2006 Annual Report
1.What major problem or issue is being resolved and how are you resolving it (summarize project aims and objectives)? How serious is the problem? Why does it matter?
American agricultural and food producers are subjected to multiple constraints of foreign competition, stringent regulatory requirements, plus demands from manufacturers and consumers and thus require sensors that enable rapid and accurate methods of quality assessment. This project provides solutions to these problems in the selected commodities of: grains, fibers, and processed foods by taking advantage of technological advances in rapid analytical systems, which rely on spectroscopic techniques. Systems of sensors and analyses to measure the quality and end use of these commodities and food products will be developed. The approaches utilize multiple regions of the electromagnetic spectrum and correlative techniques to build chemometric models for quality indices. New, small sensors will be incorporated to move the analyses from the laboratory to the field and food production plant. The project, in part, focuses on the requirements of the Nutrition Labeling and Education Act (1990), necessitating more assays by industry and regulatory agencies.
Furthermore, it provides alternative methods to reduce hazardous waste, generated by current methods, in accordance with the Resource Conservation and Recovery Act (1988) and Pollution Prevention Act (1990). This program is needed to reduce cost and increase accuracy, precision, and rapidity of essential agricultural analyses.
2.List by year the currently approved milestones (indicators of research progress)
1. Complete the NMR determination of branching ratios of pure components and mixture samples in DMSO/DSO.
2. Collect samples and assay for dietary fiber in mixed foods.
3. Set-up laboratory for performing AOAC method 966.01 for the analysis of fat in cereal and snack foods.
4. Optimize the AOAC method 966.01 method for the analysis of fat in cereal and snack foods.
5. Optimize the method for GC analysis of trans-fatty acids in cereal and snack foods.
6. Build sample data sets for analysis of trans-fatty acids in cereal and snack foods.
7. Collect sample set and spectra on FT-22N (NIR) for sticky cotton.
8. Collect sample set of trash in cotton and acquire ATR spectra using Thermo 860 FT-IR (MIR).
1. Complete the NMR determination of branching ratios of isolated starches from rice and wheat.
2. Complete the laboratory assay for dietary fiber in mixed foods.
3. Complete total fat analysis of fat in cereal and snack foods.
4. Complete the GC analysis of trans-fatty acids in cereal and snack foods.
5. Complete spectroscopic analysis of trans-fatty acids in cereal and snack foods.
6. Develop initial models for sticky cotton analysis.
7. Develop searchable MIR library for trash in cotton.
8. Generate MIR spectral library for trash in cotton in multiple instrument formats.
9. Generate NIR calibration for fiber content of flax in standing plant.
1. Determine the ability of vibrational methods to detect difference in branching ratios in rice and wheat.
2. Scan dietary fiber in mixed foods samples by NIR.
3. Complete the spectroscopic analysis, data analysis, test models of fat in cereal and snack foods.
4. Transfer technology for the spectroscopic analysis of fat in cereal and snack foods.
5. Develop spectroscopic models for trans-fatty acid analysis in cereal and
6. Transfer technology for trans-fatty acid analysis in cereal and snack foods
by spectroscopic methods.
7. Acquire spectra of cottons on field spectrographic sensor.
8. Transfer the sticky cotton analysis calibration from FT-22N to field spectrographic sensor.
9. Test spectral library for trash in cotton using portable MIR instrument(s).
10. Acquire spectra of flax with a field sensor.
11. Initiate work on the final development of an online sensor for the measurement of trash (shive) in flax fiber.
1. Utilize NMR results as reference data for NIR and Raman calibrations of branching ratios in rice and wheat.
2. Conduct analysis of data and develop method for dietary fiber in mixed foods.
3. Test the NIR model for measurement of dietary fiber in mixed foods.
4. Complete analysis for saturated, unsaturated, and monounsaturated fatty acids, data analysis and interpretation for fat in cereal and snack foods.
5. Test models for the spectroscopic analysis fat in cereal and snack foods.
6. Complete on-line measurements of sticky cotton at cotton gin and spinning plant, and transfer calibration.
7. Patent the MIR library for trash in cotton.
8. Transfer 6500 NIR calibration for fiber content in flax to field sensor.
9. Conduct field trial of sensor for fiber content in flax.
1. Use vibrational methods (NIR and Raman) results to predict the branching ratio in new samples of rice and wheat.
2. Transfer the technology from NMR and most viable vibrational method for the determination of branch ratios of starch in flours of rice and wheat.
