The adaptable use of Brassica NIRS calibration equations to identify pennycress variants to facilitate the rapid domestication of a new winter oilseed crop
Publication date: February 2019
Source: Industrial Crops and Products, Volume 128
Author(s): Ratan Chopra, Nicole Folstad, Joseph Lyons, Tim Ulmasov, Cynthia Gallaher, Liam Sullivan, Abby McGovern, Rachel Mitacek, Katherine Frels, Kayla Altendorf, Arthur Killam, Baraem Ismail, James A. Anderson, Donald L. Wyse, M. David Marks
Pennycress is being domesticated as a new winter oilseed crop to be grown between corn harvest and soybean planting the following year in the Upper Midwestern United States. The aim of this research was to evaluate seed composition traits in a large pennycress mutant population using near-infrared spectroscopy (NIRS). We tested the hypothesis that Brassica NIRS calibration equations could be used rapidly and cost effectively to evaluate pennycress seeds for protein, oil, glucosinolate, and fatty acid contents. Using calibration equations developed for Brassica, we identified a broad range for each of the traits evaluated in this study. Wet lab analyses were conducted on selected subsets of the mutant families to confirm the predicted variation for each trait using NIRS. Supporting our hypothesis, moderate to strong correlations were observed between the wet lab analyses and NIRS predictions for seven of the eight traits evaluated. For protein, oil and glucosinolate content, correlations between the NIRS predictions and wet lab values were 0.82, 0.92 and 0.78 respectively. For fatty acid content, moderate correlations for oleic acid (0.68), linoleic acid (0.78), linolenic acid (0.60) and erucic acid (0.74) were observed. These findings allowed us to use NIRS to quickly evaluate large heterogenous mutant families and identify pennycress lines harboring desirable traits required for adoption as a cover crop and to create several industrial opportunities.