ArticlePDF AvailableLiterature Review

Missing Food, Missing Data? A Critical Review of Global Food Losses and Food Waste Data


Abstract and Figures

Food losses and food waste (FLW) have become a global concern in recent years and emerge as a priority in the global and national political agenda (e.g., with Target 12.3 in the new United Nations Sustainable Development Goals). A good understanding of the availability and quality of global FLW data is a prerequisite for tracking progress on reduction targets, analyzing environmental impacts, and exploring mitigation strategies for FLW. There has been a growing body of literature on FLW quantification in the past years; however, significant challenges remain, such as data inconsistency and a narrow temporal, geographical, and food supply chain coverage. In this paper, we examined 202 publications which reported FLW data of 84 countries and 52 individual years from 1933 to 2014. We found that most existing publications are conducted for a few industrialized countries (e.g., UK and U.S.) and over half of them are based only on secondary data, which signals high uncertainties in the existing global FLW database. Despite these uncertainties, existing data indicate that per-capita food waste in the household increases with an increase of per-capita GDP. We believe more consistent, in-depth, and primary-data-based studies, especially for emerging economies, are badly needed in order to better inform relevant policy on FLW reduction and environmental impacts mitigation.
Content may be subject to copyright.
Missing Food, Missing Data? A Critical Review of Global Food Losses
and Food Waste Data
Li Xue,
Gang Liu,*
Julian Partt,
Xiaojie Liu,
Erica Van Herpen,
Åsa Stenmarck,
Clementine OConnor,
Karin O
and Shengkui Cheng
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101 Beijing, China
University of Chinese Academy of Sciences, 100049 Beijing, China
SDU Life Cycle Engineering, Department of Chemical Engineering, Biotechnology, and Environmental Technology, University of
Southern Denmark, 5230 Odense, Denmark
Anthesis Group, Oxford OX4 1RE, United Kingdom
Marketing and Consumer Behavior Group, Wageningen University, Wageningen 6708 PB, The Netherlands
IVL Swedish Environmental Research Institute, 114 27 Stockholm, Sweden
World Resources Institute, Washington, DC 20002, United States
RISE Bioscience and Materials, Agrifood and Bioscience, 223 70 Lund, Sweden
SSupporting Information
ABSTRACT: Food losses and food waste (FLW) have become a global concern in recent
years and emerge as a priority in the global and national political agenda (e.g., with Target
12.3 in the new United Nations Sustainable Development Goals). A good understanding
of the availability and quality of global FLW data is a prerequisite for tracking progress on
reduction targets, analyzing environmental impacts, and exploring mitigation strategies for
FLW. There has been a growing body of literature on FLW quantication in the past years;
however, signicant challenges remain, such as data inconsistency and a narrow temporal,
geographical, and food supply chain coverage. In this paper, we examined 202 publications
which reported FLW data for 84 countries and 52 individual years from 1933 to 2014. We
found that most existing publications are conducted for a few industrialized countries (e.g.,
the United Kingdom and the United States), and over half of them are based only on
secondary data, which signals high uncertainties in the existing global FLW database.
Despite these uncertainties, existing data indicate that per-capita food waste in the
household increases with an increase of per-capita GDP. We believe that more consistent,
in-depth, and primary-data-based studies, especially for emerging economies, are badly needed to better inform relevant policy on
FLW reduction and environmental impacts mitigation.
Food losses and food waste (FLW) occur throughout the food
chain from farm to fork. FLW has become a worldwide concern
in recent years and is widely identied as a key barrier to global
sustainability due to its adverse impacts on food security,
natural resources
(e.g., land, water, and energy), environment
(e.g., greenhouse gas emissions), and human health
(e.g., toxic
emissions from incineration). Consequently, reduction of FLW
emerges as a priority on the global and national political
agenda. For example, the United Nations have adopted a
specic target in the recently released Sustainable Development
Goals (SDG) to halve per-capita global food waste at the retail
and consumer levels and reduce food losses along production
and supply chains by 2030 (Target 12.3).
The European
and the United States
have consequently adopted this
target, and the African Unions 2014 Malabo Declaration also
includes a commitment to halve the current levels of post-
harvest losses by the year 2025.
In response to the increasing public concerns and political
attention on FLW, the past decades have seen a growing body
of literature on the quantication of FLW across the food
supply chains at global, regional, and national levels. For
example, the Food and Agriculture Organization (FAO) of the
United Nations estimated that roughly one-third of food
produced for human consumption (or 1.3 billion tons) was lost
or wasted globally.
The carbon and water footprint of this
signicant amount of FLW were estimated to be 4.4 gigatons
(or 8% of the worlds total) of CO2equivalent
and 250 km3
of blue water,
respectively. It would also mean 1.4 billion
hectares (or 28% of the worlds total) of agriculture land use
and an economic cost of about 750 million U.S. dollars (USD),
Received: January 23, 2017
Revised: May 3, 2017
Accepted: May 11, 2017
Published: May 11, 2017
Critical Review
© 2017 American Chemical Society 6618 DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
which equals the GDP of Turkey.
Many other studies at the
regional or individual country levels have also highlighted a
similar large scale of FLW (though not always directly
comparable) and its profound impacts on food security,
environment, and economic development. For example, the
EU-28 generate approximately 100 million tons of FLW
annually in which households contribute the most (45%).
to its member states, the U.K. households alone wasted about
7.2 million tons of food in 2012, over 60% of which was
identied as avoidable.
The amount of food thrown away
from households in Finland, Denmark, Norway, and Sweden
account for 30%, 23%, 20%, and 1020% of food bought,
Roughly 1/3of the edible calories produced in
Switzerland is wasted, and the household is the largest
Other industrialized countries show a similar
trend too. For example, the per-capita FLW in the United
States increased by about 50% from 1979 to 2003.
Over 4.2
million tons of FLW is disposed to landll in Australia every
year, costing over 10.5 billion USD only in waste-disposal
About 27 billion USD of food is wasted throughout
the food supply chains in Canada annually, equivalent to 40%
of all food produced and 2% of Canadas GDP.
A few national agencies and intergovernmental organizations
have been working on FLW quantication continuously over
the past decades. In particular, the FAO has released several
inuential reports on FLW quantication on a global level.
The United States Department of Agriculture Economic
Research Service (USDA-ERS) has created the Loss-Adjusted
Food Availability Data Series since 1997, reporting over 200
commodities by three stages (farm to retail, retail, and
consumer) of losses in terms of quantities, values, and
The Waste and Resources Action Programme
(WRAP) has issued a range of reports on FLW in the supply
chain, household, and food service in the United Kingdom
since 2007.
More recently, stakeholders from academia, industry, and
governmental and nongovernmental organizations have started
to join eorts in research projects and working groups for FLW
quantication and method standardization. For example, the
European Commission funded projects Food Use for Social
Innovation by Optimising Waste Prevention Strategies
(FUSIONS)(20122016) and Resource Ecient Food
and dRink for the Entire Supply cHain (REFRESH)(2015
2019) have issued a series of publications, covering various
aspects of FLW denition, quantication, and mitigation and
valorization strategies.
In June 2016, a partnership of
leading international organizations (e.g., World Resources
Institute, FAO, WRAP, United Nations Environment Pro-
gramme, and World Business Council for Sustainable Develop-
ment) launched a rst-ever global standard to measure FLW.
Despite these growing eorts on the quantication of FLW
and standardization of methodologies, several researchers have
also raised concerns on the data deciency and inconsistency
and called for better and more measurements on FLW.
summary, we argue that the existing global FLW data suer
from the following major gaps.
Their spatial coverage is narrow. Most existing studies on
FLW are conducted in industrialized countries. For
example, there are numerous publications quantifying
FLW in the United States
and Sweden;
on the
contrary, only a handful of studies illustrate FLW in low-
income countries, such as Nepal,
the Philippines,
and countries undergoing rapid dietary
transition, such as China, Brazil, and India.
There is an unbalanced focus on the dierent stages
along the food supply chain. There are a large number of
studies on food waste at the retailing and consumer
(mainly in industrialized coun-
tries, e.g., the United States), while there are fewer
studies addressing the immediate postharvest losses
(mainly in a few developing countries, e.g., India
and Vietnam
Some available data are outdated but are still used. Due
to lack of more recent data, researchers have to fall back
on older data. For example, data of the 1980s and 1990s
from the same reference were used in two publications
(published in 2005 and 2010, respectively) as the current
postharvest FLW of fresh fruits and vegetables in Egypt
and Venezuela.
There is inadequate rst-hand data and a number of
studies have to rely on data derived from literature. For
example, many studies have frequently quoted data
reported in the 2011 FAO report,
which may not
be representative or accurate for some countries and
(e.g., household food waste data in Asia
and Africa do not have a single measured data point in
this report). Data in the African Postharvest Losses
Information System (APHLIS) have also been widely
used for postharvest FLW analyses elsewhere.
The system boundary and methods as well as denition
of FLW used vary in dierent studies, which make
systematic comparison and verication of FLW data
between countries, stages, and commodities often
dicult. Thus, any extrapolation based on the existing
data and discussion on relationship between FLW and
related socioeconomic, environmental, and technological
aspects would also be uncertain.
A good and clear understanding of the availability and quality
of global FLW data is of particular importance. First, it is a
prerequisite of benchmark progress toward the global SDG
Target 12.3 and national FLW reduction targets and of
assessing the eectiveness of interventions. Second, it would
help to raise awareness, explore mitigation strategies, and
prioritize eorts on FLW prevention and reduction. Third,
better data would enable verication and comparison between
countries, food supply chains, and commodities and thus help
identify patterns and driving factors of FLW generation. Fourth,
it provides a necessary basis for further analysis of the social,
economic, and environmental impacts of FLW.
In this paper, we aim to provide a critical overview of all the
existing FLW data in the current literature. We will assess their
availability, quality, methods of measurement, and discuss their
patterns and implications for future work. A spreadsheet
database containing all the collected FLW data is supplemented
in the Supporting Information, which we believe provides a
fundamental physical database for further analyses on environ-
mental impacts and appropriate mitigation strategies of FLW.
We aim to answer the following questions in this review:
What are the bibliometric characteristics of existing
literature on FLW quantication?
What are the methods used for FLW measurement, and
what are their advantages and disadvantages?
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
What are the patterns of FLW generation among
countries, food supply chains, and commodities and
over time?
What are the implications for further research in the
2.1. System Denition. Food Losses and Food Waste.
FLW occurs at each stage throughout the food supply chain.
Distinctions between the terms food losses and food waste,
edible and inedible food waste, and avoidable and nonavoidable
food waste are sometimes made in the literature. These
distinctions were not quantitatively considered in our
comparison due to lack of consistencies and transparencies in
the reviewed literature. For example, many studies dierentiate
food loss and food waste according to the FAO,
which denes
food loss as the decrease in quantity or quality of foodand
food waste as part of food loss that has been left to spoil or
expire as a result of negligence by the actor (predominantly, but
not exclusively, the nal consumer). Food waste is usually
connected to deliberate discarding or alternative (nonfood) use
of food (e.g., animal feed) that is safe and nutritious for human
consumption. The reviewed data do not allow us to distinguish
between food loss and waste; thus, in this paper, we use FLW
to refer to the combined amount of food loss and waste.
Food Supply Chain. FLW can be related to six main
processes as shown in Figure 1 (note that not all stages are
relevant to all products; for example, fresh vegetables may be
supplied directly to market). We further categorized FLW as
three types: farm losses and waste (during agricultural
production and harvesting), postharvest losses and waste
(during postharvest handling and storage, manufacturing,
distribution, and retailing), and consumer waste (both in-
household and out-of-home).
