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CROP BREEDING, GENETICS & CYTOLOGY

Use of Near-Infrared Reflectance Spectroscopy for Selecting for High Stearic Acid Concentration in Single Husked Achenes of Sunflower

Instituto de Agricultura Sostenible, Apartado 4084, E-14080 Córdoba, Spain

^* Corresponding author (ia2veval{at}uco.es).

Half-seed analysis by gas-liquid chromatography (GLC) allows a nondestructive evaluation of the fatty acid composition of oilseeds, since in most cases the analyzed portion is representative of the whole seed. However, the sunflower (Helianthus annuus L.) mutant CAS-14 exhibits a high stearic acid concentration nonuniformly expressed along the longitudinal axis of the seed. No analytical technique is available for nondestructive selection at the single seed level in this mutant. The objective of the present research was to study the potential of near-infrared reflectance spectroscopy (NIRS) for analyzing the fatty acid composition of single husked achenes of sunflower and to evaluate its performance in a selection program for high stearic concentration in materials derived from CAS-14. A calibration set containing 2510 single husked achenes from a broad spectrum of breeding materials was developed. Reliable equations were developed for stearic acid, with r² = 0.80 and ratio of the standard error of cross validation (SECV) to the standard deviation (SD) of 0.45, oleic acid (r² = 0.89, SECV/SD = 0.34), and linoleic acid (r² = 0.91, SECV/SD = 0.30). The calibration equations were applied to the analysis of 8109 husked achenes within a selection program for high stearic acid concentration, 503 of them being further analyzed by GLC to monitor the performance of NIRS. The results revealed a close relationship between NIRS and GLC data, with r² of 0.83 for stearic acid, 0.92 for oleic acid, and 0.93 for linoleic acid concentration. It was concluded that NIRS can be used reliably for nondestructive selection for these major fatty acids at a single-seed level.

Abbreviations: GLC, gas-liquid chromatography • NIRS, near-infrared reflectance spectroscopy • SECV, standard error of cross validation

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Crop Science 2004 44: 1-4. [Full Text]