Approximately 96 billion gallons of water per day (bgd) (~0.36 cubic kilometers) are consumed for agricultural irrigation in the United States, representing roughly 83% of total national water consumption (116 bgd or 0.42 cubic kilometers) across all end-use categories [1
]. Meanwhile, it is estimated that around 40% of food produced in the U.S. is lost or wasted at some point along the supply chain [2
]. Combining these two observations together suggests that more than 30% of all the water consumed in the U.S. is ultimately wasted as the water embedded in food products that go uneaten.
Studies seeking to quantify and characterize the amount of food loss and waste (FLW) at various stages of the food supply chain have been increasing in recent years [3
]. Part of the momentum behind these studies is the growing recognition that FLW represents significant economic losses, as well as the inefficient allocation of resources (land, water, energy, fertilizers, and other material inputs) to produce food that is never consumed by humans [4
]. One of the challenges to researchers in this topic area is applying a consistent definition of food loss and waste. Some researchers suggest that food waste should only be defined as the material that ends up in a landfill where it has zero productive value [5
], while others take a broader definition to include all edible food that is intended for human consumption but ultimately does not get eaten [6
]. “Food loss” and “food waste” are often further distinguished from each other, where “food loss” may refer to only upstream losses in the supply chain, from production to delivery to the retailer, while “food waste” refers to food discarded at retail through the point of consumption (e.g., homes, restaurants, and institutions) [7
Despite the growing number of FLW studies, estimating food losses in agricultural production remains a significant challenge as losses vary significantly by crop type and from season to season [8
]. There are four main drivers of crop loss in the field: weather damage, disease and pests, market conditions, and grading/sorting of produce to meet buyer standards. Weather damage can occur as a result of extremes in temperature (both heatwaves and frost/freezing), precipitation (e.g., drought, excess moisture, flooding, and hail/snow), and other extreme events (e.g., hurricane, fire, lightning) [10
]. Disease and pests include various forms of plant disease, including fungal infections [10
], as well as damage by insects, rodents, birds, and other pests [7
]. Market conditions can prevent the harvest of entire crop areas if the crop price falls below harvesting costs, the grower is unable to secure adequate labor for harvest, or the downstream buyer changes or cancels an order [9
]. Finally, during harvest, a significant volume of product may be culled or out-graded to improve the overall quality of the product (size, shape, color, etc.), as well as increase the probability that it will actually reach its intended market in terms of ripeness and perishability [11
The relationship between FLW and the upstream water inputs for food production can be conceptualized as the “water footprint” of FLW. The water footprint, developed by Hoekstra and Chapagain [12
], is a mature indicator in the field and has been applied to assess and compare the amount of water embedded in the goods and services produced and consumed by society. The water footprint concept includes three categories of water use: “blue” water representing the use of surface and ground water, “green” water representing the direct utilization of rain water by land-based ecosystems (including rain-fed agriculture), and “gray” water representing the amount of water required to sufficiently dilute pollutants before release into the environment [13
A number of studies have estimated water footprints for geographic regions of varying scales, including global studies [14
], large regional studies (e.g., the European Union [15
]), national studies (e.g., Morocco [16
]), as well as urban systems (e.g., an analysis of 65 cities and metropolitan areas [17
]). Other studies have explored individual economic sectors, e.g., bioenergy [18
], tourism [19
], and agricultural products [20
]; specific institutions, e.g., the Barilla food company [21
] and the exchange-listed companies in the Netherlands by [22
]; as well as single products, e.g., meat products [23
] and even a very specific Brazilian soap bar [24
The water footprint approach has been applied specifically to FLW in a number of recent reports and papers. In 2012, Kummu et al. [25
] estimated the global blue water footprint of FLW to be approximately 46 trillion gallons (~174 cubic kilometers) per year, representing about 24% of the total water used for global food production. On a per unit basis, a collaborative study between the Waste and Resources Action Programme (WRAP) and the World Wide Fund for Nature (WWF-UK) estimated that 750 cubic meters (~198,000 gallons) of water is wasted per metric ton of avoidable food waste in the United Kingdom [26
]. A large-scale study of consumer food waste in the European Union (EU) estimated the per capita blue water footprint of food waste to be 27 L per day (~7.1 gallons/day) [27
In terms of FLW and global agricultural production, roughly 22% of produced cereals, 39% of fruits and vegetables, and 33% of roots and tubers are lost across various stages of the food supply chain, including consumption [25
]. Based on this data, our team narrowed our focus on the higher loss categories of fruits/vegetables as opposed to cereal crops. We further narrowed the focus to potatoes specifically, since it is the largest fruit/vegetable crop by acreage in the United States [28
]. Potatoes also had the greatest breadth and depth of data available from the three national-level data sets on pre-harvest crop loss that we identified, the United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) Census of Agriculture [29
] and Survey Program [30
], and the USDA Risk Management Agency (RMA) [10
]. Estimates of in-field potato losses at harvest were collected from the NASS Objective Yield (OY) survey [31
]. After reviewing and consolidating all of the in-field loss data, we estimate the blue water footprint of the potato losses in the United States using state-specific estimates of irrigated water application from the NASS Farm and Ranch Irrigation Survey (FRIS) [32
]. These data sources are described in further detail in the Materials and Methods section below.
