Project Number: 6612-44000-025-00
Project Type: Appropriated

Start Date: Sep 15, 2004
End Date: Sep 14, 2009

Objective:
The goal of this project is to develop and compare rapid, accurate, improved (non-destructive) and environmentally benign spectral methods to replace invasive, less accurate and less rapid current methods of analysis to determine the quality and functional end product use of agricultural commodities and food products and to assist regulatory agencies in objectively measuring and predicting quality and functionality. Specifically this involves sub-objectives to: 1) Develop an accurate method for determining starch amylose/amylopectin ratios as a measurement of grain quality to facilitate its genetic development/functionality for foods, biobased products, and biofuels. 2) Facilitate compliance with the Nutrition Labeling and Education Act (NLEA) by the development of rapid, accurate and environmentally benign spectroscopic methods for: total dietary fiber in mixed foods; for rapid analysis of fats in cereal and snack foods; and rapid analysis of trans-fatty acids in snack foods. 3) Develop methods for cotton to detect stickiness and identify trash, factors that adversely affect quality. 4) Develop methods to determine the fiber content of the standing flax plant to predict proper harvesting time and for the assessment of retted flax that provides a measurement of shive (trash) content. 5) Determine the relationships among sensory, physical, and chemical properties of poultry meat that result from non-traditional processing, such as applications that hasten the onset of rigor or air-chilling to reduce water use. 6) Determine the relationships among sensory, physical, and chemical properties of poultry meat that result from further-processing treatments, such as marination to increase yield and improve sensory quality.

Approach:
This project has multiple approaches for the objectives: 1) Proton high-resolution magic-angle-spinning (HR MAS) nuclear magnetic resonance (NMR) will be employed to measure the branching in grain starch based on the ratio of the areas of the anomeric protons (1-4/1-6). The data so obtained will serve as reference data for use in chemometric calibrations for vibrational spectroscopic techniques (near-infrared [NIR], mid-infrared [MIR] and Raman) to provide more accurate rapid analysis methods. 2) Analysis of dietary fiber in mixed meals will be conducted by homogenizing the samples and analyzing sub-samples for total dietary fiber (TDF) by Association of Official Analytical Chemists (AOAC) Method 991.43 as the reference method. Off-the-shelf cereal and snack foods will be milled and analyzed for total fat using AOAC Method 996.01 as the reference method. Fatty acids will be extracted and analyzed for the proportion of trans-fatty acids by gas chromatography (GC) as the reference method. Samples will be scanned with diffuse refection NIR and/or MIR spectrometers. Chemometric models will be developed to relate spectra to reference data and used to predict: dietary fiber; total, saturated, and trans-fat in test mixed meals; cereal products; and snack food samples. 3) Obtain stickiness values on cotton fiber samples by mini-card system as reference values. Scan samples with high-resolution NIR spectrometers. Develop spectroscopically based classification models. Export model to a field analysis based system. Integrate the system with remediation technologies. 4) Collect samples of all anticipated foreign matter (trash) that could potentially be present in cotton. Scan samples using attenuated total reflectance/Fourier transform-infrared (ATR/FT-IR). Build database of spectra. Validate with known samples and test the database using unknown samples. Identify unknown foreign matter in cotton. Develop a set of samples prepared from physically separated pure fiber and shive of flax. Grind and prepare weighed mixtures of components. Scan these samples using laboratory based NIR spectrometers. Develop a chemometric calibration for fiber and shive content of the samples. Use this calibration to predict the fiber and shive content of as-is and retted flax. 5) Develop comprehensive profiles of the measurable sensory attributes of foods and food products and relate these profiles to the food's physical and chemical properties in order to enhance product development and accurately predict end-use quality. Develop indexes, methods, or strategies to predict, evaluate, modify, and control end-use quality based on data-relationships. 6) The overall framework of the research involves six steps; (a) Develop specific sensory objectives relating to the commodity problem; (b) Select the range of characteristics encompassed by the problem that will be tested; (c) Develop the appropriate databases of sensory, chemical, physical properties; (d) Pre-process the data using multivariate methods; (e) Develop and test models to explain and predict sensory quality; (f) Test selected variables in more stringent experimental designs.