# Combining expert knowledge and neural networks to model environmental stresses in agriculture

arXiv: https://arxiv.org/abs/2111.00918 · HTML: https://mlsanity.com/paper/2111.00918/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 20 references that are in the map.
- First posted on arXiv 26 Oct 2021.

## Builds on (most cited first, 1 of 1)

- [Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems](https://mlsanity.com/paper/1903.12394/) (2019)

## Abstract (arXiv)

In this work we combine representation learning capabilities of neural network with agricultural knowledge from experts to model environmental heat and drought stresses. We first design deterministic expert models which serve as a benchmark and inform the design of flexible neural-network architectures. Finally, a sensitivity analysis of the latter allows a clustering of hybrids into susceptible and resistant ones.