Jean C. Buzby, Hodan F. Wells, and Jeffrey Hyman

Economic

Research

Service

Economic 

Information

Bulletin

Number 121

February 2014

United States Department of Agriculture

The Estimated Amount, Value, and 

Calories of Postharvest Food Losses 

at the Retail and Consumer Levels 

in the United States
Economic Research Service 

www.ers.usda.gov

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Buzby, Jean C., Hodan F. Wells, and Jeffrey Hyman. The Estimated Amount, Value, and 

Calories of Postharvest Food Losses at the Retail and Consumer Levels in the United 

States, EIB-121, U.S. Department of Agriculture, Economic Research Service, February 

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United States Department of Agriculture

Economic 

Research 

Service

Economic

Information

Bulletin

Number 121

February 2014

Abstract

This report provides the latest estimates by USDA’s Economic Research Service (ERS) 

on the amount and value of food loss in the United States. These estimates are for more 

than 200 individual foods using ERS’s Loss-Adjusted Food Availability data. In 2010, an 

estimated 31 percent or 133 billion pounds of the 430 billion pounds of food produced 

was not available for human consumption at the retail and consumer levels. This amount 

of loss totaled an estimated $161.6 billion, as purchased at retail prices. For the first time, 

ERS estimates of the calories associated with food loss are presented in this report. An 

estimated 141 trillion calories per year, or 1,249 calories per capita per day, in the food 

supply in 2010 went uneaten. The top three food groups in terms of share of total value 

of food loss are meat, poultry, and fish (30 percent); vegetables (19 percent); and dairy 

products (17 percent). The report also provides a brief discussion of the economic issues 

behind postharvest food loss.

Keywords: Food consumption, food loss, food recovery, food waste, foodservice, recycling, plate waste, processing.

Acknowledgments

The authors gratefully acknowledge Kevin Hall (National Institutes of Health), Ephraim 

Leibtag (ERS), Hayden Stewart (ERS), Jay Variyam (ERS), and Gregory Ziegler 

(Pennsylvania State University) for their reviews of the report. Thanks also to ERS editor 

Dale Simms and designer Cynthia A. Ray.

Jean C. Buzby, Hodan F. Wells, and Jeffrey Hyman

The Estimated Amount, Value, and 

Calories of Postharvest Food Losses 

at the Retail and Consumer Levels 

in the United States
ii

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Economic Research Service/USDA

Contents

Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Background. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Economics of Food Loss. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Data and Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Amount. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Calories. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22

Appendix: The ERS Loss-Adjusted Food Availability Data and Methods for Estimating 

the Amount and Value of Postharvest Food Loss. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
www.ers.usda.gov

What Is the Issue?

“Food loss” represents the amount of edible food, postharvest, that is available for human 

consumption but is not consumed for any reason; it includes cooking loss and natural shrinkage 

(e.g., moisture loss); loss from mold, pests, or inadequate climate control; and plate waste. “Food 

waste” is a component of food loss and occurs when an edible item goes unconsumed, such 

as food discarded by retailers due to undesirable color or blemishes and plate waste discarded 

by consumers. Food loss (particularly the food waste component) is becoming an increasingly 

important topic both domestically and internationally. Better estimates of the amount and value 

of food loss, including food waste, could help serve as quantitative baselines for policymakers and 

the food industry to set targets and develop initiatives, legislation, or policies to minimize food 

waste, conserve resources, and improve human nutrition. Reducing food loss would likely reduce 

food prices in the United States and the rest of the world, though the effects depend on the nature 

of supply, including import and export considerations. 

What Did the Study Find?

In the United States, 31 percent—or 133 billion pounds—of the 430 billion pounds of the available food supply at the retail and consumer levels in 2010 went uneaten. Retail-level losses represented 10 percent (43 billion pounds) and consumer-level losses 21 percent (90 billion pounds) of 

the available food supply. (Losses on the farm and between the farm and retailer were not estimated due to data limitations for some of the food groups.) 

The estimated total value of food loss at the retail and consumer levels in the United States was 

$161.6 billion in 2010. The top three food groups in terms of share of total value of food loss were 

meat, poultry, and fish (30 percent, $48 billion); vegetables (19 percent, $30 billion); and dairy 

products (17 percent, $27 billion). The total amount of food loss represents 387 billion calories 

(technically, we mean Calorie or kcal hereafter) of food not available for human consumption per 

day in 2010, or 1,249 out of 3,796 calories available per American per day. Recovery costs, food 

safety considerations, and other factors would reduce the amount of food that could actually be 

recovered for human consumption. 

United States Department of Agriculture

A report summary from the Economic Research Service February 2014

ERS is a primary source 

of economic research and 

analysis from the U.S. 

Department of Agriculture, 

providing timely information on economic and policy 

issues related to agriculture, 

food, the environment, and 

rural America.

Find the full report 

at www.ers.usda.

gov/publications/eibeconomic-informationbulletin/EIB-121.aspx

Jean C. Buzby, Hodan F. Wells, and Jeffrey Hyman

Economic

Research

Service

Economic 

Information

Bulletin

Number 121

February 2014

United States Department of Agriculture

The Estimated Amount, Value, and 

Calories of Postharvest Food Losses 

at the Retail and Consumer Levels 

in the United States

Jean C. Buzby, Hodan F. Wells, and Jeffrey Hyman

The Estimated Amount, Value, and 

Calories of Postharvest Food Losses 

at the Retail and Consumer Levels 

in the United States
The study also reviewed the literature and found that food loss is economically efficient in some cases. There is a practical limit to how much food loss the United States or any other country could realistically prevent, reduce, or recover 

for human consumption given: (1) technical factors (e.g., the perishable nature of most foods, food safety, storage, and 

temperature considerations); (2) temporal and spatial factors (e.g., the time needed to deliver food to a new destination, and the dispersion of food loss among millions of households, food processing plants, and foodservice locations); 

(3) individual consumers’ tastes, preferences, and food habits (e.g., throwing out milk left over in a bowl of cereal); 

and (4) economic factors (e.g., costs to recover and redirect uneaten food to another use).

How Was the Study Conducted?

This report uses data from ERS’s Loss-Adjusted Food Availability (LAFA) data series. This data series is ERS’s core 

Food Availability data series, adjusted for spoilage, plate waste, and other food losses and converted to daily per capita 

amounts, calories, and food pattern equivalents (previously called servings and MyPyramid equivalents). Here, the 

LAFA data series’ underlying loss assumptions are used to estimate food loss at the retail and consumer levels. The 

LAFA data series is considered to be preliminary because ERS continues to improve the underlying loss assumptions 

and the documentation of the data series. In August 2012, new estimates for consumer-level loss were incorporated 

into the data series. Therefore, the relative contribution of the different food groups out of total food loss has changed 

from previous ERS publications on food loss. The analysis is an extrapolation from the data as of September 2012 and 

is not based on an equilibrium model. For each food group covered here, we calculated the amount, value, and representative calories of food loss at the retail and consumer levels in the United States in 2010. The value estimates are 

based on retail prices. 

www.ers.usda.gov
1

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The Estimated Amount, Value, and 

Calories of Postharvest Food Losses 

at the Retail and Consumer Levels 

in the United States

Background

In 1977, a Report to Congress by the General Accounting Office (GAO) titled “Food Waste: 

An Opportunity To Improve Resource Use” (GAO, 1977) discussed the U.S. Department of 

Agriculture’s activities related to food loss in the United States, warning that: 

“The United States can no longer be lulled by past agricultural surpluses and 

must consider a future that may contain a world shortage of food. In an environment of plenty, the United States has not historically been concerned with food 

losses. Although some attention has been focused on the subject in the agricultural 

research community, in many instances, plentiful food and low prices did not justify 

the economic expenditure necessary to reduce loss. In an era of potential scarcity, 

however, it may be necessary to re-examine the present position on losses.” (p. 1) 1

Today, there is a renewed interest in the issues related to food loss, both domestically and internationally. For example, USDA and the U.S. Environmental Protection Agency (EPA) launched the 

U.S. Food Waste Challenge on June 4, 2013, and the United Nations’ Environment Programme’s 

(UNEP) World Environment Day’s major theme in June 2013 was food waste. Some findings from 

the 1977 GAO report are still relevant today, given the resources used in the production of uneaten 

food, the negative externalities associated with food loss (e.g., pollution created during food production), and the growing pressures on the global food supply (see box, “Three Reasons for a Growing 

Interest in Food Loss”). Therefore, it may become increasingly important to estimate the amount 

and value of food loss, including food waste, as a quantitative baseline for policymakers and the 

food industry to set targets and develop initiatives, legislation, or policies to minimize food waste, 

conserve resources, and improve human nutrition (Buzby and Hyman, 2012). 

“Food loss” represents the amount of edible food, postharvest, that is available for human consumption but is not consumed for any reason. It includes cooking loss and natural shrinkage (e.g., moisture loss); loss from mold, pests, or inadequate climate control; plate waste; and other causes.2

“Food waste” is a component of food loss and occurs when an edible item goes unconsumed, such 

as food discarded by retailers due to blemishes or plate waste discarded by consumers. This report 

1The 1977 report also concluded that “at present, loss represents a large misallocation of resources. For 1974, about 

66 million acres of land and 9 million tons of fertilizer were used to produce food ultimately lost. In energy, about 461 

million equivalent barrels of oil were used to produce food ultimately lost” (GAO, 1977). This amount of loss represents 

about 23 percent of all food produced for direct human consumption in 1974.

