Research Question

How has corn production in the United States changed from 2000 to 2020 in relation to temperature?

Background

NASA’s research projects that global corn production could decline by up to 24% by the end of the 21st century. This decline is largely attributed to the increasing frequency of abnormal weather patterns driven by global warming. Rising temperatures, extreme heatwaves, and irregular rainfall are expected to make corn cultivation more challenging, ultimately reducing overall production capacity.

The United States, as one of the world’s largest corn exporters, accounted for approximately 33.8% of global corn exports during the 2018/2019 season. Its significant contribution to global food supply chains highlights the importance of understanding how temperature trends affect corn harvest yields. Any disruptions in U.S. corn production could have far-reaching consequences, impacting food security and agricultural economies worldwide.

Amid the increasing challenges brought by climate change, our team’s study examines the relationship between U.S. corn harvest yields and temperature trends over the last two decades. By analyzing these patterns, the research aims to uncover the potential impacts of rising temperatures on agricultural productivity and highlight the broader implications for global food security and sustainable farming practices.

1. Data importing and processing

1.1 Source of Data and Processing

Our study used corn yield data from United States Department of Agriculture and climate data(temperature) from Kaggle which originated from National Oceanic and Atmospheric Administration.

Calculate the average summer temperature for each state, specifically for the months of June through September. This period is critical for evaluating annual corn yield as it corresponds to the crop’s primary growth season, during which temperature conditions significantly influence plant development and productivity.

# Filter for summer months (June, July, August, September) in temperature data
climate <- climate %>%
  filter(month %in% c(6, 7, 8, 9))
# Group data by year and state to calculate the summer average temperature
average_by_year_state <- climate %>%
  group_by(year, state) %>%
  summarize(
    summer_average_temp = mean(average_temp, na.rm = TRUE), # Remove NA values
    .groups = "drop"
  )

1.2 Summary Statitistics

  • The data frame contains 21 years of summer average temperatures and harvest yields for each state.
# Check the merged data
head(corn_climate)
## # A tibble: 6 × 4
##    year state      summer_average_temp yield
##   <dbl> <chr>                    <dbl> <dbl>
## 1  2000 ALABAMA                   78.6    65
## 2  2000 ARIZONA                   77.9   196
## 3  2000 ARKANSAS                  77.8   130
## 4  2000 CALIFORNIA                71.8   170
## 5  2000 COLORADO                  64.9   126
## 6  2000 DELAWARE                  71.0   162
  • Show Percentage Change in Corn Yield (2000-2020)

  • This baplot provides an overview of changes in U.S. corn harvest yields between 2000 and 2020, highlighting states with the most significant increases and decreases in production. Based on our analysis of corn yield:
Top 5 States with the Largest Increase in Corn Harvest Yields

The following states showed the most substantial growth in corn harvest yields from 2000 to 2020:

  1. Alabama
  2. South Carolina
  3. Florida
  4. Mississippi
  5. Georgia
States with Noticeable Decreases in Corn Harvest Yields

Four states experienced significant declines in corn production from 2000 to 2020:

  1. Montana
  2. Virginia
  3. Colorado
  4. Wyoming

The analysis of summer temperatures across four representative states reveals distinct regional patterns:

The data suggests a relationship between temperature and corn yield trends. States with higher average summer temperatures, such as Alabama and Georgia, demonstrate significant increases in corn production over the analyzed period. Conversely, regions with cooler or fluctuating temperatures, such as Virginia is associated with noticeable declines in corn yields.

Methodlogy Explanation

Min-Max Normalization in Analysis

The analysis utilizes Min-Max normalization to scale both temperature and yield values to a standardized range between 0 and 1. The normalization is calculated as follows:

\[ \text{Normalized Value} = \frac{\text{actual value} - \text{minimum value}}{\text{maximum value} - \text{minimum value}} \]

Why Using Min-Max Normalization?

We apply Min-Max normalization to standardize data that are measured in different units—such as temperature (°F) and yield (bushels/acre). By scaling both variables to a common range, this method facilitates a more accurate and meaningful comparison of their trends and relationships.

Advantages of Min-Max Normalization
  1. Direct Comparison Between Different Units:
    • Enables comparison between temperature (°F) and yield (bushels/acre) by standardizing the scales.
  2. Removal of Baseline Differences:
    • Eliminates baseline differences that could obscure relative performance trends.

5. Choropleth map of comparing Yield and Temperature

5.1 Comparing in 2020

What are areas colored with gray?
  • There was no data in original file since USDA does not count states without economically meaningful amount of values obtained.
Top Map: Summer Average Temperature (2020)

The United States, located in the Northern Hemisphere, shows a temperature distribution that decreases as one moves further north. Additionally, the western region exhibits relatively lower temperatures compared to the eastern region.

Bottom Map: Corn Yield (2020)

Relatively high corn yields are recorded in the western and midwestern regions. Areas with moderate or lower temperatures tend to show higher yields, whereas regions with higher temperatures shows relatively low yields.

This feature generally reflects the inverse relationship between temperature and yield which has been observed earlier by our line graph analysis.

5.2 Percent change of Yield & Temperature between 2000-2020

5.3 Percent change of Yield & Temperature between 2017-2018

Why 2017 -2018?
  • We selected the period of 2017~2018. Because 2017-2018 was the periods with most significant difference has been observed for temperature. So, we expected to identify more detailed relation between temperature and corn yield.

Why we set the midpoint of color gradient as 0.02 in temperature map?
  • Over the past 20 years, the average summer temperature in the United States has not shown a significant upward trend. Instead, it has fluctuated irregularly, moving up and down. Therefore, when comparing year-to-year changes, we adjusted the midpoint to 0.02 to emphasize the impact of temperature increases and proceeded with a comparison of temperature changes and corn yield variations.

5.5 Analysis

  • The inverse relationship between temperature and yield, which has been consistently identified, is also evident in this map data. Western regions, where temperatures decreased compared to the previous year, experienced an increase in yield, while other regions with rising temperatures saw a decline in yield.

6 Conclusion

Initially, this study was conducted to examine the impact of global warming on U.S. corn yields. Fractional part of this study result does continuously report to indicate an inverse relationship between temperature and yield, a pattern where yield decreases as temperature rises was repeatedly observed in most cases. This finding supports NASA’s scenario that global warming-induced yield reductions are a plausible outcome in the future.

However, based on our overall observation, over the past 20 years there was no significant increase in average temperatures of United States. On the other hand, a corn yield has consistently increase. We have conclude that this result suggest advancements in technology or an expansion in cultivation areas could affect as primary reason for this trend, rather than climate factor such as like temperature trend.

Also, when analyzing the overall 20-year pattern, it gives us a evident that regions with higher yields and the period after 2010 showed less impact of temperature changes on yield.

According to our after-study reserach, the main factor that most significantly affects U.S. corn yield is extreme weather events (https://nca2009.globalchange.gov/us-corn-yields-1960-2008/index.html). An increase in the Earth’s average temperature and the rising frequency of extreme weather events due to global warming will inevitably lead to future reductions in U.S. corn yields.

Reference

NASA’s Research on Global Warming

Agriculture News on U.S. Corn Exports

USDA Corn Yield Data From

Temperature Data From Kaggle Reference to NOAA