Project Number: 6612-44000-026-00
Start Date: Sep 15, 2009
End Date: Sep 30, 2010
1) Proton high-resolution magic-angle-spinning (HR MAS) nuclear magnetic resonance (NMR) will be used to measure branching in grain starch based on the ratio of the areas of the anomeric protons (1-4/1-6). The data obtained will serve as reference data for use in chemometric calibrations for vibrational spectroscopic techniques (nearinfrared [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 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 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 field analysis based system. Integrate system with remediation technologies. 4) Collect samples of all foreign matter 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. 7) Develop composites from flax fibers and renewable polyesters. The tensile properties of these bio-composites will be evaluated to obtain strength and flexibility values.