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ARS Home » Southeast Area » Athens, Georgia » U.S. National Poultry Research Center » Quality & Safety Assessment Research » Research » Publications at this Location » Publication #319990

Research Project: Develop Methods to Assess and Improve Poultry and Eggs Quality

Location: Quality & Safety Assessment Research

Title: Analysis of Peanut Seed Oil by NIR

Author
item Bansod, Babankumar - Council Of Scientific And Industrial Research (CSIR)
item Thakur, Ritula - National Institute Of Technical Teachers Training & Research
item Holser, Ronald

Submitted to: American Journal of Analytical Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/27/2015
Publication Date: 11/9/2015
Citation: Bansod, B., Thakur, R., Holser, R.A. 2015. Analysis of Peanut Seed Oil by NIR. American Journal of Analytical Chemistry. 6:917-922.

Interpretive Summary: Peanuts are an important source of edible oil and protein for the Americas and Africa. Breeding programs are working to develop new varieties with higher amounts of unsaturated oil to improve human health. Non-destructive methods are needed to identify peanut seeds with favorable traits for breeding improved varieties. Infrared light was used to select seeds that contained high amounts of the desired unsaturated oil. This method did not damage the seed and was performed in less than one minute. The method was applied to shelled peanuts and is expected to support the peanut breeding program worldwide.

Technical Abstract: Near infrared reflectance spectra (NIRS) were collected from Arachis hypogaea seed samples and used in predictive models to rapidly identify varieties with high oleic acid. The method was developed for shelled peanut seeds with intact testa. Spectra were evaluated initially by principal component analysis (PCA) followed by partial least squares (PLS). PCA performed with full spectra and reduced spectra with one principal component accounted for 97 percent to 99 percent variability, respectively. The PLS model generated from first derivative spectra provided a standard error of prediction (SEP) of 7.720. This technique provides a non-destructive method to rapidly identify high oleic peanut seeds to support the selection and cultivation of high oleic acid peanut varieties. The method can also be useful at peanut processing facilities for screening and quality assessments.