Location: Functional Foods ResearchTitle: Quantitative NIR determination of isoflavone and saponin content of ground soybeans
Submitted to: Food Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/5/2020
Publication Date: 2/19/2020
Citation: Berhow, M.A., Singh, M., Bowman, M.J., Price, N.P.J., Vaughn, S.F., Liu, S.X. 2020. Quantitative NIR determination of isoflavone and saponin content of ground soybeans. Food Chemistry. 317:126373. https://doi.org/10.1016/j.foodchem.2020.126373.
Interpretive Summary: Rapid nondestructive analytical methods using near infrared spectrometry (NIRS) is being used to determine general compositional analysis, such as percent protein, oil, fiber, and moisture, in soybeans. The technology is developing so that even certain phytochemical components such as the soy isoflavones and saponins, can be measured with this instrument. Soybeans, as do all plant species, contain a unique set of bioactive constituents in small quantities that contribute towards the plant’s ability to survive in its partcular ecological nitch and are also implicated in maintaining the health and preventing disease in the animals that consume them. Accurately measuring the levels of these compounds in ground soybeans will aid in breeding programs and nutritional assessments for beans being brought to the grain elevators and to processing plants. We have developed NIRS methodology to accurately measure isoflavone concentrations from over 2000 samples collected from 6 crop years and from soybeans grown in locations in 14 states. This enables us to create NIRS analytical methodology to assess isoflavone concentrations much more precisely than has been done previously. This will aid processers and breeders to assess isoflavone levels rapidly and accurately on large sets of samples.
Technical Abstract: Over 3000 discrete samples of soybeans were obtained from production locations around the United States during the years 2012-2016, and from the Agricultural Research Service soybean germplasm collection. The samples were ground and scanned on two near infrared spectrometers (NIRS) and analyzed by wet chemical methods in triplicate for total isoflavone composition (the various substituted forms of genistein, daidzein and glycitein), total saponin composition (the A-, B- and DMPP- groups) as well as the total carbohydrate composition (soluble sugars, total insoluble sugars, and total uronic acids). A subset selection of these samples was used to prepare NIRS calibrations. Selected preprocessing algorithms were applied to spectral data to minimize/eradicate noise or disturbance in the spectra. Multiple Linear Regression (MLR) analysis of preprocessed spectral data and wet chemistry data was used to develop models to predict individual chemical species. The selection of a suitable calibration model was based on a high regression coefficient (R^2^), and lower standard error of calibration (SEC) values. Optimized MLR regression models were then used to predict validation sets. Excellent predictions were obtained for isoflavones, however less than robust calibrations were obtained for the total saponins. The correlations were not as robust for predicting the soluble carbohydrates, insoluble and uronic acid polysaccharides and the results are presented in the supplementary material. NIRS is a suitable, rapid, nondestructive method to determine isoflavone composition in ground soybeans. Useful isoflavone compositional predictions for large numbers of soybean samples can be obtained from quickly obtained NIRS scans.