An artificial intelligence approach for identification of microalgae cultures.

In this work, a model for the characterization of microalgae cultures based on artificial neural networks has been developed. The characterization of microalgae cultures is essential to guarantee the quality of the biomass, and the objective of this work is to achieve a simple and fast method to address this issue. Data acquisition was performed using FlowCam, a device capable of capturing images of the cells detected in a culture sample, which are used as inputs by the model. The model can distinguish between 6 different genera of microalgae, having been trained with several species of each genus. It was further complemented with a classification threshold to discard unwanted objects while improving the overall accuracy of the model. The model achieved an accuracy of up to 97.27% when classifying a culture. The results demonstrate the effectiveness of the Deep Learning models for the characterization of microalgae cultures, it being a useful tool for the monitoring of microalgae cultures in large-scale production facilities while providing accurate characterization over a wide range of genera.

Immunodetection of Furcraea Necrotic Streak Virus-FNSV in fique plants (Furcraea macrophylla Baker) using a polyclonal antibody IgY produced in chicken egg yolk.

The necrotic streak of the fique (Furcraea spp.) or "Macana" disease is considered the most limiting disease for this crop in Colombia, whose causal agent is the Furcraea Necrotic Streak Virus - FNSV (RNA+). Currently, there are no strategies to control the disease, being necessary to develop methods for detection of this pathogen in the planting material before being taken to the field. In this study, polyclonal antibodies produced in egg yolk (IgY) were produced and assesses for detection FNSV. Two immunoenzymatic methodologies were standardized: dot blot immunobinding assay (DBIA) and enzyme-linked immunosorbent assay (ELISA), determining their specificity and sensitivity. The detection limit by DBIA corresponded to 8 µg/mL of purified virus suspension using 10 µg/mL of primary antibody. In the ELISA test, the primary antibody concentration of 3 µg/mL (1:800 dilution) detected the antigen at concentrations between 10 and 70 µg/mL. The polyclonal antibody anti-FNSV IgY allowed the detection of FNSV in samples of purified virus and extracts of roots and leaves of fique plants with symptoms of "Macana" disease and did not produce any signal with the control samples. Results showed the potential of using egg yolk IgY in immunological tests for the detection of FNSV in fique plants.