This is interesting and unusual, although the title and abstract don't help much. (Why is selecting on phenotype so interesting when it's what's always been done?)

If I am understanding it right, what they are proposing is essentially a GCTA on phenotypic relatedness instead of SNP genetic relatedness: using a large number of phenotypes (which will all be heritable), organisms which are phenotypically 'similar' must also be genetically similar. If you had many different measurements of an organism, you could do nearest-neighbors in the high dimensional space to find the other organisms relatively similar to it; if you can predict any of its neighbors to be a high (or low) breeding value organism, you can predict it will be higher (or lower), and select for (or against) it. This is based just on genetic similarity, not the specific traits we want to breed for, so it can be done using any set of traits as long as they are somewhat heritable.

Now, usually we don't have a lot of different high quality measurements as they are expensive to collect or are not yet available; so what can we do? Find a single measure which serves as a 'fingerprint' of similarity. In this case, the spectrum of reflected light from each light: it reflects all sorts of phenotypic traits from thickness to color to health to chlorophyll to pigmentation to water content etc etc, all mashed up into a single extremely complex measurement. The reflection is an ultra-cheap single measurement which can be done robotically at any time using a solid-state device which doesn't break down or wear out or have consumables (other than electricity). It's so complex you can't use it very well directly, but it does serve to fingerprint individuals as similar or dissimilar overall, similar to how number of shared SNPs fingerprints individuals as similar or dissimilar overall even though we don't know what SNPs are relevant or how they act. So you photograph all your plants, compute the distances, and out come estimates of breeding value without requiring pedigrees or genotyping data or waiting for maturity.

This could be done with more normal sets of measurements, or could use other exotic high-dimensional measurements (mass-spectrometry of air samples? blood sample stool samples? microbiomes? electronic health records? actigraphs? writing samples? raw brain imaging data?).