Paper
7 October 2014 Analysis of total oil and fatty acids composition by near infrared reflectance spectroscopy in edible nuts
Chari V. Kandala, Jaya Sundaram
Author Affiliations +
Abstract
Near Infrared (NIR) Reflectance spectroscopy has established itself as an important tool in quantifying water and oil present in various food materials. It is rapid and nondestructive, easier to use, and does not require processing the samples with corrosive chemicals that would render them non-edible. Earlier, the samples had to be ground into powder form before making any measurements. With the development of new soft ware packages, NIR techniques could now be used in the analysis of intact grain and nuts. While most of the commercial instruments presently available work well with small grain size materials such as wheat and corn, the method present here is suitable for large kernel size products such as shelled or in-shell peanuts. Absorbance spectra were collected from 400 nm to 2500 nm using a NIR instrument. Average values of total oil contents (TOC) of peanut samples were determined by standard extraction methods, and fatty acids were determined using gas chromatography. Partial least square (PLS) analysis was performed on the calibration set of absorption spectra, and models were developed for prediction of total oil and fatty acids. The best model was selected based on the coefficient of determination (R2), Standard error of prediction (SEP) and residual percent deviation (RPD) values. Peanut samples analyzed showed RPD values greater than 5.0 for both absorbance and reflectance models and thus could be used for quality control and analysis. Ability to rapidly and nondestructively measure the TOC, and analyze the fatty acid composition, will be immensely useful in peanut varietal improvement as well as in the grading process of grain and nuts.
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Chari V. Kandala and Jaya Sundaram "Analysis of total oil and fatty acids composition by near infrared reflectance spectroscopy in edible nuts", Proc. SPIE 9220, Infrared Sensors, Devices, and Applications IV, 92200F (7 October 2014); https://doi.org/10.1117/12.2060891
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KEYWORDS
Near infrared

Data modeling

Calibration

Reflectivity

Absorbance

Absorption

Statistical analysis

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