Call number: LD2668 .T4 1953 S5 / Master of Science

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Digitized by Kansas Correctional Industries

Call number: LD2668 .T4 1985 V464 / Master of Science

Two topics related to near infrared (NIR) imaging technology are studied in this thesis. The first is on the calibration of line-scan NIR imaging systems, the second covers the feasibility of applying the NIR imaging technology for wheat grading. In the first study, a methodology is proposed to pretreat the NIR image data acquired by the line-scan NIR imaging system used in this thesis to reduce the systematic noise introduced by the imaging system. This calibration in a standardization methodology is shown to improve the result of multivariate image analysis (MIA) based on multi-way principal component analysis (MPCA). This method represents a practical and easily used tool for calibration of line-scan NIR imaging systems in that it does not employ expensive standard reflectance material. In the second study, two projects are accomplished. In the first project, NIR imaging is used to classify different classes of wheat kernels. Multivariate statistical algorithms, soft independent modeling of class analogy (SIMCA) and partial least square discriminant analysis (PLS-DA) are used to discriminate between different types of wheat kernels using spectral features from NIR images. A new strategy of implementing multiclass PLS-DA algorithm is proposed in this part. The results from this study show that NIR imaging provides a potentially fast and objective method for qualitatively evaluating certain characteristics of wheat samples, such as fungal infection, sprout damage and foreign types of grain, which are now graded manually in wheat industry. In the second project, NIR imaging is used to predict the "falling number" (FN) of wheat samples. Three models are built between the features extracted from NIR images of the wheat kernels and the falling number measurements made on bulk samples. One uses a regular PLS algorithm, one uses the orthogonal partial least square (O-PLS) algorithm and the other uses the PLS plus canonical correlation analysis (PLS+CCA) algorithm. The models are analyzed and the performance of the algorithms is discussed. The errors in the prediction of the O-PLS model are investigated. The results from this study indicate that NIR imaging is a promising method for the rapid assessment of the FN of wheat samples. / Thesis / Master of Applied Science (MASc)

Price premiums and discounts are currently paid for various classes of wheat in the US marketplace. These premiums and the known heterogeneity of grain protein across landscapes beg the question of whether grain could be separated on the farm to maximize revenues. Theoretically, the concavity or convexity of a price function defines if an opportunity to segregate grain exists. Although this is true, prices in the market place are paid in stepped increments, which result in unique revenue maximizing solutions. This study was conducted to determine the economic feasibility of segregating wheat by protein content on the combine harvester during harvest. Both web-based and spreadsheet calculators were built to predict the best point in which to segregate a crop at, as well as define the protein level and quantity of each segregated volume of grain. The costs of segregation vary by operation, but fixed, variable, and opportunity costs are estimated to total $0.1739 bu⁻¹ if segregation is used every year. Revenue gains varied with the price schedule, field mean protein value, and the standard deviation of protein. Revenue gains increased in proportion to the size of a price step in a price schedule. Soft white winter wheat showed the greatest potential for segregation; however, on average yearly expected premiums are less than $.05 bu⁻¹, well below total variable costs. Price schedules occur which allow for profits of over $1.00 bu⁻¹ from segregation, although these are not the norm. Historically, on-combine grain segregation would not be economically feasible for the average producer. However, under certain supply and demand conditions, premiums occur that would make on-combine grain segregation profitable. Individuals will have to evaluate the feasibility on a case-by-case basis. / Graduation date: 2013

Thesis (Msc Food Sc (Food Science))--University of Stellenbosch, 2008. / South Africa as well as other grain producing and exporting countries’ grading systems strongly relies on hectolitre mass (HLM) as a guide to grain quality. It is known that these countries use either one of two types of HLM equipment. These devices consist of either a funnel or a cylindrical device (chondrometer) with a measuring cylinder of known volume underneath which is then filled with grain in a controlled manner. Subsequently the HLM devices from Australia, Canada, France, Germany, South Africa, the United Kingdom (UK) and the United States of America (USA) were compared using impurity free mixed wheat, single South African cultivars as well as maize samples. Very little variation in HLM measurements within the HLM devices was observed with intra-class correlation (ICC) agreement values close to one. Comparing the actual HLM values obtained with the respective devices showed that the results obtained with the Australian device was significantly (P < 0.05) higher, and those obtained with the South African devices significantly (P < 0.05) lower compared to the other devices. As would be expected the devices showed better overall ICC agreement when the HLM tests were performed with the single cultivar samples (ICC agreement = 0.762) as opposed to the mixed wheat samples (ICC agreement = 0.523). However, the HLM values obtained with all the devices correlated well with each other (ICC consistency >0.90) indicating that correction factors can therefore be developed to convert the HLM results between devices. When ten South African devices were compared statistical differences were observed, but the overall ICC agreement (0.975) and consistency (0.993) values indicated that the differences would not be significant in practice. Hectolitre mass determinations performed on samples prior to and after impurities have been removed revealed that the removal of impurities resulted in a significant (P < 0.05) increase in HLM. The effect of operator was shown to be significant (P < 0.05) when operators with three levels of competency, i.e. skilled, semi-skilled and unskilled, were investigated. The effect of wet and dry cycles on the HLM measurements was investigated and the results showed that wetting and drying could change the integrity of the wheat. Moisture correction factors cannot be applied to convert the HLM values of grain that underwent moisture changes as different samples responded differently to the moisture treatments. Comparing the respective devices with mixed maize samples (impurities not removed) very little variation in HLM measurements within each device was observed. The comparison of the devices revealed that the HLM measurements obtained with the Australian and French devices were significantly (P < 0.05) higher and that obtained from the Canadian device significantly (P < 0.05) lower compared to those obtained with the other devices. Again it was shown that the devices correlate well (ICC consistency > 0.97) and that correction factors can be applied to convert HLM results between devices. An alternative to the use of correction factors could be the replacement of the South African device with the German device for both wheat and maize. The removal of impurities from the maize samples significantly (P < 0.05) increased the HLM values. Therefore, it is likely that correction factors can be used to convert HLM values of maize samples before and after removal of impurities.