Development of a Smart Sensor Array for Adulteration Detection in Black Pepper Seeds using Machine Learning

Black pepper is an expensive commodity with a high risk of adulteration. Ground papaya seed the main adulterant in because it cannot be discriminated visually. There are few destructive methods. Since costlier, non-destructive method adulteration must but challenging one. The existing uses costlier equipment, bulky, involve laboratory-based testing, time consuming process. To overcome above issues, this article presents development Non-destructive E- nose gas sensor for detection. This system determines VOC controlled environment. proposed utilizes MQ2 and MQ3 arrays to identify Volatile Organic Compounds present seeds discriminate non-adulterant sample. data utilized perform qualitative analysis determine using support vector machine learning algorithm. Support Vector Machine algorithm outperforms comparison methods 100% classification accuracy. Conclusion: developed connected internet via IoT application model show results on web pages enables access by authenticated user from anywhere. Client server MQTT protocol used developing application.