Studies were conducted to establish a new technique for predicting moisture content (MC) of soybean using acoustic methodology including the development of a technique for determining the variety of soybean based on dimensional measurements. The first objective of this study is to investigate a more detailed frequency domain method of modelling the MC of four varieties of soybean: Asgrow AG5701, Delta Pine DP5915RR, Hutcheson Public, and Pioneer 95B53. Seven different levels of MC for each variety between 7% and 18% were examined using an impact chamber as the means of producing the acoustical energy. The time domain data collected by a data recorder were transformed into frequency domain and the power spectral density (PSD) was computed based on a 1024-point Fast Fourier Transform (FFT). The frequency range of the data was from 0 Hz to 8000 Hz. The frequency domain data were partitioned into multiple slices of frequency bands (sub bands), and the total energy of each sub band was computed to yield a data point and the resulting data point was normalized by dividing it by the data point from a selected slice of frequency band (reference frequency band). Statistical analyses were used to develop the models using multiple regressions. In order to facilitate the use of variety specific MC model, this study also includes dimensional measurements of the four varieties of soybean to determine whether or not it is possible to discriminate a soybean variety based on its dimensional features. The dimensional measurements were done with a dial caliper in three axes: parallel to the Hylo (d1), perpendicular to the Hylo (d2), and in the same plane as the Hylo (d3). One hundred grains of each variety of soybeans were used in the measurements.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-2028 |
| Date | 13 December 2003 |
| Creators | Al-Risaini, Mansour Ibrahim |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
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