CANOPY is an integrated production-simulation engine spanning crops, horticulture, and livestock. Each module simulates a sector in its own detail; the cascades link them so a single shock — weather, price, policy, or biosecurity — can be traced across the whole system.
Each module models production at region×year resolution from published, source-attributed relationships — yield and volume for crops, gain and output for livestock, plus quality measures (sucrose/CCS, lint and micronaire) and externalities (welfare, heat-stress, methane).
Modules publish outputs that feed others. Grain and cottonseed flow into feed availability and feedlot gain; pollination flows into orchard volume and price. The coupling is the point — it's what single-sector models can't do.
Impose a shock — an exotic-disease incursion, a cyclone or flood, a drought, an input or energy crisis, a processing-chain failure — and read the consequences across every connected sector, week by week, all the way to which sectors hold and which are pushed past viability. Uncertainty is carried through rather than hidden.
Each sector is part of one coupled engine, not a separate product. Detailed production modules are live for the sectors below and roll out across the rest of the twenty-three over time; the feedlot deep-dive is the deepest yet.
Region×year yield-response with management levers (diesel, fertiliser, water, fungicide, hives/ha) and a pollination-collapse channel.
Pollination risk →Cane volume plus CCS/sucrose output, with a burning-mode toggle. Built on the Renouf and BSES research base.
Lint t/ha and micronaire by zone and rotation, with cottonseed feeding the livestock cascade. Built on the Nguyen, Bange, and Hedayati research base.
Per-region yield response that publishes a grains factor driving the downstream feed-availability cascade.
Production with welfare and market-recovery dynamics.
Production with welfare and a heat-stress channel.
Lay production with welfare and a heat-stress channel.
Engineering-grade gain modelling with per-day-on-feed carcase-weight pricing, an economic/welfare/biosecurity cascade panel, enteric-methane life-cycle accounting, and grain/cottonseed inputs from the cropping modules.
Deep-dive →All twenty-three sectors are wired into one engine. Impose a shock on any of them and the model carries it everywhere it lands, through time, to a verdict on which sectors hold and which are pushed past viability.
Emergency animal-disease incursions and the depopulation, movement-standstill, and market-recovery dynamics that follow — traced through to the sectors and supply chains downstream.
Cyclones, floods, drought, and heat — resolved by region rather than smeared into a national average that hides where the damage actually lands.
Diesel and fertiliser price spikes and rationing, applied across every sector's cost base at once — the way a real fuel or fertiliser crisis actually propagates.
Abattoir, mill, and processor outages and water-allocation cuts — the chokepoints where a regional problem becomes a system-wide one.
The engine's signature behaviour: a shortfall in one commodity that a reserve absorbs for a season, then bites a year later across everything that depends on it. Cause and effect can sit twelve months apart — and the model holds both ends.
A briefing takes your commodity, your geography, and the question you're trying to answer, and shows you the model against it — methodology included.
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