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United States Department of Agriculture

Agricultural Research Service

Research Project: POST HARVEST MEASUREMENT AND MANAGEMENT SYSTEMS TO IMPROVE PEANUT QUALITY AND US COMPETITIVENESS

Location: Peanut Research

Title: NIR reflectance spectroscopic method for nondestructive moisture content determination of in-shell peanuts

Authors
item Kandala, Chari
item Govindarajan, K -
item Subbiah, J -

Submitted to: Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE)
Publication Type: Abstract Only
Publication Acceptance Date: June 1, 2009
Publication Date: June 1, 2009
Citation: Kandala, C., Govindarajan, K.N., Subbiah, J. 2009. NIR reflectance spectroscopic method for nondestructive moisture content determination of in-shell peanuts. Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE).

Interpretive Summary: none required.

Technical Abstract: Most of the commercial instruments presently available to determine the moisture content (MC) of peanuts need shelling and cleaning of the peanut samples, and in some cases some sort of sample preparation such as grinding. This is cumbersome, time consuming and destructive. It would be useful if the MC of the peanuts could be measured on the in-shell peanuts itself rapidly and nondestructively, particularly at the peanut buying points, where MC of the peanuts is an important factor in fixing the sale price. An NIR reflectance method is presented here by which the average MC of about 100 g of in-shell peanuts could be determined rapidly and nondestructively. The MC range of the peanut kernels tested was between 8% and 26%. NIR reflectance measurements were made at 1 nm intervals in the wavelength range of 1000 nm to 1800 nm and the spectral data was modeled using partial least squares regression (PLSR). 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 1680 nm (which is the no absorbance wavelength for water), and absorbance transformation. From these, a suitable model was selected based on model fitness measures. Predicted values of the samples tested in the above range were compared with the values determined by the standard air-oven method. The predicted values agreed well with the air-oven values with an R2 value of 0.91 and a standard error of prediction (SEP) of 1.37 for averaged spectra and an R2 value of 0.88 and SEP value of 1.55 for individual spectra. Both methods of analysis performed satisfactorily and being rapid, nondestructive and non-contact, may also be suitable for continuous monitoring of MC of in-shell peanuts as they move on conveyor belts during their processing.

Last Modified: 4/24/2014
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