As described in the previous section, there is no single data source that provides a clear estimate of in-field crop losses in the United States, so multiple data sources needed to be leveraged and integrated for this study. The USDA NASS survey data provides excellent coverage of farm production data with data for every county since the beginning of the 20th century. While the NASS survey for potatoes enables estimation of pre-harvest losses by providing estimates of both acres planted and acres harvested, these variables are not collected consistently across all crops types, which currently limits broader analysis of in-field crop types. The USDA RMA data provides additional dimension to pre-harvest losses by identifying drivers of the crop losses, but these data are only available more recently (since 2001) and only represent insured (and claimed) losses in the U.S. and not total losses. USDA NASS OY survey data provide estimates of losses at harvest, but is limited to the last five years, only to potatoes in the vegetable category, and only for the seven selected fall-producing states. Finally, the NASS FRIS data provides an estimate of water applied for potatoes, but the survey is only collected every five years and there is only one year available so far (and once again, only for potatoes in the vegetable category).
Despite the limitations of each of these data sources, in combination they present sufficient information for a high-level assessment of the embedded water associated with the in-field losses of potato production in seven major states in the United States. We found that 84.6 Mm3 of water is associated with in-field potato losses in the seven states of our study: Idaho, Washington, Wisconsin, North Dakota, Oregon, Minnesota, and Maine. The highest total blue water footprint (48.5 Mm3) and intensity of water use embedded in losses relative to total potato production was observed in Idaho (7.07 m3/tonne), which was largely driven by the large amount of both pre-harvest and harvest losses for potatoes as well as its heavy reliance on irrigated potato cultivation. Harvest losses were consistently higher than pre-harvest losses in all states, so efforts to reduce losses have the most potential for absolute reduction by targeting this category. Further, reduction in harvest losses might be more achievable since weather-based pre-harvest losses may be harder to mitigate, and there does seem to be some potential to direct smaller potatoes that are currently sorted out into the marketplace.
The broad range of blue water footprint intensities for in-field potato losses from state to state suggests that some states have a disproportionate amount of water embedded in their losses and perhaps could strive to be more efficient or pursue other crops. As discussed before, there may be limited opportunity to reduce pre-harvest losses driven by weather that is largely outside the control of the grower. For harvest losses, perhaps the acceptance of smaller potatoes by the market could lead to significantly lower quantities of harvest losses. In an anecdotal discussion with an Extension Specialist at Michigan State University, we learned that smaller potatoes may even be more desirable for snack-size potato chip bags where lower breakage has been observed for that particular packaging [37
]. Additional opportunities may exist in secondary markets, where smaller or misshapen potatoes may be sold as “ugly” or “imperfect” produce at a discount to the consumer, or sold to processors where shape and size do not matter, such as the expanding production of potato protein isolate within the plant-based protein market [38
The final lever for reducing the embedded water in the potato losses is to reduce the amount of water applied in irrigated potato cultivation, but evaluating alternative irrigation technologies and strategies for potato cultivation is beyond the scope of this paper.
Data collection in this area of study has been improving over time, and without recent additions to USDA surveys we would not have been able to complete this paper. That said, there are still many improvements to be made. We were only able to complete this analysis for potatoes as it was the only crop that had all of the necessary data readily available. Further, many of the data points used in this paper were only recently collected. This leaves any analysis of trends and causal relationships difficult or impossible to complete. For instance, the FRIS was only conducted for potatoes in 2013 as a supplement for the Census of Agriculture. As a result, no analysis could be performed on important topics such as: how weather patterns affect water application or how irrigation practices changing over time. We applaud the expansions in data collection that have been made, and hope that more robust and sustained data gathering will continue to enable further analysis by crop type and over time.
As momentum continues to build around the economic and environmental consequences of food loss and waste within both the research community and with policymakers, the improved availability and quality of data on the flows of loss and waste through the supply chain will become more and more important. Given the unique availability of data on this topic specifically relevant to potatoes, perhaps this crop can serve as the model to enhance and harmonize USDA farm-level data collection efforts on additional crops and regions moving forward. This would enable similar studies of not just embedded water, but other critical economic and natural resource investments in agriculture that are lost with forfeited crop production. Further, the importance of understanding these linkages and impacts has only increased in the dynamic context of climate change that may shift the weather-based drivers of loss over time, as well as the availability and reliability of regional resources, including water supplies.