Polycyclic epidemics are caused by pathogens capable of several infection cycles a season. They are most often caused by airborne diseases such as powdery mildew. Bimodal polycyclic epidemics can also occur. For example, in brown rot of stone fruits the blossoms and the fruits are infected at different times. For some diseases it is important to consider the disease occurrence over several growing seasons, especially if growing the crops in monoculture year after year or growing perennial plants. Such conditions can mean that the inoculum produced in one season can be carried over to the next leading to a build of inoculum over the years. In the tropics there are no clear-cut breaks between growing seasons as there are in temperate regions and this can lead to accumulation of inoculum. Epidemics that occur under these conditions are referred to as "polyetic" epidemics and can be caused by both monocyclic and polycyclic pathogens. Apple powdery mildew is an example of a polyetic epidemic caused by a polycyclic pathogen and Dutch Elm disease a polyetic epidemic caused by a monocyclic pathogen. There are many different ways to spot a disease both destructively and non-destructively. In order to understand the cause, affects, and cure for a disease, the non-destructive method is more favorable. They are techniques where sample preparation and/or repetitive processes are not necessary for measuring and observing the conditions of the plants’ health. Non-destructive approaches may include image processing, imaging-based, spectroscopy based, and remote sensing. Photography, digital imaging, and image analysis technology are useful tools to set up for image processing. Valuable data are extracted from these images and then are analyzed for diseases. But before any analysis happens, image acquisition is the first step. And within this step contains three stages. First, is energy which is the light source of  illuminating from the object of interest. Second, is the optical system such as a camera to focus on the energy. Third, is the energy measured by the sensor. To continue with the image processing, there is a pre-process where one can make certain that there are no factors such as background, size, shape of leave, light, and camera effects the analysis. After the pre-process, image segmentation is used to split the image between regions of disease and non-disease. In these images, there features of color, texture, and shape that can be extracted and used for the analysis.