This dataset consists of four sets of flower images, from three different species: apple, peach, and pear, and accompanying ground truth images. The images were acquired under a range of imaging conditions. These datasets support work in an accompanying paper that demonstrates a flower identification algorithm that is robust to uncontrolled environments and applicable to different flower species. While this data is primarily provided to support that paper, other researchers interested in flower detection may also use the dataset to develop new algorithms. Flower detection is a problem of interest in orchard crops because it is related to management of fruit load. Funding provided through ARS Integrated Orchard Management and Automation for Deciduous Tree Fruit Crops.

The primary function of the Fruit and Vegetable Market News Division of the Fruit and Vegetable Programs is to provide an exchange of information for growers, shippers, wholesalers, researchers and others on supplies, demand and prices of fresh fruit and vegetables and speciality crops.

The primary function of the Fruit and Vegetable Market News Division of the Fruit and Vegetable Program is to compile and disseminate information that will aid producers, consumers, and distributors in the sale and purchase of poultry and their related products nationally and internationally.

This record contains videos of apple trees acquired from a ground vehicle throughout the growing season at the USDA-ARS-AFRS (United States Department of Agriculture - Agricultural Research Service - Appalachian Fruit Research Station). Research in precision management methods in orchard crops revolve around locating objects of interest, namely flowers, fruitlets, and fruit, autonomously. This dataset is provided so that researchers without access to research plots or mature trees can experiment with the data acquired during the course of an ongoing project on apple flower estimation in images. The trees shown in these videos have a mixture of colors and growth habits. In particular, the four varieties represent one of each of the Lespinasse ideotypes. Reviewers of "Multi-species fruit flower detection using a refined semantic segmentation network" please find the relevant dataset here: Data from: Multi-species fruit flower detection using a refined semantic segmentation network