APPLICATION OF IMAGE-ANALYSIS WITH NEURAL-NETWORK FOR PLANT SOMATIC EMBRYO CULTURE

A method of classifying celery embryos and nonembryos using image anal ysis with a neural network to decide the time for transfer to the next culture stage in plant somatic embryo culture is presented. Since the image database of celery cells is vast, four key input parameters (ar ea, ratio of length to width, circularity and distance dispersion) wer e selected. Among these four parameters, use of the first three was fo und to be satisfactory for classification between embryos and nonembry os. Using the three parameters, the trained neural network was also ab le to classify globular, heart- and torpedo-shaped embryos at a level comparable with estimation by a human expert. By using the trained neu ral network, the number of plantlets that would be formed after the se cond regeneration culture of 14 d could be successfully predicted from number of heart- and torpedo-shaped embryos at the end of the first r egeneration stage.