2The term “postharvest food loss” simply refers to food loss after the food is harvested. Definitions of food waste and 

food loss vary worldwide (e.g., inedible portions are included in some food waste definitions). 
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Three Reasons for a Growing Interest in Food Loss

(1) Food loss means a loss of money and other resources

Food loss represents significant amounts of money and other resources invested in food production, including 

land, fresh water, labor, energy, agricultural chemicals (e.g., fertilizer, pesticides), and other inputs to produce 

food that does not ultimately meet its intended purpose of feeding people (Buzby et al., 2011). For example, 

Webber (2012) estimates that food waste represents 2.5 percent of U.S. energy consumption per year, and Hall 

et al. (2009) estimate that the production of this wasted food required the expenditure of around 300 million 

barrels of oil and over 25 percent of the total freshwater consumed by agriculture in the United States. A more 

detailed understanding of the resource implications of food loss in the United States, including estimates of the 

land used to produce wasted food, is not available.

According to the U.S. Environmental Protection Agency (EPA), food waste accounted for 34 million tons 

(almost 14 percent) out of the 250 million tons of municipal solid waste in the United States in 2010 as 

measured before recycling (EPA, 2011) (see figure). Less than 3 percent of this food waste was recovered and 

recycled, with the remainder going to landfills or incinerators (EPA, 2011). In 2010, food waste cost roughly 

$1.3 billion to landfill (Schwab, 2013). After recycling some materials, such as paper and paperboard, food 

waste was the single largest amount of municipal solid waste categorized by EPA in 2010, with 21 percent of 

the total (see figure).

Total municipal solid waste generation by material before (250 million tons) and after 

recycling (161 million tons), 2010

Source: EPA, as of September 17, 2012: http://www.epa.gov/wastes/conserve/materials/organics/food/fd-basic.htm

Paper, 17%

Food waste

21%

Wood

8%

Other, 2%

Paper, 30%

Food waste

14%

Yard waste

14%

Plastics, 12%

Metals, 9%

Rubber, leather,

and textiles

8% 

Wood, 6%

Glass

5%

Other

3%

Rubber, leather,

and textiles

11% 

Metals, 9%

Plastics, 18%

Yard waste

9%

Glass

5%

Before recycling After recycling
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(2) Food loss means that negative externalities were created throughout the supply chain

Negative externalities can arise throughout the entire food supply chain from the food’s production to the 

disposal of any uneaten food. Negative externalities are transaction costs that spill over from an action (e.g., 

food production or disposal) that can adversely affect society and the environment and that are not incorporated in market prices (e.g., the price of food). In general, food that is produced, regardless of whether it is 

consumed or wasted, contributes to pressure on the availability of fresh water and other natural resources 

(Lundqvist et al., 2008), including land needed for urbanization, forests, and protected areas, some of which 

is necessary for biodiversity and wildlife. Some of these pressures on water, land, and other resources are 

not fully internalized in prices (e.g., value of wildlife diversity in land prices). A few examples of these 

externalities include: (1) greenhouse gas emissions from cattle production (Lundqvist et al., 2008); (2) 

air pollution caused by farm machinery and trucks that transport food; (3) water pollution and damage to 

marine and freshwater fisheries from agricultural chemical and nutrient runoff during crop and livestock 

production (Aillery et al., 2005; Ribaudo et al., 2011); and (4) soil erosion, salinization, and nutrient depletion that arise from unsustainable production and irrigation practices (Hansen and Ribaudo, 2008; Sullivan 

et al., 2004). 

Additionally, incinerating food waste creates emissions that harm the environment and landfilling food waste 

generates methane gas when food waste decomposes anaerobically. Methane is 21 times more powerful in 

accelerating global warming than carbon dioxide (EPA, 2011). Landfills account for 34 percent of all humanrelated methane emissions in the United States (EPA, 2011). In addition to methane, landfills produce leachate 

(a mixture of liquid waste, organic degradation byproducts, and rainwater), which may contaminate groundwater if the landfills are not properly maintained. These negative consequences are offset to some extent when 

energy is generated from incinerating or landfilling food (e.g., tapping the methane gas).

(3) The world population is growing, so more food will be needed to feed people

Reducing food waste will become an increasingly important strategy in the future to help feed a growing 

human population. It would help by increasing the amount of food available for consumption (particularly food 

for subsistence households in developing countries) and by lowering prices. The United Nations predicts that 

the world population will reach 9.3 billion by 2050 (United Nations, 2011), and this will require a 70-percent 

increase in food production, net of crops used for biofuels (FAO, 2009). Currently, according to an ERS report, 

the number of food-insecure people reached 802 million in 2012 (Rosen et al., 2012). Low incomes have an 

important role in this level of food insecurity. Although most of this population growth will occur in developing countries, developed countries like the United States also face issues of hunger and food insecurity. 

In 2012, 49 million people lived in food-insecure households in the United States (Coleman-Jensen et al., 2013) 

out of a total population of over 305 million. Food insecurity is when the food intake of one or more household 

members is reduced and eating patterns are disrupted at times during the year because the household lacks 

money and other resources for food. Food-insecure households accounted for 14.5 percent of U.S. households: 

9.2 percent had low food security and 5.7 percent had very low food security (see figure). 
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calculates the amount and value of food loss in the United States. It does not calculate the amount 

and value of food waste or the other subcomponents of food loss. Data are unavailable on the portion 

of food loss that is food waste. The estimates of food loss provided here have had the inedible 

portions removed (e.g., bones, peach pits, and asparagus stalks). For example, the food loss estimates 

for meat, poultry, and fish provided are in boneless weight. 

Some food loss is inevitable because food is inherently perishable and some food needs to be 

discarded to ensure food safety. For example, some unsold or uneaten food at restaurants, supermarkets, or in homes is not suitable for consumption. Some losses—like the discard of moldy fruit from 

the produce shelf at the supermarket and the condemnation of diseased animals at the slaughtering 

house—are necessary to ensure the safety and wholesomeness of the food supply. Such foods are 

not recoverable for human use. Likewise at restaurants, plate scraps not taken home by patrons are 

appropriately discarded out of health considerations. Legal liability and strict food safety rules, such 

as those in the wake of the mad cow disease scare, inhibit food recovery and redistribution in some 

cases. Discarding unsafe food and food suspected of being unsafe reduces the individual and societal costs of foodborne illness and, in some cases, the potential legal liability. 

Many causes of food loss can occur across the entire food supply chain in developed countries (see 

box, “Causes of Food Loss and Waste at the Farm, Farm-to-Retail, Retail, and Consumer Levels”). 

The share of total food loss due to each of these causes is unknown. 

This report estimates the amount, value, and calories of food loss at the retail and consumer levels in the 

United States, both in total and per capita by major food group.3 No adjustments are made for changes in 

the demographic makeup of the population. Given the recent and growing interest in food loss and waste 

domestically, up-to-date estimates on the magnitude of food loss in the United States are timely. This 

report updates and extends previous ERS publications on food loss in several important ways:

1. The report updates previous ERS estimates of the amount and value of food loss for foods at the 

retail and consumer levels in the United States in 2010 using data as of September 2012. Previous 

ERS food loss estimates for 2008 are available in Buzby and Hyman (2012) (amount and value 

for all commodities), Buzby et al. (2011) (value provided only for fruits and vegetables), and 

Hodges et al. (2010) (amount estimates in tonnes). 

2. The estimates in this report incorporate new consumer-level loss assumptions, which were introduced into the Loss-Adjusted Food Availability (LAFA) data series in August 2012 (see documentation: http://www.ers.usda.gov/data-products/food-availability-(per-capita)-data-system/

loss-adjusted-food-availability-documentation.aspx) and which were not used in the aforementioned studies. 

3. This report discusses the economics of food loss in greater depth than in previous ERS reports. 

4. This report provides ERS’s first estimates of the amount of food loss in terms of calories. 

5. The LAFA data series is part of the Food Availability Data System, which now faces important 

data challenges in terms of temporarily suspended or unavailable data for some commodities 

(ERS, 2011). This means that the 2010 estimates provided in this report may be the last complete 

year for some time whereby all commodities and food groups are represented in the FADS. This 

3Here, this report uses the term “calories” to represent “Calories” (i.e., with capital “C”) or kilocalories because 

“calories” is the commonly used spelling in the media and informal publications, Wikipedia provides more information 

on this distinction (http://en.wikipedia.org/wiki/Calorie). 
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Causes of Food Loss and Waste at the Farm, Farm-to-Retail, Retail, 

and Consumer Levels 

(Farm Level (not measured in this report)

• Consumption or damage by insects, rodents, birds, or microbes (e.g., molds, bacteria),a and damage by 

unfavorable or extreme weather (e.g., droughts, floods, hurricanes, and freezes).

• Diminishing returns when harvesting additional increments of production and other factors leading to 

leaving some edible crops unharvested.

• Overplanting or overpreparing due to difficulty predicting number of buyers/customers.

Farm-to-Retail Level (not measured in this report)

• Rejection of some products for human consumption due to industry or government food safety regulations 

or standards (e.g., livestock condemned at slaughter for food safety reasons).

• Byproducts from food processing landfilled or incinerated (i.e., not diverted to other food uses such as for 

ingredients in mixed foods).

• Outgrading of blemished, misshapen, or wrong-sized foods due to minimum quality standards by buyers, 

which are the result of consumer demand for high-quality, cosmetically appealing, and convenient foods. 

• Spillage and damage, such as by equipment malfunction (e.g., faulty cold or cool storage) or inefficiencies 

during harvesting, drying, milling, transporting, or processing.

Retail Level

• Dented cans and damaged packaging. Inappropriate packaging that damages produce.b

• Unpurchased holiday foods.

• Spillages, abrasion, bruising, excessive trimming, excessive or insufficient heat, inadequate storage, 

technical malfunction.a 

• Overstocking or overpreparing due to difficulty predicting number of customers.

