Sensor based determination of the fruit bearing capacity in Malus x domestica (Borkh.) aimed at precise crop load management
type: CreativeWork
description: One major goal of commercial fruit production is a homogenous fruit quality throughout the whole orchard. For this purpose, crop load management practices in apples intend to reduce the number of fruit per tree in order to (i) optimise the carbon supply to demand balance and the (ii) fruit quality in the current season, and (iii) ensure flower bud formation for the following season. Currently, crop load management is routinely performed field uniform without taking into consideration the inter-tree variability in flower or fruit set and the photosynthetic capacity of the trees, which frequently occurs in commercial orchards. Because of the variability among the trees, uniform crop load management can lead to sub-optimal numbers of fruit per tree when targeting homogenous fruit qualities. Currently, no tree-adapted crop load management practices have been developed. One reason is the lack of plant physiological and agronomic models to evaluate the actual fruit set of individual trees and to derive management decisions from these data. For tree-adapted crop load management, the fruit set and growth capacity of all trees within an orchard, often exceeding 2,500 trees per hectare, need to be mapped. Frequent studies of georeferencing and sensing individual trees’ data are available, but the developed approaches lack further application in decision support models. The aim of this thesis was (i) to investigate inter-tree variability in flower set, fruit set, and total leaf area per tree in apple, (ii) to develop a modelling approach to estimate the trees’ capacity to produce fruit of desired diameters, the fruit bearing capacity, which is based on spatially recorded sensor data of individual trees, and finally (iii) to investigate the application of the model, future possibilities, and advantages of tree-adapted crop load management. The variance in flowers per tree was investigated in two commercially relevant apple cultivars ('Elstar': 200 trees in 2011, 2014, 2015; 'Ga…
abstract: One major goal of commercial fruit production is a homogenous fruit quality throughout the whole orchard. For this purpose, crop load management practices in apples intend to reduce the number of fruit per tree in order to (i) optimise the carbon supply to demand balance and the (ii) fruit quality in the current season, and (iii) ensure flower bud formation for the following season. Currently, crop load management is routinely performed field uniform without taking into consideration the inter-tree variability in flower or fruit set and the photosynthetic capacity of the trees, which frequently occurs in commercial orchards. Because of the variability among the trees, uniform crop load management can lead to sub-optimal numbers of fruit per tree when targeting homogenous fruit qualities. Currently, no tree-adapted crop load management practices have been developed. One reason is the lack of plant physiological and agronomic models to evaluate the actual fruit set of individual trees and to derive management decisions from these data. For tree-adapted crop load management, the fruit set and growth capacity of all trees within an orchard, often exceeding 2,500 trees per hectare, need to be mapped. Frequent studies of georeferencing and sensing individual trees’ data are available, but the developed approaches lack further application in decision support models. The aim of this thesis was (i) to investigate inter-tree variability in flower set, fruit set, and total leaf area per tree in apple, (ii) to develop a modelling approach to estimate the trees’ capacity to produce fruit of desired diameters, the fruit bearing capacity, which is based on spatially recorded sensor data of individual trees, and finally (iii) to investigate the application of the model, future possibilities, and advantages of tree-adapted crop load management. The variance in flowers per tree was investigated in two commercially relevant apple cultivars ('Elstar': 200 trees in 2011, 2014, 2015; 'Ga…
author: Penzel, Martin
language: en
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date published: 2022
date modified: 2026-07-27T21:28:35Z
provider: Technische Universität Berlin
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Technische Universität Berlin

PropertyValue
property ID: DOI
value: 10.14279/depositonce-15247