Infectious sporadic bovine abortions: retrospective analysis.

Infectious sporadic abortions in cattle are mainly caused by opportunistic bacteria and fungi usually present in environmental or gastrointestinal and reproductive microbiota of healthy animals. A retrospective analysis was carried out to evaluate the main opportunistic microorganisms involved in bovine abortions recorded at INTA Balcarce (Argentina) from 1997 to 2023, accounting for 2.2% of the total diagnosed etiologies of bovine abortion. The opportunistic agents identified as the cause of abortion in 29 fetuses were bacteria (90%) and fungi (10%). Escherichia coli (n = 8), Trueperella pyogenes (n = 5), and Histophilus somni (n = 4) were the bacterial species most often identified as causing infectious abortions, whereas Aspergillus spp. (n = 3) was implicated in all fungal abortions identified. Pure culture of bacteria or fungus was achieved from abomasal content and/or lung essential. Main microscopic findings were bronchopneumonia, myo- and epicarditis, meningitis, and portal hepatitis. Herein, we highlight the importance of detecting potential infectious bacteria in cultures to improve etiological diagnosis of bovine abortions associated with compatible microscopic findings to confirm the etiology.

Assessing the Efficiency of Phenotyping Early Traits in a Greenhouse Automated Platform for Predicting Drought Tolerance of Soybean in the Field.

Conventional field phenotyping for drought tolerance, the most important factor limiting yield at a global scale, is labor-intensive and time-consuming. Automated greenhouse platforms can increase the precision and throughput of plant phenotyping and contribute to a faster release of drought tolerant varieties. The aim of this work was to establish a framework of analysis to identify early traits which could be efficiently measured in a greenhouse automated phenotyping platform, for predicting the drought tolerance of field grown soybean genotypes. A group of genotypes was evaluated, which showed variation in their drought susceptibility index (DSI) for final biomass and leaf area. A large number of traits were measured before and after the onset of a water deficit treatment, which were analyzed under several criteria: the significance of the regression with the DSI, phenotyping cost, earliness, and repeatability. The most efficient trait was found to be transpiration efficiency measured at 13 days after emergence. This trait was further tested in a second experiment with different water deficit intensities, and validated using a different set of genotypes against field data from a trial network in a third experiment. The framework applied in this work for assessing traits under different criteria could be helpful for selecting those most efficient for automated phenotyping.