• Culling blemished, misshapen, or wrong-sized foods in an attempt to meet consumer demand.

Consumer Level

• Spillages, abrasion, bruising, excessive trimming, excessive or insufficient heat, inadequate storage, 

technical malfunction.a 

• Sprouting of grains and tubers, biological aging in fruit.a

• Consumers becoming confused over “use-by” and “best before” dates so that food is discarded while still 

safe to eat.b

• Lack of knowledge about preparation and appropriate portion sizes. For example, lack of consumer 

knowledge of when a papaya is ripe, how to prepare it, and how to use it as an ingredient are reasons for 

high papaya loss.c

• Industry or government standards may cause some products to be rejected for human consumption 

(e.g., plate waste can’t be re-used at restaurants).

• Psychological tastes, attitudes, and preferences leading to plate waste/scrapings (e.g., human aversion, such 

as “I don’t eat that,” or refusal to eat a food for religious reasons).a Consumer demand for high cosmetic 

standards.

• Seasonal factors: more food is wasted in summer.d

• Uneaten or leftover holiday foods.

Sources: a Zeigler and Floros(2011), bParfitt et al. (2010), cBuzby et al. (2009), and dGallo (1980), and the remainder was constructed by the authors, 2012. A previous version of this table was published in Buzby and Hyman (2012). Some of these examples of 

causes may occur at more than one level (e.g., spillage).
6

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emphasizes the importance of providing the 2010 food loss estimates with detailed information 

and documentation about the estimates. This documentation will change as new data and information are included in the FADS and if there is a change in the methodology of how the food loss 

estimates are calculated. 

Although ERS adjusts for farm-to-retail level losses for some of the included commodities (e.g., 

canned fruit and vegetables), ERS does not provide summary estimates of food loss at the farm-toretail levels because of the lack of comparable data for each individual food in the LAFA data series. 

The food loss estimates provided in this report at the retail and consumer levels are greater than the 

amounts of food that could be recovered and diverted to feed people. As previously mentioned, some 

uneaten food cannot be efficiently and effectively diverted due to the perishability of most foods, high 

transportation and distribution costs, and other challenges, such as the need to ensure food safety. 

On the other hand, the per capita estimates of the total amount of food available for consumption 

(i.e., the primary reason why this data series was created) using data from the LAFA data series 

are high,4 suggesting that underlying food loss assumptions and resulting food loss estimates for 

all included commodities and food groups presented here are, on average, understated. In 2010, 

the estimated calories available per capita per day was 2,547, which is high, even given the current 

obesity epidemic.5 If a person with caloric needs of 2,100 calories per day actually consumed 2,547 

calories per day, he/she would gain an implausible and unsustainable amount of weight per year or 

over a lifetime. In other words, if the underlying food loss assumptions were higher, then more food 

(i.e., associated with the loss) would be subtracted from the unadjusted amounts of food available for 

consumption and the estimated loss-adjusted amount of calories per capita per day would be lower 

than the current estimate of 2,547 calories per day and thus more realistic.

Economics of Food Loss

There is a practical limit to how much food loss the United States could realistically prevent, reduce, 

or recover for human consumption given:

1. technical factors (e.g., the perishable nature of most foods; food safety, storage, and temperature 

considerations); 

2. temporal and spatial factors (e.g., the time needed to deliver food to a new destination, and the 

dispersion of food loss among millions of U.S. households, food processing plants, and foodservice locations); 

3. individual consumers’ tastes, preferences, and food habits (e.g., a child’s distaste for bread crusts, 

the habit of throwing out milk left over in a bowl of cereal); and 

4The primary purpose of the LAFA data series is to estimate consumed amounts of food from the amount of food 

available in the U.S. food supply. This differs from approaches, such as the National Health and Nutrition Examination 

Survey (NHANES), that are based on 24-hour recalls and tend to be underestimates of actual consumption. The extent of 

underestimation is well documented (especially for calories) using doubly labeled water methods. The LAFA estimates 

of per capita availability are well above NHANES estimates, suggesting that the underlying food loss assumptions in the 

data series and the ERS food loss estimates provided here are conservative. The LAFA estimates are also higher than the 

energy requirements of many cohorts of the population as determined by the Institute of Medicine (IOM, 2005). This 

also suggests that the ERS food loss estimates are conservative.

5This 2,547 calories per capita per day is calculated from 3,796 total calories minus 1,249 calories of food loss (see 

Table 6).
7

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4. economic factors (e.g., cost and other resource constraints, such as to recover and redirect 

uneaten food to another use). These economic factors are often entwined with the technical, 

temporal, and spatial factors.

Therefore, it is unrealistic to think that the United States or any other country will ever entirely 

eliminate food waste. GAO’s 1977 Report to Congress (p. 44) considers the question of whether 

losses are economically justifiable:

“From a business standpoint, the value of food product saved for human use should 

be equal to, or greater than, the cost of saving it. To the extent that the costs exceed 

value, good business judgment dictates that the loss is an acceptable cost. In the 

course of preparing this report, no material has been found that would indicate that 

opportunities were knowingly overlooked by business owners to conserve food at an 

acceptable cost. The profit motive should dictate against such loss. The slowness of 

technology transfer, however, can serve to impede the implementation of loss-reducing 

techniques. It is, therefore, possible that opportunities to make loss physically and 

economically preventable are not being utilized. In sum, at this point, losses that have 

been identified are, for the most part, economically justifiable.”

There really are two separate challenges in reducing food loss and its environmental and other 

impacts: (1) how to reduce the amount of uneaten food in the first place (prevention), and (2) what 

to do with uneaten food once it is generated (disposal). As the first challenge is met more fully, the 

second becomes less of an issue. The impact on food prices and markets of a reduction in food loss 

depends on if the loss was prevented in the first place or if what would be counted here as “food 

loss” is diverted to other economic uses. If uneaten food is simply diverted to other economic uses 

beyond human consumption (e.g., animal feed or energy generation) so that domestic demand for 

food and domestic food production remains roughly the same, then there won’t be downward pressure on food prices and the agriculture and food industry’s business will remain roughly unchanged. 

However, if food loss is prevented or reduced to the extent that less food is needed to feed people 

(i.e., the demand for food decreases), then this would likely reduce food prices in the United States 

and the rest of the world. However the effects on food prices will depend on the relevant supply and 

demand elasticities (i.e., economic measures of the responsiveness of supply and demand to a change 

in its price). For example, if more food is exported to offset the effect on food markets from domestic 

reductions in food loss, then food prices may not decrease as much as without the boost in exports. 

If the domestic demand for food decreases, then the demand for inputs like land, labor, and capital 

may decline as well. If per capita food loss is significantly reduced by increased food consumption by 

people already consuming above their energy needs, then the costs associated with increased obesity 

may grow. It is important to note that the value of food loss estimated in this report is for one snapshot 

in time and would change as retail prices change in response to supply and demand factors. 

All of the loss assumptions used in the LAFA data series are currently available on the ERS website, 

and some of this commodity-specific information may be helpful when analyzing food loss for a 

particular commodity at the retail or consumer level (ERS, 2012a). Additional types of economic 

costs could be included in a benefit-cost analysis of a specific loss-reducing initiative. These costs 

could include the costs of disposing of unused food, the cost and value of food going to a lower value 

use (e.g., animal feed), and the lost opportunity cost of resources wasted. Data are largely unavailable on exactly where, why, and how food losses and waste occur and the economic incentives to 

reduce these losses. 
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In some cases, the amount and value estimates in this report are likely too aggregated to provide 

helpful measures of the economic incentives for a specific food company to reduce food loss. A 

food company would need more tailored estimates to help inform its decision to reduce food loss, 

particularly if the decision involves multi-ingredient foods or commodities not covered in the LAFA 

data series (e.g., LAFA provides data on commodities and whole foods such as eggs, beef, and fresh 

spinach). For example, a food company may weigh the costs of switching to more expensive packaging for fresh meat against the benefits of having that packaging extend the shelf life of the meat. 

In short, companies will adopt a loss-reducing practice if it is economically justifiable, that is, if the 

benefits outweigh the costs. This cost-benefit analysis may include consideration of consumer goodwill toward a firm, such as when a sandwich shop donates uneaten yet wholesome food to a community feeding organization at the end of each day.

More specific food loss estimates could help policymakers in designing food-loss-reducing regulations. Publicizing where and how much food goes uneaten and the value of this loss may help inform 

policymakers about the issue and help increase the efficiency of the farm-to-fork food system and food 

recovery efforts to feed the growing human population. Other policy issues related to food loss include 

sustainability, the impact on international trade, and government funding of research and development 

for loss-reducing technologies (e.g., for food, food packaging, and food system practices).

Losses at the consumer level occur for many reasons, such as different tastes and preferences or 

consumers buying more than they need (see box, “Causes of Food Loss and Waste at the Farm, 

Farm-to-Retail, Retail, and Consumer Levels”). For many Americans, food purchases are a small 

component of all household spending, weakening incentives to reduce food loss on monetary 

grounds alone. The average American spent 11.2 percent of disposable income on food in 2010.6 

Consumer food loss is widespread, so mitigating it will be challenging. There are an estimated 119 

million households (U.S. civilian population), over a half a million dining establishments (i.e., fullservice restaurants, fast-food outlets), and numerous other places where people eat (e.g., schools, 

institutions, and prisons) across the United States. 