Food Commodity Groups. A total of 10 groups of food
commodities were dened according to the classication used
by the FAO and characteristics of the data in the literature: (1)
cereal and cereal products (e.g., wheat, maize, and rice); (2)
roots and tubers (e.g., potatoes, sweet potatoes, and cassava);
(3) oilseeds and pulses (e.g., peanuts, soybeans, and olives); (4)
fruits; (5) vegetables; (6) meat; (7) sh and seafood; (8) dairy
products; (9) eggs; and (10) others or not specied.
Geographical and Temporal Boundary. We included all of
the reported FLW data at the global, regional, and national
levels and from as early as possible until December 2015 in the
literature. The countries were grouped as medium/high-income
countries and low-income countries (see Table S2) based on
per-capita GDP and the grouping principle of FAO.
2.2. Literature Selection. To ensure a broad coverage of
literature containing FLW data, both Web of Science and
Google Scholar were used in the literature search. In addition,
we also explored the grey literature, i.e., reports prepared by
academic institutions, industrial associations, and governmental
and nongovernmental organizations, considering their signi-
cant amount in recent years. Food wasteor food losses
were used as keywords in the search of titles of publications,
and only articles published in English by December 2015 were
ltered (more details in section 1 of the Supporting
To further ensure the relevance of the selected publications,
we reviewed the abstracts, keywords, and method details of all
the publications to screen out articles that contained data (e.g.,
weight and monetary values) on FLW for at least one food
commodity, one food supply stage, and one region or country.
Finally, 202 publications form the body of literature that we
reviewed and examined in depth in this analysis.
2.3. Data Extraction and Treatment. The compiled FLW
data were measured by dierent metrics, e.g., by physical
weight, caloric value, or by monetary value. They were also
reported in several ways: (i) single values, (ii) values in a range,
or (iii) mean value or mean values with a variation. These
values were either in absolute terms or as percentages. All of
these dierences were considered in our extraction of data from
the literature (details are shown in the Supporting Informa-
Whenever possible, comparison and trend analysis of data by
physical weight (in terms of both percentage and absolute
values) were conducted across countries and over time and by
food commodity. To facilitate the comparison, original data
were further processed as follows:
If the original data points were reported in a range, the
arithmetic averages were rst determined based on the
minimum and maximum values. Furthermore, global
median values were generated and used in the
comparison of per-capita farm FLW and postharvest
FLW among dierent food commodities because median
values are not strongly aected by extreme values
(compared to average values) and thus might be more-
representative in the comparison. Consumer waste was
usually reported as the weight of cooked food, which was
kept in the database and comparison.
The values reported as the total amount of FLW in a
region or country were divided by their corresponding
population in the same year, for the convenience of
comparison on a per-capita level. When the year of
estimation was not specied, 2 years before the year of
Figure 1. Food supply chain for FLW used in this review. Note that
we put wastealongside lossesfor the farm and postharvest stages
because some of the losses in these stages are arguably wastefuland
avoidable, which makes it dicult to distinguish between loss and
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
publication was assumed as a reference for population
and per-capita GDP. Population statistics and GDP data
(in current USD) were obtained from the World Bank.
We introduced a food losses and food waste rate
(FLWR) for each food supply stage, which was dened
as the proportion of FLW at each stage of the food
supply chain to the amount of total food initially
produced (reference ow, corresponding to a ctive
output of 100% of the amount produced). FLWR was
calculated by considering the proportion of FLW across
each single stage (see Figure 1), as shown below:
rriFLWR (1 )( 2)
where rirepresents the proportion of FLW at the stage to be
calculated (between 0 and 1), and rjrepresents the proportion
of FLW at the previous stages of the food supply chain. Note
that the FLWRs are additive, while the proportion of FLW at
each stage (r) are not additive because the mass ow is
successively decreasing. For the reference stage (i= 2) the r(i1)
is set to 0. The proportion of FLW at individual stages, r, was
derived from the reviewed literature (either directly or by
dividing the quantity of FLW reported in the literature by total
production reported in the FAOSTAT).
3.1. Bibliometric Analysis of Literature on FLW
Quantication. Type of Publications. The 202 reviewed
publications were composed of 5 types: peer-reviewed journal
articles (53.5%), reports (35.6%), PhD and master theses
(5.9%), conference proceedings (3.0%), and book chapters
(2.0%). The 108 journal articles were published in 69 dierent
journals, covering a wide range of disciplines, and about 45% of
them were published in 10 journals (in descending order in
terms of number of published articles), i.e., Waste Management
(15.7%), Waste Management & Research (7.4%), Resources,
Conservation and Recycling (5.6%), Food Policy (4.6%),
Journal of Cleaner Production (2.8%), Environmental Science
& Technology (1.9%), Journal of Industrial Ecology (1.9%),
Journal of Environmental Management (1.9%), Environmental
Science & Policy (1.9%), and Sustainability (1.9%).
Distribution of Countries and Year of Estimation. The
compiled FLW data covered 84 countries (reported 498 times
in total) and 52 individual years (reported 383 times in total)
from 1933 to 2014. This adds up to 2933 rows and 5898 data
points of FLW physical data in the compiled database (one row
represents the entire food supply chain of one food community
in one country or region; see the supplementary spreadsheet).
Figure 2 illustrates the geographical distribution of case
countries and the top 10 countries that have been studied. It
can be seen that most of the existing data were found for the
United Kingdom
and the United States,
both of which accounted for over 10% in terms of reported
times, respectively. Then countries in Northern and Western
Europe, i.e., Sweden,
followed with a share of 5.4%, 4.4%,
and 3.2%, respectively. Figure 3a shows the temporal trend of
the year of estimation (see Figure S1 for the trend in terms of
year of publication). Reported FLW data were found as early as
Figure 2. Geographical distribution of case countries (with the name of top 10 countries) reported in the reviewed literature. The numbers are the
times that individual countries are reported.
Figure 3. (a) Temporal trend of reported FLW data in terms of year of estimation; (b) the number of publications covering dierent food-supply
stages and dierent development levels of countries.
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
1933, and then the number stayed steady and low until 1995.
After 1995, the number went up considerably and over 60%
was seen in the past decade (38.1% from 2006 to 2010 and
25.1% from 2011 to 2014).
Data Coverage along the Food Supply Chain and across
Countries. Figure 3b illustrates the number of publications
covering dierent food supply stages and development levels of
countries (medium- and high-income countries versus low-
income countries). It can be seen that most of the studies have
included the retailing and consumption stages. Household was
covered in almost half (49%) of all the publications, followed
by the retailing stage (35%). However, only a small share
(18%30%) of publications covered the stages between
agricultural production and distribution (agricultural produc-
tion:26.7%;postharvesthandling and storage: 18.8%;
manufacturing: 28.7%; and distribution: 21.8%).
The number of publications on FLW amount of medium-
and high-income countries was substantially higher than that of
low-income countries throughout the food supply chain except
for the postharvest handling and storage stage, for which the
number of publications was the same for both. Publications
covering the retailing and consumption stages were mostly
found for the medium- and high-income countries, with very
few data sources in developing and emerging countries. Low-
income countries showed a clear focus in the early and middle
food-supply stages (especially agricultural production and
postharvest handling and storage).
3.2. Overview, Advantages, and Disadvantages of
Dierent Methods Used for FLW Quantication. Table 1
summarizes methods that were used to quantify FLW in the
reviewed publications. They can be categorized as two groups:
(i) direct measurement or approximation based on rst-hand
data and (ii) indirect measurement or calculation derived from
secondary data.
Direct measurement involves several ways to directly
quantify or estimate the actual amount of FLW:
Weighing: Using weighing scales to measure the total
weight of FLW; usually used in restaurants, hospitals, and
schools; may or may not include compositional analysis
of FLW with each fraction being weighed.
Garbage collection: Separating FLW from other
categories of residual waste containers to determine the
weight and proportion of FLW and from weight data
derived from separate FLW collections; may or may not
Table 1. Description of Advantages, Disadvantages, and Examples of Dierent Methods Used for FLW Quantication
method symbol time cost accuracy objectivity reliability
example of case
countries and regions
food supply
chain reference
direct measurement or approximation
based on rst-hand data
weighing W ••• ••• ••• ••• ••• Portugal P6b Ferreira et
Italy P6b Falasconi et
G••• ••• ••• ••• ••• Austria P6a Lebersorger
Sweden P6a Bernstad et
surveys S •• •• •• •• •• Sweden P5 Gustavsson et
U.K. P1, P2, P3,
Mena et al.
diaries D ••• •• •• •• •• U.K. P6a Langley et
Sweden P6a Sonesson et
records R • • •• •• •• Sweden P5 Eriksson et
Sweden P5 Scholz et al.
observation O •• • U.K. P6b Sonnino et
Italy P6b Saccares et
indirect measurement or calculation
derived from secondary data
modeling M •• • •• United States P6 Hall et al.
EU-27 P1, P2, P3,
P4, P5, P6
Khan et al.
food balance F • • •• ••• •• United States P6 Buzby et al.
global P1, P2, P3,
P4, P5, P6
Gustavsson et
use of proxy
P• • •• ••• •• Austria P5 Lebersorger et
Singapore P6a Grandhi et
use of
L• • •• ••• global P1, P2, P3,
P4, P5, P6
Lipinski et
Denmark P1, P3, P4,
Halloran et
Note: •••, high; ••, medium; , low. Cost includes both economic cost and labor cost of conducting the research. P1: agricultural production and
harvesting; P2: postharvest handling and storage; P3: manufacturing; P4: distribution; P5: retailing; and P6: consumption (including P6a: household
and P6b: out of home).
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
include compositional analysis of FLW. It can be
collected from the curb
or collected by households
at home and handed over to researchers.
Surveys: Collecting information regarding peoples
perceptions or behaviors on FLW through questionnaires
that are answered by a large number of individuals and
face-to-face interview of key stakeholders in this eld. In
these surveys, people can be asked to directly estimate
the amount of food waste in their household, e.g., in
number of portions,
or to estimate the percentage of
food items bought into the household that goes to
Visual tools have sometimes been used to help
people indicate the amount of food waste.
Diaries: Gathering data via keeping a daily record on the
amount and types of FLW for a period of time;
commonly used for households and commercial kitchens.
Households are sometimes provided with weighing scales
to measure the weight of food waste.
Records: Determining the amount of FLW via the
routinely collected information that is not initially used
for FLW record (e.g., warehouse record books, point of
sales data, data from food manufacture regulatory
sources); usually used for the retailing stage and food
manufacture (especially supermarkets and larger food
Observation: Using scales with several points to evaluate
food leftover by visual method or by counting the
number of items to assess the volume of FLW.
Indirect measurement includes methods derived from
existing data of various secondary sources:
Modeling: Using mathematical models based on factors
that aect the generation of FLW to calculate the amount
of FLW.
Food balance: Calculating FLW by using a food balance
sheet (e.g., from FAOSTAT) or human metabolism (e.g.,
relating body weight to the amount of food eaten) based
on inputs, outputs, and stocks along the food supply
Use of proxy data: Inferring quantities of FLW by using
data from companies or statistical agencies (mostly used
for scaling data to produce aggregated FLW estimates).
Use of literature data: Directly using data from literature
or calculating the amount of FLW based on the data
reported in other publications.
Figure 4 illustrates how these methods were used in each of
the 202 publications. The result shows that only a small share
(around 20%; blue colors in Figure 4) of the reviewed
publications has relied on direct measurement or approxima-
tion based on rst-hand data. The remaining majority relied on
indirect measurement or calculation derived from secondary
data (red-yellow colors in Figure 4); over 40% of them were
based only on literature data, and about 1/3used a combination
of literature data with one or two other types of methods in the
quantication, for example, with modeling
or proxy
(indirect measurement) or with weighing or
(direct measurement). For the 138
publications that used literature data (Figure 5), their estimates
often relied on each other and pointed to a handful of
publications; over a quarter of them cited data from the top 10
cited publications, and the number of citations has increased
greatly since 2008. Such a high share of use of secondary data
may signal high uncertainties in the available global FLW
database, especially when the literature data are not
representative but used for a dierent country or a dierent
year than it was collected for originally.
