Development of a low cost optimized handheld embedded odor sensing system (HE-Nose) to assess ripeness of oranges

Presented work addresses the development and application of artificial olfactory (e-nose) as an efficient nondestructive handheld system to extract quality attributes of variety of orange cultivars at various cultivated lands. An ARM-9 (S3C2440 controller) based advance embedded electronic nose system has been developed for on-site odor acquisition, processing and ripeness level prediction for various orange cultivars. Developed handheld electronic nose system is light weight, low power, and easy operable to every consumer. Various statistical multivariate data analysis techniques (PCA, LDA, QDA, and KNN) implementation on electronic nose measurements helped estimating optimal harvest dates for various orange cultivars. Developed handy system has been optimized in the sense of selectivity, sensitivity of gas sensors using the implementation of temperature control for heating element of the gas sensors. Various temperature, humidity models also have been developed to improve the performance of developed system in different environmental conditions. Data acquisition process has been performed using developed system for 100 orange samples have two different cultivars (mandarin and sweet orange). Extracted parameters have been subjected towards supervised Levenberg–Marquardt back-propagation algorithm to training and testing of developed handheld electronic nose system to predict quality parameters of oranges. A good correlation has been found between developed handheld electronic nose system signals and quality attributes indicators and it shows that system can successfully detect and predict various quality parameters of orange samples. Results of developed handheld electronic nose system have been validated with commercial standard electronic nose Alpha Fox 3000 system and it has been observed that efficiency varies around 94 ± 0.3 %.

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