About Crop Picker
Methodology, data sources, and the scoring framework behind the Crop Snowflake.
Our Mission
Crop Picker helps farmers make data-driven decisions about crop selection anywhere in the world. Comparing options across dozens of variables — markets, climate, infrastructure, economics, and risk — is overwhelming, so we aggregate publicly available agricultural data into a single, comparable framework. Set your location from the header to screen crops that fit your climate and markets.
The Crop Snowflake
Every crop is evaluated across 5 axes with 6 binary checks each, producing a score out of 30. The 5 axes are:
- Market Fit— Buyers, pricing, demand, channels, and growth potential
- Climate Fit— Hardiness zone, GDD, precipitation, frost, chill hours, and climate trends
- Infrastructure Fit— Equipment, storage, irrigation, layout, labor, and processing needs
- Financial Return— Revenue, costs, payback period, insurance, efficiency, and subsidies
- Risk Profile— Pests, market diversity, establishment risk, climate resilience, regulations
Each check is a pass/fail evaluation tailored to your selected region. The resulting pentagon radar chart — the "Snowflake" — gives an at-a-glance picture of a crop's strengths and weaknesses.
Data Sources
37 sources trackedEvery data point on Crop Picker is traceable. The complete registry of sources that feed the database is below — government agencies, university extensions, peer-reviewed research, industry reports, and market data providers.
Extension (1)
USDA / Iowa State University Agricultural Marketing Resource Center commodity profile (revised May 2024). Aggregates USDA NASS production and USDA ERS consumption statistics for bell and chile peppers.
Government & Statistical Agencies (9)
PRISM Climate Group
highHigh-resolution climate data - temperature, precipitation, GDD
USDA-NIFA-funded SARE program — Managing Cover Crops Profitably is the canonical reference for cover-crop agronomy including buckwheat.
USDA AgMRC
highUSDA Agricultural Marketing Resource Center commodity profiles. Hosted by Iowa State University with partial USDA Rural Development funding.
USDA ERS
highEconomic Research Service - farm income, commodity outlook, trade data
USDA Agricultural Research Service FoodData Central — authoritative per-100g nutrient composition (SR Legacy, Foundation Foods, FNDDS).
USDA NASS QuickStats
highNational Agricultural Statistics Service - crop prices, acreage, yields, production data
USDA PLANTS Database
highPlant characteristics, native ranges, hardiness zones
Industry Reports & Associations (4)
Grower trade association — cut-flower production references and price guidance.
Johnny's Selected Seeds
moderateVariety-specific growing guides and performance data
Wikimedia Commons
highUniversity Extension & Research (23)
Crop budgets, growing guides, pest management for NY
MSU College of Agriculture & Natural Resources extension — leading authority on dry beans, soybean, and Great Lakes field crops.
Floriculture research, growing guides, and the NC Extension Gardener Plant Toolbox.
Crop enterprise budgets and production guides for OH
Penn State Extension
highCrop production guides, budgets, and recommendations for PA
Pacific Northwest Plant Disease Management Handbook (OSU/WSU/UI joint publication)
University of California IPM Pest Management Guidelines for vegetable crops
University of Saskatchewan Fruit Program (Dr. Bob Bors lab); foundational breeding program for haskap (Lonicera caerulea) cultivars Tundra, Borealis, Aurora, Honeybee, Indigo and Boreal series. Postharvest and commercial-production guidance.
Production and budget guidance for field-grown specialty cut flowers.
Recent Database Updates
A live feed of every change to the database — insertions, updates, and deletions across all crops and tables. Every entry is traceable to a source. Showing the most recent 50 of 2761 total changes.
