In this study, it was aimed to determine some element contents and some quality properties and to compare these parameters at each stage in the chemically refining process of crude corn oil. Color (lovibond tintometer), free fatty acidity, peroxide values and fatty acid compositions were determined in the samples of corn oil taken from consecutive stages of chemically refining. Also, the content of elements (Na, Mg, K, Ca, Fe, Pb, Cd, Ni, Mn, Zn, Co, Cr, P, Cu) was analyzed, by using inductively-coupled plasma-mass spectrometry (ICP-MS) and inductively-coupled plasma-optical emission spectrometry (ICP-OES) after microwave digestion. The color (Lovibond tintometer), free fatty acidity and peroxide values in the chemically refining process varied between 2.7-16, %0.09-2.12, 10.95-1.08 mEqO2/kg, respectively. Oleic, linoleic and linolenic acid contents changed between 30.486-30.580%, 54.339-54.703% and 0.972-0.993%, respectively, in the chemically refining stages. While no trans fatty acids detected in crude corn oil and after degumming-neutralization step, very low amount of trans oleic acid (0.040%) and total trans linoleic acid (0.132%) was detected in bleached corn oil. The total trans fatty acid content little more increased in the last stage of the chemically refining. However, total trans fatty acid content of refined corn oil was < 0.3%. It was clearly seen that Na, Mg, K, P, Ca, Mn, Fe, Pb, Ni, Cr, Cu element contents decreased significantly at the end of the chemically refining process. Although Cd, Co and Zn elements were determined in crude corn oil, these elements were not detected in the refined corn oil. The results obtained showed that the chemically refining process effected some of the quality properties of corn oil and especially the changes in the element contents.

The present study was focused on the design and implementation of an experimental recognition system for dirty chicken eggshell by using an image analysis technique. Image analysis based observation and evaluation techniques can be used efficiently and effectively for agricultural product quality control. Dirt stains on eggs are the result of mainly by feces (black to light brown stains), uric acid (white stains), yolk, and blood. The experimental system was used to obtain dark level images of dirty stains of chicken eggs owing to feces. For this aim, the dirty chicken eggs which have dirty parts were put under a webcam, and dirtiness degree was evaluated by using developed image analysis software at the LabVIEW platform. For the experiment, 100 clean and 100 dirty eggs were used to accurate the determination of dark stains. The results of the research showed that the designed experimental system pointed an accuracy of 99.8% at painted grade eggs. On the other hand, the accuracy of the differentiation of the dirt stains by feces was 98.5%. The developed system can be upgraded for developing egg sorting machines by presence-absence of dirty stains in eggshell.