The advantages and disadvantages of dierent methods were
evaluated based on dierent criteria (e.g., time, cost, and
accuracy) listed in Table 1.
Weighing and garbage collection result in relatively
objective and accurate information on FLW. The two
methods may result in a total quantication of FLW (i.e.,
operational data), or they can yield far more granular
data at food product category level. However, these two
methods are more time-consuming and expensive than
other methods and usually can only be conducted when
space is available for sorting food. For example, to
characterize the plate waste in Portuguese hospitals each
year, Ferreira et al. weighed plate waste in almost 8000
meals during 8 weeks by individual items (soup, main
dish, fruit, and bread) in a case hospital.
Of course, the
accuracy of a waste composition analysis depends on
methodological decisions, and various sources of error
have been identied.
In particular, in-home food
waste that is disposed of by other means than curb side
collection (e.g., sink garbage disposals, home compost-
ing, and animal feed) is usually not observed.
Surveys, diaries, records, and observation are other ways
of direct measurement and approximation of FLW data
and are relatively less time-consuming and expensive
comparing to direct weighing. However, they largely
depend on personal perceptions, the manner that raw
data was collected, and the subjectivity of observers,
which may reduce the accuracy of the data. For surveys,
for instance, potential biases in FLW estimates can occur
because this method relies on peoples memory, and
people may provide socially desirable answers. Keeping a
food waste diary can be a considerable task for
participants, and this is reected in a tapering of
enthusiasm of participants
as well as diculties in
recruitment and high dropout rates.
Moreover, the
accuracy of diaries has been questioned, as keeping a
diary can by itself lead to increased awareness and
Figure 4. Overview of the methods used in the 202 reviewed
publications. Each dot represents one publication, and the colors
indicate dierent methods used. L: use of literature data; P: use of
proxy data; F: food balance; M: modeling; G: garbage collection; W:
weighing; O: observation; D: diaries; R: records; and S: surveys. For
the convenience of visualization, we have aggregated similar methods,
i.e., L/P, W/O, and D/R, in groups (see Figure S2 for a more-
disaggregated version).
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
behavioral change.
For observation, it requires
less time than weighing but varies in accuracy and
reliability. For example, Hanks and colleagues compared
three types of observation measurements (quarter-waste,
half-waste, and photograph) in a school cafeteria setting,
and they found that on-site visual methods outperformed
photographs in inter-rater and intermethod reliability.
Indirect measurement or calculation derived from
secondary data is more widely used due to their low
cost and high feasibility. However, these methods usually
bear higher uncertainty. For example, results from
modeling are heavily aected by the choice of model
parameters and their relationship with the quantities of
FLW. The accuracy of the food balance method depends
primarily on the quality and comprehensiveness of the
food balance sheet data. The use of proxy data and
literature data is the easiest among all methods, but its
accuracy depends ultimately on the quality and
representativeness of the source data that is used.
Arguably, no direct or indirect measurements can be all-
satisfactory by themselves. The direct measurements, despite
the advantage, are commonly performed in a certain
community or city and a certain stage of the food supply
chains involving limited number of participants, resulting in an
inevitable issue of lack of representativeness (especially
problematic for big countries like China and the United
States). The indirect measurements, on the contrary, can
provide an overall picture for the whole country or region and
for dierent stages. One way to go forward could be an
integrated approach of coupling direct with indirect measure-
ments: statistics-based estimation of FLW at the national and
regional levels to determine the magnitude of the problem
(more for policy-making and strategy-setting) and rst-hand
measurements at the ground level plus in-depth examination of
FLW drivers and aecting factors so as to design eective
intervention steps.
The choice of method has critical inuences on the
determined amount of FLW, which sometimes leads to data
discrepancy in the reviewed publications. For example,
EUROSTAT reported that about 5.7 million tons of FLW
were generated from the manufacturing sector in Italy in
while another model-based study estimated 1.9 million
tons for the sector.
The reason for such a signicant
dierence is that the two publications were based on dierent
data sources and assumptions. The former included both FLW
and byproducts that were reused and recycled, while the latter
one depended on the loss share of the manufacturing stage and
methodologies reported by FAO.
As another example,
Zhou reported that the wasted amount of wheat, maize, and
vegetables were 4.2, 4.9 and, 4.3 million tons in the early 1980s
in China, respectively,
whereas Smil estimated the wasted
quantity of these three food types as 1.9, 2.0, and 10.9 million
tons, respectively.
This discrepancy can be explained by the
fact that the data source of the former publication was the
FAOSTAT food balance sheet, whereas the latter was based on
Figure 5. Citation network of the 138 publications that used literature data. Each dot represents a publication. The size of the dot indicates the
number of citations, and the arrow represents the direction of citation. The dots in white on the right denote publications outside the citation
network. The top 10 cited publications are 1, Kantor et al., 1997;
2a, WRAP, 2009;
2b, Gustavsson et al., 2011;
3a, WRAP, 2008;
3b, Monier
et al., 2010;
3c, Buzby and Hyman, 2012;
4a, Kader, 2005;
4b, Kranert et al., 2012;
5a, Buzby et al., 2009;
and 5b, Langley et al., 2010.
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
various literature data and assumed cereal waste at 4% and
vegetable waste at 10%.
3.3. Statistical Analysis of FLW Data. Farm Losses and
Waste. In general, farm FLW in agricultural production in low-
income countries is higher than that in medium- and high-
income countries because the former countries usually have less
advanced technology and infrastructure in harvest processing.
For example, it was estimated that FLW during agricultural
production accounts for 13% of the total FLW along the whole
supply chain in Canada,
whereas this stage made up the
largest share (26%) of the overall FLW in South Africa.
There is not much information about FLW by commodity
groups in agricultural production and harvesting (Figure 6).
According to the compiled data (note that the data are from a
global panel for dierent countries and years, and the same
goes for the statistical analysis in the Postharvest Loss and
Waste and Farm Losses and Waste sections below), the median
of cereal farm FLW is the largest among all food categories, at a
level of approximately 16 kg/cap. It was estimated that
approximately 59% of grain was lost in China at this stage,
which is similar to that of Ghana,
Armenia, and Turkey.
Fruits and vegetables are the second largest in farm FLW, with
a median of 13 kg/cap. However, the magnitude of fruits and
vegetables losses and waste varies signicantly between
developing and developed countries. For example, it was
estimated that 2030% of total fruits and vegetables production
was lost at the agricultural stage in China,
while this share was
only 615% in Italy.
This big dierence can be explained by
the use of more advanced and new technologies and
innovations in more developed countries (where farm FLW
is mainly in the form of outgrades). The farm FLW rates of
meat and sh and dairy products and eggs are relatively small.
Postharvest Losses and Waste. Figure 7 presents
postharvest FLW (during postharvest handling and storage,
manufacturing, distribution, and retailing) of the four most-
relevant food commodities in the literature along the supply
The postharvest FLW of cereals and cereal products vary
greatly at dierent stages. The major FLW are found at
the postharvest handling and storage stage (over 18 kg/
cap) and in developing countries. For example, it was
reported that cereals had the highest postharvest FLW
out of all food commodities in South and Southeast Asia.
In particular, rice as the staple food in the Philippines had
a postharvest FLW rate of 10%.
The retailing stage
seconds this with a median value of over 10 kg/cap,
followed by the manufacturing and distribution stages
(approximately 5 kg/cap).
Fruits and vegetables dominate postharvest FLW among
all food commodities. For example, it was estimated that
the manufacturing FLW of fruits and vegetables was over
33 kg/cap in South Africa,
which was much higher than
that of all other food groups or stages. FLW at
manufacturing stage in developed countries are relatively
low, e.g., only about 5 kg/cap in Denmark.
distribution stage shows a high FLW of approximate 17
kg/cap, which is about 4 and 6 kg/cap, respectively,
higher than the postharvest handling and storage and
manufacturing stages. The FLW at retailing stage is the
smallest, about 3 kg/cap.
Meat and sh products contribute the least to
postharvest FLW. Their FLW at postharvest handling
and storage stage is very small, at about 0.3 kg/cap. The
FLW at manufacturing and retailing stages are similar,
both with a median value of about 1.3 kg/cap. One study
reported that the FLW rates of meat at postharvest
handling and storage, manufacturing, and distribution in
Turkey were 0.2%, 5%, and 0.5%, respectively.
The median FLW of dairy products and eggs is observed
at approximately 6, 3, 0.2, and 3.4 kg per capita for the
four substages, respectively. A study found that the FLW
rates of milk at manufacturing and distribution stages in
Ukraine were 315% and 811%, respectively, due
mainly to poor cooling systems.
FLW at the retailing stage in the United States is a particular
focus in the literature. It was estimated that about 2.4 million
tons of food (excluding inedible parts) was lost at the retailing
stage in 1995,
but it has gone up to 19.5 million (including
part of inedible food) tons in 2010, representing 10% of the
available food supply in the United States
Cereal products,
vegetables, and fruits contribute the most to the retailing FLW,
roughly about 10.5, 8, and 6 kg per capita, respectively, while
meat and sh products contributes the least (details in Figure
S3 and Table S8). For example, some studies reported that the
retailing FLW of cereal products equaled to 12% of the U.S.
food supply.
It should be noted that retailing FLW in
industrialized countries, including the United States, is likely to
be dominated by supermarkets but not street markets and
nonsupermarkets (often found in less-developed countries). In
2005 and 2006, for example, the U.S. supermarket FLW for
fresh fruits, vegetables, and meat and seafood were, on average,
11.4%, 9.7%, and 4.5%, respectively.
These data are consistent
with estimates from other industrialized countries, indicating
that fresh products and bakery make up the largest share of
retailing FLW due to factors such as expired sell-by dates,
product damage and quality issues, and improper stock
Consumer Food Waste. Household Food Waste. In
medium- and high-income countries, household food waste
makes up the largest share in the total FLW, mainly because of
poor purchase planning, cooking or serving too much,
overstocking, and misinterpretation of best beforeand use
Figure 6. Per-capita farm FLW of dierent food commodities.
Detailed data are available in Table S3.
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
In the EU, about 45 million tons or 45% of the
total FLW was found at the household level.
Food waste
arising from households represented 51% of total FLW
throughout the food supply chain in Canada
and 19% of
food and drink purchased by U.K. households, equivalent to
70% of U.K. postfarm-gate FLW (i.e., FLW during postharvest
stages and consumption).
Similar patterns can also be
observed in the households in the United States,
and Australia.
Low-income countries, on the
contrary, show a relatively small share of food waste in
households due to limited disposable household income.
However, upon closer inspection, we see little primary data
available at household level in emerging and developing
countries, and household food waste, especially in cities, may
be much larger than anticipated. Without signicant primary
research in these countries, generalizations should be made
Figure 8a presents a positive relationship between per-capita
GDP and household food waste per capita. When per-capita
GDP rises, the amount of per-capita food waste generated in
households also increases. This pattern agrees with observa-
tions in a few previous studies.
For example, it
was reported that in 2007, the food waste generated in
households in South Africa was only 7.3 kg/cap,
while U.K.
households generated 109.3 kg/cap,
though data robustness
for the South African estimate is expected to be limited
Figure 7. Per-capita postharvest FLW of cereals and cereal products, fruits and vegetables, meat and sh, and dairy products and eggs at dierent
stages. Detailed data are shown in Tables S4S7.
Figure 8. Correlation between per-capita GDP and per-capita consumer food waste: (a) households (R2= 0.34, P< 0.05); and (b) food service
sector (R2= 0.01, P> 0.05). Data are in Tables S9 and S10. Note that an outlier in panel a is excluded for the convenience of visualization (see
Figure S4 for the original version). Panel b distinguishes restaurants (empty circles) and other food service sectors (e.g., canteens; lled circles), and
the circles with a cross enclosed are for restaurants in Japan.
