JST  Vol.2 No.1 , March 2012
Sensing of Moisture Content of In-Shell Peanuts by NIR Reflectance Spectroscopy
ABSTRACT
It was found earlier that moisture content (MC) of intact kernels of grain and nuts could be determined by Near Infra Red (NIR) reflectance spectrometry. However, if the MC values can be determined while the nuts are in their shells, it would save lot of labor and money spent in shelling and cleaning the nuts. Grain and nuts absorb low levels of NIR, and when NIR radiation is incident on them, a substantial portion of the radiation is reflected back. Thus, studying the NIR reflectance spectra emanating from in-shell peanuts, an attempt is made for the first time to determine the MC of in-shell peanuts. In-shell peanuts of two different market types, Virginia and Valencia, were conditioned to different moisture levels between 6% and 26% (wet basis), and separated into calibration and validation groups. NIR absorption spectral data from 1000 nm to 2500 nm in 1 nm intervals were collected from both groups. Measurements were obtained on 30 replicates within each moisture level. Reference MC values for each moisture level in these groups were obtained using standard air-oven method. Partial Least Square (PLS) analysis was performed on the calibration data, and prediction models were developed. The Standard Error of Calibration (SEC), and R2 of the calibration models were computed to select the best calibration model. The selected models were used to predict the moisture content of peanuts in the validation sets. Predicted MC values of the validation samples were compared with their standard air-oven moisture values. Goodness of fit was determined based on the lowest Standard Error of Prediction (SEP) and highest R2 value obtained for the prediction models. The model, with reflectance plus normalization spectral data with an SEP of 0.74 for Valencia and 1.57 for Virginia type in-shell peanuts was selected as the best model. The corresponding R2 values were 0.98 for both peanut types. This work establishes the possibility of sensing MC of intact in-shell peanuts by NIR reflectance method, and would be useful for the peanut and allied industries.

Cite this paper
J. Sundaram, C. V. Kandala, K. Govindarajan and J. Subbiah, "Sensing of Moisture Content of In-Shell Peanuts by NIR Reflectance Spectroscopy," Journal of Sensor Technology, Vol. 2 No. 1, 2012, pp. 1-7. doi: 10.4236/jst.2012.21001.
References
[1]   USDA, “AMS Farmers Stock Peanut Inspection Instructions,” Washington DC, 2000.

[2]   R. Rachaputi, “Primary Industries and Fisheries,” 2010. www.dpi.qld.gov.au/26_11899.htm

[3]   K. H. Norris and W. L. Butler, “Techniques for Obtaining Absorption Spectra on Intact Biological Samples,” Transactions on Bio-Medical Electronics, Vol. 8, No. 1, 1961, pp. 153-157. doi:10.1109/TBMEL.1961.4322890

[4]   K. H. Norris and I. R. Hart, “Principles and Methods of measuring Moisture Content in Liquids and Solids,” Reinhold, New York, 1965, pp. 19-25.

[5]   K. H. Norris, “Early History of Near Infrared for Agricultural Applications,” NIR News, Vol. 3, 1992, pp. 12- 13.

[6]   K. N. Govindarajan, C. V. K. Kandala and J. Subbiah, “NIR Reflectance Spectroscopy for Nondestructive Moisture Content Determination in Peanut Kernels,” Transactions of the ASABE, Vol. 52, No. 5, 2009, pp. 1661-1666.

[7]   D. Cozzolino, M. J. Kwiatkowski, R. G. Dambergs, W. U. Cynkar, L. J. Janik, G. Skouroumounis and M. Gishen, “Analysis of Elements in Wine Using Near Infrared Spectroscopy and Partial Least Squares Regression,” Talanta, Vol. 74, No. 4, 2008, pp. 711-716. doi:10.1016/j.talanta.2007.06.045

[8]   S. Nimaiyar, M. R. Paulsen and R. L. Nelson, “Rapid Analysis of Fatty Acids in Soybeans Using FTNIR,” ASABE Paper No. 046118, 2004.

[9]   B. Pérez-Vich, L. Velasco and J. M. Fernández-Martínez, “Determination of Seed Oil Content and Fatty Acid Composition in Sunflower through the Analysis of Intact Seeds, Husked Seeds, Meal and Oil by Near-Infrared Reflectance Spectroscopy,” Journal of the American Oil Chemists’ Society, Vol. 75, No. 5, 1998, pp. 547-555. doi:10.1007/s11746-998-0064-1

[10]   L. Velasco and H. C. Becker, “Estimating the Fatty Acid Composition of the Oil in Intact Seed Rapeseed (Brassica napus L.) by Near Infrared Reflectance Spectroscopy,” Euphytica, Vol. 101, No. 2, 1998, pp. 221-230. doi:10.1023/A:1018358707847

[11]   J. K. Daun, K. M. Clear and P. Williams, “Comparison of Three Whole Seed near Infrared Analyzers for Measuring Quality Components of Canola Seed,” Journal of the American Oil Chemists’ Society, Vol. 71, No. 10, 1994, pp. 1063-1068. doi:10.1007/BF02675897

[12]   R. S. Bhatty, “Measurement of Oil in Whole Flaxseed by Near-Infrared Reflectance Spectroscopy,” Journal of the American Oil Chemists’ Society, Vol. 68, No. 1, 1991, pp. 34-38. doi:10.1007/BF02660306

[13]   B. L. Tillman, D. W. Gorbet and G. Person, “Predicting Oleic and Linoleic Acid Content of Single Peanut Seeds Using Near-Infrared Reflectance Spectroscopy,” Crop Science, Vol. 46, No. 5, 2006, pp. 2121-2126. doi:10.2135/cropsci2006.01.0031

[14]   M. Iwamoto and S. Kawano, “Advantages and Disadvantages of NIR Applications for the Food Industry,” In: I. Murray and I. A. Cowe, Eds., Making Light Work: Advances in Near Infrared Spectroscopy, VCH, Weinheim, 1992, pp. 367-375.

[15]   ASAE, “Moisture Measurement—Un-Ground Grain and Seeds,” 37th Edition, ASABE, St. Joseph, 1990.

 
 
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