This range of food loss combined with economies of scale suggest that large, industry-led initiatives 

or government-led policies, such as information campaigns and additional changes in Federal laws, 

may have the greatest potential to reduce food loss in the next decade. One example of a large initiative to reduce food waste is the Waste Resources Action Programme (WRAP). WRAP estimates 

that between 2007 and 2012, household food waste in the United Kingdom decreased 15 percent 

despite a 4-percent increase in the number of households (Goodwin, 2013). This is presumably due 

in part to its campaign to raise awareness of the issue by consumers, businesses, and local authorities 

(e.g., Love Food Hate Waste launched in 2007).7 There have been other major campaigns launched 

to raise public awareness of food waste and to promote reduction, such as the Food Wise Hong 

Kong Campaign launched in December 2012. In the United States, there have been several laws 

(e.g., Bill Emerson Good Samaritan Food Donation Act, Internal Revenue Code 170(e)(3), and the 

U.S. Federal Food Donation Act of 2008) that have encouraged food donation by providing liability 

protection to donors or tax incentives, though the full impact on food loss or food waste has not been 

measured.8

6In 2010, the average American spent $4,016 on food (both for at-home and away-from-home consumption) (ERS, 

2012b) out of an average disposable income of $36,016 in 2010 (BLS, 2012).

7For more information on WRAP, see Quested and Parry (2011) and www.wrap.org.uk

8See http://www.usda.gov/oce/foodwaste/resources/donations.htm for more information.
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Currently, there is a growing list of participants in the U.S. Food Waste Challenge undertaking activities to reduce, recover, or recycle food waste, and these participants include six USDA agencies, 

major food companies, smaller private firms, universities and colleges, sports teams, and entertainment resorts, among others.9 Even a modest, yet economically feasible, decrease in food loss from 

small loss-reducing initiatives or newly adopted processing, packaging, and storage technologies 

could lessen the environmental impacts of food waste generation and disposal. And if wholesome 

food is recovered for human consumption in this process, it could reduce food insecurity by supplementing existing food assistance efforts and could potentially provide tax savings to farms, food 

retailers, and foodservice establishments that donate food. However, no single intervention would 

be a panacea and, as previously mentioned, food loss will never be entirely eliminated. Substantial 

inroads in reducing food loss would likely require a combination of approaches. Prior to the adoption 

of new initiatives, policies, or laws to reduce food loss, both the costs and benefits should be considered. For example, while redirecting edible and wholesome food to food banks takes advantage of 

food already available for consumption, food safety and transportation challenges and costs need to 

be considered. 

In the end, economic incentives and consumer behavior will be paramount in reducing food loss, 

and these efforts must coexist with obtaining an acceptable return on investment by food industry 

members; protecting the environment and worker safety; and fulfilling consumer demand for food 

safety, quality, variety, and affordability. 

9See http://www.usda.gov/oce/foodwaste/participants.htm for details.
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Data and Methods

ERS’s Loss-Adjusted Food Availability (LAFA) data are derived from ERS per capita Food 

Availability data adjusted to remove the inedible portions (e.g., bones, pits, and peels) and to 

account for food spoilage, plate waste, and other losses (e.g., cooking loss). The primary purpose 

of the LAFA data is to more closely estimate actual per capita intake. In addition to providing the 

estimated amount of pounds per capita ingested per year and per day, the data series also provides 

estimates of the loss-adjusted number of calories consumed daily (per capita) and daily food pattern 

equivalents (previously called servings and MyPyramid equivalents). Here, we use the underlying 

food loss assumptions in the LAFA data series as of September 2012 to estimate food loss for 

2010 at the retail and consumer levels, both per capita and in total for the United States. The series 

currently covers more than 200 agricultural commodities from 1970 to the most recent year of data. 

The data for individual commodities are aggregated into food groups to facilitate comparison with 

Federal dietary recommendations.10

The appendix discusses the construction of the LAFA data series, provides a list of commodities 

covered (see appendix box, “Commodity Coverage in the 2010 Loss-Adjusted Food Availability 

Data,” p. 26), and discusses some of the limitations of the data. The appendix also provides detail 

on the steps that we followed for estimating the amount, value (i.e., using 2010 retail prices), and 

calories of food loss in the United States. This data series is considered to be preliminary because 

ERS continues to improve the underlying food loss assumptions and documentation (for details, see 

http://www.ers.usda.gov/data-products/food-availability-(per-capita)-data-system/loss-adjustedfood-availability-documentation.aspx). The LAFA data can be accessed on the ERS website through 

Excel spreadsheets that provide all of the current loss assumptions and a largely consistent structure 

for the data series (i.e., the sequence of steps by which the different types of losses are removed from 

the system) (ERS, 2012a). 

10Currently, the series is calibrated for comparison against the 2005 Dietary Guidelines for Americans, but ERS has 

plans to update the LAFA data with the 2010 Dietary Guidelines for Americans.
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Results

The results from our analysis of ERS’ Loss-Adjusted Food Availability data pertain to the amount, 

value, and calories of food loss at the retail and consumer levels in the United States in 2010. Each 

subsection includes two tables (one for total and one for per capita estimates) and a figure that 

divides the total food loss estimate into shares by food group.

Amount

ERS estimates that 31 percent or 133 billion pounds of the 430 billion pounds of the edible and available food supply at the retail and consumer levels in the United States in 2010 went uneaten (table 1). 

Retail-level losses represented 10 percent (43 billion pounds) and consumer-level losses 21 percent 

(90 billion pounds) of the available food supply. Losses on the farm and between the farm and retailer 

were not estimated due to data limitations for some of the food groups. Had these losses been included, 

total postharvest loss in the United States would be over 31 percent of the food supply. For example, for 

fresh produce alone, an estimated 12 percent goes uneaten in developed countries from production to 

retail sites, with a range from 2 to 23 percent for individual commodities (Kader, 2005).

Our estimates are based on the current loss assumptions in the LAFA data series, which include 

retail-level loss estimates from Buzby et al. (2009). That study—comparing supplier shipment data 

with point-of-sale data from six large supermarket retailers—found that annual supermarket losses 

for 2005 and 2006 averaged 11.4 percent for fresh fruit, 9.7 percent for fresh vegetables, and 4.5 

percent for fresh meat, poultry, and seafood. ERS is currently in the process of obtaining 2011 and 

2012 retail-level food loss estimates for these commodities.11 The loss assumptions for all other 

foods in the data series at the retail level have not been updated (i.e., added fats and oils, added 

sugars and sweeteners, grains, dairy products, and processed fruit and vegetables (frozen, canned, 

dried, and juice).12 

New (2010) estimates of consumer-level loss for most commodities (Muth et al., 2011) were incorporated into the LAFA data series in August 2012 (see ERS (2012a) for details).13 This is the primary 

reason why the shares of loss by food group differ from other recent ERS publications, particularly 

the drop in share for the meat, poultry, and fish group (Buzby and Hyman, 2012; Buzby et al., 2011). 

When the 133 billion pounds of food loss at the retail and consumer levels in 2010 is broken down 

by food group, the top three food groups in terms of loss are: (1) dairy products (25 billion pounds 

or 19 percent); (2) vegetables (25 billion pounds or 19 percent); and (3) grain products (18.5 billion 

pounds or 14 percent) (fig. 1).

11Some data users have suggested that the total retail-level loss estimates of 10 percent and 43 billion pounds are high 

given modern packaging, cold-chain, and inventory tracking technologies and other business practices that are commonly 

used by retailers. 

12The LAFA data series is based on individual commodities/foods, not processed products. The added fats and oils 

group includes foods that are typically added to other foods when eaten and do not include the naturally occurring fats 

in meat and dairy products, for example. Similarly, added sugars and syrups are caloric foods added to foods during 

processing or preparation. Added sugars and sweeteners do not include naturally occurring sugars, such as those found in 

milk and fruit. Non-caloric sweeteners are not included in the LAFA data series.

13RTI International used a numerical estimation method to calculate consumer-level food loss estimates using Nielsen 

Homescan data and National Health and Nutrition Examination Survey (NHANES) data. ERS then analyzed how the 

LAFA per capita data would change if the proposed RTI estimates of consumer-level food loss were incorporated into the 

data series (Muth et al., 2011). 
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Table 1

Estimated total food loss in the United States, 2010

Commodity

Food 

Supplya

Losses from food supplyb

Retail level Consumer level

Total retail and 

consumer level

Billion 

pounds

Billion 

pounds Percent

Billion 

pounds Percent

Billion 

pounds Percent

Grain products 60.4 7.2 12 11.3 19 18.5 31

Fruit 64.3 6.0 9 12.5 19 18.4 29

 Fresh 37.6 4.4 12 9.5 25 13.9 37

 Processed 26.7 1.6 6 2.9 11 4.5 17

Vegetables 83.9 7.0 8 18.2 22 25.2 30

 Fresh 53.5 5.2 10 12.8 24 18.0 34

 Processed 30.4 1.8 6 5.3 18 7.1 24

Dairy products 83.0 9.3 11 16.2 20 25.4 31

 Fluid milk 53.8 6.5 12 10.5 20 17.0 32

 Other dairy 

 products 29.1 2.8 10 5.7 19 8.5 29

Meat, poultry, and fish 58.4 2.7 5 12.7 22 15.3 26

 Meat 31.6 1.4 4 7.2 23 8.6 27

 Poultry 22.0 0.9 4 3.9 18 4.8 22

 Fish and seafood 4.8 0.4 8 1.5 31 1.9 39

Eggs 9.8 0.7 7 2.1 21 2.8 28

Tree nuts and 

peanuts 3.5 0.2 6 0.3 9 0.5 15

Added sugar and 

sweeteners 40.8 4.5 11 12.3 30 16.7 41

Added fats and oils 26.0 5.4 21 4.5 17 9.9 38

Total 430.0 43.0 10 89.9 21 132.9 31

aFood supply at the retail level, which is the foundation for the retail- and consumer-level loss stages in the loss-adjusted 

data series.

bTotals may not add due to rounding.

