| Popis: |
In the sexual reproductive life cycle of flowering plants, the growth of the pollen tube plays a vital role. The pollen tube grows towards the ovary of the flower where it delivers male reproductive material. This growth often involves twists and turns as the pollen tube navigates towards the ovary. Current growth models are a collection of mathematical equations to explain observable linear growth behavior in pollen tubes. However, there are few studies on the relationship between the fluorescence signal at the tip of the cell and the growth behavior (straight vs. turning). In this paper, we propose a method of extracting features from the tip fluorescence signal which will be used to distinguishing between straight vs. turning growth behavior. The tip signal is obtained as a ratio of the average membrane-to-cytoplasm fluorescence values over time. A two-stage scheme is used to automatically detect individual growth intervals/cycles from the tip signal and split the experimental video into growth segments. In each growth segment, we extract relevant features. An initial classification uses structure-based features to distinguish between straight vs. turning growth cycles. The signal-based features are then used to train a Naive Bayes classifier to refine the miss-classifications of the initial classification. Our results show that this two-stage process yields good classification results. |
