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15. Phenotypic characterization and genome analysis reveal the probiotic potential of a banyan endophyte Bacillus velezensis K1.

Author

Soni, Riteshri, Keharia, Hareshkumar, Shah, Krina, and Jain, Neeraj

Subjects
BACILLUS (Bacteria), PROBIOTICS, ESCHERICHIA coli, PANTOTHENIC acid, VITAMIN B2, PHENOTYPES, GENOMES, VITAMIN B1
Abstract

Aim The current study aimed to scrutinize the probiotic traits and safety aspects of Bacillus velezensis K1 through experimental and supporting genome studies. Methods and Results The seven cultures previously isolated from the aerial roots of Ficus benghalensis were initially screened for their antibacterial activity as well as acid and bile tolerance. The isolate K1 was found to be the most potent and was further investigated for probiotic traits and safety. K1 showed tolerance to simulated digestive juices and 0.3% bile. It showed notable aggregation, cell surface hydrophobicity, and adherence to HT-29 cells. K1 significantly prevented the adhesion of E. coli O157: H7 and S. enterica ATCC 13076 to HT-29 in cell culture assays. K1 could hydrolyze phytate and complex polysaccharides. The genes related to stress tolerance, adhesion, antimicrobial activity, and production of vitamins, viz. thiamine, riboflavin, pyridoxine, pantothenic acid, folate, and biotin were annotated in the K1 genome. K1 was found to be non-hemolytic, noncytotoxic, as well as susceptible to antibiotics. No virulence or toxin-encoding genes were identified in its genome. Conclusions B. velezensis K1 is a prospective probiotic with the ability to tolerate gastrointestinal stress, adhere to intestinal surfaces, and inhibit enteropathogens. [ABSTRACT FROM AUTHOR]

Published
2023
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23. Expiry Prediction and Reducing Food Wastage using IoT and ML

Author

Nair, Kartik, Sekhani, Bhavya, Shah, Krina, Karamchandani, Sunil, Nair, Kartik, Sekhani, Bhavya, Shah, Krina, and Karamchandani, Sunil

Abstract

This paper details development of a low-cost, small-size, and portable electronic nose (E-nose) for the prediction of the expiry date of food products. The Sensor array is composed of commercially available metal oxide semiconductors sensors like MQ2 sensor, temperature sensor, and humidity sensor, which were interfaced with the help of ESP8266 and Arduino Uno for data acquisition, storage, and analysis of the dataset consisting of the odor from the fruit at different ripening stages. The developed system is used to analyze gas sensor values from various fruits like bananas and tomatoes. Responding signals of the e-nose were extracted and analyzed. Based on the obtained data we applied a few machine learning algorithms to predict if a banana is stale or not. Logistic regression, Decision Tree Classifier, Support Vector Classifier (SVC) & K-Nearest Neighbours (KNN) classifiers were the binary classification algorithms used to determine whether the fruit became stale or not. We achieved an accuracy of 97.05%. These results prove that e-nose has the potential of assessing fruits and vegetable freshness and predict their expiry date, thus reducing food wastage.

Published
2021

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