Soybeans
QUIETStress 3/10
- Sorriso: week-ahead forecast shows severe deficit rainfall
- Rosario: severe deficit rainfall — 32% of the 30-day normal
- Harbin: severe deficit rainfall — 36% of the 30-day normal
Guided scenario
What if a severe La Niña hits South American crops?
La Niña's crop damage concentrates in Argentina and southern Brazil — corn and soy. Model a severe event. Note: a strong El Niño is underway right now, so this is the counterfactual.
1The setup
La Niña dries out Argentina and southern Brazil while wetting Australia — the damage concentrates rather than spreading evenly. The 2020–23 triple-dip brought Argentina its worst drought in 60 years: the last four months of 2022 saw 44% of average rainfall, soybean and corn yields fell roughly 40% below normal, and wheat output roughly halved. In 2010–11 a strong La Niña (ONI −1.7°C) coincided with the FAO Food Price Index hitting a then-record 238 points — though Russia's 2010 wheat export ban overlapped and is not attributable to La Niña. Farmdoc's yield analysis finds a strong La Niña link in Argentina, a weak one in the US, and none in Brazil. As of September 2026 the Pacific is tilting the other way — NOAA's Climate Prediction Center has an El Niño advisory on — so treat this as the mirror-image question. Argentina and Brazil together ship 55.9% of world soybean exports (2024 vintage).
2Right now
Corn
WATCHStress 5/10
- Sorriso: week-ahead forecast shows severe deficit rainfall
- Pergamino: severe deficit rainfall — 39% of the 30-day normal
- Zhengzhou: severe deficit rainfall — 20% of the 30-day normal
Monitor data as of Sep 24, 2026. Scores are observed readings, not forecasts.
How the shock travels
Argentine corn and soybean yields
La Niña dries Argentina's Pampas: the 2020–23 triple-dip cut soybean and corn yields roughly 40% below normal after the last four months of 2022 ran at 44% of average rainfall.
Evidence: USDA PSD + farmdoc yield analysis — 44% of average rainfall Sep–Dec 2022; yields ~40% below normal
Paraná River barging
Drought dropped the Paraná to its lowest in ~80 years, stranding grain barges and forcing lighter loads on the export route.
Evidence: River gauge reporting — lowest in ~80 years (2022–23)
Global food prices
The 2010–11 strong La Niña coincided with the FAO Food Price Index hitting a then-record 238 points, as drought hit wheat, corn, and soy stocks together.
Evidence: FAO Food Price Index — 238 points, Feb 2011 (then-record)
Caveat: Russia's 2010 wheat export ban overlapped and is not attributable to La Niña — the 2011 record had multiple causes
Australian wheat (offset)
La Niña wets Australia: the 2020–23 episode delivered record crops that partly offset South American losses.
Evidence: ABARES crop reports — record Australian crops 2020–23
3The exposure
Disruption hits:
- Brazil53.6%
- United States30.7%
- Paraguay4.0%
- Canada3.1%
- Argentina2.3%
How the shock travels
Follow the shock downstream — from the soybeans market, through processors, to the shelf. These are the usual stages, not this scenario's outcome: exposure at each step, never a prediction.
Day 0: soybean futures spike
timing not establishedLag basis: lag not established in sources reviewed
soybean futuresSoybean crushers and vegetable oil
timing not establishedLag basis: lag not established in sources reviewed
cooking oilvegetable oilmargarinebiodieselArcher-Daniels-Midland
ADMAg Services and Oilseeds segment crushes oilseeds into vegetable oils and oilseed protein meal; Carbohydrate Solutions converts corn and wheat into sweeteners, starches and ethanol
Soymeal, animal feed and meat
typically months (length not precisely quantified) →Lag basis: CRS Farm-to-Food Price Dynamics (R40621): time lags in retail price response to farm price changes are generally months in length, even for perishables like milk, meat, and fresh fruits and vegetables
soybean mealanimal feedchickenporkTyson Foods
TSNCorn, soybean meal and other feed ingredients represented roughly 61% of the cost of growing a live chicken in fiscal 2023
Source: Tyson Foods FY2023 10-K
Illustrative scenario. Not a prediction. Not financial advice. Company entries describe factual exposure to the commodity — not a view on any stock.
Trade map
Who ships it, who can’t do without it
2024 vintage · annual data, 1–2y lagSourced trade structure — the scenario’s shock geography at country resolution. Exposure, not a forecast.
Soybeans · Argentina + Brazil
Top exporters
Brazildominant
53.6% of world exports
United Statesdominant
30.7% of world exports
Paraguay
4% of world exports
Canada
3.1% of world exports
Argentina
2.3% of world exports
Note: soya beans
Exposed importers
Shocked exporters: Argentina, Brazil
85.3% of Thailand’s soybeans imports come from Brazil
71.8% of Spain’s soybeans imports come from Brazil
67.7% of China’s soybeans imports come from Brazil
36.1% of Mexico’s soybeans imports come from Brazil
Strait of Malacca
via Strait of Malacca / Singapore Strait · 25% of global soybean exports
Source: Chatham House, 2015 (published 2017)
Suez Canal
via Suez Canal
Route share unknown — No sourced figure; Brazilian soy to EU/Asia routing is split with no single published corridor share. Corridor-share research (Sep 2026): no commodity-specific corridor figure found in public sources -- not zero, just unsourced.
