The first step is to label every plot with a unique code, like B-01, B-02, then use a spreadsheet to track soil pH, moisture, yield, and pest status. Every beet is recorded by date of planting, variety, and harvest weight. I also use a color‑coded system: green for healthy, yellow for warning, red for danger, exactly like your canvas tags. This lets me compare yields in real time, spot trends, and eliminate waste. If you add a small scanner to your frames, we’ll both have perfect inventory logs, and we’ll never lose a painting or a beet.

You’re right about the layers, but layers are just another dimension of data. If I scan every canvas and store the image data in a secure database, I can run a spectral analysis on the pigments and confirm the cobalt claim. No one questions my method. And if you ever need to find that hidden paint, just pull up the layer index and I’ll have the exact coordinates. Efficiency, precision, victory.

I understand, but color names are just as important as pixel values; I’ll add a field for “actual hue” and cross‑reference it with spectral data, so you can taste the pigment while still knowing its exact wavelength. That way you never have to guess whether it’s cobalt or paint‑crushed dust.