Multiple Linear Regression Calibrations for Barley and Malt Protein Based on the Spectra of Hordein

Abstract

The feasibility of using NIR spectral information from barley and malt hordein was assessed as to the suitability of developing improved NIR calibrations to predict protein in barley and malt. Using extracted hordein it was possible to gain more information on wavelengths relevant to predict protein with reduced errors. Strong correlations for grain protein and NIR wavelengths were found at 1,116, 1,268, 2,040, 2,068, 2,188 and 2,300 nm. Multiple linear regression equations provided improved predicting power for barley and malt protein with a standard error of prediction of 0.15 and 0.17%, respectively, whereas partial least squares regression gave a standard error of prediction of 0.22 and 0.27% for barley and malt, respectively. The use of NIR becomes more pronounced in breeding programs as NIR is a rapid and non-destructive technique allowing the screening of early generation lines with limited grain quantities. Also, the spectral analysis of native components from resting grain components will assist in building calibrations that provide qualitative values rather than just ranking breeding lines.

Development of a Single Kernel NIR Barley Protein Calibration and Assessment of Variation in Protein on Grain Quality

“…For commercial malting, barley protein should be within a defined range, depending upon the country where the barley is grown, as well as malting and brewing specifications. Barley breeding programs use these protein targets when carrying out grain quality screening on thousands of breeding lines, usually with near infrared (NIR) spectroscopy 3,9,12,18,20,24 . However, a single sample of barley can have considerable variation in protein content.…”

Enhanced NIR Calibration for Wort Fermentability Using Orthogonal Signal Correction

“…Sojholm et al 31 found that the key pre- n/a n/a n/a n/a dictors for the amount of extract fermented in a laboratory scale fermentation test fall in the 1500-1863 and 2050-2400 nm regions; however, the signs on their PLS regression coefficients do not all agree with these findings. As for nitrogen sources, class II aromatic amino acids such as phenylalanine and tyrosine have been assigned to 1680 nm whereas glutamine, probably less important for fermentation, has been assigned to 2170 nm 18 . Assignments of N-H groups have been reported at 1528 nm and 2048 nm 17 and a N-H stretch is assigned to 1982 nm 6 .…”

“…Many brewing related quality characteristics measured using NIR techniques have been investigated. Some examples include the measurement of barley and malt moisture, nitrogen, and amino acid content 2,18,38 , whole hop cone moistures, ␣ and ␤ acids, and oils 23 , wort extract content 24,31 , and fermentable sugars and free ␣-amino nitrogen 8,10,24,29,32,34 . Both Halsey 24 and Sjoholm et al 31 studied calibration models for fermentability and comment on moderate success.…”

“…The application of multivariate calibration techniques such as PLS 25 has generally gained acceptance over MLR or Principal Component Regression (PCR). In situations where specific wavelengths have been assigned to certain functional groups, some researchers opt to using MLR 18 ; however, due to potential collinearity issues the MLR approach is not recommended.…”

Comparison of fermentation results and quality of the agricultural distillates obtained by application of commercial amylolytic preparations and cereal malts

“…Proteins are essential for the quality of malt. First, high protein content decreases available carbohydrates, adversely influencing the fermentation process, and second, proteolysis (protease hydrolysis producing amino acids and peptides) during malting and mashing is necessary for yeast metabolism [42,43]. Yeast growth requires the uptake of nitrogen for the synthesis of protein and other nitrogenous components of the cell, but yeasts can only utilize low molecular weight nitrogenous materials such as inorganic ammonium ion, urea, amino acids and small peptides.…”