3. Transfer technology for the analysis of fat in cereal and snack foods.
4. Submit patent for trans-fatty acid analysis technique in cereal and snack foods and transfer the technology for use in product labeling.
5. Generate MIR spectral library for trash in cotton in multiple instrument formats.
6. Final development of an online sensor for the measurement of trash (shive) in flax fiber.
7. Transfer technology of the field sensor for the measurement of trash (shive) in flax fiber.
4a.List the single most significant research accomplishment during FY 2006.
NIR Determination of Total Dietary Fiber in Homogenized Mixed Meals
Analysis of total dietary fiber (TDF) in mixed meals takes regulatory agencies at least 4 days to perform. The NIR models developed in this study provide substantial savings in time of 2-3 days when screening mixed meals for TDF content if samples are dried or dried and defatted prior to obtaining the NIR spectra. This work was reported in the Journal of Agricultural and Food Chemistry in 2006, 54:292-298. Furthermore, the NIR models developed were found to be dependent on absorbance by functional chemical groups present in carbohydrates and lignin.
4b.List other significant research accomplishment(s), if any.
The nuclear magnetic resonance (NMR) determination of the branching ratio in has been extended to isolated corn starch. This method does not require the isolation of the starch and has many advantages over the iodine binding method.
A new prototype instrument has been produced sub-planting the previous one. It initially provides a sensor by which to detect sticky cotton, a major problem for the cotton industry.
5.Describe the major accomplishments to date and their predicted or actual impact.
Data was collected at high resolution that is suitable for the prediction on sticky cotton and an instrument has been designed to accomplish this purpose. This will provide an online detection method to permit remediation steps to solve a problem that has cost the cotton industry $200,000,000 over a 4-year period in just TX, AZ and CA. This impacts the ginning and spinning operations of the cotton industry. This relates to milestone 3.1-12, Component 1 of the National Program Action Plan: Quality, Characterization and Preservation under NP306, and specifically problem area 1c.
A mid-infrared method has also been developed to assist the textile industry. A database has been developed for use with laboratory and portable mid-infrared instruments that will identify the trash components present in cotton products that produce defects in fabrics. This will permit textile manufactures to determine the source of many fabric defects caused by foreign matter and give them the ability to check raw materials for these contaminates, before they cause a manufacturing problem. This will be of particular benefit to US manufacturers of high quality fabrics. This relates to milestone 3.2-12 Component 1 of the National Program Action Plan: Quality, Characterization and Preservation under NP306, and specifically problem area 1c.
An instrumental method was developed to measure the shive (trash) content in flax fiber. An ASTM method for the objective quality measurement of flax fiber (linen) has been approved. This will provide a means for the determination of the proper end use of processed raw material and a means to determine the quality and thus price of the raw material in the market place. This relates to milestone 4-12c, component 1 of the National Program Action Plan: Quality, Characterization and Preservation under NP306, and specifically problem area 1c.
A near-infrared method was developed to measure total fat in cereal food products and mixed foods. This provides a rapid non-destructive method of analysis for fat in foods and supports the national effort to control obesity in the individuals in the US. It will permit more effective means of analysis for the control of fats in cereal foods and enhance the efficiency of regulatory controls. This relates to milestones 2.2-12a and 2.2-12b component 1 of the National Program Action Plan: Quality, Characterization and Preservation under NP306, and specifically problem areas 1a & 1b.
6.What science and/or technologies have been transferred and to whom? When is the science and/or technology likely to become available to the end-user (industry, farmer, other scientists)? What are the constraints, if known, to the adoption and durability of the technology products?
As soon as the database for foreign matter in cotton is patented an instrument manufacturer is ready to license it. Availability to the industry is waiting on the patent. The same instrument manufacturer is developing a smaller instrument to use with the database. The National Cotton Council has requested that the database be demonstrated at the Beltwide Conferences, January 7-12, 2007 in New Orleans, LA.
The prototype of a new instrument to measure sticky cotton has been produced this year and is currently being tested. The USDA patent on the database that supports this application is still in progress. Production of a commercial instrument should begin in the FY 2007-2008 period. The cotton industry should adopt this immediately. Applications to other industries will be pursued.