Per capita losses at the retail and consumer levels for each commodity (not shown) were estimated by multiplying the 

quantity of that commodity available for consumption by the appropriate loss assumption. Individual loss estimates were 

then multiplied by the U.S. population and summed up into their respective food groups and retail or consumer levels. 

Source: ERS (2012a) and the U.S. population on July 1, 2010 (309.75 million). 
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In 2010, the average amount of food loss per American was 429 pounds, of which 139 pounds at 

the retail level and 290 pounds at the consumer level went uneaten (table 2). At the consumer level, 

59 pounds of vegetables, 52 pounds of dairy products, and 41 pounds of meat, poultry, and fish per 

capita from the food supply in 2010 went uneaten. 

Value 

The total value of food loss at the retail and consumer levels was an estimated $161.6 billion in 2010 

(table 3). The two food groups with the highest value of losses were meat, poultry, and fish ($48.5 

billion) and vegetables ($30 billion). These estimates are based on the value of foods as purchased at 

retail prices. The calculations are described more fully in the appendix.

When the total value of food loss at the consumer level in 2010 is broken down by food group, 

the meat, poultry, and fish group comprises almost a third (30 percent) of the total (fig. 2), a much 

greater share than by weight (12 percent in figure 1) because foods in this group tend to cost more 

per pound than many other foods.

Figure 1

Estimated total amount of food loss in the United States by food group, 2010 

Source: ERS (2012a).

Grain products, 18.5, 13.9%

Fruit, 18.4, 13.9%

Vegetables, 25.2, 19.0%

Dairy products, 25.4, 19.1%

Meat, poultry, and fish,

15.3, 11.5% 

Eggs, 2.8, 2.1%

Tree nuts and peanuts, 

0.5, 0.4%

Added sugar and sweeteners,

16.7, 12.6% 

Added fats and oils,

9.9, 7.5%

Billion pounds
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Table 2

Estimated per capita amount of food loss in the United States, 2010

Commodity

Food 

Supplya

Losses from food supplyb

Retail level Consumer level

Total retail and 

consumer level

Pounds Pounds Percent Pounds Percent Pounds Percent

Grain products 195 23 12 36 19 60 31

Fruit 208 19 9 40 19 59 29

 Fresh 121 14 12 31 25 45 37

 Processed 86 5 6 9 11 15 17

Vegetables 271 23 8 59 22 81 30

 Fresh 173 17 10 41 24 58 34

 Processed 98 6 6 17 18 23 24

Dairy products 268 30 11 52 20 82 31

 Fluid milk 174 21 12 34 20 55 32

 Other dairy 

 products 94 9 12 18 19 27 29

Meat, poultry, and fish 189 9 5 41 22 49 26

 Meat 102 5 4 23 23 28 27

 Poultry 71 3 4 13 18 15 22

 Fish and seafood 16 1 8 5 31 6 39

Eggs 32 2 7 7 21 9 28

Tree nuts and 

peanuts 11 1 6 1 9 2 15

Added sugar and 

sweeteners 132 14 11 40 30 54 41

Added fats and oils 84 18 21 15 17 32 38

Total 1,388 139 10 290 21 429 31

aFood supply at the retail level, which is the foundation for the retail- and consumer-level loss stages in the loss-adjusted 

data series.

bTotals may not add due to rounding.

Per capita losses at the retail and consumer levels for each commodity (not shown) were estimated by multiplying the 

quantity of that commodity available for consumption by the appropriate loss assumption. Individual loss estimates were 

then multiplied by the U.S. population and summed up into their respective food groups and retail or consumer levels. 

Source: ERS (2012a) and the U.S. population on July 1, 2010 (309.75 million). 
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Table 3

Estimated total value of food loss at the retail and consumer levels in the United States, 2010

Commodity

Food 

Supplya

Losses from food supplyb

Retail level Consumer level

Total retail and 

consumer level

Billion 

dollars

Billion 

dollars Percent

Billion 

dollars Percent

Billion 

dollars Percent

Grain products 36.1 4.3 12 6.9 19 11.2 31

Fruit 62.2 5.8 9 14.1 23 19.8 32

 Fresh 37.1 4.2 11 10.4 28 14.7 40

 Processed 25.0 1.5 6 3.7 15 5.2 21

Vegetables 0.1 9.6 9 $20.4 19 30.0 28

 Fresh 62.1 6.9 11 $13.2 21 20.1 32

 Processed 46.6 2.8 6 $7.2 15 10.0 21

Dairy products 91.5 8.3 9 18.6 20 27.0 29

 Fluid milk 20.0 2.4 12 4.0 20 6.4 32

 Other dairy 

 products 71.5 5.9 8 14.6 20 20.5 29

Meat, poultry, and fish 181.9 8.8 5 39.7 22 48.5 27

 Meat 83.4 3.8 5 19.3 23 23.2 28

 Poultry 73.6 2.9 4 12.5 17 15.4 21

 Fish and seafood 24.8 2.1 8 7.9 32 9.9 40

Eggs 10.9 0.8 7 2.3 21 3.1 28

Tree nuts and 

peanuts 12.1 0.7 6 1.3 11 2.1 17

Added sugar and 

sweeteners 16.4 1.8 11 4.8 29 6.6 40

Added fats and oils 34.2 6.6 19 6.8 20 13.4 39

Total 554.0 46.7 8 114.9 21 161.6 29

aFood supply at the retail level, which is the foundation for the retail- and consumer-level loss stages in the loss-adjusted 

data series.

bTotals may not add due to rounding.

Per capita losses at the retail and consumer levels for each commodity (not shown) were estimated by multiplying the 

quantity of that commodity available for consumption by the appropriate loss assumption. Individual loss estimates were 

then multiplied by the U.S. population and summed up into their respective food groups and retail or consumer levels. 

Source: ERS (2012a) and the U.S. population on July 1, 2010 (309.75 million). 
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Per capita, food loss in 2010 totaled $522 per year at retail prices: $151 per year at the retail level 

and $371 at the consumer level (table 4). The latter amounts to 9.2 percent of the average dollar 

value spent on food per consumer in 2010 ($4,016) (ERS, 2012b) and 1 percent of the average 

disposable income ($36,016) (BLS, 2012). The yearly total of 290 pounds (table 2) of food loss per 

capita in 2010 at the consumer level, at an estimated retail price of $371, translates into 0.8 pound or 

roughly $1 per day. This is slightly lower than the $390 of food loss per capita in 2008 estimated in 

Buzby and Hyman (2012), largely because new consumer-level food loss estimates were adopted in 

the LAFA system in August 2012. At the consumer level, three food groups made up 68 percent of 

the total food loss: meat, poultry, and fish ($128/year per capita); vegetables ($66/year); and dairy 

products ($60/year). 

For comparison, another recently published study that used the same LAFA data but different 

assumptions and retail prices estimated that the economic and climate change impacts of food loss 

for 134 commodities in the United States cost $198 billion in 2009 (Venkat, 2012). This translates 

into $400 per person.

Figure 2

Estimated total value of food loss in the United States by food group, 2010 

Source: ERS (2012a).

Grain products, $11.2, 6.9% 

Fruit, $19.8, 12.3%

Vegetables, 

$30.0, 18.6%

Dairy products, $27.0, 16.7%

Meat, poultry, & fish, 

$48.5, 30.0% 

Eggs , $3.1, 1.9%

Tree nuts & peanuts, $2.1, 1.3% 

Added sugar & sweeteners, 

$6.6, 4.1% 

Added fats & oils, 

$13.4, 8.3%

Billion dollars
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Table 4

Estimated per capita value of food loss at the retail and consumer levels in the United States, 2010

Commodity

Food 

Supplya

Losses from food supplyb

Retail level Consumer level

Total retail and 

consumer level

Dollars Dollars Percent Dollars Percent Dollars Percent

Grain products 117 14 12 22 19 36 31

Fruit 201 19 9 45 23 64 32

 Fresh 120 14 11 34 28 47 40

 Processed 81 5 6 12 15 17 21

Vegetables 351 31 9 66 19 97 28

 Fresh 201 22 11 43 21 65 32

 Processed 150 9 6 23 15 32 21

Dairy products 295 27 9 60 20 87 29

 Fluid milk 65 8 12 13 20 21 32

 Other dairy 

 products 231 19 8 47 20 66 29

Meat, poultry, and fish 587 28 5 128 22 157 27

 Meat 269 12 5 62 23 75 28

 Poultry 238 9 4 40 17 50 21

 Fish and seafood 80 7 8 25 32 32 40

Eggs 35 2 7 8 21 10 28

Tree nuts and 

peanuts 39 2 6 4 11 7 17

Added sugar and 

sweeteners 53 6 11 15 29 21 40

Added fats and oils 111 21 19 22 20 43 39

Total 1,788 151 8 371 21 522 29

aFood supply at the retail level, which is the foundation for the retail- and consumer-level loss stages in the loss-adjusted 

data series.

bTotals may not add due to rounding.

Per capita losses at the retail and consumer levels for each commodity (not shown) were estimated by multiplying the 

quantity of that commodity available for consumption by the appropriate loss assumption. Individual loss estimates were 

then multiplied by the U.S. population and summed up into their respective food groups and retail or consumer levels. 

Source: ERS (2012a) and the U.S. population on July 1, 2010 (309.75 million). 
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Calories

This report provides ERS’s first estimates of the number of calories of food loss at the retail and 

consumer levels in the United States to help put the magnitude of this food loss into perspective. In 

total, out of the entire U.S. food supply in 2010, an estimated 387 billion calories of food were available each day but were not consumed for any reason (table 5). This amount of food loss translates 

into 141 trillion calories per year. Of course, many factors would affect whether these foods could be 

diverted to feed people in real life, such as food safety considerations and storage and transportation 

costs. Additionally, this food loss estimate is based on calories alone and does not address the more 

complex nutritional needs of individual people, such as for specific vitamins and minerals. 

