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Nondestructive moisture content determination of three different market type in-shell peanuts using near infrared reflectance spectroscopy

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Abstract

A near infrared reflectance (NIR) method is presented here by which the average moisture content (MC) of about 100 g of in-shell peanuts could be determined rapidly and nondestructively. MCs of three market type peanuts, Runners, Valencia and Virginia were determined by this method while the peanuts were in their shells (in-shell peanuts). The MC range of the peanuts tested was between 6 and 26 %. NIR reflectance measurements were made at 1 nm intervals in the wavelength range of 1,000–1,800 nm and the spectral data was modeled using partial least squares regression analysis. Eight different models were developed by utilizing different data preprocessing methods such as, Norris-Gap first derivative with a gap size of 3, peak normalization with 1,680 nm (which is the no absorbance wavelength for water), and transformation from reflectance to absorption. Applying model fitness measures, a suitable model was selected out of these. Predicted values of the samples tested were compared with the values determined by the standard air-oven method. The predicted values agreed well with the air-oven values with an R 2 value better than 0.93 for all three types of in-shell peanuts. This method being rapid, nondestructive, and non contact, may be suitable for measuring and monitoring MCs of different types of peanuts, while they are in their shells itself, in the peanut industry.

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Notes

  1. Moisture content is expressed in % wet basis throughout this paper.

  2. Mention of company or trade names is for the purpose of description only and does not imply endorsement by the US Department of Agriculture.

  3. SEC = \( \left( {\frac{1}{n - p - 1}\sum\limits_{i = 1}^{n} {{\text{e}}_{i}^{2} } } \right)^{\frac{1}{2}} \) where n is the number of observations, p is the number of variables in the regression equation with which the calibration is performed, and ei is the difference between the observed and reference value for the ith observation.

  4. SEP = \( \left( {\frac{1}{n - 1}\sum\limits_{i = 1}^{n} {({\text{e}}_{i} - {\bar{\text{e}}})^{2} } } \right)^{\frac{1}{2}} \) where n is the number of observations, ei is the difference in the moisture content predicted and that determined by the reference method for the ith sample, and \( {\bar{\text{e}}} \) is the mean of ei for all of the samples.

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Authors and Affiliations

  1. National Peanut Research Laboratory, ARS, USDA, Dawson, GA, 39842, USA

    Chari V. Kandala & Jaya Sundaram

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  1. Chari V. Kandala
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  2. Jaya Sundaram
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Correspondence to Chari V. Kandala.

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Kandala, C.V., Sundaram, J. Nondestructive moisture content determination of three different market type in-shell peanuts using near infrared reflectance spectroscopy. Food Measure 8, 132–141 (2014). https://doi.org/10.1007/s11694-014-9173-8

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  • DOI: https://doi.org/10.1007/s11694-014-9173-8

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