AN IMAGE-ANALYSIS TECHNIQUE FOR ACCURATE COUNTING OF POLLEN ON STIGMAS

Pollen counting is an important element of research in pollination, an d the majority of current methods involve manual counting. An image-pr ocessing technique has been developed for accurate counting and sizing of small particles, and this was tested on almond pollen grains. Our automatic process was found to be several times faster than manual cou nting and more accurate, with an average error of only 3 %. Because of its simplicity, it is an attractive tool for research on such topics as pollen viability or germination. It was found that in the methods u sing vials there were 'residues' of c. 17 % on the vial walls and on t he handling tools. In addition, the first drop from each vial containe d, on average, 1.65 times more grains than the average number of grain s in all drops, whereas the last drop from each vial contained fewer g rains than the average. This phenomenon was correlated with the non-un iform pollen distribution in the suspension. An automatic counting sys tem is therefore, recommended, to avoid the problem, otherwise a calib ration procedure should be used that accounts for both the residues on the tools and the non-uniformity of contents of sample drops.