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ARS Home » Midwest Area » Peoria, Illinois » National Center for Agricultural Utilization Research » Bio-oils Research » Research » Publications at this Location » Publication #320806

Research Project: ACCELERATED DEVELOPMENT OF COMMERCIAL HYDROTREATED RENEWABLE JET (HRJ) FUEL FROM REDESIGNED OILSEED FEEDSTOCK SUPPLY CHAINS

Location: Bio-oils Research

Title: Development of near-infrared spectroscopy calibrations to measure quality characteristics in intact Brassicaceae germplasm

Author
item Oblath, Emily
item Isbell, Terry
item Berhow, Mark
item Allen, Brett
item Archer, David
item BROWN, JACK - University Of Idaho
item Gesch, Russell - Russ
item Hatfield, Jerry
item Jabro, Jalal "jay"
item Kiniry, James
item Long, Daniel

Submitted to: Industrial Crops and Products
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/9/2016
Publication Date: 5/17/2016
Publication URL: http://handle.nal.usda.gov/10113/62886
Citation: Oblath, E.A., Isbell, T.A., Berhow, M.A., Allen, B., Archer, D., Brown, J., Gesch, R.W., Hatfield, J.L., Jabro, J.D., Kiniry, J.R., Long, D.S. 2016. Development of near-infrared spectroscopy calibrations to measure quality characteristics in intact Brassicaceae germplasm. Industrial Crops and Products. 89:52-58.

Interpretive Summary: Rapeseed, along with other oilseeds from the mustard family, is a potential feedstock for biofuel production but minor seed components can cause poor oil quality and increased refining costs. A rapid screening method using near-infrared spectroscopy was developed for six oilseed species from the mustard family. Intact seeds can be quickly analyzed for characteristics of interest including moisture, oil, fatty acid profile, nitrogen, glucosinolate, and chlorophyll content. Traditional analysis methods for many of these characteristics can be time-consuming and require large amounts of seeds to be destroyed. This rapid screening method allows samples to be non-destructively scanned in less than two minutes each. This is particularly useful for situations when only a small amount of seed is available, such as screening large numbers of samples from genetic trials to choose the best varieties for future research.

Technical Abstract: Determining seed quality parameters is an integral part of cultivar improvement and germplasm screening. However, quality tests are often time cnsuming, seed destructive, and can require large seed samples. This study describes the development of near-infrared spectroscopy (NIRS) calibrations to measure moisture, oil, fatty acid profile, nitrogen, glucosinolate, and chlorophyll content in six species from the Brassicaceae family. Rapeseed and similar oilseeds are potential feedstocks for producing hydrotreated renewable jet fuel. Screening samples with NIRS would allow cultivars with desirable characteristics to be quickly identified. A total of 367 samples of six species (Brassica napus, Brassica carinata, Brassica juncea, Brassica rapa, Sinapis alba, and Camelina sativa) were scanned with NIRS. Global calibrations for all six species were developed using modified partial least squares regression with reference values obtained through wet chemistry techniques. Comparing predicted values to reference data, the coefficients of determination (r2) and ratios of performance to deviation (RPD) varied, with some calibrations performing better than others. The calibration equations for seed oil content (r2 = 0.98, RPD = 7.3) and nitrogen (r2 = 0.98, RPD = 5.3) performed very well while the equations for moisture (r2 = 0.98, RPD = 5.3) performed very well while the equations for seed moisture (r2 = 0.98, RPD = 3.8) and glucosinolate content (r2 = 0.92, RPD = 2.3) were more qualitative. Large variation was observed for chlorophyll content (0-390 mg/kg) so two calibration equations were developed, one for the higher and one for the lower range of values. When combined, these calibrations also showed very good performance (r2 = 0.99, RPD = 14). The performance of the calibrations for the fatty acids was more varied, with some performing very well, such as the calibration for C18:3 (r2 = 0.99, RPD = 9.9), and others, such as C22:0 (r2 = 0.69, RPD = 1.9), showing poor correlation.