Empirical validation of physics-informed transfer benefits

Establish empirically, for the target multispectral or hyperspectral agri-food experiment, whether physics-informed spectral-reconstruction approaches improve physical consistency and transfer across relevant sensing or acquisition conditions.

Background

The taxonomy identifies physics-informed methods as reconstruction approaches that incorporate physical structure through simulated data, physics-aware architectures, forward models, camera response functions, mixing assumptions, or other domain knowledge. Such methods are motivated by the possibility that physical constraints can improve the plausibility of reconstructed spectral information and its transfer beyond the conditions represented in the training data.

However, the paper does not establish that these benefits occur reliably in agri-food MSI/HSI experiments. Their effectiveness remains dependent on the target sensing configuration, physical assumptions, data coverage, and evaluation design, so empirical validation is required for each intended application.