Multiple digital imaging companies can gather apple orchard data to map flower bud load, flower cluster number and fruitlet number at the tree level. However quickly matching photographic survey data to maps which can accurately guide management decisions remains challenging. Over the past year, Cornell University has partnered with several companies which can collect and apply survey data to guide precision pruning, precision blossom thinning, and precision fruitlet thinning in high density apple orchards of Western New York. Photographs and surveys from companies which collect single tree information provided the highest resolution information to guide precision sprayers. Precision sprayers were able to successfully apply treatments to the tree level, but the survey data first needed to be transformed into task maps which defined unique tree positions using the same GPS system used to collect the data and then control the sprayer to avoid an offset. Improving orchard management using digital tools may help improve crop load management but the success of this effort depends on the treatment resolution (section of row vs individual tree) as well as when crop load was modified, such as pruning, blossom, and or fruitlet timing.
