GIPSA maintains a strong presence, internationally in the evaluation and quantification of grain inspection methods. Our laboratories work with the latest technologies, and through these technologies and our ongoing efforts, we're helping improve the quality of U.S. grain available to the global market. But to enhance the marketing and facilitation of grain into the future, we're also conducting internal research and participating in development and collaborative efforts with other governmental entities, laboratories, and private business. The research and analysis we conduct is in response to the prevailing trends and desires of the current market.
As agricultural crops evolve and varieties with enhanced traits are developed, reliable tests must be developed to quantify the quality traits important to the market. Rapid tests and test kits are evaluated that detect biotechnology derived grains and oil seeds, analyze protein, moisture, oil and mycotoxins. Being able to accurately predict the end-use quality of wheat has become a major objective in recent years. Milling, baking, and grain processors are looking to rapid testing methods to replace current chemical and rheological tests. With the development of such new testing procedures, reference methods are needed to validate and improve their accuracy.
Objective grain quality assessments (both official and unofficial) depend on reliable, well-standardized measurement methods. Grain inspection methods can be classified as reference (direct) methods or secondary (indirect) methods. Reference methods are those that "define" the quantity or quality in question. Often, reference methods are traceable to more fundamental standards, such as mass, length, time, temperature, or electrical charge.
To provide the market with rapid, cost-effective quality assessments, GIPSA develops "secondary" methods, based on national reference methods, for routine inspection use. These secondary methods make physical, chemical, electronic, and/or optical measurements related to the desired quality characteristics. Usually such secondary methods "predict" grain quality by using data from several different measurements. For example, dielectric moisture meters use sample weight and temperature data as well as dielectric constant data, and near-infrared spectrometers use data from many different near-infrared wavelengths. These data are applied to mathematical equations (calibrations) to compute the desired final result. GIPSA determines the specific form and coefficients of calibrations through sophisticated statistical algorithms such as multiple linear regression, partial least squares regression, principal components analysis, and artificial neural networks. GIPSA's reference methods are the basis for these calibrations.
GIPSA conducts research and development to develop, evaluate, and improve reference methods and secondary methods for grain quality analysis to better meet global grain inspection and grain marketing needs. For More information on GIPSA Methods visit our