Reviewed August 2026 against USDA National Agricultural Statistics Service (NASS) Quick Stats, USDA Foreign Agricultural Service (FAS) circulars, and USDA Economic Research Service (ERS) international productivity data.

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Agriculture in South America and agriculture in South Dakota sit on opposite ends of the same commodity chain, and the numbers make the contrast concrete. Brazil produced 12.5 million metric tons of corn in the 2024/25 marketing year, per USDA FAS, while South Dakota alone harvested 1,085,850,000 bushels of corn in the same window, according to USDA NASS Quick Stats. Neither figure means much without the other for context, and that comparison — yield density, crop mix, and the technology closing the gap — is what this article covers.

Two Agricultures, One Comparison

“Agriculture in South America” and “agriculture South Dakota” look like unrelated search terms, but anyone trading grain, tracking export competition, or benchmarking farm productivity ends up asking both questions in the same sitting. South America supplies a growing share of the world’s corn, soybeans, and wheat; South Dakota is one of the top corn and cattle states in the US Corn Belt. Put their published figures side by side and the differences in scale, land base, and yield technology become measurable rather than anecdotal.

This article sticks to verified, dated figures from USDA’s three main statistical arms — NASS for US state-level data, FAS for country-level production abroad, and ERS for cross-country productivity comparisons — plus the FAO and World Bank sources analysts use to track global trends. Where a number is not published for a specific country or region, that gap is stated plainly rather than filled with a guess.

Agriculture in South America: Production by Country

South American agriculture is not one system — it spans the pampas of Argentina, the cerrado of Brazil, and the high-altitude valleys of the Andes, each with distinct crops and climate constraints. The clearest dated figures available from USDA FAS cover two countries directly:

• Brazil corn: 12.5 million metric tons produced in the 2024/25 marketing year, according to the USDA FAS February 2025 production circular. This figure is one line item within Brazil’s much larger total corn crop (which USDA tracks in successive circulars through the year) and should not be read as the country’s full annual output — it reflects the specific circular period cited here.
• Peru wheat: average yield of 1.7 metric tons per hectare in the 2024/25 marketing year, per USDA FAS’s Grain and Feed Annual report for Lima. Peru’s wheat sector is smallholder-dominated and concentrated in Andean valleys, which explains a yield well below the flat, mechanized wheat belts of North America or Western Europe.

Beyond these two data points, USDA FAS also publishes country pages for Argentina and Chile, but detailed cereal-by-cereal yield figures (metric tons per hectare) for those two countries were not available in the research pulled for this article. If you need Argentina’s soybean or corn yield for a specific marketing year, the most direct path is USDA FAS’s Buenos Aires post reports at USDA FAS Grain and Feed Annual reports filtered to the Argentina or Santiago post, published on roughly the same annual cycle as the Peru report cited above.

For a regional benchmark rather than a single country, USDA ERS tracks a combined Americas maize yield average of 8 tonnes per hectare for the 2023–2024 period, covering North and South America together in its International Agricultural Productivity dataset. That regional blend sits well above Peru’s 1.7 MT/ha wheat figure, but wheat and maize are different crops grown under different conditions, so the two numbers describe different things rather than a single trend.

Why South America’s Numbers Are Reported the Way They Are

USDA FAS reports on foreign agriculture through two channels: standing production circulars (issued monthly, covering major grains across many countries at once) and Grain and Feed Annual reports (issued once a year per country, with more local detail on planting practices, consumption, and trade). The Brazil corn figure above comes from a circular; the Peru wheat figure comes from an annual report. That is why one is a national total and the other is a per-hectare average — the two report types answer different questions by design. When comparing South American countries against each other, match report type to report type, not headline number to headline number.

Agriculture in South Dakota: The 2025 Numbers

South Dakota’s agricultural output is tracked at the state level by USDA NASS through its Quick Stats database, updated as part of the annual state overview cycle. The figures below cover the crop and livestock year reported in 2025 (largely reflecting the 2024 harvest, per NASS convention):

• Corn: 1,085,850,000 bushels produced, valued at $4.1 billion for the marketing year.
• Soybeans: 237,820,000 bushels produced, valued at $2.3 billion for the marketing year.
• Wheat (all classes, grain): 64,140,000 bushels produced.
• Cattle inventory: 3,550,000 head, as of January 1, 2026.

