4.6 Article

Near infrared reflectance spectroscopy as a tool to predict non-starch polysaccharide composition and starch digestibility profiles in common monogastric cereal feed ingredients

Journal

ANIMAL FEED SCIENCE AND TECHNOLOGY
Volume 285, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.anifeedsci.2022.115214

Keywords

Cereal; Near infrared reflectance spectroscopy; Non-starch polysaccharides; Starch digestibility; Resistant starch; Starch

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This study found that near infrared reflectance spectroscopy (NIRS) technology can accurately predict the composition of cereal grains, including non-starch polysaccharides (NSP), monosaccharide sugars, lignin, cellulose, and total starch content. It also showed the relationship between NIR and the digestibility of starch fractions in the grains for the first time.
Carbohydrates are the main components of cereal grain ingredients and are comprised predominantly of starch which varies in the rate and extent of digestibility, and non-starch polysaccharides (NSP) from plant cell walls. These components are traditionally measured by chemical methods but there is interest in developing more rapid, cost effective predictions by use of near infrared reflectance spectroscopy (NIRS) technology. In this study, around 400 samples of wheat, corn, barley, wheat bran, oats, rye, corn germ, and sorghum were collected over several years to develop global NIR calibrations. Chemical analysis was performed for NSP, including details on solubility and individual constituent sugars, as well as separate determinations of cellulose and lignin. Total starch content and starch digestibility were characterized by the method of Englyst as rapidly (RDS) and slowly (SDS) digestible starch, and resistant starch (RS) determined as total starch content minus RDS and SDS. The same samples were scanned (400 to 2500 nm, every 0.5 nm) by two NIRS machines: a Foss model DS2500 and a Bruker Tango FT-NIR (Fourier transform near-infrared spectroscopy). The NIRS calibrations were developed by using the combined set of different cereal grains. The modified Partial Least Squares Regression method was employed to establish correlations between the reference chemical analysis and the collected NIRS spectra. The correlation between the NIRS and reference data for total and insoluble NSP and the main component sugars (arabinose, xylose, and glucose) were robust (R2 = >0.97) with a 1-VR > 0.96 and RPD values > 5.3. Similarly, the NIRS predicted lignin (R2 = 0.94; 1-VR = 0.93) and to a lesser extent cellulose (R2 = 0.70; 1-VR = 0.98) but still highly correlated with the reference data. The predicted total starch content was excellent (R2 = 0.99; 1-VR = 0.99). The NIRS prediction for RDS and SDS were lower in linearity (R2 = 0.81 and R2 = 0.97, respectively) but more than sufficient to provide an estimate of the starch digestion profile for many of the raw materials evaluated. In addition, the robust NIRS predictions for total starch content, RDS and SDS could then provide information to calculate the RS fraction of the ingredients. In conclusion, compared with the reference chemical data for this large set of cereal grains the global NIR calibrations developed provide a good prediction of NSP, monosaccharide sugars, lignin, cellulose , total starch content in cereal grains , for the first time an NIR relationship with starch digestibility fractions in the grains has been shown.

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