How we map this
Exporter and importer shares are 2024 vintage · annual data, 1–2y lag from UN Comtrade and OEC (BACI/CEPII); an importer counts as exposed when ≥20% of its soybeans imports come from a shocked exporter. The shock geography is the scenario’s own focus selection. Annual data with a 1–2 year reporting lag — the structure moves slowly, the prices don’t.
4Adjust the assumptions
La Niña strength (ONI)Strong (−1.5 to −1.9°C)
Historical check: The closest episode, US drought, 2012, saw soybeans futures move +52.7% (large band); your 70% disruption setting sits in the large band.
What share of Argentina + Brazil’s soybeans exports is disrupted.
Resolution: Oceanic Niño Index ≤ −1.5°C in any overlapping 3-month season (NOAA Climate Prediction Center)
Share of world exports
0%50%100% of world exports
Argentina + Brazil soybeans — 55.9% of world Soybeans exports (Share of global export value (USD) — 2024 vintage)
Exposed under your assumptions: 39.1% (55.9% × 70% severity)
The hatched area is modeled from your assumptions, not a measured outcome.
Exposed ≠ lost — affected trade can reroute, draw stocks, or substitute. This sizes the exposure, not the damage.
120d
Historical check: The closest episode, US drought, 2012, lasted 235 days (long); your 120-day drought duration sits in the medium band.
Resolution: Length of the growing-season moisture deficit (2022–23: four months at 44% of normal rainfall)
60d
Your assumption — not a measured buffer.
Resolution: Assumed days of stockpile cover — an assumption, not a measured buffer
Disruption timeline
090180270365 days
Disruption: 120 days
Assumed cover: 60 days — your assumptionYour assumption
60 days buyers can't ride out — not automatically a physical shortage
What this would have meant
At these settings, about 39.1% of the world's soybeans exports would be exposed to the disruption, and the disruption runs 120 days against 60 days of assumed stockpile cover, leaving about 60 days beyond what the assumed stockpile covers.
The closest recorded episode, US drought, 2012, saw soybeans futures rise +52.7% in 235 days (13 Jan 2012 → 4 Sep 2012), and for consumers: fats and oils (CPI, US) moved from -1.2% to -0.4% (no lag window was published for this episode). Illustrative — what happened then, not what will happen now.
What this assumes
- Exposure: Target share 55.9% × severity 70% = 39.1% exposed.
- Uncovered days: max(0, 120 − 60) = 60.
- Exposed ≠ lost: affected trade can reroute, draw down stocks, or find substitutes — this number sizes the exposure, not the damage.
- Exporter share ≠ spare capacity: rivals may not be able to surge supply to fill the gap.
- Combined share is the sum of the focus exporters' individual shares — a scenario hitting all of them at once.
- Stockpile cover of 60 days is your assumption, not a measured buffer.
- Results are physical-exposure arithmetic from your stated assumptions — not a price forecast.
Analog check
Your settings look closest to US drought, 2012 (same commodity, same shock type, similar size, similar supply concentration). The episode's measured moves, caveats included: soybeans futures +52.7% in 235 days (13 Jan 2012 → 4 Sep 2012); Fats and oils (CPI, US): the retail move wasn't measured for this episode — the futures leg above and the farm-share bound below are all we can honestly say. The fats-and-oils basket spans palm, canola and other oils — palm oil prices fell through 2012; substitution across oils dilutes any soybean-only signal..
Only about 11.8¢ of every US consumer food dollar — and 18.5¢ of every food-at-home dollar — reaches the farm (USDA, 2024) — that's a ceiling, not a prediction: margins can absorb a spike or amplify it.
Illustrative — what happened then, not what will happen now. Your scenario differs: your 120-day disruption vs the episode's 235-day.
How we matched this
- Commodity: requirement — Both are soybeans — non-soybeans episodes are excluded outright.
- Shock type: 2/2 — Both are a drought shock.
- Size: 1/1 — Your 70% disruption setting band: large; episode futures moved +52.7% (13 Jan 2012 → 4 Sep 2012) — band: large. Severity is % of shipments disrupted, not a price move: this banding is a v1 matching heuristic.
- Duration: 0/1 — Your disruption: 120-day (medium); episode: 235-day (long) — trough-to-peak run-up window.
- Supply concentration: 1/1 — Your hazard zone: 55.9% of world exports (high); episode disrupted ~40% (high) — US share of global soybean exports 2011/12 = 40% (USDA ERS, Oil Crops Outlook OCS-12e, May 2012).
Score 4/5 — close analog (headline).
Want the full controls? Reopen soybeans on its commodity page.
5What happened before
For perspective, not prediction
El Niño: the climate driver that doesn't always deliver
Recurring — 2009-10, 2015-16, 2023-24
“El Niño moves the weather, not always the price. In 2015–16 wheat fell sharply but tracked outcomes were mixed (rice +7.7%, soy +2.1%) while sugar spiked — fear the mechanism, measure the outcome.”
Price moves were observed around the event — not proof the event caused the entire move.
Read the full recordWhat to watch
- NOAA CPC's monthly ONI table — severe La Niña means ≤ −1.5°C in any overlapping 3-month season
- Rainfall across Argentina's Pampas and southern Brazil through the growing season (2022 ran at 44% of average)
- Paraná River levels — drought dropped it to its lowest in ~80 years, stranding grain barges
- USDA WASDE cuts to Argentine corn and soybean production estimates
- The active El Niño: CPC's advisory and strength probabilities show which way the Pacific is actually tilting
Curated by Morrowfly — these are things to check, not monitor conditions.
Make it yours
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