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
(extrapolated from Sub-Saharan estimates, which are less
wealthy and industrialized than South Africa).
However, it is interesting to observe that, when per-capita
GDP gets higher than a certain level (roughly 50 000 USD),
per-capita food waste generation tends to level o. This might
reect the increasing awareness of the public, food waste
prevention campaigns, stricter regulation (e.g., clearer labeling
and longer shelf life), and eect of market mechanisms (e.g.,
increasing cost of food purchase and food waste disposal). For
example, campaigns such as Zero Wasteand Love Food
Hate Wastehave been taken against food waste in
and the United Kingdom.
This may also
relate to higher consumption of prepared meals and less
cooking from scratch (which may transfer food waste from
household kitchen to food manufacturing to some extent) in
more-auent countries and the fact that waste generation data
are based on the management of waste (which is generally
much higher in more-auent countries).
Out-of-Home Food Waste. A number of studies have
estimated how much food has been wasted away from home,
i.e., in the food service industry, which is dened as a sector
responsible for preparing or serving food outside home,
including, for example, restaurants,
care centers,
military institutions,
transport hubs, and
in-ight catering.
The research on food waste in the food service sector has
mostly been conducted in industrialized countries. For example,
it was estimated that 0.92 million tons of food was wasted in
the food service outlets each year in the United Kingdom
(equivalent to 17% of all meals served), 75% of which was
In Germany, the food service sector accounted for
17% (the second largest source) of total FLW along the supply
In Finland, 0.0750.085 million tons of food was
wasted in food service, which was the third largest contributor
of FLW (20%) following households (35%) and food industry
It should be noted that China, as the largest
emerging economy in the world, was also experiencing a high
level of food waste in the catering and restaurant sector,
accounting for about 1117% of all food served.
On the whole, food waste per capita at away-from-home
consumption is lower than that in households (Figure 8b). It is
assumed that with higher per-capita GDP and living standards,
people tend to consume more food outside the home, which
may consequently result in a larger amount of food waste due
to various reasons (e.g., oversized dishes and taste). Yet the
correlation between per-capita GDP and per-capita food waste
out-of-home appears insignicant. The reason may be that the
food service sector is varied and includes both the for prot
(e.g., restaurant) and cost(e.g., care center) parts, leading to a
mixed pattern of food waste generation. Interestingly,
restaurant food waste in Japan shows a declining pattern in
recent years (the circles with a cross in Figure 8b). This may be
partly explained by the impact of the implementation of the
Food Recycling Law (which is to reduce food waste generation
by introducing specic targets for industry sectors) in Japan in
May 2001, which contributed to a reduction of out-of-home
food waste from 3.1 million tons in 2007 to 1.92 million tons in
2012. Accordingly, food waste per capita decreased from 24.22
to 15.05 kg in Japan.
In Figure 9, we take cereals and the United States, China, and
South Africa as examples of industrialized, emerging, and
developing countries to illustrate how the FLWR at dierent
stages along the supply chain evolves at dierent development
levels of an economy.
As the United States is a highly industrialized country,
there are few data on its FLWR of cereals at postharvest
stages (it can also be assumed to be low). The FLWR at
agricultural production, postharvest handling and storage,
manufacturing, and distribution stages in South Africa are
all higher than those in China. This reects the fact that
with increasing awareness and growing economy, more-
Figure 9. FLWR of cereals along the supply chain in the United States, China, and South Africa. The vertical chart on the left represents per-capita
GDP in current USD in 2015 for these three countries (according to the World Bank). P1: agricultural production and harvesting; P2: postharvest
handling and storage; P3: manufacturing; P4: distribution; P5: retailing; and P6: consumption. N.A. means not available. The reference ow is
assumed to be a ctive output of 100% of the amount produced. Due to a lack of FLW percentage for each stage in South Africa, the average amount
of waste reported between 2007 and 2009 was divided by the average quantity of production during the same period to calculate the FLWR.
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
advanced harvesting technologies and more-ecient
storage systems are applied in agricultural production,
and improved transportation with large volumes and
relatively low costs are largely used in China.
This also
implies a huge potential of improving the technologies
and infrastructure in less-developed countries as an
ecient way to reduce FLW.
The consumer cereal waste also increases as a country
develops and increases its GDP. The FLWR of cereals at
consumption stage in the United States is the highest
(15.8%), followed by the retailing stage (12%). In China,
with rapid economic development and household
income increase, the FLWR of cereals at the con-
sumption stage has increased in recent years to 6.4%,
higher than that of all other stages. As a lower-income
country, South Africa shows a low FLWR of cereals at
consumer stage yet (1.1%). It should be noted that,
because the production and consumption structure of
cereals (in terms of rice, wheat, maize, other cereals, and
bakery products) varies in dierent countries, it can be a
factor behind these dierences as well.
3.4. Data Gaps and Recommendations for Future
Study. Our review suggests that the quantication of FLW has
become a research hotspot in recent years, with over 60% of
FLW data reported for the recent decade. Whereas these
growing eorts provide an order-of-magnitude understanding
of the scale of global FLW and for a few countries (e.g., the
United States and the United Kingdom) and stages in the food
supply chain (e.g., household), the extent of FLW in many
other countries and stages remains poorly understood. The
existing data are also often based on secondary sources (over
half of the reviewed publications) and outdated or inconsistent
data sources (e.g., due to choice of method). Moreover, in line
with the First Principle of Food Waste proposed by Rathje,
the potential for waste is expected to increase with continuing
urbanization, increasing household income, and growing
demand for more perishable foods. Yet the FLW data gaps
and deciencies are most-signicant for those countries and
regions that have undergone the most-rapid shifts away from
starchy staples toward more varied and fresh diets (e.g., China
and India).
Therefore, the existing global FLW data should be
used and interpreted with care.
To address these data gaps, we highlight the following
directions for future study:
First, the systems and methodologies for FLW
quantication should be standardized, as is already
highlighted in the literature. Important aspects to be
considered include: the denition of FLW (e.g.,
questions regarding avoidable versus unavoidable food
stages of the food supply chain (e.g., dierent
segments in distribution and consumption), destination
of FLW (e.g., donation, feed, energy use, or landll),
classication of food commodities and conversion factors
(e.g., factor to convert cooked food items to raw food
materials), units of measurement (e.g., physical weight or
calories), and the methods of measurement (cf. section
3.2 above). This would enable the comparison of existing
data across countries, commodities, and food supply
chains, which would further help explore patterns and
driving factors of FLW generation. For example, the
European FUSIONS project released a food waste
quantication manual
in 2016; the rst global Food
Loss and Waste Protocol
published in 2016 provides a
standard that can be used by any entity (e.g., a country, a
company, a city, or an individual store or food outlet)
and should be promoted more widely.
Second, more data based on direct measurement are
badly needed. Our review shows that only around 20% of
the existing publications on FLW quantication are based
on rst-hand data, and any quotation of unrepresentative
data from literature may lead to high uncertainties.
Despite the higher time, labor, and economic cost, more
eld work and primary data collection should be
encouraged and would help verify existing data, improve
the accuracy and reliability of the data, and ll in the gaps
in countries where data are currently not available.
Third, more attention should be paid to countries
outside the current focus area (the United States and
Europe), especially to big developing and emerging
economies (e.g., the BRICs: Brazil, Russia, India, China,
and South Africa). There is less information regarding
FLW in those countries, but the scale may be signicant
(e.g., a preliminary study
shows that consumer food
waste in China is already higher than that of the total of
EU-27). These countries are also experiencing a rapid
shift in terms of dietary change, urbanization, and
household income increase, and thus, their FLW is
expected to grow in the coming years. The use of
outdated data may have led to an overestimation of
agricultural FLW and underestimation of consumer food
waste in developing countries.
Social and cultural
context are also very important for FLW quantication
and mitigation, which can only be addressed when more
data for specic countries and cultures are available.
Fourth, more in-depth analyses on FLW at dierent food
supply stages should be conducted. Household food
waste is a clear current focus (covered in almost half of
the reviewed publications, though almost exclusively in
developed countries). Research should be expanded to
food supply chains with less data and poorer under-
standing, e.g., FLW in other segments during out-of-
home consumption (e.g., canteens and restaurants) and
postharvest and retailing in developing countries. A
more-detailed quantication at each stage would also
help a better understanding of the driving factors of FLW
at dierent stages.
Fifth, consistent databases (global, regional, and na-
tional) using a common reporting framework on FLW
should be established, maintained, and made available to
the public, with joint eorts from all stakeholders along
the entire food chain. Such databases would provide a
baseline for monitoring the progress of FLW reduction,
which is important for tracking progress toward SDG
Target 12.3, and national political targets on FLW.
Governmental and nongovernmental organizations such
as UN Environment and FAO and national statistical
agencies should take a stronger leadership in this eort
(the data series reported by WRAP and USDA-ERS are
good examples). Companies should be encouraged to
report their FLW regularly (e.g., in their annual corporate
social responsibility report). In the long run, the
measurable, reportable, and veriable (MRV)principle
that is widely acknowledged in greenhouse gas emissions
reduction targets may be appropriate for tracking FLW
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
Last but not least, quantication of FLW is only a rst
step; the aim of better data measurement and monitoring
is to help better-understand the social, economic, and
environmental impacts of FLW, identify hotspots where
actions should be prioritized, develop long-term
scenarios to inform relevant policy-making, understand
which policies and strategies have been most-eective at
achieving FLW reductions, and contribute overall to the
reduction of FLW and the sustainability of the food
system. Research focusing on these topics should
naturally be conducted in parallel.
SSupporting Information
The Supporting Information is available free of charge on the
ACS Publications website at DOI: 10.1021/acs.est.7b00401.
Additional details on the literature selection. Figures
showing temporal trends, an overview of methods, per-
capita FLW, and experimental relationships. Tables
showing metadata used in the paper. (PDF)
A table showing compiled food losses and food waste
data reported in the reviewed publications (by physical
weight). (XLSX)
Corresponding Author
*Phone: 45-65509441; e-mail:
Gang Liu: 0000-0002-7613-1985
The authors declare no competing nancial interest.
This work is funded by National Natural Science Foundation of
China (key program, project no. 71233007), National Key
Research and Development Plan of China (project no.
2016YFE0113100), and the Danish Agency for Science,
Technology and Innovation (International Network Pro-
gramme, reference nos. 5132-00029B and 6144-00036). We
thank Yao Liu for research assistance.
(1) The Economist Intelligence Unit. Food Loss and Its Intersection
with Food Security; EIU: London, United Kingdom, 2014; http://www.
(2) FAO. Food Wastage Footprint: Impacts on Natural Resources;
FAO: Rome, Italy, 2013.
(3) Katajajuuri, J. M.; Silvennoinen, K.; Hartikainen, H.; Jalkanen, L.;
Koivupuro, H. K.; Reinikainen, A. Food waste in the food chain and
related climate impacts. In Proceedings of the 8th International
Conference on Life Cycle Assessment in the Agri-Food Sector (LCA Food
2012); Corson, M. S.; van der Werf, H. M. G., Eds.; INRA: Rennes,
France, 2012; pp 627632.
(4) Pham, T. P. T.; Kaushik, R.; Parshetti, G. K.; Mahmood, R.;
Balasubramanian, R. Food-waste-to-energy conversion technologies:
Current status and future directions. Waste Manage. 2015,38, 399
(5) United Nations. United Nations Sustainability Development Goals
Home Page.
consumption-production/ (accessed November 20, 2016).
(6) European Commission Food Safety Home Page; http://ec. (accessed January
11, 2017).