7.List your most important publications in the popular press and presentations to organizations and articles written about your work. (NOTE: List your peer reviewed publications below).
Sohn, M., Himmelsbach, D.S., Kays, S.E., Archibald, A.D., and Barton, F.E., II. NIR-FT Raman spectroscopy for nutritional classification of cereal foods. NIR News, 17:6-7, 2006.
Kays, S.E., Morris, J.B., Kim, Y. 2006. Genetic variation in total and soluble dietary fiber among cyamopsis tetragonoloba (L.) taub. genotypes. Journal of Food Quality. 29(4):383-392.
Kim, Y., Singh, M., S.E. Kays. 2006. Near-infrared spectroscopy for measurement of total dietary fiber in homogenized meals. Journal of Agricultural and Food Chemistry. 54:292-298.
Kays, S.E., Vines, L.L., Kim, Y., Koehler, P.E. 2005. Prediction of monounsaturated, polyunsaturated, and saturated fats by nir and ft-nir spectroscopy in processed cereal products [abstract]. Federation of Analytical Chemistry and Spectroscopy Societies Final Program. P. 188
Sohn, M., Kays, S.E., Himmelsbach, D.S., Barton II, F.E. 2005. Nutritional classification of cereal food products using ft-raman and near-infrared spectroscopy [abstract]. The 32nd Federation Of Analytical Chemistry And Spectroscopy Societies (FACSS). Paper No. 611. p.201.
Kim, Y., Kays, S.E., Singh, M. 2005. Nir and ft-nir spectroscopy for the measurement of total dietary fiber in mixed foods. Eastern Analytical Symposium. Paper number 554.
Sohn, M., Himmelsbach, D.S., Kays, S.E., Barton II, F.E. 2005. Chemometric processing of Ft-Raman and near-infrared spectral data for nutritional classification of cereal products [abstract]. 44th Eastern Analytical Symposium. Abstract # 287.
Himmelsbach, D.S., Hellgeth, J.W., Mcalister III, D.D. 2006. Development and use of an atr/ft-ir spectral dataabase to identify foreigh matter in cotton. Beltwide Cotton Conferences, National Cotton Council. pp. 2386-2397.
Himmelsbach, D.S., Akin, D.E., Kim, J., Hardin, I.R. 2006. Chemical structural investigation of the cotton fiber base and associated seed coat: fourier-transform infrared mapping and histochemistry. Beltwide Cotton Conferences, National Cotton Council. pp 2398-2409.
Himmelsbach, D.S., De Haseth, J.A., Delwiche, S.R. 2005. Prediction of SDS sedimentation volumes for wheat via FT-NIR and FT-Raman spectroscopy. Proceedings of the United States-Japan Cooperative Program in Natural Resources Food and Agriculture Panel. 34th Annual Meeting, Susono, Shizzoka, Japan. pp. 74-77.
Sohn, M., Himmelsbach, D.S., Morrison III, W.H., Akin, D.E., Barton II, F.E. 2006. Partial least squares regression calibration for determining wax content in processed flax fiber by near-infrared spectroscopy. Journal of Applied Spectroscopy. 60(4):437-440.
Kim, Y., Kays, S.E. 2006. Simultaneous determination of major components and energy in homogenized meals using near-infrared spectroscopy [abstract]. Pittsburgh Conference. Paper No. 1250-4P.
Kim, Y., Kays, S.E. 2006. Rapid multiple component analysis of macronutrients and energy in several types of homogenized meals using near-infrared spectroscopy. National Meeting of Institute of Food Technologists/Food Expo. Paper No. 078H-05.
Sohn, M., Himmelsbach, D.S., Kays, S.E., Archibald, D.D., Barton II, F.E. 2005. Nir-ft/raman spectroscopy for nutritional classification of cereal foods. Cereal Chemistry. 82(6):660-665.
Sohn, M., Himmelsbach, D.S., Kays, S.E., Archibald, D.D., Barton II, F.E. 2006. Nir-ft/raman spectroscopy for nutritional classification of cereal foods. NIR news (Near Infrared Reflectance News). 17(5):6-7.
Kays, S.E., Shimizu, N., Barton Ii, F.E.,II, Ohtsubo, K. 2006. Near-infrared transmission and reflectance spectroscopy for determination of dietary fiber in barley. Crop Science. 45:2307-2311.