Detection of Lettuce Plant Conditions Based on Images using Backpropagation Method

In cultivating different ways should be possible, one of which is utilizing the aquaculture strategy. Lettuce is remembered for plants that can be developed utilizing this strategy. Produce great lettuce, it deals with and great plant the executives. Direct observing requires a ton of energy and takes a great deal of time since you need to really look at the state of the plants individually. With these issues, a framework was intended to distinguish the state of the lettuce leaves involving a camera as a picture catch instrument. This exploration planned to make a work area based framework for recognizing the state of lettuce utilizing the Backpropagation characterization strategy. The states of lettuce plants are separated into two classes in view of lettuce leaves with sound green tips, and lettuce leaves with less great leaf tips with yellow tone and earthy colored spots. Identification of lettuce plant conditions utilizing pictures taken with a Raspberry-pi camera. The consequence of this exploration is the framework can identify sound leaf condition class and leaf condition class with yellow tone and earthy colored spots. The result of the framework is as class names and likelihood values from the order results. With a parameter in the form of a training data partition of 90% and 10% test data, the accuracy rate is 98%.