Patrick Nestler
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Patrick Nestler has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Stefan Streif
Technische Universitt Chemnitz, Chemnitz, Germany
2 shared publications - Alexander Kobelski
Automatic Control and System Dynamics Lab, Technische Universität Chemnitz, Straße der Nationen 62, 09111 Chemnitz, Germany
1 shared publication - Christopher Shaw
Leibniz Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany, igb-berlin.de
1 shared publication - Mareike Mauerer
Division Biosystems Engineering, Albrecht Daniel Thaer-Institute of Agricultural and Horticultural Sciences, Humboldt-Universität zu Berlin, Albrecht-Thaer-Weg 3, 14195 Berlin, Germany
1 shared publication - Thorsten Rocksch
Division Biosystems Engineering, Albrecht Daniel Thaer-Institute of Agricultural and Horticultural Sciences, Humboldt-Universität zu Berlin, Albrecht-Thaer-Weg 3, 14195 Berlin, Germany
1 shared publication - Uwe Schmidt
Division Biosystems Engineering, Albrecht Daniel Thaer-Institute of Agricultural and Horticultural Sciences, Humboldt-Universität zu Berlin, Albrecht-Thaer-Weg 3, 14195 Berlin, Germany
1 shared publication
Latest Publications
- Open Access
- 17 September 2026
- Published by Elsevier in Computers and Electronics in Agriculture
- Vol. 256
Optimization of fish feed formulation and pH regulation in on-demand coupled aquaponic systems: A model-based framework for sustainable nutrient and water management
- 17 September 2026
- Published by Elsevier in Computers and Electronics in Agriculture
- Vol. 256
Open AccessOptimization of fish feed formulation and pH regulation in on-demand coupled aquaponic systems: A model-based framework for sustainable nutrient and water management
- Open Access
- 10 September 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (18) , 8140
An Algorithm for Nutrient Mixing Optimization in Aquaponics
Controlled environment agriculture is a promising alternative to conventional production methods, as it is less affected by climate change and is often more sustainable, especially in circular and recycling frameworks such as aquaponics. A major cost factor in such facilities, however, is the need for skilled labor. Depending on available resources, there are endless possibilities on how to choose ingredients to realize a desired nutrient solution. At the same time, the composition of the desired solution is subject to fluctuations in fish water quality, fertilizer availability, weather, and plant development. In high-evaporation scenarios, e.g., summer, nutrient solutions might be mixed multiple times per day. This results in a complex, multi-variable task that is time-consuming to solve manually, yet requires frequent resolution. This work aims to help solve this challenge by providing methods to automate the nutrient mixing procedure. A simple mass-balance-based model of a nutrient mixing tank with connections to different water sources, drains, and fertilizers is provided. Using methods of static optimization, a program was developed which, in consideration of various process constraints and optimization variables, is able to calculate the necessary steps to mix the desired solution. The program code is provided in an open-source repository. The flexibility of the method is demonstrated in simulation scenarios. The program is easy to use and to adapt, and all necessary steps are explained in this paper. This work contributes to a higher automation level in CEA.
- 10 September 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (18) , 8140
Open AccessAn Algorithm for Nutrient Mixing Optimization in Aquaponics
Controlled environment agriculture is a promising alternative to conventional production methods, as it is less affected by climate change and is often more sustainable, especially in circular and recycling frameworks such as aquaponics. A major cost factor in such facilities, however, is the need for skilled labor. Depending on available resources, there are endless possibilities on how to choose ingredients to realize a desired nutrient solution. At the same time, the composition of the desired solution is subject to fluctuations in fish water quality, fertilizer availability, weather, and plant development. In high-evaporation scenarios, e.g., summer, nutrient solutions might be mixed multiple times per day. This results in a complex, multi-variable task that is time-consuming to solve manually, yet requires frequent resolution. This work aims to help solve this challenge by providing methods to automate the nutrient mixing procedure. A simple mass-balance-based model of a nutrient mixing tank with connections to different water sources, drains, and fertilizers is provided. Using methods of static optimization, a program was developed which, in consideration of various process constraints and optimization variables, is able to calculate the necessary steps to mix the desired solution. The program code is provided in an open-source repository. The flexibility of the method is demonstrated in simulation scenarios. The program is easy to use and to adapt, and all necessary steps are explained in this paper. This work contributes to a higher automation level in CEA.