QUANTITATIVE ESTIMATION OF CORN ENDOSPERM VITREOSITY BY VIDEO IMAGE-ANALYSIS

Vitreosity, or hardness, is an important grain quality factor for com. An increasing amount of research is aimed at understanding the geneti c and biochemical basis of vitreosity and at improving vitreosity of h igh-lysine (opaque-2) com through breeding strategies. Previous method s for quantifying vitreosity were destructive, subjective, or required sophisticated equipment and expertise. This study evaluated a simple video image analysis procedure for quantifying vitreosity and determin ed how various processing steps affected the results. Kernels were sur rounded with modeling clay and viewed on a light box with a monochrome video camera. The video signal was captured to a personal computer an d analyzed with commercially available hardware and software. A segreg ating F2 population from a cross of vitreous Pool 29 QPM X nonvitreous B73o2 was classified visually into 10% steps of vitreosity. High corr elations were observed between visual classification and average grays cale values of captured video images at all stages of processing. Gray scale value was inversely proportional to kernel thickness. Removing i mage background and eliminating a segment corresponding to the embryo area increased the average grayscale range and resolution, but adjustm ent for kernel thickness did not substantially improve the correlation . This method allows researchers and breeders to quantify vitreosity o f corn and other cereal grains on a continuous scale with readily avai lable equipment and expertise and overcomes the problems of subjectivi ty, destructiveness, and complexity associated with other approaches.