2008 Annual Report
1a.Objectives (from AD-416)
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.
1b.Approach (from AD-416)
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.
This research supports National Program 306 Quality and Utilization of Agricultural Products, Component 1 Quality Characterization, Preservation, and Enhancement, Problem Area 1b Methods to Evaluate and Predict Quality. The use of the prototype field portable near infrared [NIR] developed in 2006 was expanded to assess moisture in peanuts and at-line field study is scheduled for early Fiscal Year 2009 (Objective 1). This will likely find commercial application. Liquid chromatograph-solid phase extraction-nuclear magnetic resonance [LC-SPE-NMR] was utilized to separate and make absolute determination of the structure of phenolic glycerols isolated from biomass or synthesized from bio-diesel by-product glycerol and plant phenolics (Objective 1). A commercial hand-held NIR was utilized to predict the fiber content of flax, detect high versus low oleic acid content peanuts and latex in dandelion roots (Objective 4). NIR models were developed for the prediction of both cis- and trans-fatty acids in ground cereal products (Objective 2.3). Developed, improved and validated processing technologies for: the effect of aging time on sensory quality of poultry leg meat and the effect of electric stimulation on texture quality of poultry breast meat texture. Predicted and assessed the sensory quality of poultry meat using non-destructive and/or new sensor technologies to include: the relationship between sensory juiciness of cooked chicken breast meat and NIR measurement and relationship between sensory juiciness and dielectric spectroscopic measurement, the effect of aging, storage method and storage time on NIR spectral profiles of chicken breast meat, and the effect of aging and storage method on dielectric spectral profiles of chicken breast meat. Infrared and Raman mapping were utilized to assess the chemical nature of bio-mass grasses and detailed structure of rice, barley and corn endosperm tissue as related to bio-fuel production (Objective 1).
Specific Cooperative Agreement #58-6612-4-0252: The previously developed semi-portable NIR instrument that was developed by adapting an existing mid-infrared instrument was successfully used to scan peanuts for their moisture content. Improved instrumentation is being evaluated due to a need to improve the reliability and durability of the prototype spectrometer systems. Additional search algorithms were developed to more efficiently search our infrared databases. Advanced chemometric processing to include improved methods for calibration transfer between instruments was pursued.
Non-funded Cooperative Agreement #58-6612-5-0258: Developed, improved and validated processing technologies with regard to the effect of the reformulation of cookies with a sugar alternative blend of sucralose (Splenda®) and Isomalt on their sensory descriptive profiles. This agreement was terminated on 12/31/07 and the final report submitted on 03/21/08 and is provided with this report.
Spectroscopic determination of trans-fat in processed cereal products.
Data was analyzed and near-infrared [NIR] models developed for prediction of trans and cis fatty acid content directly in ground cereal products. Reports on the adverse effects of trans fats on health have led to increased interest in rapid and accurate methods of measuring trans fat in foods. Traditionally, gas chromatographic methods are used, which are time-consuming and solvent based. Alternatively, rapid infrared [IR] spectroscopic methods for determination of trans fat are available but are limited to direct use on fats or oils. The models developed in this study allow determination of trans fat spectroscopically without requiring the prior extraction of oil and, thus, provides substantial savings in time. The regression coefficients for the models indicated that the optimum wavelengths for prediction of trans fatty acids were in the overtone regions for lipid absorption and for cis fatty acids were in the overtone and combination regions. This research supports National Program 306 Quality and Utilization of Agricultural Products, Component 1 Quality Characterization, Preservation, and Enhancement, Problem Area 1b Methods to Evaluate and Predict Quality.
Immediate determination crop quality in the field.
It was determined that a commercial hand-held near-infrared [NIR] was utilizable for a multitude of field applications to include: prediction the fiber content of flax, detection high versus low oleic acid content peanuts and latex in dandelion roots. This enables immediate assessment of the quality of agricultural materials without transporting them to the laboratory. This on-site non-invasive method of field selection of the highest quality of materials saves money, time and resources. This research supports National Program 306 Quality and Utilization of Agricultural Products, Component 1 Quality Characterization, Preservation, and Enhancement, Problem Area 1b Methods to Evaluate and Predict Quality.
5.Significant Activities that Support Special Target Populations
|Number of Non-Peer Reviewed Presentations and Proceedings||5|
Sohn, M., Himmelsbach, D.S., Barton Ii, F.E., Griffey, C.A., Brooks, W., Hicks, K.B. 2007. Near-Infrared analysis of ground barley for use as a feedstock for fuel ethanol production. Journal of Applied Spectroscopy. 61 (11). p. 1178-1183.
Robinson, J.E., Singh, R., Kays, S.E. 2007. Evaluation of an automated hydrolysis and extraction method for quantification of total fat and lipid classess in cereal products.. Food Chemistry, Vol. 107, pages 1144-1150.
Lumor, S.E., Jones, K.C., Ashby, R.D., Strahan, G.D., Kim, B., Lee, G., Shaw, J., Kays, S.E., Chang, S., Foglia, T.A., Akoh, C.C. 2007. Synthesis and Characterization of Canola Oil-Stearic Acid-Based Trans-Free Structured Lipids for Possible Margarine Application. Journal of Agricultural and Food Chemistry. 55(26):10692-10702.
Zhuang, H., Nelson, S.O., Trabelsi, S., Savage, E.M. 2008. Dielectric Properties of Uncooked Chicken Breast Muscles from 10 to 1800 MHz. Poultry Science. 86:2433-2440.
Zhuang, H., Savage, E.M., Kays, S.E., Himmelsbach, D.S. 2007. A survey of the quality of six retail brands of boneless skinless chicken breast fillets obtained from retail supermarkets in Athens, Georgia area. Journal of Food Quality. 30:1068-1082.
Lee, C., Zhong, R., Richardson, E.A., Himmelsbach, D.S., Mcphail, B.T., Ye, Z. 2007. The PARVUS gene is expressed in cells undergoing secondary wall thickening and essential for glucuronoxylan biosynthesis. Plant And Cell Physiology 48: 1659-1672, 2007.
Himmelsbach, D.S., Manful, J.T., Coker, R.D. 2008. Changes in Rice with Variable Temperature Parboling: Thermal and Spectroscopic Assessment. Cereal Chemistry. 85: 384-390
Sohn, M., Himmelsbach, D.S., Barton Ii, F.E., Griffey, C.A., Brooks, W., Hicks, K.B. 2008. Near-infrared analysis of whole kernel barley: comparison of three spectrometers. Applied Spectroscopy. 62(4). p. 427-432 2008.
Loudermilk, J.B., Himmelsbach, D.S., Barton II, F.E., de Haseth, J.A. 2008. Novel Search Algorithims for a Mid-Infrared Spectral Libary of Cotton Contaminants. Applied Spectroscopy. 62: 661-670 (2008)