Effect of Immobilized Nitrifying Bacterial Consortium on Ammonia Biodegradation in Aquaculture Pond and Enhanced Growth of Labeo rohita: An In Vitro and In Vivo Studies

Efficacy of Saccharothrix algeriensis NRRL B-24137 to suppress Fusarium oxysporum f.sp. vasinfectum induced wilt disease in cotton

Fusarium cotton wilt is a devastating disease of the cotton crop throughout the world, caused by Fusarium oxysporum f.sp. vasinfectum (FOV). Chemical control has many side effects, so, biological controls have been widely used for the management of Fusarium wilt. This study aimed to investigate the possible use of an actinomycetes Saccharothrix algeriensis (SA) NRRL B-24137 to control FOV. To access in-vitro anti-Fusarium ability of SA NRRL B-24137, dual culture assay, spore germination and seed germination tests were carried out. Following in-vitro investigations, several pot tests in a greenhouse environment were used to evaluate the biological control potential of SA NRRL B-24137 against FOV. Dual culture assay and spore germination revealed that SA NRRL B-24137 showed significant anti-Fusarium activity.During spore germination 87.77% inhibition of spore germination were observed. In pot experiments, SA NRRL B-24137 primed cotton seeds resulted in a 74.0% reduction in disease incidence. In soil there was a significant reduction in FOV spores in the presence of SA NRRL B-24137. Positive correlation was also observed on different concentrations of SA NRRL B-24137 towards FOV reduction. The results of this study showed that SA NRRL B-24137 has the potential to be employed as a biocontrol agent against Fusarium cotton wilt, improving cotton growth characteristics and yield.

Long-term post-storage reactivation of a nitrifying sludge in a sequential batch reactor: physiological and kinetic evaluation

Production, preservation and recovery of sludge with stabilized nitrifying activity over long time can be difficult. Information on the ability of nitrifying sludge to regain its nitrifying activity after long-term storage is still scarce. In this work, the physiological and kinetic changes during the reactivation and stabilization of a nitrifying sludge previously exposed to ampicillin (AMP) were evaluated in a sequential batch reactor (SBR) after its long-term storage (1 year) at 4 °C. After storage, both ammonium and nitrite oxidizing processes were slow, being nitrite oxidation the most affected step. During the reactivation stage (cycles 1-6), physiological and kinetic activity of the nitrifying sludge improved through the operating cycles, in both its ammonium oxidizing and nitrite oxidizing processes. At the end of the reactivation stage, complete nitrifying activity was achieved in 10 h, reaching ammonium consumption efficiencies (ENH4 +) close to 100% and nitrate yields (YNO3 -) of 0.98 mg NO3 --N/mg NH4 +-N consumed without nitrite accumulation. During the stabilization stage (cycles 7-17), results indicated that the sludge could maintain a steady-state respiratory process with restoration percentages of 100% for nitrifying specific rates (qNH4 + and qNO3 -) with respect to their values obtained before storage. Furthermore, during the addition of 15 mg AMP/L (cycles 18-21), the sludge preserved its metabolic capacity to biodegrade 90% of AMP in 2 h. Therefore, long-term storage of nitrifying sludge could be used to preserve nitrifying inocula as bioseeds for bioremediation and bioaugmentation strategies.

Face emotion recognition based on infrared thermal imagery by applying machine learning and parallelism

Over time for the past few years, facial expression identification has been a promising area. However, darkness, lighting conditions, and other factors make facial emotion identification challenging to detect. As a result, thermal images are suggested as a solution to such problems and for a variety of other benefits. Furthermore, focusing on significant regions of a face rather than the entire face is sufficient for reducing processing and improving accuracy at the same time. This research introduces novel infrared thermal image-based approaches for facial emotion recognition. First, the entire image of the face is separated into four pieces. Then, we accepted only four active regions (ARs) to prepare training and testing datasets. These four ARs are the left eye, right eye, and lips areas. In addition, ten-folded cross-validation is proposed to improve recognition accuracy using Convolutional Neural Network (CNN), a machine learning technique. Furthermore, we incorporated a parallelism technique to reduce processing-time in testing and training datasets. As a result, we have seen that the processing time reduces to 50%. Finally, a decision-level fusion is applied to improve the recognition accuracy. As a result, the proposed technique achieves a recognition accuracy of 96.87 %. The achieved accuracy ascertains the robustness of our proposed scheme.

Water quality assessment of East Kolkata Wetland with a special focus on bioremediation by nitrifying bacteria

East Kolkata Wetlands (EKW) is designated as International Ramsar site and are the hotspot for large-scale wastewater aquaculture practices. However, the continued surveillance of physicochemical properties of water and application of an eco-friendly approach are essential to ensure safe aquaculture practices. In the present study, we assessed the seasonal variation in physicochemical parameters of water across EKW and investigated the role of nitrifying bacteria as probiotics. We statistically analyzed various physicochemical properties of water samples from EKW. Results of the statistical analysis indicated a significant variation in all the physicochemical parameters across the selected water bodies of EKW (p < 0.01). We isolated and enumerated Nitrosomonas sp. and Nitrobacter sp. and assessed their ability to degrade trichloroethylene (TCE). The role of Nitrosomonas sp. and Nitrobacter sp. were further investigated and established through a small-scale experiment. Two microbial isolates, NSW3 and NBW2, displayed superior TCE degradation ability at pH 5, and the application of these strains as probiotics were found to improve the quality of water and survival rate of fishes in the treated experimental tanks. Our findings suggest that the application of the above mixed bacterial cultures in aquaculture could be an effective and environment-friendly approach for safe and productive aquaculture operations.