Browsing by Subject "Cotton -- Grading"
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Item A multi-stage hedonic market model of cotton characteristics with separable supply and demand(Texas Tech University, 1989-05) Bowman, Kenneth RayThis study examined the impacts of fiber characteristics on cotton prices from 1976 to 1986 for 4 production and marketing regions of the United States. A set of 11 equations were estimated to determine the effects of cotton fiber characteristics on cotton prices. Trash, color, staple length, micronaire, and strength were found to have statistically significant impacts on cotton prices. Length uniformity was not statistically significant. Characteristic effects were found to vary across time and across regions. However, trends in attribute values were similar for all characteristics across all regions. Characteristic price flexibilities were calculated using the regional base prices and characteristic averages of each year. Cotton prices were not price responsive with respect to characteristic variation. In this context, percentage changes in characteristic levels did not cause equivalent percentage changes in cotton prices. A set of 24 equations found that cotton characteristic values were functions of other characteristics as well as characteristic specific demand shifters, base price and proportion of open end spindles to ring spindles. Characteristic impacts on characteristic values were similar across regions, though some variation of effects were present. The effects of base price were also similar across regions. The proportion of open end spindles to ring spindles affected characteristic values with the largest impacts occurring in the West. Separate systems of equations were constructed to estimate the effects of environmental variables on each cotton characteristic in each production region of the country. Seasonal rainfall and temperature affected characteristics in all regions though parameter estimates and functional forms varied considerably among production areas. There is a growing recognition of the need to understand the values of fiber characteristics. Fiber characteristic values affect the revenues of producers and the costs of buyers. The results of this study demonstrate that there is a functioning market for cotton characteristics. The characteristics model constructed in this paper is useful because it presents an alternative to the current method of determining fiber quality premiums and discounts.Item Assessment of trash content of cotton using 2D x-ray imagery(Texas Tech University, 2004-08) Dogan, Mehmet SerdarTrash content of raw cotton is a critical quality attribute. Therefore, its assessment is crucial for evaluating its processing and market value. Current technologies, including gravimetric and surface scanning methods, suffer from various limitations. Furthermore, worldwide, the most commonly used method still is human grading. Thus, the need for implementing new technologies is growing. One of the best alternatives to aforementioned approaches is x-ray imaging since it allows a thorough analysis of contaminants in a very precise and quick manner. In other work, we have successfully used x-ray tomographic imaging in the detection and classification of cotton contaminants. In this work, we choose to use x-ray radiographic imaging because of its real-time applicability. The segmentation of trash particles in 2D transmission images is difficult since the background cotton is not uniform. In addition, there is considerable overlap between the gray levels of subtle trash types and dense cotton. We dealt with this problem by characterizing and identifying the background cotton via scale-space filtering followed by a "background normalization" process that removes the background cotton successfully, while leaving the trash particles intact. Furthermore, we have successfully employed stereo x-ray vision for recovering the depth information of the piled trash in controlled samples. While adding to the accuracy with which the trash is counted, this method is much faster than the tomographic approach, as it requires only two projections. We tested our technique on 280 cotton radiographs—graded from 1 to 7 according to its trash content by expert graders—and compared the results with the existing systems of cotton trash evaluation. Results obtained with the proposed method were highly correlated with those obtained using the current systems. Given that the approach described here provides the trash mass in real-time, when realized, it will have a wide-spread usage in the cotton industry.