These four figures alone put South Dakota’s corn crop, in bushel terms, at roughly 87 times the raw tonnage figure cited for Brazil’s corn above — though the comparison has a unit mismatch that matters: South Dakota’s number is bushels of a single US state, and Brazil’s is metric tons of an entire country’s corn crop tracked through one FAS circular, not its full annual total. Converting bushels to metric tons (a US bushel of corn weighs approximately 25.4 kg, a standard USDA conversion factor) puts South Dakota’s 1,085,850,000-bushel figure at approximately 27.6 million metric tons — more than double the 12.5-million-ton Brazil circular figure, though again, that Brazil number is not Brazil’s full national corn output for the year, so this is a comparison of one US state against one reporting snapshot of one country, not state-versus-nation.

Cattle and the Land Behind the Numbers

South Dakota’s 3,550,000-head cattle inventory as of January 1, 2026 reflects the state’s dual identity as both a row-crop and rangeland state — corn and soybean ground in the east, grazing land dominating the west. NASS reports this inventory annually as part of its January cattle survey; the next update follows the same January cycle, published at USDA NASS Quick Stats state overview for South Dakota.

To pull the current-year figures for any of these categories yourself — corn, soybeans, wheat, or cattle — the state overview page above accepts a state parameter and refreshes annually each January when NASS finalizes the prior crop year’s harvest data.

Yield Comparison: Americas Maize vs. Andean Wheat

Direct South America vs. South Dakota yield-per-hectare comparisons are limited by what USDA actually publishes in comparable units. NASS reports South Dakota in bushels per acre; USDA ERS and FAS report international figures in metric tons per hectare. The cleanest apples-to-apples comparison available from the brief compiled for this article is the ERS regional maize average against Peru’s wheat average — two different crops, but the only two per-hectare figures confirmed across both regions:

This table is deliberately limited to figures that are actually published and dated. Argentina’s corn and soybean per-hectare yields, and Chile’s agricultural production volumes, are tracked by USDA FAS but were not available with specific figures in the research compiled for this piece — a genuine data gap, not an oversight. If those figures matter for your analysis, USDA FAS country pages for Argentina (Buenos Aires post) and Chile (Santiago post) are the direct source, updated on the same production-circular and annual-report cadence described above for Brazil and Peru.

Water and Soil Constraints Shared by Both Regions

South Dakota farmers and South American farmers face structurally different but comparably serious water constraints. In South Dakota, corn and soybean production east of the Missouri River depends on growing-season rainfall supplemented by limited irrigation, and yield in a given year swings with drought or excess moisture — which is exactly why NASS’s annual figures (like the 1,085,850,000-bushel corn number above) move meaningfully year to year rather than tracking a flat trend line.

In the Andean and high-desert zones of Peru, Bolivia, and northern Chile and Argentina — the same general geography that hosts major lithium brine deposits — wheat and pasture farming depend on snowmelt-fed rivers and shallow aquifers that are also drawn on by mineral processing operations. Peru’s 1.7 MT/ha wheat average reflects farming under exactly these constraints: smallholder plots, limited irrigation infrastructure, and elevation-driven growing seasons far shorter than South Dakota’s.

Neither region’s water story reduces to a single number that stays accurate for long, which is why the durable approach is a method rather than a stat: track basin-level water allocation and soil salinity trends directly, rather than relying on a one-time figure. Satellite-based soil and water monitoring gives both South Dakota row-crop operations and South American highland farms a way to check current conditions against their own historical baseline, rather than against a global average that may not apply to their specific watershed.

Satellite Monitoring for Cropland and Subsurface Resources

Whether the question is a South Dakota soybean field’s moisture stress or an Andean valley’s soil salinity near a brine operation, the verification method is the same: remote sensing that reads vegetation health, soil condition, and water presence without a site visit. Farmonaut’s satellite-based mineral detection platform applies this to subsurface mineral signatures, and the same multispectral approach underpins crop health and soil monitoring more broadly — useful anywhere farmland sits near active mineral exploration or extraction, from South Dakota’s own mineral belts to the lithium-bearing salt flats of the central Andes.

• Crop stress detection: multispectral imagery flags drought or nutrient stress before it is visible on the ground, applicable to both Corn Belt row crops and Andean wheat plots.
• Soil salinity mapping: relevant wherever brine processing, irrigation runoff, or natural mineralization affects adjacent farmland.
• 3D subsurface mapping: Farmonaut’s 3D mineral mapping product assesses prospective mineral zones without ground disturbance — a method that reduces early-stage exploration impact on adjacent farmland regardless of which country it is deployed in.

Applying This in South Dakota

South Dakota sits atop mineral resources beyond its farmland, and operations that monitor both cropland and subsurface conditions from the same satellite feed avoid duplicating fieldwork. Farmonaut’s agricultural satellite analytics support irrigation scheduling and early stress detection on row crops, the same underlying imagery used for mineral prospectivity work elsewhere.

