Rapid single flax (Linum usitatissimum) seed phenotyping of oil and other quality traits using single kernel near infrared spectroscopy

Abstract

AbstractThe growing interest in the rapid measurement of seed ingredients using single‐kernel NIR (SKNIR) spectroscopy as a nondestructive measurement technique allows fast analysis of sample seed variance that can have effects on breeding and end‐use processing. Flax (Linum usitatissimum), an oilseed crop grown in the Northwest United States and worldwide, is highly beneficial for human health, food, and fiber. Its health benefits include its high protein and omega‐3 fatty acids content. Therefore, seed composition profiles are an important aspect of breeding. The goals of this research were the development of single seed NIR calibration models for protein, oil, and weight of intact flax seeds. In this study, SKNIR spectroscopy was used on a diverse set of flax accessions comprising of 306 samples to create prediction models on a custom built SKNIR instrument. Spectra data and reference protein, oil, and weight were used to build partial least squares (PLS) models. Calibration models provided reasonable prediction of these traits and could be used for screening purposes. PLS statistics were oil (R2 = 0.82, SEP = 1.72), weight (R2 = 0.74, SEP = 0.71), and protein (R2 = 0.62, SEP = 0.96) for validation data sets comprising of one‐third of the total samples. In conclusion, prediction models showed that SKNIR spectroscopy could be a very beneficial nondestructive technique to determine oil and weight as well as rapid screening of protein in single flax seeds while not requiring extensive preparation as compared to traditional techniques.