The Unified Grain Moisture Algorithm is
capable of improved accuracy and allows the combination of many grain types
into a single “unified calibration”. The purposes of this research were to
establish processes for determining unifying parameters from the chemical and
physical properties of grains. The data used in this research were obtained as
part of the United States Department of Agriculture-Grain Inspection, Packers
and Stockyards Administration's Annual Moisture Calibration Study. More than
5,000 grain samples were tested with a Hewlett-Packard 4291A Material/Impedance
Analyzer. Temperature tests were done with a Very High Frequency prototype
system at Corvinus University of Budapest. Typical chemical and physical
parameters for each of the major grain types were obtained from the literature.
Data were analyzed by multivariate chemometric methods. One of the most
important unifying parameters (Slope) and the temperature correction
coefficient were successfully modeled. The Offset and Translation unifying
parameters were not modeled successfully, but these parameters can be estimated
relatively easily through limited grain tests.
Improving the accuracy of sea surface salinity retrieval using GNSS-R data to correct the sea state effect
