From General to Specialized: The Need for Foundational Models in Agriculture

TL;DR

This paper evaluates the effectiveness of existing foundational models for agricultural tasks, proposes a requirements framework for an ideal agricultural foundation model, and emphasizes the need for specialized models in agriculture.

Contribution

It introduces a requirements framework for agricultural foundation models and empirically compares existing models, highlighting the necessity for dedicated agricultural foundational models.

Findings

Existing models show limited effectiveness in agriculture-specific tasks.

A framework for ideal agricultural foundation models is proposed.

Empirical evaluation underscores the need for specialized agricultural models.

Abstract

Food security remains a global concern as population grows and climate change intensifies, demanding innovative solutions for sustainable agricultural productivity. Recent advances in foundation models have demonstrated remarkable performance in remote sensing and climate sciences, and therefore offer new opportunities for agricultural monitoring. However, their application in challenges related to agriculture-such as crop type mapping, crop phenology estimation, and crop yield estimation-remains under-explored. In this work, we quantitatively evaluate existing foundational models to assess their effectivity for a representative set of agricultural tasks. From an agricultural domain perspective, we describe a requirements framework for an ideal agricultural foundation model (CropFM). We then survey and compare existing general-purpose foundational models in this framework and empirically evaluate two exemplary of them in three representative agriculture specific tasks. Finally, we highlight the need for a dedicated foundational model tailored specifically to agriculture.