Starchless Mutant Allelic Series as Quantitative Test of CRB N-Scaling

Plants have a remarkable ability to sense gravity and grow in the right direction — roots down, shoots up. Deep inside certain specialized cells, tiny starch-filled granules called statoliths act like biological ball bearings, settling toward the bottom of the cell and telling the plant which way is 'down.' But here's what scientists don't fully understand: how *precise* is this sensing system, and how much of that precision actually comes from the statoliths themselves versus some other backup mechanism? This hypothesis borrows a powerful idea from statistics called the Cramér-Rao bound — essentially a mathematical law that sets the absolute best precision any measurement system can achieve, based on how much information it has to work with. The proposal is elegant: use mutant plants that make progressively fewer statoliths (thanks to genetic tweaks that reduce starch production) to create a spectrum from 'lots of statoliths' to 'almost none.' Then measure how precisely each mutant can detect gravity. If statoliths are the main information source, the math predicts a very specific relationship — precision should degrade in a predictable, calculable way as statolith numbers drop. If it doesn't follow that curve, something else is doing part of the sensing job. This is essentially using genetics as a dial and statistics as a ruler to dissect a biological sensor that plants evolved hundreds of millions of years ago. The beautiful part is that it's not just a yes/no question — the math gives you a quantitative prediction you can actually test in a lab.

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