RESEARCH PAPER
Carbon consumption of developing fruit and the fruit bearing capacity of individual RoHo 3615 and Pinova apple trees
Martin Penzel 1, 2  
,   Alan Neil Lakso 3  
,   Nikos Tsoulias 1, 4  
,   Manuela Zude-Sasse 1  
 
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1
Horticultural Engineering, Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Germany
2
Agromechatronics – Sensor-based Process Management in Agriculture, Technische Universität Berlin, Germany
3
Horticulture Section, Cornell AgriTech, Cornell University, Geneva, NY 14456, USA
4
Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, Greece
CORRESPONDING AUTHOR
Manuela Zude-Sasse   

Horticultural Engineering, Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Max-Eyth-Allee 100, 14469, Potsdam, Germany
Final revision date: 2020-09-03
Acceptance date: 2020-09-15
Publication date: 2020-10-19
 
Int. Agrophys. 2020, 34(4): 409–423
 
KEYWORDS
TOPICS
ABSTRACT
This paper describes an approach to estimate the photosynthetic capacity and derive the optimum fruit number for each individual tree, in order to achieve a defined fruit size, which is named as the fruit bearing capacity of the tree. The estimation of fruit bearing capacity was carried out considering the total leaf area per tree as measured with a 2-D LiDAR laser scanner, LALiDAR, and key carbon-related variables of the trees including leaf gas exchange, fruit growth and respiration, in two commercial apple orchards. The range between minLALiDAR and maxLALiDAR was found to be 2.4 m² on Pinova and 4.3 m² on RoHo 3615 at fully developed canopy. The daily C requirement of the growing fruit and the associated leaf area demand, necessary to meet the average daily fruit C requirements showed seasonal variation, with maximum values in the middle of the growing period. The estimated fruit bearing capacity ranged from 33-95 fruit tree-1 and 45-121 fruit tree-1 on the trees of Pinova and RoHo 3615, respectively. This finding demonstrates sub-optimal crop load at harvest time in both orchards, above or below the fruit bearing capacity for individual trees. In conclusion, the LiDAR measurements of the leaf area combined with a carbon balance model allows for the estimation of fruit bearing capacity for individual trees for precise crop load management.
 
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