(7) United States Department of Agriculture. USDA and EPA Join
with Private Sector, Charitable Organizations to Set Nation's First Food
Waste Reduction Goals.
organizations-set (accessed November 20, 2016).
(8) Lipinski, B.; OConnor, C.; Hanson, C. SDG Target 12.3 on Food
Loss and Waste: 2016 Progress Report; Champions 12.3: The Hague,
The Netherlands, 2016;
(9) Gustavsson, J.; Cederberg, C.; Sonesson, U.; Otterdijk, R.; van
Meybeck, A. Global Food Losses and Food Waste: Extent, Causes and
Prevention; FAO: Rome, Italy, 2011.
(10) FAO. Food Wastage Footprint &Climate Change; FAO: Rome,
Italy, 2015.
(11) FUSIONS. Food Waste Data Set for EU-28; Wageningen
University Publishing: Wageningen, The Netherlands, 2015.
(12) WRAP. Household Food and Drink Waste: A Product Focus;
Waste & Resources Action Programme (WRAP): Banbury, U.K.,
(13) Gjerris, M.; Gaiani, S. Household food waste in Nordic
countries: Estimations and ethical implications. Nord. J. Appl. Ethics
2013,7(1), 623.
(14) Beretta, C.; Stoessel, F.; Baier, U.; Hellweg, S. Quantifying food
losses and the potential for reduction in Switzerland. Waste Manage.
2013,33 (3), 764773.
(15) Hall, K. D.; Guo, J.; Dore, M.; Chow, C. C. The Progressive
increase of food waste in America and its environmental impact. PLoS
One 2009,4(11), e7940.
(16) Verghese, K.; Lewis, H.; Lockrey, S.; Williams, H. The Role of
Packaging in Minimising Food Waste in the Supply Chain of the Future;
RMIT University: Melbourne, 2013.
(17) Gooch, M.; Felfel, A.; Marenick, N. Food Waste in Canada;
Value Chain Management Centre: Oakville, Ontario, 2010.
(18) FAO. Mitigation of Food Wastage: Societal Costs and Benets;
FAO: Rome, Italy, 2014.
(19) Buzby, J. C.; Guthrie, J. F. Plate Waste in School Nutrition
Programs: Final Report to Congress; Economic Research Service E
FAN-02-009, United States Department of Agriculture: Washington,
DC, 2002.
(20) Buzby, J. C.; Wells, H. F.; Axtman, B.; Mickey, J. Supermarket
Loss Estimates for Fresh Fruit, Vegetables, Meat, Poultry, and Seafood and
Their Use in the ERS Loss-Adjusted Food Availability Data; Economic
Information Bulletin Number 44, Economic Research Service; United
States Deparment of Agricuture: Washington, DC, 2009.
(21) Muth, M. K.; Karns, S. A.; Nielsen, S. J.; Buzby, J. C.; Wells, H.
F. Consumer-Level Food Loss Estimates and Their Use in the ERS Loss-
Adjusted Food Availability Data; Technical Bulletin No. 1927,
Economic Research Service; United States Department of Agriculture:
Washington, DC, 2011.
(22) Buzby, J. C.; Wells, H. F.; Aulakh, J. Food Loss: Questions about
the Amount and Causes Still Remain; United States Department of
Agriculture: Washington, DC, 2014.
(23) Buzby, J. C.; Wells, H. F.; Hyman, J. The Estimated Amount,
Value, and Calories of Postharvest Food Losses at the Retail and Consumer
Levels in the United Statess; Economic Information Bulletin, EIB-121;
United States Deparment of Agricuture: Washington, DC, 2014.
(24) WRAP. Understanding Food Waste - Key Findings of WRAPs
Recent Research on the Nature, Scale And Causes of Household Food
Waste; Waste & Resources Action Programme (WRAP): Banbury,
U.K., 2007.
(25) WRAP. The Food We Waste; Waste and Resources Action
Programme (WRAP): Banbury, U.K., 2008.
(26) WRAP. Household Food and Drink Waste in the U.K. (2009);
Waste and Resources Action Programme (WRAP): Banbury, U.K.,
(27) WRAP. New Estimates for Household Food and Drink Waste in the
U.K.; Waste and Resources Action Programme (WRAP): Banbury,
U.K., 2011.
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
(28) WRAP. The Composition of Waste Disposed of by the U.K.
Hospitality Industry; Waste and Resources Action Programme
(WRAP): Banbury, U.K., 2011.
(29) WRAP. Reducing Food Waste through Retail Supply Chain
Collaboration; Waste and Resources Action Programme (WRAP):
Banbury, U.K., 2011.
(30) WRAP. Household Food and Drink Waste in the United Kingdom
2012; Waste and Resources Action Programme (WRAP): Banbury,
U.K., 2013.
(31) Refresh Home Page.
(accessed November 20, 2016)
(32) O
̈stergen, K.; Gustavsson, J.; Bos-Brouwers, H.; Timmermans,
T.; Hansen, O.-J.; Møller, H.; Anderson, G.; OConnor, C.; Soethoudt,
H.; Quested, T.; et al. FUSIONS Denitional Framework for Food
Waste; Wageningen University Publishing: Wageningen, The Nether-
lands, 2014.
(33) FUSIONS. Food Waste Quantication Manual to Monitor Food
Waste Amounts and Progression; Wageningen University Publishing:
Wageningen, The Netherlands, 2016.
(34) FUSIONS. Estimates of European Food Waste Levels;
Wageningen University Publishing: Wageningen, The Netherlands,
(35) World Resources Institute. Food Loss and Waste Accounting and
Reporting Standard; WRI: Washington, DC, 2016; http://www.wri.
(36) Partt, J. Global Food Waste Campaigns Suer from Data
Deciency; Guardian Professional: London, U.K., 2013.
(37) Liu, G. Food Losses and Food Waste in China: A First Estimate;
OECD Food, Agriculture and Fisheries Papers, No. 66; OECD
Publishing: Paris, France, 2014.
(38) Shafiee-Jood, M.; Cai, X. Reducing food loss and waste to
enhance food security and environmental sustainability. Environ. Sci.
Technol. 2016,50 (16), 84328443.
(39) Kling, W. Food waste in distribution and use. J. Farm Econ.
1943,25 (4), 848859.
(40) Pimentel, D. Environmental and social implications of waste in
U.S. agriculture and food sectors. J. Agric. Environ. Ethics 1990,3(1),
(41) Kantor, L. S.; Lipton, K.; Manchester, A.; Oliveira, V. Estimating
and addressing Americas food losses. Food Rev. 1997,20 (1), 212.
(42) Hackes, B. L.; Shanklin, C. W.; Kim, T.; Su, A. Y. Tray service
generates more food waste in dining areas of a continuing-care
retirement community. J. Am. Diet. Assoc. 1997,97 (8), 879882.
(43) Harrington, J. M.; Myers, R. A.; Rosenberg, A. A. Wasted fishery
resources: discarded by-catch in the USA. Fish Fish 2005,6(4), 350
(44) Jones, T. W. Using Contemporary Archaeology and Applied
Anthropology to Understand Food Loss in the American Food System;
University of Arizona: Tucson, AZ, 2005.
(45) Okazaki, W. K. Identication and assessment of food waste
generators in Hawaii. Master of Science Thesis, University of Hawaii,
Honolulu, HI, 2006.
(46) Griffin, M.; Sobal, J.; Lyson, T. An analysis of a community food
waste stream. Agric. Human Values 2009,26 (1), 6781.
(47) Ritter, M. J.; Ellis, M.; Berry, N. L.; Curtis, S. E.; Anil, L.; Berg,
E.; Benjamin, M.; Butler, D.; Dewey, C.; Driessen, B.; et al. Review:
Transport losses in market weight pigs: I. A review of definitions,
incidence, and economic impact. Prof. Anim. Sci. 2009,25 (4), 404
(48) Buzby, J. C.; Hyman, J.; Stewart, H.; Wells, H. F. The value of
retail- and consumer-level fruit and vegetable losses in the United
States. J. Consum. Aff. 2011,45 (3), 492515.
(49) Hodges, R. J.; Buzby, J. C.; Bennett, B. Postharvest losses and
waste in developed and less developed countries: opportunities to
improve resource use. J. Agric. Sci. 2011,149 (S1), 3745.
(50) Whitehair, K. J. Investigation of strategies to decrease food
waste in college and university food service. Ph.D. Dissertation, Kansas
State University, Manhattan, KS, 2011.
(51) Buchner, B.; Fischler, C.; Gustafson, E.; Reilly, J.; Riccardi, G.;
Ricordi, C.; Veronesi, U. Food Waste: Causes, Impacts and Proposals;
Barilla Center for Food & Nutrition: Parma, Italy, 2012.
(52) Buzby, J. C.; Hyman, J. Total and per capita value of food loss in
the United States. Food Policy 2012,37 (5), 561570.
(53) Gunders, D. Wasted: How America is Losing up to 40% of Its Food
from Farm to Fork to Landll; Natural Resources Defense Council:
New York, 2012.
(54) Venkat, K. The climate change and economic impacts of food
waste in the United States. Int. J. Food Syst. Dyn. 2012,2(4), 431446.
(55) Heller, M. C.; Keoleian, G. A. Greenhouse gas emission
estimates of U.S. dietary choices and food loss. J. Ind. Ecol. 2015,19
(3), 391401.
(56) Lebersorger, S.; Schneider, F. Food loss rates at the food retail,
influencing factors and reasons as a basis for waste prevention
measures. Waste Manage. 2014,34 (11), 19111919.
(57) Eriksson, M. Supermarket food waste: Prevention and
management with the focus on reduced waste for reduced carbon
footprint. Ph.D. Dissertation, Uppsala University, Uppsala, Sweden,
(58) Loke, M. K.; Leung, P. Quantifying food waste in Hawaiis food
supply chain. Waste Manage. Res. 2015,33 (12), 10761083.
(59) Love, D. C.; Fry, J. P.; Milli, M. C.; Neff, R. A. Wasted seafood
in the United States: Quantifying loss from production to
consumption and moving toward solutions. Glob. Environ. Chang.
2015,35, 116124.
(60) Okawa, K. Market and Trade Impacts of Food Loss and Waste
Reduction; OECD Food Agriculture and Fisheries Papers, No. 75;
OECD Publishing: Paris, France, 2015.
(61) Thyberg, K. L.; Tonjes, D. J.; Gurevitch, J. Quantification of
food waste disposal in the United States: A meta-analysis. Environ. Sci.
Technol. 2015,49 (24), 1394613953.
(62) Engström, R.; Carlsson-Kanyama, A. Food losses in food service
institutions: Examples from Sweden. Food Policy 2004,29 (3), 203
(63) Sonesson, U.; Anteson, F.; Davis, J.; Sjödé
n, P. O. Home
transport and wastage: Environmentally relevant household activities
in the life cycle of food. Ambio 2005,34 (4), 371375.
(64) Gustavsson, J. The climate change impact of retail waste from
horticultural products. Master of Science Thesis, University of
Gothenburg, Gothenburg, Sweden, 2010.
(65) Gustavsson, J.; Stage, J. Retail waste of horticultural products in
Sweden. Resour. Conserv. Recycl. 2011,55 (5), 554556.
(66) Williams, H.; Wikström, F.; Otterbring, T.; Löfgren, M.;
Gustafsson, A. Reasons for household food waste with special
attention to packaging. J. Cleaner Prod. 2012,24 (3), 141148.
(67) Nilsson, H. Integrating sustainability in the food supply chain -
Two measures to reduce the food wastage in a Swedish retail store.
Master Thesis, Uppsala University, Uppsala, Sweden, 2012.
(68) Eriksson, M. Retail food wastage: A case study approach to
quantities and causes. Master Thesis, Swedish University of
Agricultural Sciences, Uppsala, Sweden, 2012.
