Characterization of peach tree crown by using high-resolution images from an unmanned aerial vehicle

Yue Mu,Kiyoshi Honda,Koji Noshita,Daisuke Takata,Bangyou Zheng,Wei Guo,Yuichiro Fujii,Seishi Ninomiya

doi:10.1038/s41438-018-0097-z

Abstract

In orchards, measuring crown characteristics is essential for monitoring the dynamics of tree growth and optimizing farm management. However, it lacks a rapid and reliable method of extracting the features of trees with an irregular crown shape such as trained peach trees. Here, we propose an efficient method of segmenting the individual trees and measuring the crown width and crown projection area (CPA) of peach trees with time-series information, based on gathered images. The images of peach trees were collected by unmanned aerial vehicles in an orchard in Okayama, Japan, and then the digital surface model was generated by using a Structure from Motion (SfM) and Multi-View Stereo (MVS) based software. After individual trees were identified through the use of an adaptive threshold and marker-controlled watershed segmentation in the digital surface model, the crown widths and CPA were calculated, and the accuracy was evaluated against manual delineation and field measurement, respectively. Taking manual delineation of 12 trees as reference, the root-mean-square errors of the proposed method were 0.08 m (R2 = 0.99) and 0.15 m (R2 = 0.93) for the two orthogonal crown widths, and 3.87 m2 for CPA (R2 = 0.89), while those taking field measurement of 44 trees as reference were 0.47 m (R2 = 0.91), 0.51 m (R2 = 0.74), and 4.96 m2 (R2 = 0.88). The change of growth rate of CPA showed that the peach trees grew faster from May to July than from July to September, with a wide variation in relative growth rates among trees. Not only can this method save labour by replacing field measurement, but also it can allow farmers to monitor the growth of orchard trees dynamically.

Highlights

It is well known that the development of tree canopy affecting both quality and yield of peaches[1]
The specific objectives of this study were to (1) propose a new unmanned aerial vehicles (UAVs) image analysis method for the accurate and efficient characterization of crown width and crown project area of peach trees, (2) evaluate its performance, and (3) use it to analyse the growth of peach trees in 2017 in Okayama, Japan
Accuracy comparison with other researches We demonstrated a UAV image analysis method for accurate and efficient determination of crown width and crown projection area (CPA) of peach trees and evaluated its accuracy against field measurements

Summary

Introduction

It is well known that the development of tree canopy affecting both quality and yield of peaches[1]. In Japan, to achieve high economic production, manipulation and management of the tree canopy are essential. Precision farming applies the appropriate timing, amount, and location of fertilizer and pesticides to crop management[2]. The preliminary step of precision farming is acquiring as much growth data from the crop as possible[3], which depends on accurately describing the morphological and structural characteristics of crops. Relevant morphological characteristics include crown width, height, area, and volume. Crown width is important for precision spraying[4,5,6] and machine harvesting[7], while crown projection area (CPA)

Objectives

Results

Discussion

Conclusion