Abstract
<jats:p> CERIS-JGRA replaces the environmental mean in Finlay-Wilkinson regression with a climate-derived index, so that reaction norm association mapping can dissect the genetics of phenotypic plasticity. Its defining design choice forecloses that objective. An index correlated at ρ with the environmental means decomposes exactly into ρ times the mean plus a residual, and its loading on informative variation orthogonal to the mean, τ, cannot exceed √(1 − ρ <jats:sup>2</jats:sup> ). Sensitivity independent of mean performance is orthogonal to the mean by definition, reaching the slope only through τ, and the non-centrality of a plasticity-specific test goes as τ <jats:sup>2</jats:sup> . The algorithm maximizes ρ, minimizing by construction the channel carrying the signal it is used to detect. Simulation confirms this. A parameter-free expression reproduces observed power across 189 conditions to a root mean square error of 0.030. Power to detect plasticity-specific loci falls from 0.64 at ρ = 0 to 0.009 at ρ = 0.99 and 0.003 at ρ = 0.996, invariant to architecture, coupling and environment count. Holding ρ at 0.5 while reducing τ from 0.87 to zero drops power from 0.576 to 0.000: governs discovery as a proxy, not a cause. Panel size compensates, scaling as 1 / (1 − ρ <jats:sup>2</jats:sup> ): 125-fold at ρ = 0.996. Reimplemented on published sorghum data, the search returns the published index, photothermal time 18 to 43 days after planting, first of 27,144 candidates, at τ = 0.083. We recommend reporting τ beside ρ, and reading slope loci found below τ ≈ 0.15 as mean-performance loci. </jats:p>