(69) Eriksson, M.; Strid, I.; Hansson, P. A. Food losses in six Swedish
retail stores: Wastage of fruit and vegetables in relation to quantities
delivered. Resour. Conserv. Recycl. 2012,68 (6), 1420.
(70) Marthinsen, J.; Sundt, P.; Kaysen, O.; Kirkevaag, K. Prevention of
Food Waste in Restaurants, Hotels, Canteens and Catering; Nordic
Council of Ministers: Copenhagen, Denmark, 2012.
(71) Bernstad Saraiva Schott, A.; Andersson, T. Food waste
minimization from a life-cycle perspective. J. Environ. Manage. 2015,
147, 219226.
(72) Bernstad, A. Household food waste separation behavior and the
importance of convenience. Waste Manage. 2014,34 (7), 13171323.
(73) Eriksson, M.; Strid, I.; Hansson, P.-A. Waste of organic and
conventional meat and dairy productsA case study from Swedish
retail. Resour. Conserv. Recycl. 2014,83 (83), 4452.
(74) Brä
utigam, K.-R.; Jörissen, J.; Priefer, C. The extent of food
waste generation across EU-27: Different calculation methods and the
reliability of their results. Waste Manage. Res. 2014,32 (8), 683694.
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
(75) Zhou, Z. Food waste in retailing stores in Sweden: A welfare
simulation analysis. Master Thesis, University of Gothenburg,
Gothenburg, Sweden, 2014.
(76) Filho, W. L.; Kovaleva, M. Food Waste and Sustainable Food
Waste Management in the Baltic Sea Region; Hamburg University of
Applied Sciences: Hamburg, Germany, 2015.
(77) Choudhury, M. L. Recent developments in reducing postharvest
losses in the Asia-Pacic region. In Postharvest Management of Fruit and
Vegetables in the Asia-Pacic Region; Rolle, R. S., Ed.; Asian Productivity
Organization: Tokyo, Japan, 2006.
(78) Parfitt, J.; Barthel, M.; Macnaughton, S. Food waste within food
supply chains: Quantification and potential for change to 2050. Philos.
Trans. R. Soc., B 2010,365 (1554), 30653081.
(79) Kader, A. A. Increasing food availability by reducing postharvest
losses of fresh produce. Acta Hortic. 2005,682, 21692175.
(80) El-Mobaidh, A. M.; Razek Taha, M. A.; Lassheen, N. K.
Classification of in-flight catering wastes in Egypt air flights and its
potential as energy source (chemical approach). Waste Manage. 2006,
26 (6), 587591.
(81) Partt, J.; Barthel, M. Global Food Waste Reduction: Priorities for
a World in Transition; U.K. Governments Foresight Project on Global
Food and Farming Futures: London, U.K., 2011.
(82) Davies, T.; Konisky, D. M. Environmental Implications of the
Foodservice and Food Retail Industries; Resources for the Future:
Washington, DC, 2000.
(83) Fehr, M.; Romão, D. C. Measurement of fruit and vegetable
losses in Brazil: a case study. Environ. Dev. Sustain. 2001,3(3), 253
(84) Stenmarck, Å.; Hanssen, O. J.; Silvennoinen, K.; Katajajuuri, J.-
M.; Werge, M. Initiatives on Prevention of Food Waste in the Retail and
Wholesale Trades; Nordic Council of Ministers: Copenhagen, Den-
mark, 2011.
(85) Parry, A.; Bleazard, P.; Okawa, K. Preventing Food Waste: Case
Studies of Japan and the United Kingdom; OECD Food Agriculture &
Fisheries Papers, No. 76; OECD Publishing: Paris, France, 2015.
(86) Kachru, R. P.; General, A. D. Status of the Post-Harvest Sector in
South Asia; Indian Council of Agricultural Research: New Delhi, India,
(87) Gangwar, R. K.; Tyagi, S.; Kumar, V.; Singh, K.; Singh, G. Food
production and post harvest losses of food grains in India. Food Sci.
Qual. Manag. 2014,31,4853.
(88) Naziri, D.; Quaye, W.; Siwoku, B.; Wanlapatit, S.; Viet, T.;
Bennett, B. The diversity of postharvest losses in cassava value chains
in selected developing countries. J. Agric. Rural Dev. Trop. Subtrop.
2014,115 (2), 111123.
(89) Oelofse, S. H. H.; Nahman, A. Estimating the magnitude of food
waste generated in South Africa. Waste Manage. Res. 2013,31 (1), 80
(90) Lipinski, B.; Hanson, C.; Lomax, J.; Kitinoja, L.; Waite, R.;
Searchinger, T. Reducing Food Loss and Waste (Creating a Sustainable
Food Future, Installment Two); World Resources Institute and United
Nations Environment Programme: Washington, DC, 2013.
(91) Springer, N.; Flaherty, R.; Robertson, K. Losses in the Field: An
Opportunity Ripe for Harvesting; BSR: New York, 2013; https://www.
(92) Kelleher, K. Fishery Green Growth and Waste;Fisheries
Committee, OECD Trade and Agriculture Directorate: Paris, 2013.
(93) Nahman, A.; de Lange, W. Costs of food waste along the value
chain: Evidence from South Africa. Waste Manage. 2013,33 (11),
(94) Prusky, D. Reduction of the incidence of postharvest quality
losses, and future prospects. Food Secur. 2011,3(4), 463474.
(95) World Bank. Missing food: The Case of Postharvest Grain Losses in
Sub-Saharan Africa; The World Bank: Washington, DC, 2011.
(96) Segrè
, A.; Falasconi, L.; Politano, A.; Vittuari, M.. Background
Paper on the Economics of Food Loss and Waste; FAO: Rome, Italy,
(97) FAO. Denitional Framework of Food Loss; FAO: Rome, Italy,
(98) Cathcart, E. P.; Murray, A. M. T. A Note on the percentage loss
of calories as waste on ordinary mixed diets. J. Hyg. 1939,39 (1), 45
(99) Wenlock, R. W.; Buss, D. H.; Derry, B. J.; Dixon, E. J.
Household food wastage in Britain. Br. J. Nutr. 1980,43 (1), 5370.
(100) Edwards, J. S. A.; Nash, A. H. M. The nutritional implications
of food wastage in hospital food service management. Nutr. Food Sci.
1999,99 (2), 8998.
(101) Barton, A. D.; Beigg, C. L.; Macdonald, I. A.; Allison, S. P.
High food wastage and low nutritional intakes in hospital patients.
Clin. Nutr. 2000,19 (6), 445449.
(102) Hyde, K.; Smith, A.; Smith, M.; Henningsson, S. The challenge
of waste minimisation in the food and drink industry: a demonstration
project in East Anglia, UK. J. Cleaner Prod. 2001,9(1), 5764.
(103) Garnett, T. Fruit and Vegetables &U.K. Greenhouse Gas
Emissions: Exploring the Relationship; University of Surrey: Surrey,
U.K., 2006.
(104) Hogg, D.; Barth, J.; Schleiss, K.; Favoino, E. Dealing with Food
Waste in the U.K.; Waste and Resources Action Programme (WRAP):
Banbury, U.K., 2007.
(105) Caswell, H. Britains battle against food waste. Nutr. Bull. 2008,
33 (4), 331335.
(106) Langley, J.; Yoxall, A.; Manson, G.; Lewis, W.; Waterhouse, A.;
Thelwall, D.; Thelwall, S.; Parry, A.; Leech, B. The use of uncertainty
analysis as a food waste estimation tool. Waste Manage. Res. 2009,27
(3), 199206.
(107) Defra. Household Food and Drink Waste Linked to Food and
Drink Purchases; Defra: London, U.K., 2010.
(108) Langley, J.; Yoxall, A.; Heppell, G.; Rodriguez, E. M.; Bradbury,
S.; Lewis, R.; Luxmoore, J.; Hodzic, A.; Rowson, J. Food for thought?
A U.K. pilot study testing a methodology for compositional
domestic food waste analysis. Waste Manag. Res. 2010,28 (3), 220
(109) Sonesson, U.; Davis, J.; Ziegler, F. Food Production and
Emissions of Greenhouse Gases: An Overview of the Climate Impact of
Dierent Product Groups; The Swedish Institute for Food and
Biotechnology: Gothenburg, Sweden, 2010.
(110) Sonnino, R.; McWilliam, S. Food waste, catering practices and
public procurement: A case study of hospital food systems in Wales.
Food Policy 2011,36 (6), 823829.
(111) Pham, T. M. H. Food waste recycling: An empirical study of
the eects of selected socio-economic factors and information on food
waste recycling practices. A case study of Norwich householders.
Master of Science Thesis, University of East Anglia, Norwich, U.K.,
(112) Escaler, M.; Teng, P. Mind the Gap: Reducing Waste and Losses
in the Food Supply Chain; RSIS Centre for NonTraditional Security
(NTS) Studies: Singapore, 2011.
(113) Carr, W.; Downing, E. Food Waste in U.K.; House of
Commons: London, U.K., 2014; http://researchbriengs.les.
(114) Mena, C.; Terry, L. A.; Ellram, L.; Williams, A. Causes of waste
across multi-tier supply networks: Cases in the U.K. food sector. Int. J.
Prod. Econ. 2014,152, 144158.
(115) Rispo, A.; Williams, I. D.; Shaw, P. J. Source segregation and
food waste prevention activities in high-density households in a
deprived urban area. Waste Manage. 2015,44,1527.
(116) Blanke, M. Challenges of reducing fresh produce waste in
Europe: From farm to fork. Agriculture 2015,5(3), 389399.
(117) Vanham, D.; Bouraoui, F.; Leip, A.; Grizzetti, B.; Bidoglio, G.
Lost water and nitrogen resources due to EU consumer food waste.
Environ. Res. Lett. 2015,10 (8), 084008.
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
(118) Xu, Z.; Sun, D.-W.; Zhang, Z.; Zhu, Z. Research developments
in methods to reduce carbon footprint of cooking operations: a review.
Trends Food Sci. Technol. 2015,44 (1), 4957.
(119) Russ, W.; Meyer-Pittroff, R. Utilizing waste products from the
food production and processing industries. Crit. Rev. Food Sci. Nutr.
2004,44 (1), 5762.
(120) Schneider, F. Considerations on Food Losses in Life Cycle
Approach of Food Supply Chain. Presented at the 3rd International
Conference on Life Cycle Management, Zurich, Switzerland, August
2729, 2007; pp 2729.
(121) Kranert, M.; Hafner, G.; Barabosz, J.; Schneider, F.;
Lebersorger, S.; Scherhaufer, S.; Schuller, H.; Leverenz, D.
Determination of Discarded Food and Proposals for a Minimization of
Food Wastage in Germany; Institute for Sanitary Engineering,
University of Stuttgart: Stuttgart, Germany, 2012.
(122) Federal Ministry of Food Agriculture and Consumer
Protection (BMELV). German government investigates post-harvest
losses; (accessed May 2,
(123) Blanke, M. M. Reducing ethylene levels along the food supply
chain - a key to reducing food waste? J. Sci. Food Agric. 2014,94 (12),
(124) Rossaint, S.; Kreyenschmidt, J. Intelligent label a new way to
support food waste reduction. Proc. Inst. Civ. Eng.: Waste Resour.
Manage. 2015,168 (2), 6371.
(125) Jörissen, J.; Priefer, C.; Brä
utigam, K.-R. Food waste generation
at household level: Results of a survey among employees of two
European research centers in Italy and Germany. Sustainability 2015,7
(3), 26952715.
(126) Silvennoinen, K.; Katajajuuri, J. M.; Hartikainen, H.; Jalkanen,
L.; Koivupuro, H. K.; Reinikainen, A. Food waste volume and
composition in the Finnish supply chain: special focus on food service
sector. In Fourth International Symposium on Energy from Biomass and
Waste; CISA Publisher: Venice, Italy, 2012.
