The ripeness of oil palm fruits is one of the key factors for crude palm oil qualities. Recently, electronic nose systems have been developed intensively for fruit quality assessment which relates odors to ripeness levels. This study developed an electronic nose system to characterize the ripeness levels of oil palm fruits using output voltage of each sensor and fruit hardness. The system consisted of a sensor chamber and a sample chamber. The sensor chamber consisted of eight MOS gas sensor modules of MQ series. Samples were oil palm fruits taken from oil palm fresh fruit bunches (FFB) which were previously categorized traditionally into unripe, ripe, over ripe, peeled and put into the sample chamber. Some of the fruits were also used for hardness measurement. To quantify the output voltages for each sensor, integrated trapezoid areas were calculated and related to the fruit hardness values. The results showed a significant voltage difference of each sensor for the three ripeness levels. Only four out of eight sensors showed significantly higher voltages. Three sensors which can significantly differentiate the ripeness levels are MQ3, MQ5, and MQ135 which MQ135 is the best. This shows that the electronic nose is potential for oil palm fruits. Keywords: electronic nose, fruit hardness, MOS gas sensor, oil palm fruit, ripeness
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.