Food Loss in the US: What Foods Do Americans Waste the Most?

As food loss continues to rise across the United States, identifying the most wasted food types is critical to curbing food waste, lowering landfill methane emissions, and improving food security. These insights also provide actionable data for companies to optimize processing efficiency and empower consumers to make more conscious purchasing decisions. 

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Between 30-40% of the United States’ food supply – roughly 133 billion pounds and $161 billion-worth of food – is wasted. This makes food the single-largest category of material that is placed in municipal landfills. 

There are various considerations worth noting when it comes to food waste. For a starter, the food that’s wasted could have been used to feed millions of people in need. The resources required to grow, produce, and transport this amount of food could also have also been utilized more efficiently. 

Another key consideration is the amount of methane that generates from it. When organic food waste decays in landfills, it releases enormous quantities of methane – a major contributor to the total greenhouse gas emissions, responsible for 25% of global warming, second only to carbon dioxide. An estimated 58% of methane released into the atmosphere from municipal landfills in the US comes from food waste.

The Data

Historical food loss data for the US from the Food and Agriculture Organization (FAO) between 2000 and 2022 was used to generate the statistics for this analysis. 

Food loss percentage data for different commodities (raw or lightly processed agricultural goods) was averaged across all food supply processes that were in the dataset to get the average annual food loss percentage for each commodity that occurs between all these processes. The food supply processes in the dataset included harvests, retail, and the whole supply chain (not all commodities had data across all three processes, but some of them had a combination of the three). 

All commodities were assigned to one food group:

Statistical Analysis: Comparing Food Loss Percentages For Different Food Groups

Statistical measures (mean, standard deviation, variance, skewness, kurtosis) were generated to evaluate food loss percentages within each food category and across all commodities.

• Spread (mean, variance, standard deviation): The mean reflects the average loss, while higher variance and standard deviation indicate a wider spread in percentages for each food group.
• Symmetry (skewness): Positive skewness shows that most loss values cluster at lower percentages (pulling the mean higher than the median). Negative skewness shows losses cluster at higher percentages.
• Extreme values (kurtosis): Higher kurtosis indicates that food loss is tightly concentrated around the mean, but punctuated by extreme localized spikes (outliers). Lower values point to more evenly distributed loss rates.

Here is how these metrics break down across food groups:

Table 2 reveals stark contrasts in food loss across different categories. Fruit juices suffer from the highest average loss by a wide margin, whereas nuts and animal products record the lowest.

Loss rates vary dramatically depending on the commodity.

Fruit juices suffer from overwhelmingly the highest overall loss rates, with half of all juice commodities losing between 25% and 42% along the supply chain and a median loss of around 34%. By contrast, nuts and animal products consistently experience the lowest loss percentages, staying well below 5%.

While most vegetables maintain a relatively stable loss baseline of around 10%, this group displays extreme volatility. High standard deviation and positive skewness are driven by severe upward outliers, including a single vegetable commodity with a loss rate exceeding 60% that significantly inflates the overall category average. Conversely, fruits exhibit a far more balanced distribution around a 7% median loss, with fewer extreme spikes pulling the data in either direction. (Note: Kurtosis values for animal products and nuts could not be calculated due to small sample sizes of just three commodities each).

Figure 1 illustrates these distributions visually, highlighting both the wide interquartile range of fruit juices and the prominent outlier points within the vegetable supply chain. 

In terms of the highest average food losses among all groups, the following bar chart visualizes the top 10 commodities that have the highest average food loss percentage values:

As for the lowest average food losses among all groups, the following bar chart visualizes the top-10 commodities with the lowest values:

Final Thoughts

Across all commodities, fruit juices represent the highest-loss category, averaging a 32.66% loss rate across supply chain processes compared to the overall commodity baseline of 10.20%. Grapefruit juice recorded the highest individual loss within this group, followed closely by orange juice. Among single commodities, mustard seed saw the most severe loss, exceeding 60%. Other commodities with elevated loss rates (10% to 20%) included fresh oranges and key vegetables such as green garlic, tomatoes, okra, and spinach. Overall, intervention efforts yield the highest potential impact when targeted at fruit juices, followed by vegetables, which averaged an 11.90% loss.

Conversely, nuts and animal products generated the lowest loss rates, averaging 2.17% and 2.06% respectively. Sheep meat recorded the lowest single-commodity loss rate at near 0%, with walnuts slightly higher at roughly 0.33%. Other low-loss commodities were dominated by nuts, livestock, and select whole fruits, including apples, cherries, cranberries, grapefruits, and pomelos. Given their high retention rates, nuts and animal products represent a lower priority for loss reduction interventions compared to processed juices and produce.

While this US dataset highlights historical trends across supply processes, future research could expand in three directions: integrating international data sources to assess global supply chain losses; isolating household per-capita waste to guide individual consumer choices; and analyzing farm-level harvesting and processing metrics to inform targeted corporate supply chain interventions. 

Identifying these commodity-specific loss hotspots remains essential for designing targeted policy interventions, reducing agricultural resource waste, and guiding sustainable food systems strategy globally.

Featured image: Wikimedia Commons.