Interestingly, the food group shares of total calories that went uneaten (fig. 3) are noticeably different 

than the shares for the amount (fig. 1) or value (fig. 2) of food loss. In particular, the shares for 

added fats and oils, added sugars and sweeteners, and grains are much higher for the calories figure, 

reflecting these foods’ caloric density per pound.

Daily food loss for the average American totaled 1,249 calories (out of 3,796 calories available per 

capita per day), of which 460 calories occurred at the retail level and 789 calories occurred at the 

consumer level (table 6). At the consumer level, the average daily food loss per American included 

187 calories of added sugar and sweeteners, 166 calories of grain products, and 154 calories of added 

fats and oils. In comparison, Kevin Hall and others at the National Institutes of Health used data 

from the Food and Agriculture Organization’s (FAO) food balance sheets and a mathematical model 

of human energy expenditure to calculate the energy content of food waste in the United States. Hall 

et al. (2009) estimated that food waste, on average, is equivalent to 1,400 calories per person per day 

or 150 trillion total calories per year versus ERS’s estimate of 1,249 calories per person per day and 

141 trillion total calories per year.
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Table 5

Estimated total calories of food loss at the retail and consumer levels in the United States, 2010

Commodity

Food 

Supplya

Losses from food supplyb

Retail level Consumer level

Total retail and 

consumer level

Billion 

calories

Billion 

calories Percent

Billion 

calories Percent

Billion 

calories Percent

Grain products 273.0 32.8 12 51.3 19 84.1 31

Fruit 37.1 3.1 8 8.8 24 11.9 32

 Fresh 19.4 2.1 11 6.5 33 8.5 44

 Processed 17.7 1.1 6 2.3 13 3.4 19

Vegetables 52.6 3.8 7 10.1 19 13.9 26

 Fresh 22.4 2.0 9 6.7 30 8.7 39

 Processed 30.2 1.8 6 3.4 11 5.2 17

Dairy products 183.1 8.1 9 23.4 21 33.9 30

 Fluid milk 113.7 5.1 12 6.8 20 10.8 32

 Other dairy 

 products 62.2 2.4 8 16.6 21 23.0 29

Meat, poultry, and fish 7.2 0.6 4 38.9 21 47.0 26

 Meat 113,688 5,069 4 25.7 23 30.8 27

 Poultry 62,164 2,417 4 10.9 18 13.3 21

 Fish and seafood 7,208 583 8 2.2 31 2.8 39

Eggs 15.5 1.1 7 4.0 26 5.1 33

Tree nuts and 

peanuts 25.8 1.5 6 2.3 9 3.8 15

Added sugar and 

sweeteners 193.0 21.2 11 58.0 30 79.3 41

Added fats and oils 282.1 60.2 21 47.8 17 108.0 38

Total 1,175.8 142.3 12 244.5 21 386.9 33

aFood supply at the retail level, which is the foundation for the retail- and consumer-level loss stages in the loss-adjusted 

data series.

bTotals may not add due to rounding.

Per capita losses at the retail and consumer levels for each commodity (not shown) were estimated by multiplying the 

quantity of that commodity available for consumption by the appropriate loss assumption. Individual loss estimates were 

then multiplied by the U.S. population and summed up into their respective food groups and retail or consumer levels. 

Source: ERS (2012a) and the U.S. population on July 1, 2010 (309.75 million). 
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Grain products, 84.1, 21.7%

Fruit, 11.9, 3.1%

Vegetables, 13.9, 3.6%

Dairy products, 33.9, 8.8%

Meat, poultry, and fish,

47.0, 12.1% 

Eggs, 5.1, 1.3%

Tree nuts and peanuts, 

 3.8, 1.0%

Added sugar and sweeteners,

79.3, 20.5%

Added fats and oils, 

108.0, 27.9%

Billion calories

Figure 3

Estimated total number of calories of food loss in the United States per day by food 

group, 2010

Source: ERS (2012a).
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Table 6

Estimated daily per capita calories of food loss at the retail and consumer levels in the 

United States, 2010

Commodity

Food 

Supplya

Losses from food supplyb

Retail level Consumer level

Total retail and 

consumer level

Calories Calories Percent Calories Percent Calories Percent

Grain products 881 106 12 166 19 271 31

Fruit 120 10 8 28 24 38 32

 Fresh 63 7 11 21 33 28 44

 Processed 57 3 6 7 13 11 19

Vegetables 170 12 7 33 19 45 26

 Fresh 72 6 9 22 30 28 39

 Processed 97 6 6 11 11 17 17

Dairy products 367 34 9 75 21 109 30

 Fluid milk 109 13 12 22 20 35 32

 Other dairy 

 products 258 21 8 53 21 74 29

Meat, poultry, and fish 591 26 4 126 21 152 26

 Meat 367 16 4 83 23 99 27

 Poultry 201 8 4 35 18 43 21

 Fish and seafood 23 2 8 7 31 9 39

Eggs 50 3 7 13 26 16 33

Tree nuts and 

peanuts 83 5 6 7 9 12 15

Added sugar and 

sweeteners 623 69 11 187 30 256 41

Added fats and oils 911 194 21 154 17 349 38

Total 3,796 460 12 789 21 1,249 33

aFood supply at the retail level, which is the foundation for the retail- and consumer-level loss stages in the loss-adjusted 

data series.

bTotals may not add due to rounding.

Per capita losses at the retail and consumer levels for each commodity (not shown) were estimated by multiplying the 

quantity of that commodity available for consumption by the appropriate loss assumption. Individual loss estimates were 

then multiplied by the U.S. population and summed up into their respective food groups and retail or consumer levels. 

Source: ERS (2012a) and the U.S. population on July 1, 2010 (309.75 million). 
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Discussion

In 2010, an estimated 133 billion pounds of food at the retail and consumer levels in the United 

States went uneaten, and this amount is valued at $161.6 billion using retail prices. This amount of 

food loss translates into 141 trillion calories in 2010. These estimates suggest that annual food loss in 

the United States is substantial. 

As with any research with quantitative values, the resulting estimates produced here may be low or high. 

ERS food loss estimates could be low for various reasons. Many foods are not included in the system 

(e.g., soybeans, soy milk, and coconut milk) and so losses for these foods are not counted. Additionally, 

the LAFA data series suggests that the average American consumed 2,547 calories per day in 2010, which 

is high even considering the prevalence of obesity in the United States, implying that the estimated food 

loss is low or that there are other issues. The LAFA estimates are also higher than the energy requirements of most age cohorts as determined by the Institute of Medicine ((IOM), 2005), further suggesting 

that the ERS food loss estimates are conservative. Hall et al. (2009) suggest that the loss estimates from 

the LAFA estimate are low and/or that the assumptions of a roughly constant proportion of food waste 

are becoming progressively worse over time (p. 3).14 Hall et al. (2009), however, do not offer suggestions 

on how to obtain better estimates of food loss, and the study predates the incorporation of new consumerlevel loss estimates from Muth et al. (2011) into the LAFA data series in August 2012. Also, the estimated 

$161.6 billion of food loss was calculated using retail prices. Had we used foodservice prices (which are 

typically higher), then the estimated value of food loss would have been higher. 

There are several reasons why the ERS food loss estimates could be high. Some of the individual loss estimates may be high, particularly at the retail level. The ERS food loss estimates assume that food loss has 

no residual value or economic use. But in reality, there may be a residual use if the food loss is diverted to 

another economic use, such as for animal feed or to create energy.15 That is, by redirecting food for use 

as energy inputs, for example, less food or other inputs would need to be purchased from other sources 

for these purposes. In essence, if data had been available on the amount of food diverted to lower value 

uses and on the economic value of these uses, then the ERS estimate of the total amount of food loss 

could have been adjusted downwards. However, data limitations preclude these refinements. The U.S. 

Environmental Protection Agency (EPA) has developed a food waste hierarchy of preferred uses for available food that goes unconsumed by people (see box, “EPA’s Food Recovery Hierarchy”). It is possible that 

some of the factors that might cause the estimates to be high or low could cancel each other out.

There is a practical limit to how much food loss the United States can prevent or reduce given technical and spatial factors; consumers’ tastes, preferences, and food habits; and economic factors. 

Therefore, the amount of food loss that could be prevented or reduced will be less than the ERS food 

loss estimates. Nevertheless, these updated estimates are a unique contribution to the literature and 

are useful in providing perspective to the issue of food loss in the United States. 

14Hall et al. (2009) write that “food waste has progressively increased from about 30 percent of the available food 

supply in 1974 to almost 40 percent in recent years” using the Food and Agriculture Organization’s balance sheets. By 

contrast, what they call the ‘USDA’ food waste estimate (calculated by subtracting the USDA food availability data 

adjusted for spoilage and wastage from the FAO food supply data) is an approximately constant proportion of the total 

food supply. They conclude that “while the USDA estimate of food waste was within 5 percent of our calculation in 1974, 

it was ~25 percent too low in 2003.” 

15As an aside, these uses of the food waste may harm the environment less than landfilling or incinerating the food 

waste. Here, the creation of energy using food waste does not include corn used for ethanol, which was already removed 

as a direct industrial use of corn in the supply and disappearance (i.e., use) balance sheets.
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EPA’s Food Recovery Hierarchy

The U.S. Environmental Protection Agency (EPA) endorses its food recovery hierarchy, where 

the ideal situation would be to reduce the production of food waste at the source. When food 

waste is generated, the first preference is to recover wholesome food from all points in the 

food production, marketing, and consumption chain to feed people who are food insecure. 

