARBAO-II), 2003

Initiated in 2003 by the European Union, ARBAO-II aims to establish a monitoring of antimicrobial susceptibility among the veterinary laboratories in all European countries based on validated methodologies. This includes an external quality control system for the most important bacterial pathogens. In 2003 two trials were performed. The first on Salmonella and Escherichia coli involved 31 laboratories in 18 countries and the second on Staphylococcus and Streptococcus included 22 laboratories in 15 countries. For the E. coli strains, 92.8% of the results complied with the reference MICs, for Salmonella 93.7%, for Streptococcus 80.4% and for Staphylococcus 93.1%. Most problems were observed when testing florfenicol (79.2% correct), gentamicin (84.2%) and amoxicillin + cl (84.9%) in E. coli; streptomycin in Salmonella (62.5%); gentamicin (56.7%), lincomycin (71.4%), clindamycin (75.4%), TMP + sulfonamides (75.7%) and chloramphenicol (78.5%) in Streptococcus; erythromycin (81.5%) and oxacillin (78.2.5%) in Staphylococcus. A few laboratories caused most deviations. However, there was no correlation between good performance for one bacterial group and good performance for other groups. This study showed that most laboratories are capable of performing correct susceptibility testing for E. coli and Salmonella, even though performance of some laboratories can be improved, and that some problems exist for Staphylococcus and Streptococcus. This clearly shows the need for continuous harmonisation of methodologies within the EU.     

Does post‐anthesis heat stress affect plant phenology,physiology, grain yield and protein content of durum wheat in a semi‐arid Mediterranean environment?

Increasing air temperature due to changing climate is projected to decrease the length of the growing season, hasten vegetative development and maturation, and ultimately affect yield of many C3 crops. Previous multilocation trials highlighted strong relationships between thermal trends in the interval “beginning of flowering‐end of grain filling” and grain yield, and protein content in durum wheat (Triticum turgidum subsp. durum (Desf.) Husn.). With the aim to confirm these relationships, nine durum wheat genotypes, including old (Capeiti 8, Senatore Cappelli and Trinakria) and modern (Amedeo, Arcangelo, Mongibello, Simeto, and Svevo) varieties and a Sicilian landrace (Russello) were grown at three different sites representing a climate gradient in Sicily, Italy. Moreover, the effect of post‐anthesis heat stress on these durum wheats was further investigated in two contrasting environments: open‐field (control—C) and greenhouse heat stress (HS). HS shortened the interval “beginning‐end of flowering” of 1.5 days across genotypes, and the “end of flowering‐beginning of grain filling” and maturation of 4.9 days, with a range of 1 day in Arcangelo to 11 days in Cappelli. Advances in main phenophases significantly decreased kernel weight (KW) and grain yield (GY), whereas grain protein content (PC) increased. As expected, a negative relationship was observed between GY and PC, while positive relationships were found for GY and grain‐filling duration (GFD), and GY and KW. Genotypes responded differently to heat stress, as evidenced by the net photosynthesis, transpiration rate, instantaneous water use efficiency and dry matter accumulation in kernels. Genotypes were ranked according to the heat susceptibility index (HSI): Amedeo, Arcangelo, Capeiti 8, Svevo and Trinakria resulted heat‐tolerant. These varieties were characterized by an early trigger of dry matter accumulation in kernels under HS (Amedeo, Arcangelo and Trinakria), or showed similar length of the GFD (Capeiti 8) between environments. The multilocation trial confirmed a negative relationship between maximum temperatures and grain yield, and a positive relationship between minimum temperatures and protein content during grain–filling periods. Research focusing on agronomic strategies, phenology and breeding for tolerance to heat stress is of strategic importance to cope with the detrimental effect of global warming in semi‐arid climates.     

Bayesian hierarchical modelling to enhance the epidemiological value of abattoir surveys for bovine fasciolosis

Four classes of Bayesian hierarchical models were evaluated using an historical dataset from an abattoir survey for fasciolosis conducted in Victoria, Australia. The purpose of this analysis was to identify areas of high prevalence and to explain these in terms of environmental covariates. The simplest of the Bayesian models, with a single random effect, validated the use of smoothed maps for cartographic display when the sample sizes vary. The model was then extended to partition the random effect into spatially structured and unstructured components, thus allowing for spatial autocorrelation. Rainfall, irrigation, temperature-adjusted rainfall and a remotely sensed surrogate for rainfall, the normalised difference vegetation index (NDVI), were then introduced into the models as explanatory variables. The variable that best explained the observed distribution was irrigation. Associations between prevalence and both rainfall and NDVI that were significant in fixed effects models were shown to be due to spatial confounding. Nevertheless, provided they are used cautiously, confounded variables may be valid predictors for the prevalence of disease.