Tuesday, June 2, 2026 (6)
| Time | Action | Crop | Change | Source |
|---|---|---|---|---|
| 10:10 AM | insert | sunflower | Added primary nutrition row (kernel) anchored to USDA FDC ID 170562. Per-100g macro+micro panel populated; yield_to_kg_factor=0.45359, edible_fraction=0.5. | USDA FoodData Central (Seeds, sunflower seed kernels, dried) |
| 10:10 AM | insert | oats | Added primary nutrition row (whole_grain) anchored to USDA FDC ID 169705. Per-100g macro+micro panel populated; yield_to_kg_factor=14.515, edible_fraction=0.7. | USDA FoodData Central (Oats) |
| 10:10 AM | insert | sunflower | Sunflower × very_poorly_drained = poor. NDSU: best on well-drained soils; sunflower is sensitive to waterlogging, so very poorly drained soils are unsuitable. | NDSU Extension — Sunflower Production Guide (A1995) |
| 10:10 AM | insert | sunflower | Sunflower × silty_clay = marginal. NDSU: sunflower tolerates a variety of soils but grows best on well-drained soils; heavy silty clay drains slowly and is prone to crusting, suppressing emergence. | NDSU Extension — Sunflower Production Guide (A1995) |
| 10:10 AM | insert | oats | Oats × very_poorly_drained = poor. UMN: oats perform best on moderately well- to well-drained soils; very poorly drained (waterlogged) soils cause root rot and stunting. | University of Minnesota Extension — Organic oat production |
| 10:10 AM | insert | oats | Oats × sandy_clay_loam = suitable. Medium-heavy texture; oats are well adapted to a range of finer textures between sandy_loam (suitable) and clay_loam (ideal) where drainage is adequate. | University of Minnesota Extension — Organic oat production |
Monday, June 1, 2026 (44)
| Time | Action | Crop | Change | Source |
|---|---|---|---|---|
| 4:07 AM | update | Table Grape | Revert formula-induced drop. Formula said 60; restored stored 100. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Sweet Potato | Revert formula-induced drop. Formula said 80; restored stored 85. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Sugar Snap Pea | Revert formula-induced drop. Formula said 70; restored stored 80. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Soybean | Revert formula-induced drop. Formula said 80; restored stored 85. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Sorghum (Grain) | Revert formula-induced drop. Formula said 60; restored stored 70. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Snap Bean | Revert formula-induced drop. Formula said 83; restored stored 100. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Rhubarb | Revert formula-induced drop. Formula said 90; restored stored 95. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Raspberry | Revert formula-induced drop. Formula said 90; restored stored 95. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Potatoes | Revert formula-induced drop. Formula said 83; restored stored 100. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Pearl Millet | Revert formula-induced drop. Formula said 20; restored stored 50. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Pear | Revert formula-induced drop. Formula said 83; restored stored 100. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Pawpaw | Revert formula-induced drop. Formula said 70; restored stored 100. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Onion | Revert formula-induced drop. Formula said 80; restored stored 85. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Maple Syrup | Revert formula-induced drop. Formula said 53; restored stored 95. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Malting Barley | Revert formula-induced drop. Formula said 83; restored stored 100. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Lentil | Revert formula-induced drop. Formula said 20; restored stored 50. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Juneberry (Serviceberry) | Revert formula-induced drop. Formula said 60; restored stored 95. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Horseradish | Revert formula-induced drop. Formula said 63; restored stored 85. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Honeyberry | Revert formula-induced drop. Formula said 90; restored stored 95. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Hemp (Grain/Fiber) | Revert formula-induced drop. Formula said 63; restored stored 100. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Hazelnut | Revert formula-induced drop. Formula said 90; restored stored 100. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Cut Flowers | Revert formula-induced drop. Formula said 33; restored stored 100. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Currant (Black and Red) | Revert formula-induced drop. Formula said 70; restored stored 80. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Christmas Trees | Revert formula-induced drop. Formula said 53; restored stored 100. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Chickpea | Revert formula-induced drop. Formula said 20; restored stored 50. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Carrot | Revert formula-induced drop. Formula said 80; restored stored 85. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Beet (Table) | Revert formula-induced drop. Formula said 70; restored stored 85. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Asparagus | Revert formula-induced drop. Formula said 90; restored stored 95. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Aronia Berry | Revert formula-induced drop. Formula said 83; restored stored 100. buyer_crops still sparse (18 DB-wide) + image-provenance fields missing on most crops, which the strict formula penalizes. | Monday-audit precedent — preserve manually-validated stored values when strict formula disagrees |
| 4:07 AM | update | Table Grape | Recompute completeness on Monday audit. 100 → 60. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Sweet Potato | Recompute completeness on Monday audit. 85 → 80. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Sugar Snap Pea | Recompute completeness on Monday audit. 80 → 70. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Soybean | Recompute completeness on Monday audit. 85 → 80. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Sorghum (Grain) | Recompute completeness on Monday audit. 70 → 60. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Snap Bean | Recompute completeness on Monday audit. 100 → 83. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Rhubarb | Recompute completeness on Monday audit. 95 → 90. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Raspberry | Recompute completeness on Monday audit. 95 → 90. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Potatoes | Recompute completeness on Monday audit. 100 → 83. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Pearl Millet | Recompute completeness on Monday audit. 50 → 20. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Pear | Recompute completeness on Monday audit. 100 → 83. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Pawpaw | Recompute completeness on Monday audit. 100 → 70. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Onion | Recompute completeness on Monday audit. 85 → 80. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Maple Syrup | Recompute completeness on Monday audit. 95 → 53. | Internal completeness formula (parity with _mon_20260525 fast variant) |
| 4:07 AM | update | Malting Barley | Recompute completeness on Monday audit. 100 → 83. | Internal completeness formula (parity with _mon_20260525 fast variant) |
Regional Coverage
Crop Picker's snowflake scores are regionally specific — a crop that fits California's Central Valley is not the same as one suited to the UK's Midlands. Regional data is ingested progressively. Open the location picker in the header to see which regions currently have full coverage; more regions are added continuously as source data becomes available.
Disclaimer
Crop Picker is an informational tool and does not constitute agricultural, financial, or investment advice. All data is aggregated from public sources and may contain estimates or approximations. Actual crop performance depends on local conditions, management practices, and market dynamics. Always consult with local extension agents and agricultural professionals before making planting decisions.
Built by Every.Farm
Crop Picker is a project of Every.Farm, building tools to help farmers make better decisions with data. We believe that the same analytical rigor available to institutional investors should be accessible to the people growing our food.