Protein Content of Single Kernels of Wheat by Near-Infrared Reflectance Spectroscopy

• Published in: Journal of cereal science 1998-05, Vol.27 (3), p.241-254
• Main Author: Delwiche, S.R.
• Format: Article
• Language: English
• Subjects: Biological and medical sciences; Cereal and baking product industries; Food industries; Fundamental and applied biological sciences. Psychology; wheat, single kernel, protein, near-infrared
• ISSN: 0733-5210; 1095-9963
• DOI: 10.1006/jcrs.1997.0165

Protein content is well known to affect the functional properties of processed wheat products. Traditionally performed on aliquots (0·25–2·2 g) from samples ranging in size from 30–40 g (for combustion and Kjeldahl analyses) to several hundred grams (for whole-grain near-infrared analysis), these methods inherently do not provide information on single-kernel protein variability. Inspection procedures by the United States Department of Agriculture for grading and classification of wheat are undergoing change to provide the processor or end user with information on the variability of several single-kernel properties including hardness, moisture, weight, and wheat class. The present study has focused on demonstrating the feasibility of measuring crude protein content of single wheat kernels by near-infrared reflectance. More than 300 commercial wheat samples from the 1992 U.S. harvest, representing five (hard red winter, hard red spring, soft red winter, hard white, and soft white) of the six (durum excluded) market classes were chosen, from which 10 kernels were randomly selected and handled on a single-kernel basis. Handling consisted of reflectance scanning (1100–2498 nm), drying (for moisture compensation), and combustion (for reference protein-content determination). Partial least squares and multiple linear regression models, when applied to samples excluded from calibration, demonstrated standard errors of performance ranging from 0·462 to 0·720% protein depending on the modeling technique, number of classes used to develop the model, and the wheat class tested. The pooling of wheat classes to produce a general model did not diminish model accuracy. Best results were achieved with an 1100–1400-nm region. Model performance worsened as the wavelength region widened or as the minimum wavelength shifted from 1100 nm to higher values.