Providing food for livestock, zoo animals, and pets would be the second best option, followed 

by recycling food and food waste for industrial purposes. These three options would help 

conserve resources and reduce food waste disposal costs. For example, the feasibility of anaerobic digesters that use feedstock, food and agricultural waste, and wastewater plant biosolids 

to produce biogas fuel and other valuable outputs (e.g., compost material) is being explored in 

developed countries. 

Food recovery hierarchy

Source: http://www.epa.gov/osw/conserve/materials/organics/food/fd-gener.htm#food-hier

Most preferred

Least preferred

Composting food to improve soil fertility is a relatively low-priority option, and its use is not 

widespread in the United States. However, some cities, counties, and State agencies are investigating the benefits of curbside collection of residential food waste (e.g., in bins or compostable 

kitchen bags) to compost with collected yard trimmings. According to the EPA (2009), there 

were around 3,510 community composting programs in operation in the United States in 2008, 

so expanding these to incorporate food waste might be a viable option. The last resort should 

be using landfills and incinerators to dispose of food waste because of the negative impacts on 

the environment. These impacts are partly offset if energy is created during incineration and 

landfilling (e.g., tapping the methane gas).
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Appendix—The ERS Loss-Adjusted Food Availability Data 

and Calculation Details for the Amount and Value of 

Food Loss

Since 2005, the updated Food Availability (Per Capita) Data system has had three separate but 

related data series that each look differently at the food available for consumption in the United 

States. The first series, the Food Availability data, is the foundation for the other two series: (1) the 

Nutrient Availability data16 and (2) the Loss-Adjusted Food Availability (LAFA) data (formerly 

called the Food Guide Pyramid Servings data). This loss-adjusted series is the foundation of this 

report and is essentially the Food Availability data adjusted for food spoilage and other losses to 

more closely approximate actual per capita intake (http://www.ers.usda.gov/data-products/foodavailability-(per-capita)-data-system/loss-adjusted-food-availability-documentation.aspx). The 

primary purpose of the LAFA data is to estimate daily per capita food intake and present this information in two forms: the number of calories consumed daily and the number of food pattern equivalents consumed daily.17 Here, we use the embedded food loss assumptions to estimate food loss at 

the retail and consumer levels for 2010 using the LAFA data as of September 2012.

Construction of the Core Food Availability Data

In essence, the Food Availability data measure the use of basic commodities—such as wheat, beef, 

and shell eggs—produced at the farm level or an early stage of processing and available for human 

consumption. They do not measure food use of highly processed foods−such as bakery products, 

frozen dinners, and soups−in their finished form. Ingredients of highly processed foods, however, 

are included as components of less processed foods such as sugar, flour, fresh vegetables, and meat.

The Food Availability data series is based on records of annual commodity flows from production 

to end uses. This involves the development of supply and disappearance (i.e., “supply and use”) 

balance sheets for each major commodity from which human foods are produced. In general, the 

total annual available supply of each commodity consists of the sum of production, imports, and 

beginning stocks. These three components are either directly measured or estimated by government 

agencies using sampling and statistical methods. From this total supply, exports, ending stocks, and 

total measurable nonfood uses are subtracted. For most commodity categories, measurable nonfood 

uses are farm inputs (feed and seed) and industrial uses. In a few cases, supplies for human food use 

are measured directly and one of the other use components becomes the residual. This is the case for 

wheat, in which flour production is measurable and available from manufacturers’ reports on flour 

milling and, therefore, use for livestock feed becomes the residual.

Per capita food availability is calculated by dividing the annual total food supply for a specific year 

by the U.S. total resident population plus Armed Forces overseas for that same year. Yearly population estimates are from the U.S. Census Bureau. For commodities not shipped overseas in substantial 

amounts, such as fluid milk and cream, ERS uses the resident population as the base. No adjustments are made for changes in the demographic makeup of the population. 

16This nutrient series is compiled by USDA’s Center for Nutrition Policy and Promotion (CNPP) in what it calls the 

Nutrient Content of the U.S. Food Supply and is outside the scope of this report.

17These food pattern equivalents were formerly called the Food Guide Pyramid serving equivalents and are defined by 

the 2005 Dietary Guidelines for Americans and its supporting MyPyramid Plan Food Guidance System. 
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Construction of the Loss-Adjusted Food Availability Data 

The current ERS per capita Food Availability data were converted into daily per capita food pattern 

equivalents comparable to those identified in Federal dietary recommendations using a multistage 

process. Each commodity was assigned to one of five major food groups (fruit, vegetables, meat, 

dairy, and grains) or to one of two additional groups for discretionary added fats and oils and added 

sugar/sweeteners. The core Food Availability data were adjusted for spoilage and other losses by 

subtracting estimated losses from the “primary” weight reported in the data series to create the 

Loss-Adjusted Food Availability data series. Depending on the commodity, loss was estimated 

at up to three different stages in the marketing system (i.e., farm-to-retail, retail, and consumer). 

ERS calculates summary estimates of food loss for each commodity in the Loss-Adjusted Food 

Availability data series at the retail and consumer levels. Although the data system also takes into 

account food losses between the farm and retailer, ERS cannot calculate summary estimates of food 

loss between the farm and retailer because of data limitations for some of the food groups. Onfarm 

or pre-harvest losses, such as from hail damage on a field crop, are not included in the system. 

Inedible portions of all foods—seeds, pits, and inedible peels—were also subtracted from the data, 

and thus the loss-adjusted food availability estimates and the food loss estimates do not include inedible parts. For example, estimates for meat, poultry, and fish are provided as boneless weight. The 

data were converted from pounds per capita per year to grams (or ounces) per capita per day to be 

comparable with Federal dietary recommendations.

Estimation Details for this Report

Given the recent and growing interest in food loss and waste domestically (e.g., U.S. Food Waste 

Challenge), up-to-date estimates on the magnitude of food loss in the United States are timely. This 

report updates the ERS loss estimates to 2010 and extends previous ERS estimates and publications 

on food loss in several important ways, such as incorporating new consumer-level loss assumptions 

and providing calorie estimates for the first time.

We used prices consumers would have paid, on average, for foods if bought at retail. In total, we 

compiled estimates of the amount and value of food loss for more than 200 individual foods in the 

Loss-Adjusted Food Availability (LAFA) data and then aggregated these values to estimate the total 

value of food loss at both the retail and consumer levels in the United States in 2010 and the value 

by food group. The analytical method for calculating the amount, value, and calories of food loss for 

each commodity in the LAFA data consisted of five key steps. 

First, we identified the individual commodities in the LAFA data for our analysis by each food 

group. In particular, we identified 62 fresh and processed fruit, 67 fresh and processed vegetables, 

and 86 other individual foods in the LAFA data for our analysis (see Appendix Box). The LAFA 

data can be accessed online through Excel spreadsheets that provide all of the current loss assumptions and the structure of the calculations for each food in the data series. More information on the 

LAFA data is summarized on the ERS website (ERS, 2011). 

Second, we estimated national average retail prices in 2010 using Nielsen Homescan data for each 

individual commodity in the LAFA data series consumed at home in 2010. This method for determining average prices was used in previous research (e.g., Reed et al. (2004), Stewart et al. (2011), 

Buzby et al. (2011), and Buzby and Hyman (2012)). Members of the Homescan consumer panel in 

60,648 households reported the foods they purchased, the quantities they bought, and the prices they 
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Commodity Coverage in the 2010 Loss-Adjusted Food 

Availability Data

The “Dairy” spreadsheet has 34 commodities—Plain whole milk, Plain 2-percent milk, Plain 1-percent milk, 

Skim milk, Whole flavored milk, Low-fat flavored milk, Buttermilk, Refrigerated yogurt, Cheddar cheese, 

Other American cheese, Provolone cheese, Romano cheese, Parmesan cheese, Mozzarella cheese, Ricotta 

cheese, Other Italian cheese, Swiss cheese, Brick cheese, Muenster cheese, Blue cheese, Other miscellaneous 

cheese, Regular cottage cheese, Low-fat cottage cheese, Regular ice cream, Low-fat ice cream (ice milk), 

Frozen yogurt and other miscellaneous frozen products, Evaporated and condensed canned whole milk, 

Evaporated and condensed bulk whole milk, Evaporated and condensed bulk and canned skim milk, Dry 

whole milk, Nonfat dry milk, Dry buttermilk, Dairy share of half-and-half, and Dairy share of eggnog. 

The “Fats” spreadsheet has 15 commodities—Added fats and oils, Butter, Margarine, Lard, Edible beef tallow, 

Shortening, Salad and cooking oils, Other edible fats and oils, Dairy fats, Fat share of half and half, Light 

cream, Heavy cream, Sour cream, Cream cheese, and Fat share of eggnog. 

The “Fruit” spreadsheet has 62 commodities—Fresh oranges, Fresh tangerines, Fresh grapefruit, Fresh 

lemons, Fresh limes, Fresh apples, Fresh apricots, Fresh avocados, Fresh bananas, Fresh blueberries, Fresh 

cantaloupe, Fresh cherries, Fresh cranberries, Fresh grapes, Fresh honeydew, Fresh kiwifruit, Fresh mangoes, 

Fresh papaya, Fresh peaches, Fresh pears, Fresh pineapple, Fresh plums, Fresh strawberries, Fresh watermelon, Canned apples and applesauce, Canned apricots, Canned sweet cherries, Canned tart cherries, Canned 

peaches, Canned pears, Canned pineapple, Canned plums, Canned olives, Frozen blackberries, Frozen blueberries, Frozen raspberries, Frozen strawberries, Other frozen berries, Frozen apples, Frozen apricots, Frozen 

sweet cherries, Frozen tart cherries, Frozen peaches, Frozen plums and prunes, Other frozen fruit, Dried 

apples, Dried apricots, Dried dates, Dried figs, Dried peaches, Dried pears, Dried plums, Raisins, Grapefruit 

juice, Lemon juice, Lime juice, Orange juice, Apple juice, Cranberry juice, Grape juice, Pineapple juice, and 

Prune juice.

