Source: SOUTH CAROLINA STATE UNIVERSITY submitted to NRP
CHEMOMETRIC SOFTWARE ROUTINE DEVELOPMENT FOR SPECTROSCOPIC DATA ON FOOD AND FIBER COMMODITIES
Sponsoring Institution
Agricultural Research Service/USDA
Project Status
COMPLETE
Funding Source
USDA COOPERATIVE AGREEMENT
Reporting Frequency
Annual
Accession No.
0405535
Grant No.
(N/A)
Cumulative Award Amt.
(N/A)
Proposal No.
(N/A)
Multistate No.
(N/A)
Project Start Date
Apr 1, 2002
Project End Date
Sep 30, 2004
Grant Year
(N/A)
Program Code
[(N/A)]- (N/A)
Recipient Organization
SOUTH CAROLINA STATE UNIVERSITY
(N/A)
ORANGEBURG,SC 29117
Performing Department
BIOLOGICAL SCIENCES
Non Technical Summary
(N/A)
Animal Health Component
20%
Research Effort Categories
Basic
30%
Applied
20%
Developmental
50%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
2041530200030%
2041540200030%
6041540200030%
6041842200010%
Knowledge Area
204 - Plant Product Quality and Utility (Preharvest); 604 - Marketing and Distribution Practices;

Subject Of Investigation
1842 - Flax; 1540 - Hard red winter wheat; 1530 - Rice;

Field Of Science
2000 - Chemistry;
Goals / Objectives
Develop improved global chemometric processing of spectroscopic data for the analysis of chemical components in rice, wheat, and flax.
Project Methods
Near-infrared (NIR), mid-infrared (MIR), and Raman spectroscopy will be explored as rapid noninvasive methods to evaluate the chemical composition of rice, wheat, and flax. NIR spectra will be obtained using a Bruker Vector 22/N FT-NIR. Mid-infrared and Raman spectra will be obtained on a Nicolet Magna 850 FT-IR and Raman 950 instruments. Reference values for rice and wheat protein will be obtained using a LECO combustion analysis instrument. Other reference data has already been acquired. Chemometric multivariate analysis using MATLAB and PLS Tool Box software will be used to generate global routines for assessing and selecting data preprocessing that will provide improved models from reference data and spectroscopic data. The models will be validated with separate known sample sets and finally be used to predict unknown samples solely from spectroscopic data.

Progress 04/01/02 to 09/30/04

Outputs
4. What were the most significant accomplishments this past year? D. Progress Report This SCA supports the primary project 6612-44000-021-00D by providing for the development of software routines for multivariate calibration methods for food and fiber commodities. This SCA with the Computer Science Department of South Carolina State University SCA was terminated effective 1 May 2004. It was determined that South Carolina State no longer could provide assistance in software development due to no longer having personnel interested in project. The person that had been involved in the project is now an employee of ARS and is working in this CRIS under a student appointment. Thus, that person is providing the needed software development in that status and the agreement with South Carolina State is no longer required. Under the project a global chemometric program was initiated to process chemical and spectral data. This project has continued under the funding of the primary project and is now near completion.

Impacts
(N/A)

Publications