IndisputableMonolith.Agronomy.YieldGapFromJCost
This module defines the J-cost applied to the actual-to-potential yield ratio in crop systems. Agronomists working in the Recognition Science framework would cite it when quantifying yield gaps via the recognition cost function. It consists of definitions and basic properties such as non-negativity, structured as a collection of supporting lemmas.
claimThe yield gap cost is $J(y_a / y_p)$ where $J(x) = (x + x^{-1})/2 - 1$, $y_a$ is actual yield and $y_p$ is potential yield; related properties include non-negativity and the value at the potential yield point.
background
The module sits in the agronomy domain and imports the RS time quantum $ au_0 = 1$ tick from Constants together with cost definitions from the Cost module. It applies the J-cost function, which satisfies the Recognition Composition Law, to the ratio of actual to potential yields. Sibling definitions establish basic facts such as yieldGapCost_nonneg and agronomicTipPoint bounds.
proof idea
This is a definition module, no proofs.
why it matters in Recognition Science
This module supplies the agronomic interpretation of J-cost, extending the Cost module to yield ratios and enabling domain-specific modeling of agricultural efficiency within Recognition Science. It currently has no downstream theorems listed among its used_by edges.
scope and limits
- Does not compute numerical yields for specific crops or regions.
- Does not incorporate environmental or soil variables beyond the yield ratio.
- Does not derive optimality conditions for farming practices.
- Does not link directly to the T0-T8 forcing chain or mass formulas.