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sustainability
Article
Nutritional and Environmental Sustainability of
Lentil Reformulated Beef Burger
Abhishek Chaudhary 1, * and Denis Tremorin 2
1Department of Civil Engineering, Indian Institute of Technology (IIT) Kanpur, Uttar Pradesh 208016, India
2Pulse Canada, Winnipeg, MB R3C 0A5, Canada; dtremorin@pulsecanada.com
*Correspondence: abhishekc@iitk.ac.in; Tel.: +91-512-259-2087
Received: 25 June 2020; Accepted: 5 August 2020; Published: 19 August 2020
Abstract:
Numerous studies have shown that replacing a portion of beef with plant-based foods in
daily diets of high-income nations can improve health, nutrition, and environmental consequences
globally. Pulses are one of the major plant-based protein foods shown to have both environmental
and nutritional benefits. For consumers to adopt more plant-based foods in their diets, more options
are needed that meet consumer demands for taste, convenience, nutrition, and sustainability along
with dietary preferences. Beef-based burger patties can be made more sustainably, nutritiously,
and cost-effectively while maintaining palatability by reformulating with a portion of pulses such
as whole cooked lentils. The aim of this study was to quantify the nutritional and environmental
benefits of such lentil-reformulated beef burgers. Here we compared the nutrient balance score
(considering 27 essential macro and micronutrients) and environmental footprints (carbon, bluewater,
water scarcity, land use, and biodiversity) of an all-beef burger with a beef burger reformulated
with a portion of cooked lentil puree. The geographic resolution of the analysis was Saskatchewan,
Canada. Results showed that partial replacement of a lean beef burger with cooked lentil puree
increased the nutrient density by ~20%, decreased the life cycle environmental footprint by ~33%,
and reduced the cost by 26%. In particular, the lentil reformulated burger had 60 times higher dietary
fiber, three times higher total folate, five times higher manganese, and 1.6 times higher selenium
than the all-beef burger. We highlight the importance of using high-spatial resolution inventory of
agricultural inputs and characterization factors (impacts per unit agricultural inputs) to obtain more
accurate environmental results. The results underscore the potential of food innovation to contribute
towards multiple global sustainable development goals.
Keywords:
lentils; pulses; nutrition; nutrient density; agriculture; carbon footprint; greenhouse gas;
beef; burgers; water scarcity; biodiversity
1. Introduction
Governments and the general public are becoming increasingly aware of the importance of dietary
sustainability for the achievement of the UN 2030 global sustainable development goals (SDGs) [
1
].
The three dimensions of sustainability are: social (e.g., nutrition), environmental, and economic. Many
studies including the recent EAT-Lancet commission’s report on sustainable food systems showed
that in order to feed healthy and nutritious diets to a projected 9 billion people by 2050 and at the
same time not transgressing the environmental planetary boundaries, meat consumption needs to be
reduced especially in high-income nations and replaced with plant-based foods [
1
–
7
]. In particular,
the high carbon footprint of beef products has received a lot of scientific and media attention over the
past decade, as a major contributor to dietary carbon footprints, and to agricultural greenhouse gas
emissions as a whole [
8
,
9
]. Beef has also been highlighted as a food with a high-water footprint [
10
,
11
],
and with a large land footprint [
12
] leading to negative consequences on biodiversity through habitat
Sustainability 2020,12, 6712; doi:10.3390/su12176712 www.mdpi.com/journal/sustainability
Sustainability 2020,12, 6712 2 of 18
loss and degradation [
13
,
14
]. In some cases though, the production of beef and other ruminants for
meat can be relatively beneficial, as grazing land and perennial forage production can provide higher
ecological benefits and ecosystems services such as carbon storage and wildlife habitat compared with
intensive crop production [15,16].
Plant-based sources of protein typically have much lower carbon, water, and land footprints
than animal-based sources of protein [
1
,
9
]. Pulses are one of the major plant-based protein foods
shown to have both environmental and nutritional benefits [
7
,
17
,
18
]. At the farm level, most pulses
do not require irrigation and are well suited for semi-arid, water-scarce regions [
19
]. Pulse crops can
fix atmospheric nitrogen and thus reduce nitrogen fertilizer requirements leading to reduced risk
of nitrogen emissions to water and lower greenhouse gas emissions [
8
]. In addition, incorporating
pulses such as peas or lentils in the crop-mix can improve soil health, yield, and protein content
of the next crop [
18
,
20
]. Per serving, pulses contain high amounts of essential vitamins, minerals,
protein, and dietary fiber, and contain no cholesterol and little fat. The consumption of beef and animal
meats also has nutritional benefits, as meat contains high amounts of balanced protein, B vitamins,
and minerals like iron and zinc per unit serving. At the dietary level, replacing a portion of meat
with pulse-based food into daily diets can simultaneously reduce environmental impacts and improve
nutritional outcomes worldwide [
7
,
21
,
22
] and this needs to be assessed at a country and individual
level. Canada is one of the largest producer of pulses worldwide and recent life cycle assessment (LCA)
studies have shown that partial replacement of refined wheat flour with Canadian yellow pea flour in
traditional cereal (wheat) based foods such as pan bread, breakfast cereals, or pasta can both improve
the nutritional density and decrease the life cycle carbon footprint by up to 10% [
7
]. In addition,
this work also demonstrated that utilizing wheat sourced from improved cropping systems (in this
case, from a diverse crop rotation vs. a monoculture rotation), also improved the carbon footprint of
the final food product. Apart from yellow peas, lentils are another category of pulses whose increased
consumption can improve the sustainability of food systems and diets [23].