(127) Silvennoinen, K.; Korhonen, O. Food waste volumn and
composition in Helsinki region households. Presented at the 6th
International Conference on Life Cycle Management (LCM),
Gothenburg, Sweden, August 2528, 2013; http://conferences.
(128) Katajajuuri, J.-M.; Silvennoinen, K.; Hartikainen, H.; Heikkilä,
L.; Reinikainen, A. Food waste in the Finnish food chain. J. Cleaner
Prod. 2014,73 (12), 322329.
(129) Silvennoinen, K.; Heikkilä, L.; Katajajuuri, J.-M.; Reinikainen,
A. Food waste volume and origin: Case studies in the Finnish food
service sector. Waste Manage. 2015,46, 140145.
(130) Dennison, G. J.; Dodd, V. A.; Whelan, B. A socio-economic
based survey of household waste characteristics in the city of Dublin,
Ireland. II. Waste quantities. Resour. Conserv. Recycl. 1996,17 (3),
(131) Gutié
rrez-Barba, B. E.; Ortega-Rubio, A. Household food-
waste production and a proposal for its minimization in Mexico. Life
Sci. J. 2013,10 (3), 17721783.
(132) Stefan, V.; van Herpen, E.; Tudoran, A. A.; Lä
hteenmäki, L.
Avoiding food waste by Romanian consumers: The importance of
planning and shopping routines. Food Qual. Prefer. 2013,28 (1), 375
(133) Martindale, W. Using consumer surveys to determine food
sustainability. Br. Food J. 2014,116 (7), 11941204.
(134) Rathje, W. L.; Murphy, C. Rubbish!: The Archaeology of
Garbage; University of Arizona Press: New York, 2001.
(135) Khan, M. Z. A.; Burney, F. A. Forecasting solid waste
composition An important consideration in resource recovery and
recycling. Resour. Conserv. Recycl. 1989,3(1), 117.
(136) Liu, J.; Lundqvist, J.; Weinberg, J.; Gustafsson, J. Food losses
and waste in China and their implication for water and land. Environ.
Sci. Technol. 2013,47 (18), 1013710144.
(137) Moreno, L. Sustainable Food Management Through the Food
Recover Challenge; Environmental Protection Agency, Washington,
DC, 2011;
(138) Gooch, M. Cut Waste, Grow Prot: How to Reduce and Manage
Food Waste, Leading to Increased Protability and Environmental
Sustainability; Value Chain Management Centre: Oakville, Ontario,
(139) An, Y.; Li, G.; Wu, W.; Huang, J.; He, W.; Zhu, H. Generation,
collection and transportation, disposal and recycling of kitchen waste:
A case study in Shanghai. Waste Manage. Res. 2014,32 (3), 245248.
(140) Bala, B. K.; Haque, M. A.; Hossain, A.; Majumdar, S. Post
Harvest Loss and Technical Eciency of Rice, Wheat and Maize
Production System: Assessment and Measures for Strengthening Food
Security; Bangladesh Agricultural University: Mymensingh, Bangladesh,
(141) Reardon, T.; Chen, K.; Minten, B.; Adriano, L. The Quiet
Revolution in Staple Food Value Chains: Enter the Dragon, the Elephant,
and the Tiger; Asian Development Bank: Mandaluyong City,
Philippines, 2012.
(142) Stoner, J. M. S. Applying the concept of sustainable
consumption to seafood: how product loss through post-harvest
seafood supply chains undermines seafood sustainability. Master
Thesis, Dalhousie University, Halifax, Nova Scotia, 2013.
(143) Suthar, S.; Singh, P. Household solid waste generation and
composition in different family size and socio-economic groups: A case
study. Sustain. Cities Soc. 2015,14 (1), 5663.
(144) Kaminski, J.; Christiaensen, L. Post-Harvest Loss in Sub-Saharan
AfricaWhat Do Farmers Say?; The World Bank: Washington, DC.
(145) Papargyropoulou, E.; Padfield, R.; Rupani, P. F.; Zakaria, Z.
Towards sustainable resource and waste management in developing
countries: The role of commercial and food waste in Malaysia. Int. J.
Waste Resour. 2014,4(3), 27.
(146) Edjabou, M. E.; Jensen, M. B.; Götze, R.; Pivnenko, K.;
Petersen, C.; Scheutz, C.; Astrup, T. F. Municipal solid waste
composition: Sampling methodology, statistical analyses, and case
study evaluation. Waste Manage. 2015,36,1223.
(147) Monier, V.; Mudgal, S.; Escalon, V.; OConnor, C.; Gibon, T.;
Anderson, G.; Montoux, H.; Reisinger, H.; Dolley, P.; Ogilvie, S.; et al.
Preparatory Study on Food Waste Across EU27; European Commission:
Brussels, Belgium, 2010.
(148) Dias-Ferreira, C.; Santos, T.; Oliveira, V. Hospital food waste
and environmental and economic indicators - A Portuguese case study.
Waste Manage. 2015,46, 146154.
(149) Lebersorger, S.; Schneider, F. Discussion on the methodology
for determining food waste in household waste composition studies.
Waste Manage. 2011,31 (910), 19241933.
(150) Dahlé
n, L.; Lagerkvist, A. Methods for household waste
composition studies. Waste Manage. 2008,28 (7), 11001112.
(151) Parizeau, K.; von Massow, M.; Martin, R. Household-level
dynamics of food waste production and related beliefs, attitudes, and
behaviours in Guelph, Ontario. Waste Manage. 2015,35, 207217.
(152) Sharp, V.; Giorgi, S.; Wilson, D. C. Methods to monitor and
evaluate household waste prevention. Waste Manag. Res. 2010,28 (3),
(153) Hanks, A. S.; Wansink, B.; Just, D. R. Reliability and accuracy
of real-time visualization techniques for measuring school cafeteria tray
waste: validating the quarter-waste method. J. Acad. Nutr. Diet. 2014,
114 (3), 470474.
(154) Gustavsson, J.; Cederberg, C.; Sonesson, U.; Emanuelsson, A.
The Methodology of the FAO Study: Global Food Losses and Food Waste
- Extent, Causes and Prevention- FAO, 2011; The Swedish Institute for
Food and Biotechnology: Gothenburg, Sweden, 2013.
(155) Z Zhou, Z.; Tian, W.; Wang, J.; Liu, H. Food Consumption
Trends in China. Report submitted to the Australian Government;
Department of Agriculture, Fisheries and Forestry: Queensland,
Australia, 2012;
consumption-trends-in-china (accessed December 10, 2012).
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
(156) Smil, V. Chinas food: availability, requirements, composition,
prospects. Food Policy 1981,6(2), 6777.
(157) Falasconi, L.; Vittuari, M.; Politano, A.; Segrè
, A. Food waste in
school catering: An Italian case study. Sustainability 2015,7(11),
(158) Scholz, K.; Eriksson, M.; Strid, I. Carbon footprint of
supermarket food waste. Resour. Conserv. Recycl. 2015,94,5665.
(159) Saccares, S.; Scognamiglio, U.; Moroni, C.; Marani, A.;
Calcaterra, V.; Amendola, M.; Civitelli, G.; Cattaruzza, M. S.;
Ermenegildi, A.; Morena, V. Evaluation model of plate waste to
monitor food consumption in two different catering settings. Ital. J.
Food Saf. 2014,3(2), 18.
(160) Grandhi, B.; Appaiah Singh, J. What a waste! A study of food
wastage behavior in Singapore. J. Food Prod. Mark. 2016,22, 471485.
(161) Halloran, A.; Clement, J.; Kornum, N.; Bucatariu, C.; Magid, J.
Addressing food waste reduction in Denmark. Food Policy 2014,49,
(162) Spescha, G.; Reutimann, J. Reducing Food Waste - A Hidden
Opportunity for Investors; 2013;
(163) Themen, D. Reducing of Food Losses and Waste in Europe and
Central Asia for Improved Food Security and Agrifood Chain Eciency;
FAO: Rome, Italy, 2014.
(164) Holm, T. Reduction of FLW in Europe and Central Asia;
Synthesis Report prepared for Food and Agriculture Organization of
the United Nations; Regional Oce for Europe and Central Asia
(REU): Budapest, Hungary, 2013.
(165) Koivupuro, H.-K.; Hartikainen, H.; Silvennoinen, K.;
Katajajuuri, J.-M.; Heikintalo, N.; Reinikainen, A.; Jalkanen, L.
Influence of socio-demographical, behavioural and attitudinal factors
on the amount of avoidable food waste generated in Finnish
households. Int. J. Consum. Stud. 2012,36 (2), 183191.
(166) Reynolds, C. J.; Mavrakis, V.; Davison, S.; Høj, S. B.; Vlaholias,
E.; Sharp, A.; Thompson, K.; Ward, P.; Coveney, J.; Piantadosi, J.;
et al. Estimating informal household food waste in developed
countries: The case of Australia. Waste Manage. Res. 2014,32 (12),
(167) Baker, D. Measuring and addressing the ecological impact of
household food waste in Australia. In 16th Biennial Australian
Association for Environmental Education Conference Leading Change:
Living for One Planet; AAEE National Conference Committee:
Canberra, Australian, 2010;
(168) Thi, N. B. D.; Kumar, G.; Lin, C.-Y. An overview of food waste
management in developing countries: Current status and future
perspective. J. Environ. Manage. 2015,157, 220229.
(169) Lee, P.; Willis, P.; Hollins, O. Waste Arisings in the Supply of
Food and Drink to Households in the U.K.; Waste and Resources Action
Programme (WRAP): Banbury, U.K., 2010.
(170) Zorpas, A. A.; Lasaridi, K. Measuring waste prevention. Waste
Manage. 2013,33 (5), 10471056.
(171) Quested, T. E.; Parry, A. D.; Easteal, S.; Swannell, R. Food and
drink waste from households in the U.K. Nutr. Bull. 2011,36 (4),
(172) Liwei, G.; Shengkui, C.; Xiaochang, C.; Dan, Z.; Xiaojie, L.; Qi,
Q.; Yao, L. An overview of the resources and environmental issues
from wasted food in urban catering across China. J. Resour. Ecol. 2013,
4(4), 337343.
(173) Okazaki, W. K.; Turn, S. Q.; Flachsbart, P. G. Characterization
of food waste generators: A Hawaii case study. Waste Manage. 2008,
28 (12), 24832494.
(174) Blomgren, M.; Bylund, J. The connection between the issue of
food waste and its collection for biogas: A case study of the
municipality of Stockholm. Master Thesis, Stockholm University,
Stockholm, Sweden, 2013.
(175) Whitehair, K. J.; Shanklin, C. W.; Brannon, L. A. Written
messages improve edible food waste behaviors in a university dining
facility. J. Acad. Nutr. Diet. 2013,113 (1), 6369.
(176) Li, X. D.; Poon, C. S.; Lee, S. C.; Chung, S. S.; Luk, F. Waste
reduction and recycling strategies for the in-flight services in the airline
industry. Resour. Conserv. Recycl. 2003,37 (2), 8799.
(177) O
̈stergren, K.; Anderson, G.; Easteal, S.; Gustavsson, J.;
Hansen, O. J.; Moates, G.; Møller, H.; Politano, A.; Quested, T.;
Redlingshöfer, B.; et al. Food waste prevention: the challenge of
making appropriate denitional and methodological choices for
quantifying food waste levels. Presented at the 6th International
Conference on Life Cycle Management (LCM), Gothenburg, Sweden,
August 2528, 2013.
Environmental Science & Technology Critical Review
DOI: 10.1021/acs.est.7b00401
Environ. Sci. Technol. 2017, 51, 66186633
... Recently, several investigations have focused on the implications of the methodologies adopted for the measurement of food waste through the FSC stages (Kafa and Jaegler, 2021;Corrado et al., 2019;Xue et al., 2017). Some of these studies are focused on only a single FSC stage, the consumption stage (Dou et al., 2021;Withanage et al., 2021), but all of them show significant discrepancies in the results depending on the data sources used and the measurement methods applied (Caldeira et al., 2019a;2019b;Corrado and Sala, 2018;Delley and Brunner, 2018). ...
