About Me/Career
Hi there! I’m Moritz, a PhD student 🎓 at the intersection of crops 🌾 and technology 💻, asking the question how we can use technology to advance crop science and agriculture in a practical and meaningful way. For this, I have developed a range of skills, including programming microcontrollers in C, 3D printing, Python, CAD design, PCB design, image analysis (including hyperspectral, multispectral, and RGB imaging), neural networks, and two degrees worth of plant and crop science (full skill list with showcases).
On this website, I share blog posts on a variety of topics and provide some background information on me and my work.
Education / Experience - Timeline
- use technology to advance crop science in a practical and meaningful way
- the "SmartWheat" project is working on developing AI-driven models for climate-resilient wheat breading using imaging data, crop modeling, and machine learning techniques
- Development of autonomous Systems for remote sensing on potatoes
- Multispectral imaging
- www.rapagra.nl
- AI Meets Agriculture:
- building the largest crop growth dataset for AI in plant sciences
- Paper by the chairgroup regarding there aproach
- Software-Development:
- Clean, geo-locate, and standardize diverse datasets using Python and pandas, ...
- WUR Chair Group for Artificial Intelligence
- Specialization: Crop Science
- Relevant courses:
- Research Methods in Crop Science
- Systems Analysis and Modelling
- Modeling of functional diversity in crop production
- Drones in agriculture
- Programming in Python
- Grade: 1.0 (German system)
- GPA: 4.0 (grade translation)
- Relevant courses
- Computational Biology
- Plant Genetics
- Programming in C
- ~ 600 h
- Lab work:
- western blot
- sterile work
- establishment and maintaining cell lines
- life cell imaging
- 3D-printing of cell scaffolds
- Teaching: assistant for practical courses, and tutoring
- Grade: 1.3 (German system)
- Cum Laude / with distinction
- GPA: 3.5 (grade translation)
- Major: plant biotechnology
- Relevant courses:
- biosystem engineering
- biostatistics
- imaging methods in lifescience
- crop breeding
- biochemistry
- pedology
- microbiology
- Thesis: “Development of an automated hyperspectral imaging approach for apple russeting quantification" (Grade: 1.0)
- Grade: 1.0 (German system)
- GPA: 4.0Â (grade translation)
- Awarded by the GDCh as the best graduate of the year
- Relevant courses
- biotechnological work
- molecular genetic methods
- protein biochemical
- enzymatic methods
Locations of my study
Blog Posts about Career
PhenoSelect: Training a Neural Network Because I Refuse to Click on 100,000 Leaves
An introduction to PhenoSelect, an open-source deep learning pipeline designed to automate leaf...
How to Image a Whole Apple
A deep dive into the process of building a custom hardware and software...
Beyond the Naked Eye OR Why More Data Isn’t Always Better
An exploration into how hyperspectral imaging and machine learning can be used to...
Modeling the Future of Agrivoltaics: Simulating AV with LEDs
Modeling the Future of Agrivoltaics: Simulating AV with LEDs A Blog Post A...
Expanding the Pipeline: Incorporating Canopy Height and Canopy Temperature
This blog post explores how to expand a drone-based pipeline for crop analysis....
From Drone Images to Insights: Using Neural Networks for Canopy Coverage Detection and Measurement
This blog explores the development of a complete workflow—from drone images to accurate...
The Power of small Micro-Electronics Projects
The Power of small Micro-Electronics Projects A Blog Post This anecdote demonstrates the...
Phenotype to Genotype Gap
This report explores the genetic and phenotypic components of ideotypes, emphasizing their role...