Where Minerals and Farmland Overlap

South America’s lithium-bearing salt flats — the Salar de Atacama in Chile, Salar de Uyuni in Bolivia, and Salar del Hombre Muerto in Argentina — sit within the same general highland geography that produces Peru’s wheat and much of the region’s pastoral grazing. There is no published government dataset that ties lithium-region boundaries directly to agricultural production figures; that overlap is geographic and observational, not a statistic to cite. Farmers and land managers operating near these zones are better served by monitoring their own local water and soil conditions directly than by relying on a national average that will not reflect a specific basin.

• Native woodlands and pastures in these highlands support grazing and small-scale forestry historically managed by local communities.
• Livestock feedstock production continues alongside mineral operations in many of these zones.
• Export-oriented agriculture elsewhere in South America — Brazil’s corn and soybean belts, Argentina’s pampas — operates independently of the lithium triangle’s highland geography.

Calculator: Corn Revenue per Acre vs. per Hectare

Comparing South Dakota’s per-acre corn economics against a South American per-hectare figure requires converting both yield and price into the same unit — this calculator does that conversion using your own numbers, seeded with South Dakota’s reported $4.1 billion corn value against its 1,085,850,000-bushel production.

Comparative Table: Production, Yield, and Value

Risks and Data Gaps to Watch

Not every figure a reader wants for this comparison exists in a citable government source yet, and pretending otherwise is worse than saying so. The gaps below are genuine holes in the publicly available data, not oversights in this article:

• Argentina and Brazil per-hectare yields: USDA FAS tracks both countries' production volumes closely, but detailed cereal-by-cereal yield figures (MT/ha) comparable to Peru's wheat figure were not available in the sources compiled here. Check USDA FAS's country-specific Grain and Feed Annual reports directly for the current marketing year.
• Chile production volumes: USDA FAS maintains a Chile country page, but specific production figures were not extracted for this article. The FAS Santiago post's annual reports are the direct source.
• Regional farm-gate prices: USDA does publish South American commodity price data in some reports, but the geographic basis (which region within a country, which market) was not specified in the sources reviewed here — treat any regional price you find elsewhere with the same scrutiny.
• Lithium-region agricultural statistics: no government dataset ties the lithium triangle's geographic boundaries directly to farm production figures. This overlap remains observational, based on shared highland geography, not a citable statistic.

For any of these gaps, the durable fix is the same: go to USDA FAS's GAIN report library or FAOSTAT (FAO FAOSTAT, referenced generally as a global data source, though no specific figure from it appears in this article) directly, filtered to the country and marketing year you need, rather than relying on a secondhand aggregation that may be stale by the time you read it.

A Durable Checklist for Comparing Any Two Agricultural Regions

Whatever two regions you are comparing — South Dakota against Brazil, Iowa against Argentina, or any pair that comes up next season — this checklist keeps the comparison honest regardless of which year's figures you are pulling:

1. Match report type to report type (a production circular is not an annual report; a state inventory count is not a national production total).
2. Confirm the unit before comparing — bushels, metric tons, and MT/ha are not interchangeable without an explicit conversion, and the conversion factor should be stated, not assumed.
3. Note the exact reporting period (marketing year, calendar year, or "as of" date) rather than treating a figure as evergreen.
4. Check whether the value is for a full crop year or a snapshot circular — Brazil's corn figures, for instance, are updated multiple times per year and a February circular is not a final annual total.
5. When a figure is missing for one side of the comparison, say so and name the source where it should appear, rather than filling the gap with an estimate.

FAQ: Agriculture in South America and South Dakota

Conclusion: Reading the Numbers Forward

The comparison between agriculture in South America and agriculture in South Dakota is not a single ranking — it is several distinct, dated figures that answer different questions. Brazil's 12.5-million-metric-ton corn circular figure for 2024/25 and South Dakota's 1,085,850,000-bushel corn crop for the same general period describe different report types measuring different scopes; Peru's 1.7 MT/ha wheat yield and the Americas' 8-tonnes/ha maize average describe different crops. None of these numbers should be read as static — USDA NASS refreshes South Dakota's figures every January, and USDA FAS updates its South American circulars and annual reports on a rolling schedule throughout the year.

The checklist above — match report type, confirm units, note the period, flag genuine gaps — is what keeps this comparison usable after the next data release moves every one of today's numbers. Pair that method with direct satellite monitoring of the fields and basins that matter to you, rather than a single annual government figure, and the comparison stays accurate long after this article's numbers are out of date.