Nano Green uses Machine Learning approach with Deep Learning techniques in differentiating gold and silver nanoparticles biosynthesized, using plant extract based on its SPR (Surface Plasmon Resonance). The colour of the solution and SEM images for the same was generated using augmentation technique. This image will be highly useful in finding out the approximate size of nanoparticles in the sample which can be explored during the optimization of the nanoparticle by various parameters like pH, Temperature, and many more which would otherwise require a lot of SEM analysis to be done.
Bacterial Colony Count uses Computer Vision OpenCV for counting bacterial colonies for different procedures accurately. Counting bacterial colonies on agar plates is a crucial but laborious task, that is prone to manual errors. A photograph/picture of the plate will deliver/give an accurate count of colonies and CFU/ml value on the addition of the dilution factor and volume plated.
Blue White Screening is an effective and rapid method for determination of transformed bacteria. Counting of white (transformed) and blue (non-transformed) colonies is essential for determining transformation efficiency. Manual counting of colonies of agar plates is prone to errors and is a tedious task. Hence, a software was developed using Computer Vision OpenCV. The software differentiates between blue and white colonies and counts them along with the calculation of transformation efficiency.
The products were developed with the suggestions and support of Ms. Sneha Nayak and Ms. Louella Concepta Goveas, Asst. Professors, Dept. of Biotechnology, NMAMIT, Nitte.
Dr. Niranjan N Chiplunkar, Principal, NMAMIT congratulated the team for carrying out this interdepartmental research activity.
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