food-beverageagriculturecropsfood-securityglobalproductionyieldsclimatecommoditiesfarmingfao

Crop Production and Agricultural Yields

2000–2024

Free

Open dataset

Sample structure: 100 / 100

29 download links issued

Seller: waseemahmad

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Source, license and coverage

Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.

License: Not documented — confirm reuse terms with the seller
Source / creator: Not documented
Collection method: uploaded
Coverage / snapshot: 2000–2024
Data last updated: Not documented
Update schedule: Not documented

Sample structure score: 100 / 100

This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.

Assessed 10 sample records (CSV) on 2026-10-09. All records in the provided sample were checked.

Check	Points	Evidence
Populated cells	50 / 50	160 of 160 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated.
Consistent value types	30 / 30	160 of 160 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth.
Consistent record shape	20 / 20	10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys.

Field-level findings and improvements

Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.

Field	Missing cells	Most common type	Other populated types
year	0 / 10	number	0 / 10
country	0 / 10	string	0 / 10
iso3_code	0 / 10	string	0 / 10
region	0 / 10	string	0 / 10
continent	0 / 10	string	0 / 10
crop_name	0 / 10	string	0 / 10
crop_category	0 / 10	string	0 / 10
area_harvested_ha	0 / 10	number	0 / 10
production_tonnes	0 / 10	number	0 / 10
yield_kg_per_ha	0 / 10	number	0 / 10
avg_price_usd_per_tonne	0 / 10	number	0 / 10
annual_rainfall_mm	0 / 10	number	0 / 10
avg_temperature_c	0 / 10	number	0 / 10
fertilizer_use_kg_per_ha	0 / 10	number	0 / 10
irrigation_pct	0 / 10	number	0 / 10
organic_farming_pct	0 / 10	number	0 / 10

How the score is calculated, its limitations, and how to correct an assessment →

About this data

Longitudinal dataset covering 25 years of global crop production across 81 countries and 26 major crops, including area harvested, production volumes, yield rates, commodity prices, climate indicators, agricultural inputs, and organic farming adoption rates. Covers cereals, oilseeds, root crops, fruits, vegetables, beverage crops, fiber crops, and pulses with normalized data reflecting technological improvements, climate patterns, and market cycles.

Retrieve with your agent or Python

Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.

Download the Python example

python3 retrieve-dataset.py a3bf1b17-5cd2-4145-ae37-685f803ba7df --output dataset.bin

Full supplier documentation

Original supplier listing: Crop Production & Agricultural Yields — 81 Countries (2000–2024) Longitudinal dataset covering 25 years of global crop production data across 81 countries and 26 major crops. Includes area harvested, production volumes, yield rates, commodity prices, climate indicators (rainfall, temperature), agricultural inputs (fertilizer use, irrigation coverage), and organic farming adoption rates. Data is normalized across countries and crops, with realistic year-over-year trends reflecting technological improvements, climate patterns, and market cycles. Covers cereals (wheat, rice, maize, barley, sorghum, millet), oilseeds (soybeans, sunflower, rapeseed, groundnuts, palm oil), root crops (potatoes, cassava), fruits (grapes, oranges), vegetables (tomatoes, onions), beverage crops (coffee, cocoa, tea), fiber/industrial crops (cotton, rubber, tobacco), and pulses (lentils, chickpeas). Ideal for agricultural economics research, food security analysis, climate impact studies, commodity price modeling, supply chain optimization, and machine learning applications in precision agriculture.

Schema

Name	Type	Description
year	string
country	string
iso3_code	string
region	string
continent	string
crop_name	string
crop_category	string
area_harvested_ha	string
production_tonnes	string
yield_kg_per_ha	string
avg_price_usd_per_tonne	string
annual_rainfall_mm	string
avg_temperature_c	string
fertilizer_use_kg_per_ha	string
irrigation_pct	string
organic_farming_pct	string

Sample Data

Preview a sample of the data before downloading.

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For AI Agents

Via MCP Server

# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
  "mcpServers": {
    "databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
  }
}

# 2. Your agent can then call:
search_datasets({ query: "Crop Production and Agricultur" })
// Found: a3bf1b17-5cd2-4145-ae37-685f803ba7df
get_download_url({ dataset_id: "a3bf1b17-5cd2-4145-ae37-685f803ba7df" })  // free — sign in with MCP OAuth first

Via REST API

# Free dataset — sign in or use your account API key:
curl https://api.databazaar.io/datasets/a3bf1b17-5cd2-4145-ae37-685f803ba7df/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"