8 April 2009 Estimation of moisture and oil content of in-shell nuts with a capacitance sensor using discrete wavelet analysis
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Abstract
Moisture and oil contents are important quality factors often measured and monitored in the processing and storage of food products such as corn and peanuts. For estimating these parameters for peanuts nondestructively a parallel-plate capacitance sensor was used in conjunction with an impedance analyzer. Impedance, phase angle and dissipation factor were measured for the parallel-plate system, holding the in-shell peanut samples between its plates, at frequencies ranging between 1MHz and 30 MHz in intervals of 0.5 MHz. The acquired signals were analyzed with discrete wavelet analysis. The signals were decomposed to 6 levels using Daubechies mother wavelet. The decomposition coefficients of the sixth level were passed onto a stepwise variable selection routine to select significant variables. A linear regression was developed using only the significant variables to predict the moisture and oil content of peanut pods (inshell peanuts) from the impedance measurements. The wavelet analysis yielded similar R2 values with fewer variables as compared to multiple linear and partial least squares regressions. The estimated values were found to be in good agreement with the standard values for the samples tested. Ability to estimate the moisture and oil contents in peanuts without shelling them will be of considerable help to the peanut industry.
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Chari V. Kandala, Jaya Sundaram, K. N. Govindarajan, Chris L. Butts, Jeyam Subbiah, "Estimation of moisture and oil content of in-shell nuts with a capacitance sensor using discrete wavelet analysis", Proc. SPIE 7294, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2009, 72940Z (8 April 2009); doi: 10.1117/12.815385; https://doi.org/10.1117/12.815385
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