Investigation on strawberry freshness by rapid determination using an artificial olfactory system

ABSTRACT

In 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%.

KEYWORDS:

• Accuracy
• Artificial olfactory system
• Freshness
• Nonlinear model
• Strawberry

Funding

This work is supported by Research Project of Department of Education of Zhejiang Province (No. Y201534661).

Additional information

Funding

This work is supported by Research Project of Department of Education of Zhejiang Province (No. Y201534661).