... Specifically, two recent important studies have applied different measurement methods to quantify the FW generated at very different scales and to different EU countries (Ammann et al., 2021;Caldeira et al., 2021), obtaining important discrepancies in the results. The variety of measurement methods to obtain FW data is wide and a complete classification is shown by Xue et al. (2017). These authors suggest that the methods can be divided into two categories: (i) direct methods, based on first-hand data, like direct weighing, compositional -3, 7-8, 11-12, 14-16, 19-20, 22, 35-36, 39, 80- analysis, diary-keeping, surveys, records, and (ii) indirect methods, derived from secondary data, like mass balances, modelling, existing data, use of factors, ratios and coefficients. ...
... Direct Methods are used to obtain data directly, which makes them, in comparison with indirect methods, expensive and slow. They are usually used in a specific FSC stage involving a limited number of participants, thus resulting in a lack of representativeness (Xue et al., 2017). On the other hand, these methods allow to obtain data of their specific study case, representing and considering the specific characteristics and circumstances of the work. ...
... When any of these elements invoke unpleasant situation or sensations, fret, phobias, disquietedness, or restlessness, the human mind enters a stressed condition or anxiety. Prolonged stressed conditions lead to a stage when the person faces the onset of anxiety symptoms, such as unusual panic situations characterized by hypertension, sweating, palpitation, chest pain, migraine, papillary dilation, shortness of breath, and so on [134,135]. According to a WHO report, more than 260 million people are suffering from depression with varying levels and approximately 800,000 people die by committing suicide every year [136]. ...
... The authors attributed this toxicity to the presence of sesquiterpenes, including α-trans-bergamotene, in the chemical profile of the EO. Matsuda et al. [134] reported that the compound β-trans-bergamotene has moderate toxicity against cancer cells and has not yet shown satisfactory results for possible use as a drug. ...
... FLW consists of food loss (FL) and food waste (FW), which often have different conceptual boundaries in terms of edibility and avoidability in the literature 2 . Although FAO has defined FL and FW clearly, the lack of consistency between the definitions challenges their dichotomous identifications; hence, they are not separated in our study and many other studies as well 2,44 . We use the generic term 'FLW' to refer to the entirety of FL and FW in this paper. ...
Full-text available
Global greenhouse gas (GHG) emissions from food loss and waste (FLW) are not well characterized from cradle to grave. Here GHG emissions due to FLW in supply chain and waste management systems are quantified, followed by an assessment of the GHG emission reductions that could be achieved by policy and technological interventions. Global FLW emitted 9.3 Gt of CO2 equivalent from the supply chain and waste management systems in 2017, which accounted for about half of the global annual GHG emissions from the whole food system. The sources of FLW emissions are widely distributed across nine post-farming stages and vary according to country, region and food category. Income level, technology availability and prevailing dietary pattern also affect the country and regional FLW emissions. Halving FLW generation, halving meat consumption and enhancing FLW management technologies are the strategies we assess for FLW emission reductions. The region-specific and food-category-specific outcomes and the trade-off in emission reductions between supply chain and waste management are elucidated. These insights may help decision makers localize and optimize intervention strategies for sustainable FLW management.
... Meskipun tampaknya tersedia makanan yang cukup untuk memberi makan populasi dunia, hampir 11 persen dari populasi global adalah rawan pangan [25] . Food and Agriculture Organization (FAO) mencatat sepertiga dari total makanan yang diproduksi untuk konsumsi terbuang setiap tahunnya sebagai Food Loss and Waste (FLW) [26]. ...
Full-text available
Food security is a priority issue that the global community must pay attention to. In the midst of the agricultural sector which was experiencing rapid growth, several country in the world, especially developing countries, were still experiencing food insecurity. This situation was exacerbated by the COVID-19 pandemic that occurred at the end of 2019, which had impacted on food security in many countries. Ef orts to reduce FLW are ongoing with the aim of reducing food loss at the production stage and along the supply chain. The need for improvement of FLW in the food supply chain itself includes the stages of production, storage and handling, processing (packaging), distribution (sales) to the consumption stage. Hence, minimizing FLW cannot be done separately. Otherwise, it must be doncollaboratively by each stakeholder involved in each stage of the Food Supply Chain.
... Spatial planning can also be considered in terms of environmental protection and socioeconomic development, for example, pig and poultry farms can be relocated to reduce the threat of high livestock density to the environment and humans Yu et al., 2019). Third, reducing red meat consumption has been shown to be the most promising option for reducing N losses (Alexander et al., 2017;Willett et al., 2019), and studies have revealed that 12% of food per capita is wasted in restaurants or school cafeterias (XHNA, 2020;Xue et al., 2017). Currently, the government is emphasizing the importance of reducing food waste by implementing the "clean your plate" initiative, while the decision to change the diet structure to include more plant-derived food has not been widely discussed. ...
Full-text available
The N footprint is considered as an indicator of potential environmental damage from N. Quantitative analysis of N footprint distribution, sources and drivers can help mitigate its negative impacts and promote sustainable N management. In this study, we constructed a city-scale food N footprint (FNF) framework for the Qinghai-Tibet Plateau (QTP) using a N mass balance approach. We quantitatively analyzed the FNF during food production and consumption on the QTP from 1998 to 2018. We used the logarithmic mean Divisa index decomposition method to analyze the driving forces of the FNF, and the decoupling of the FNF. The results showed that the per capita FNF of the QTP increased from 24.92 kg N cap-1 in 1998 to 27.70 kg N cap-1 in 2018, and the total FNF increased by 35.11% from 1998 to 2018. The spatial distribution of the FNF was uneven, with N losses from crop production and animal production being the leading contributing source to the FNF (86%). Economic development and urbanization were the main driving forces behind the FNF increase, while N consumption intensity inhibited the growth of the FNF. With the rapid growth of GDP, the FNF in the eastern part of the QTP grew relatively slowly, indicating a gradual decoupling of the FNF from economic development. To reconcile the relationship between socioeconomic drivers and the FNF, it is necessary to focus on coupling relationships between subsystems within the food production and consumption system to promote N recycling.
Food loss and waste is relevant for all stages of a food supply chain. Methodological and empirical solutions are needed to properly quantify these losses. The present paper embarks on the quantification of food loss in the Lithuanian food processing sector. This issue has not received substantial coverage in the literature yet, even though the transition economies face serious food losses due to malfunctioning markets and limited understanding of the issue of food loss and waste in general. In this paper, by exploiting the questionnaire survey, the food loss rates in the major sub-sectors of the Lithuanian food industry are assessed and the root causes behind food loss are identified. The results are then extrapolated to provide insights into the extent of food loss in the Lithuanian food industry as a whole. The results suggest that an estimated 10.9 thousand tonnes of food, or 4 kg per capita, may be lost at the processing level each year in the country. Issues related to processing operations as well as product non-compliance with commercial standards appear as the underlying causes for food loss.
Hundreds of million tons of food waste (FW) is annually generated from the household sectors. Also, it is regarded as a main conduit for the spread of antibiotic resistance genes (ARGs) in the ‘human–environment’ loop. This paper mainly reviews recent studies on the occurrence and dynamics of ARGs in FW and discusses the ins, outs, and spreads of ARGs by the vermicomposting. Our analysis shows that the concentration of FW-borne ARGs and their major hosts (human pathogens) can be effectively reduced and eliminated in the earthworm guts, respectively, due to the increased bacterial fitness cost for ARG-spreading and earthworm immune responses. Of particular interest, the removal performance could be improved by the measures including agricultural waste co-composting and enforced aeration, which concurrently lead to an elevated vermicomposting loading rate and enhanced quality of compost end-products. Furthermore, our review argues that functional microbial inoculum-feeding possibly results in microbial colonization and stable reproduction in earthworm guts. This proposed optimization approach may be instrumental to contain the spread of ARGs and increase the vermicomposting treatment efficiency at the same time.
Secondary metabolites (SMs), usually of complex structure and low molecular weight, have remarkable biological activities and, unlike the primary metabolites, are presented in low concentrations and in certain groups of plants. These, in turn, arouse great interest, not only for the biological activities exerted by plants in response to environmental stimuli, but also for the immense pharmacological activity they possess. Many are of commercial importance, not only in the pharmaceutical area, but also in the food, agronomy, perfumery, and other important sectors. In general, secondary metabolites are natural compounds produced in plants with the main objective of protection against abiotic and biotic stresses, besides having important nutritional and pharmacological aspects in human nutrition, they are also sources of aromatic additives, dyes, antioxidants and exert numerous functions. There are many ways to extract these compounds, but green chemistry can generate economic benefits in industrial chemical processes, such as reducing the need for investments in storage and effluent treatment, as well as the payment of compensation for any environmental damage. In addition, the use of bioresidues as promising sources of secondary metabolites is a promising way to promote the circular economy and take advantage of these by-products through bioactive compounds and their application as additives in new food sources. Currently one of the challenges is to produce sources of secondary metabolites from domesticated plants, since these have differences from wild ones, and the domestication process could preserve defense traits, such as changing the significantly, in addition to domestication-related climate changes, which may also attribute other characteristics to the secondary metabolites. Moreover, another interesting biotechnology applied to obtain large-scale SMs naturally produced by fungi is heterologous expression, which consists in the transcription of one or more genes from the cluster data gene of the fungi producing the target compound in a secondary host, which in most studies are yeasts or filamentous fungi. The use of these compounds in turn must be in force within the parameters allowed by legislation for food incorporation and in the industry in general, since they differ according to the sources, uses, toxicological levels, and the regulations regarding their certifications. However, secondary metabolites emerge as a promising source for new opportunities of application, emphasizing their potential to act as strong and natural additives for several industrial purposes.
Full-text available
One effort to encourage households to reduce their waste is based on educational programs. However the educational-program evaluation is nascent and there is a lack of and poor quality of proposals. This field study contributes to the filling of this literature gap. Forty-one volunteer families took part in a quasi-experimental study with two nonrandomized groups, using a pretest and posttest design. During a full year, wastes were weighed weekly (1,432 samples) and a workshop aimed at the minimizing of food-waste production behavior, home technology, and composting was offered. Significance differences (95%) were measured when a paired Student's t-test and a Chi square test were used. Four main conclusions were made. (1) The average production of food wastes in Mexico was similar to other developed countries, (2) the food-waste reduction and the workshop were not independent, (3) the workshop increased environmental awareness and capacity building, and (4) food-waste weighing was a feasible and robust tool to measure the impact of the workshop.
Full-text available
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 s161.6 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.
While food shortage remains a big concern in many regions around the world, almost one third of the total food production is discarded as food loss and waste (FLW). This is associated with about one quarter of land, water, and fertilizer used for crop production, even though resources and environmental constraints are expected to limit food production around the world. FLW reduction represents a potential opportunity to enhance both food security and environmental sustainability and therefore has received considerable attention recently. By reviewing the recent progress and new developments in the literature, this paper highlights the importance of FLW prevention as a complementary solution to address the Grand Challenge of global food security and environmental sustainability. However, raising awareness only is not enough to realize the expected FLW reduction. We identify the knowledge gaps and opportunities for research by synthesizing the strategies of FLW reduction and the barriers, including 1) filling the data gaps, 2) quantifying the socioeconomic and environmental impacts of FLW reduction strategies, 3) understanding the scale effects, and 4) exploring the impacts of global transitions. It is urgent to take more aggressive yet scientifically-based actions to reduce FLW, which require everyone's involvement along the food supply chain, including policy makers, food producers and suppliers, and food consumers.