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CROP BREEDING & GENETICS

Predicting Oleic and Linoleic Acid Content of Single Peanut Seeds using Near-Infrared Reflectance Spectroscopy

^a Univ. of Florida, North Florida Research and Education Center, 3925 Hwy. 71, Marianna, FL 32446
^b Agronomy Dep., Univ. of Florida, 2062 McCarty Hall, Gainesville, FL 32611

^* Corresponding author (btillman{at}ufl.edu)

One objective of peanut breeders is to develop cultivars with elevated oleic acid content (>740 g kg^–1). Testing single seeds for oleic acid content is possible using gas chromatography (GC), but it is time-consuming and requires cutting a portion of the seed which could reduce germination. Using single, intact peanut seeds, we developed a near-infrared reflectance spectroscopy (NIR) calibration equation relating oleic acid measured with GC to oleic acid predicted by NIR. The slope of the regression line of oleic acid measured with GC on oleic acid predicted by NIR was 1.01 g kg^–1 (P > t < .0001) and the intercept was not different from zero. An independent set of 95 peanut seeds was used to validate the NIR calibration. The slope of the regression line was 1.01 g kg^–1 (P > t < .0001) and the intercept was not different from zero. By selecting seeds with at least 700 g kg^–1 NIR predicted oleic acid content, only four of the 43 seeds (validation set) with elevated oleic acid content were misclassified by NIR, and none with normal oleic acid content were misidentified. Results were similar for linoleic acid content. This research shows that NIR prediction of oleic acid and linoleic acid using intact peanut seeds is accurate and rapid and should be especially useful for early generation screening.

Abbreviations: NIR, near-infrared reflectance spectroscopy • GC, gas chromatography • PLS, principal least squares • RMSECV, root mean squared error of cross-validation • RMSEP, root mean squared error of prediction