Data

Corn: Attainable crop yields

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What you should know about this indicator

  • Attainable yields are more conservative than biophysical 'potential yields', but should be achievable using current technologies and management (e.g. fertilizers and irrigation).
  • Attainable yields are based on assessments for the year 2000. Real attainable yield pre-2000 may be lower; and post-2000 may be higher than these values.
Corn: Attainable crop yields
Attainable yields are estimates of feasible crop yields calculated from high-yielding areas of similar climate. Yields are measured in tonnes per hectare.
Source
Mueller et al. (2012)with major processing by Our World in Data
Last updated
March 2, 2026
Next expected update
March 2027
Date range
1850–2025
Unit
tonnes per hectare

Sources and processing

Mueller et al. – Closing yield gaps through nutrient and water management

Retrieved on
March 26, 2024
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Mueller, N., Gerber, J., Johnston, M. et al. (2012) - Closing yield gaps through nutrient and water management. Nature 490, 254-257. https://doi.org/10.1038/nature11420
Retrieved on
March 26, 2024
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Mueller, N., Gerber, J., Johnston, M. et al. (2012) - Closing yield gaps through nutrient and water management. Nature 490, 254-257. https://doi.org/10.1038/nature11420

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

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How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Corn: Attainable crop yields”, part of the following publication: Hannah Ritchie, Pablo Rosado, and Max Roser (2022) - “Crop Yields”. Data adapted from Mueller et al.. Retrieved from https://archive.ourworldindata.org/20260304-110441/grapher/maize-attainable-yield.html [online resource] (archived on March 4, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Mueller et al. (2012) – with major processing by Our World in Data

Full citation

Mueller et al. (2012) – with major processing by Our World in Data. “Corn: Attainable crop yields” [dataset]. Mueller et al., “Closing yield gaps through nutrient and water management” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260304-110441/grapher/maize-attainable-yield.html (archived on March 4, 2026).

Quick download

Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/maize-attainable-yield.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/maize-attainable-yield.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/maize-attainable-yield.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/maize-attainable-yield.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/maize-attainable-yield.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/maize-attainable-yield.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/maize-attainable-yield.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/maize-attainable-yield.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear