Predicting resprouting of Platanus × hispanica following branch pruning by means of machine learning.

ABSTRACT:

Introduction

Resprouting is a crucial survival strategy following the loss of branches, being it by natural events or artificially by pruning. The resprouting prediction on a physiological basis is a highly complex approach. However, trained gardeners try to predict a tree's resprouting after pruning purely based on their empirical knowledge. In this study, we explore how far such predictions can also be made by machine learning.

Methods

Table-topped annually pruned Platanus × hispanica trees at a nursery were LiDAR-scanned for two consecutive years. Topological structures for these trees were abstracted by cylinder fitting. Then, new shoots and trimmed branches were labelled on corresponding cylinders. Binary and multiclass classification models were tested for predicting t

SUBMITTER: Shu Q 

PROVIDER: S-EPMC10954810 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature