Abstract
ABSTRACTIn this paper, strawberry freshness forecasting performed using artificial olfactory system (AOS) was investigated. Human sensory evaluation (HSE), firmness, total soluble sugar (TSS), and reducing sugar content (RSC) of the samples were examined to provide physical/chemical references for the AOS system. AOS responses to strawberry samples were measured and measurement data were analyzed by principal component analysis (PCA) and stochastic resonance (SR). Experimental results indicated that the PCA method qualitatively discriminated strawberry samples in different freshness levels. The strawberry freshness forecasting model was established based on AOS. The forecasting model successfully discriminated strawberry samples with regression coefficients of R2 = 0.98159. Validating experiment results indicated that the developed model using AOS presented a predictive accuracy of 92%.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
