Additional Funding Sources
This research is supported by the Specialty Crop Block Grant of the Idaho State Department of Agriculture.
Abstract
Having the ability to predict crop yield early into the season is crucial to farmers. The current method of predicting crop yield is to count the number of blossoms of one tree and multiplying that value of the number of trees in the orchard. With this method, the farmer is assuming that all trees will produce an equal amount of crop. The flaw of the current method is, each tree will not produce the same amount and therefore could affect the crop yield prediction. With the use of the Blossom Counting App, we can provide a tool for farmers to count blossoms in an efficient way. The Blossom Counting App consists of two folds, the front end, and the back end. The front end is responsible for the user interface and allowing the user to input the image they want to process. The requirement needed for the front end was using the language known as Swift. The back end is responsible for handling the image processing. The requirements needed to build the back end were using the programming language C++ and a library called OpenCV. Currently, the app is still in its development phase attempting to take into account multiple variables that decrease the performance of the app.
Blossom Counting App
Having the ability to predict crop yield early into the season is crucial to farmers. The current method of predicting crop yield is to count the number of blossoms of one tree and multiplying that value of the number of trees in the orchard. With this method, the farmer is assuming that all trees will produce an equal amount of crop. The flaw of the current method is, each tree will not produce the same amount and therefore could affect the crop yield prediction. With the use of the Blossom Counting App, we can provide a tool for farmers to count blossoms in an efficient way. The Blossom Counting App consists of two folds, the front end, and the back end. The front end is responsible for the user interface and allowing the user to input the image they want to process. The requirement needed for the front end was using the language known as Swift. The back end is responsible for handling the image processing. The requirements needed to build the back end were using the programming language C++ and a library called OpenCV. Currently, the app is still in its development phase attempting to take into account multiple variables that decrease the performance of the app.