The “Grain” spreadsheet has 9 commodities—White and whole wheat flour, Durum flour, Rice, Rye flour, 

Corn flour and meal, Corn hominy and grits, Corn starch, Barley products, and Oat products. 

The “Meat” spreadsheet has 24 commodities—Beef, Veal, Pork, Lamb, Chicken, Turkey, Fresh and frozen 

fish, Fresh and frozen shellfish, Canned salmon, Canned sardines, Canned tuna, Canned shellfish, Other 

canned fish, Cured fish, Eggs, Peanuts, Almonds, Hazelnuts (filberts), Pecans, Walnuts, Macadamia nuts, 

Pistachio nuts, Other tree nuts, and Coconut. 

The “Sugar” spreadsheet has 6 commodities—Cane and beet sugar, High fructose corn sweetener, Glucose, 

Dextrose, Honey, and Edible syrups. 

The “Vegetable” spreadsheet has 67 commodities—Fresh artichokes, Fresh asparagus, Fresh bell peppers, 

Fresh broccoli, Fresh Brussels sprouts, Fresh cabbage, Fresh carrots, Fresh cauliflower, Fresh celery, Fresh 

collard greens, Fresh sweet corn, Fresh cucumbers, Fresh eggplant, Fresh escarole and endive, Fresh garlic, 

Fresh kale, Fresh head lettuce, Fresh Romaine and leaf lettuce, Fresh lima beans, Fresh mushrooms, Fresh 

mustard greens, Fresh okra, Fresh onions, Fresh potatoes, Fresh pumpkin, Fresh radishes, Fresh snap beans, 

Fresh spinach, Fresh squash, Fresh sweet potatoes, Fresh tomatoes, Fresh turnip greens, Canned asparagus, 

Canned snap beans, Canned cabbage (sauerkraut), Canned carrots, Canned sweet corn, Canned cucumbers 

(pickles), Canned green peas, Canned mushrooms, Canned chile peppers, Canned potatoes, Canned toma-
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paid. The data include purchases at retail outlets—such as supercenters, grocery stores, farmers’ 

markets, mass merchandisers, and drugstores—but not at restaurants or other foodservice outlets. 

This means that foods consumed away from home are not included in our estimated prices. Nielsen 

further provides projection factors that allow data users to estimate what all households across the 

United States paid for foods and the quantities they bought. 

Third, as a validation step, when our estimates fell outside of the expected range, we examined the 

data more closely to determine if there had been computational errors or outliers. Additionally, it is 

likely that some households made mistakes when reporting information to Nielsen or, because the 

recording process is time-consuming, failed to report some purchases. However, validation studies 

confirm the suitability of Homescan data. For example, Einav et al. (2008) found that errors in 

the Homescan data are of the same order of magnitude as reporting errors in major governmentcollected data sets. Moreover, their findings suggest that errors in Homescan data are unlikely to 

affect estimates of average prices paid by all households.

Fourth, we multiplied the estimated price by the annual amount of food loss for each individual 

food in the LAFA data series at the retail and consumer levels. The amounts of loss for each type of 

commodity were calculated by multiplying per capita quantities available at each level by the corresponding food loss assumptions and by the U.S. population on July 1, 2010 (309.75 million). We then 

estimated the total value of losses by summing individual valuations over each commodity group in 

the LAFA data series.

Fifth, we estimated the number of calories representing food loss in 2010 for each commodity in the 

LAFA data series. One strength of this data series is that it estimates the calories available for each 

commodity in a given year. Using this information with the retail- and consumer-level loss estimates, 

we were able to estimate the number of calories from the food supply at both levels that went uneaten.

We basically followed the same steps as used in Buzby and Hyman (2012) and Buzby et al. (2011), 

with a few exceptions:

1. For five fresh vegetables, we used specific consumer price indexes (CPIs) to inflate the 2006 

Nielsen fresh vegetable prices to 2010 prices [2006 was the most recent year available]. In 

particular, we used the lettuce CPI for fresh romaine and leaf lettuce. For fresh broccoli, sweet 

toes, Other canned vegetables, Frozen asparagus, Frozen snap beans, Frozen broccoli, Frozen carrots, Frozen 

cauliflower, Frozen sweet corn, Frozen green peas, Frozen lima beans, Frozen potatoes, Frozen spinach, 

Miscellaneous frozen vegetables, Dehydrated onions, Dehydrated potatoes, Potato chips and shoestring potatoes, Dry peas and lentils, Dry edible beans, Dry black beans, Dry great northern beans, Dry lima beans, Dry 

navy beans, Dry pinto beans, Dry red kidney beans, and Other dry beans. 

Total: 215 commodity categories.1 Some of these categories, such as “other frozen fruit,” include more than 

one commodity so there are more than 215 commodities in total represented in the Food Availability Data 

System.

1Two commodities (eggnog; half-and-half) were split into a dairy share and a fat share. To avoid double counting, we reduce the 

sum (217) of the above groups to 215.

Source: Computed by Jeanine Bentley, ERS, August 6, 2012.
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corn, cucumbers, and spinach, we used the CPI for “other fresh vegetables,” which is for fresh 

vegetables other than for potatoes, lettuce, and tomatoes. In the earlier two articles, we inflated 

the 2006 fresh prices with the CPI value for all fresh vegetables from the U.S. Bureau of Labor 

Statistics (BLS).

2. For fresh apricots, there were enough observations of fresh apricots in the 2010 Nielsen 

Homescan data that there was no need to adjust from an earlier price as in Buzby et al. (2011). 

3. For veal, Buzby and Hyman (2012) used fresh veal only from 2008 Nielsen data to estimate the 

2008 price for veal. In this report, we used both fresh and frozen veal together.

Limitations of the Data

As with the basic Food Availability data, the Loss-Adjusted Food Availability data series does not 

measure actual consumption or the quantities ingested. This is because neither series is based on 

direct observations of individual intake. Therefore, data are not available by socioeconomic, demographic, and geographic (State, regional, or city) breakdowns, and in most cases, it is not known if 

such data exist. Detailed documentation is available on ERS’s website (ERS, 2012a).

The limited ability of researchers to measure food loss accurately suggests that actual loss rates may 

differ from the assumptions used in this data series. In general, the underlying estimates of farm-toretail (not measured in this report), retail, and consumer-level food losses used in the Loss-Adjusted 

Food Availability data series may be understated or overstated due to limitations in the underlying 

published studies. Food loss, particularly at the consumer level, is by nature difficult to measure 

accurately. Participants in household surveys on food waste tend to be highly “reactive”—changing 

their behavior during the survey period instead of acknowledging how much food they typically 

discard—or misstating their true levels of product discard (Gallo, 1980). Studies that observe food 

loss by inspecting landfill garbage are also prone to errors. Such studies are not nationally representative and may not account for food fed to pets and other animals, put in garbage disposals, or 

composted at home (Gallo, 1980). Plate waste studies, such as for schoolchildren at lunchtime 

(Buzby and Guthrie, 2002), often target only a slice of the total U.S. population, and the findings 

cannot be easily or reliably extrapolated to other demographic categories.

Food loss for individual commodities, in particular, may vary over time. There are good reasons 

why food loss for a particular commodity could increase or decrease. On the one hand, new food 

technologies and food production/processing practices may reduce food losses over time (e.g., 

improvements in the preservation of bread, nanotechnologies in food packaging to reduce spoilage) 

(Buzby, 2010). On the other hand, food loss for a particular commodity could increase, such as from 

greater trimming of food to cut down on fats. However, the ERS data currently do not capture most 

of these changes in food loss because for most commodity- and food-loss-level pairings, the same 

loss assumption is applied throughout the span of the data in the LAFA data series (e.g., the retaillevel loss estimate for fresh apples is the same 8.6 percent over 1970-2011). The exception is that the 

retail-level loss estimates for beef account for greater trimming of fat over time. 

Additionally, ERS’s LAFA data series uses well-documented data for inedible loss assumptions, but 

these amounts are not consistently applied to the data series in the same step or level. In particular, 

the data series removes the inedible share for fresh fruits, fresh vegetables, and eggs at the consumer 

level while the inedible shares for meat, poultry, and fish are removed at the primary-to-retail level, 
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so that these estimates in the LAFA data series are presented in boneless weight.18 What this means, 

in effect, is that for fresh fruits, fresh vegetables, and eggs, the inedible share is included at the retail 

weight but then subtracted prior to the consumer weight.

Despite the limitations, both the per capita Food Availability data and the per capita Loss-Adjusted 

Food Availability data are useful for economic analyses because they serve as indirect measures of 

trends in food consumption and food loss. In other words, both data series provide an indication of 

whether Americans, on average, are consuming more or less of various foods over time. As we have 

seen in this report, the Loss-Adjusted Food Availability series also provides estimates of food loss 

by commodity, by food group, and in total.

18In the ERS Food Availability Data system, the weight at the primary distribution level is dictated for each 

commodity by the structure of the marketing system and data availability. In most cases, the primary weight 

is the farm weight. For meat and poultry, the primary weight is the carcass weight, which is then converted to 

a boneless weight when accounting for farm-to-retail losses.
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