Submitted to: Journal of the American Oil Chemists' Society
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 6, 2010
Publication Date: April 30, 2010
Repository URL: http://dx.doi.org/10.1007/s11746-010-1589-7
Citation: Sundaram, J., Kandala, C., Holser, R., Windham, W., Butts, C.L. 2010. Determination of In-shell Peanuts Moisture, Oil and Fatty Acids Composition Using Near Infrared Reflectance Spectroscopy. Journal of the American Oil Chemists' Society. 87(10). DOI10.1007/s11746-1589-7. Interpretive Summary: Moisture, total oil and fatty acids of the peanut play important role in peanut quality. A device which can measure these rapidly and nondestructively is very useful in quality assessment. Techniques using near infrared (NIR) spectroscopy for food quality measurements are becoming more popular in food processing and inspection of agricultural commodities. NIR spectroscopy has several advantages over conventional physical and chemical analytical methods of food quality analysis. It is a rapid and non destructive method and provides more information about the components and chemical structure of food products. It can be used to measure several parameters simultaneously. In this work a Foss NIR spectroscope was used to measure the total oil and fatty acids of peanuts. Peanuts of Virginia type were used. Before collecting the NIR spectrum of the conditioned samples, total oil and fatty acids were determined using standard methods, with three replicates. These samples were then separated into two different groups, one for calibration and the second for validation. To collect the NIR spectrum peanut samples from each group were placed in a rectangular sample cup with a transparent glass base. Light was allowed to fall on the sample from the bottom of the sample cup and the light reflected by the samples was collected. This was repeated on 30 samples. Several pretreatments were done on the collected data from both calibration and validation groups. PLS analysis was then carried on the calibration groups to develop models for the individual pretreatments. These models were tested on the validation groups to predict the total oil and fatty acids of the peanuts. Predicted values of the total oil and fatty acids were compared with their reference values determined by the standard methods.
Technical Abstract: Oil and moisture content of peanuts are important factors in peanut grading. A method that could rapidly and nondestructively measure these parameters for in-shell peanuts would be extremely useful. NIR reflectance spectroscopy was used to analyze the moisture, total oil and fatty acid content of Virginia and Valencia types of in-shell peanuts. NIR absorbance spectra were collected in the wavelength range from 400nm to 2500 nm using a NIR instrument. Average values of moisture and total oil contents of all samples were determined by standard air-oven and Soxtec methods, respectively. Fatty acids were converted to the corresponding methyl esters and measured using gas chromatography. Partial least square (PLS) analysis was performed on the calibration set and models were developed for prediction using the raw spectral data and its derivative function. The best model was selected based on the coefficient of determination (R2), Standard error of prediction (SEP) and residual percent deviation (RPD) values.