Published: 25 June 2020| Version 1 | DOI: 10.17632/w2t9w75cv6.1
Dolores del Brio,


The dataset is composed of 60 pear tree images. They were taken during full bloom in a pear orchard located at National Institute of Agricultural Technology (INTA) Experimental Station, General Roca, Argentina (39° 1’ 40’’ S; 67° 44’ 34’’ W).The orchard was established in 2003 with ‘Williams’ cultivar pear trees grafted on seedling rootstock .Trees were planted in a total area of 1.8 ha at a distance of 2m between trees by 4m between rows and were trained as espalier. A few days before full bloom, images were obtained from 30 trees, under two conditions: i) natural daylight between 10 am and 13 pm (PE_FL_DA_2018), ii) at night with the artificial flash light of the camera (PE_FL_NI_2018). A black curtain was unfolded behind the trees when images were obtained under daylight conditions in order to avoid interference from neighboring trees. All images were taken with an RGB digital camera (14.1 MP) at approximately 3.0 m from the tree in a 90° angle to the row. An object of known dimensions (a 15x15 cm square) was placed in each tree as a scale reference. Simultaneously, all the flower clusters on each tree were manually counted. Images taken by using different proximal sensors can be used to estimate the number of flowers or fruits in trees. The accuracy of those methods has been studied and tested in different fruit species by many researchers with encouraging results. A similar dataset has been published by the same contributors in Mendeley Data Repository for apple trees.



Object Detection, Precision Agriculture, Pear, Image Analysis