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WTRFC Project Synopsis: Decision Support Tool for Precision Orchard Management

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Written by Achyut Paudel, Manoj Karkee – Washington State University, Jostan Brown, Joe Davidson, Cindy Grimm, and Ashley Thompson – Oregon State University, Jan. 22, 2023

Traditional broad-acre orchard management practices do not result in targeted actions that are optimal for individual trees. This results in wasted resources and causes suboptimal fruit yield and quality. Recognizing the issue, our project aimed to enhance precision orchard fertilization practices by addressing individual tree nutrition requirements through a combination of automated sensing, machine learning algorithms, decision support tools, and variable rate technology.

In this project, we employed modern RGB-depth sensors to understand the unique characteristics of each tree. Over three years, the data was collected from 200 sample trees spread across 17 rows in a commercial orchard. Our outputs included canopy features like normalized area, tree trunk diameter, yellowness index, and yield. These features, crucial for assessing a tree’s nitrogen status, were selected based on feedback from experienced horticulturalists and growers.

We obtained these canopy features using machine vision and then used machine learning to develop a model predicting the needed nitrogen application level for each tree. The project also introduced a robotic method for nitrogen application, guided by real-time camera inputs. During our testing in October 2023, the robotic system showcased its ability to autonomously navigate the orchard, precisely localize itself within inches of each tree, and spray a test solution. The system achieved variable rate application by adjusting spray distance, ensuring that the root zones of the trees received the required treatment.

This project signifies a substantial advancement in orchard management, ensuring each tree receives tailored care for optimal growth and quality fruit production. By addressing the need for precision in nitrogen management, the project paves the way for efficient and sustainable orchard cultivation practices.

2 images of the robot in an orchard, indicating the camera and spray nozzle
Figure: Precision Nitrogen Application Robot (Ground Platform: Warthog, Clearpath Robotics) developed by Washington State University and Oregon State University shown working at Yakima Valley Orchards, Prosser, WA. The picture shows different sensors attached to the robot and the spray nozzle for spraying a test solution. (Picture Credits: Achyut Paudel, Washington State University)


Achyut Paudel professional photo
Achyut Paudel
Washington State University

Jostan Brown
Jostan Brown
Oregon State University

Manoj Karkee professional photo
Manoj Karkee
Washington State University

Joseph R. Davidson professional photo
Joseph R. Davidson
Oregon State University

Cindy Grimm professional photo
Cindy Grimm
Oregon State University

Ashley Thompson
Ashley Thompson
Oregon State University

Project Report and Additional information

Project Final Report

Publications from work:


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