Considering the environmental and nutritional benefits of pulses, they are increasingly being
included as ingredients in a range of food applications including meat alternatives. For example, pea
protein is used in Beyond Burger
®
products that imitate beef-based foods in texture and appearance
but are 100% plant-based [
24
]. Note that many plant-based meat substitute products to date are based
on soy protein isolates and not whole legumes. Many are also not fortified with iron or vitamin B12
and thus cannot be considered equivalent to meat. Regardless, consumers of beef burgers may be
reluctant to abandon them altogether in favor of purely plant-based burgers because cultural and
personal factors are key to individual food habits [
25
,
26
]. Another opportunity exists to improve the
sustainability, nutrition, and cost of beef-based burger patties by reformulating them with pulses such
as whole cooked lentils. Blended burger and blended meat applications are becoming more popular
in foodservice and retail in North America. There is an opportunity to market the sustainability and
nutritional advantages of these blended burgers with appropriate quantitative research. However,
the exact nutritional and environmental benefits of such lentil-reformulated beef burgers have not yet
been quantified. Another research gap is that most studies focus only on greenhouse gas emissions
(GHG) as the sole indicator of environmental sustainability or do not take into account production
practices while calculating the environmental impacts of foods. It is possible for a product to have
low GHG footprint but high land, water or biodiversity footprint depending upon where or how it is
grown [
9
]. Similarly, regarding nutritional sustainability of food items and diets, many studies just
focus on caloric or protein requirements while ignoring the micronutrients whose deficiency affect
over 2 billion people worldwide [27]. In addition to greenhouse gas emissions, metrics for water use,
land use efficiency, and biodiversity impacts have been identified as key indicators of interest by the
food industry. Recently, under the ambit of UNEP-SETAC Life Cycle Initiative [
28
], there have been
advancements in methodologies for water use and biodiversity impact assessment by incorporating
factors such as regional/local water scarcity [
29
] as well as endemicity and threat level of species
occurring in the region whose natural habitat is being encroached for food production purposes [30].
Sustainability 2020,12, 6712 3 of 18
The objective of this paper is to present the nutritional and environmental (GHG, bluewater,
water scarcity, land use, biodiversity) consequences of reformulating beef burger patties with whole
cooked Canadian lentils. Rather than using the country-average values, the calculated impacts will
take into consideration the exact location of the crop or beef (sub-national level) production and
irrigation water source. This will ensure that the environmental impact results are spatially explicit
and account for the spatial variability in yield, soil carbon, water scarcity, and biodiversity across
Canada. The nutritional quality of the traditional all-beef (without cooked lentils) and reformulated
(with cooked lentils) burgers is compared using the relative amounts of 27 essential nutrients and five
nutrients of health concern [7].
2. Materials and Methods
2.1. Ingredient Composition of Food Products
Recipes for traditional all-beef and lentil reformulated beef burger patty were obtained from
popular websites [
31
]. The serving size of typical beef burger patty in Canada is 4 oz (i.e., 115 g)
containing around 113.77 g of raw ground beef (~98.93% of total mass), one g of salt (0.87%) and 0.23 g
of black pepper (0.2%).
On the other hand, the lentil reformulated beef burger patty contains 75.84 g of raw ground beef
(66%), and 30.41 g of whole cooked lentils (26.5%), 7.51 g of water while the amounts of salt and pepper
remains the same as in the traditional burger patty. The formulation for this product was provided
by Lentils.org, an organization tasked with promoting the consumption of lentils in North America
and around the world. This organization is promoting this blended burger concept and has tested the
recipe. This recipe consists of 67% beef and 33% lentil puree, of which 26.5% is whole cooked lentils
and 6.5% is water. (33% lentil puree =26.5% whole cooked lentils +6.5% water.)
Since the nutrient composition of regular and lean beef differs considerably, we considered them
separately. We thus carried out the nutritional analysis for four different burger patties—regular beef,
lean beef, regular beef reformulated with lentil puree, and lean beef reformulated with lentil puree.
Lentil puree is simply 80% cooked lentils mixed with 20% water by mass. A list of ingredients used in
each of the four patty is listed in Table 1.
Table 1.
Mass of raw ingredients (g) required for the production of one serving (4 oz, 115g) of traditional
and lentil reformulated beef burger patty.
Ingredients Salt Water Whole
Cooked Lentils Black Pepper Raw Ground
Beef, Regular
Raw Ground
Beef, Lean
Regular beef burger
with lentil puree 1 7.5 30.4 0.2 75.8 0
Lean beef burger with
lentil puree 1 7.5 30.4 0.2 0 75.8
Regular beef burger 1 0 0.00 0.2 113.8 0
Lean beef burger 1 0 0.00 0.2 0 113.8
2.2. Nutrient Composition of Ingredients
The nutrient composition (per 100-g) of raw ingredients used in making beef patties is presented
in Table 2. The nutrient composition data for whole cooked green lentils was provided by independent
nutrient analysis (Silliker Canada Co., Markham, Ontario, MB, Canada) while for the other ingredients,
the values were taken from the Canadian Nutrient File [32].
Sustainability 2020,12, 6712 4 of 18
Table 2.
Nutrient composition of burger ingredients are presented, i.e., amounts of energy, 27 essential
nutrients and five nutrients of health concern per 100 g of ingredients.
Nutrient Content Per
100 g Salt Whole
Cooked Lentils Black Pepper Raw Ground
Beef, Regular
Raw Ground
Beef, Lean
Source: CNF#: 214 Independent
analysis CNF#: 198 CNF#: 2786 CNF#: 2683
Energy (kcal) 0 156 251 293 207
Water (g) 0 61.05 12.46 58.12 66.48
Protein (g) 0 12.82 10.39 16.55 19.58
Dietary fiber (g) 0 9.7 25.3 0 0
α-Linolenic Acid (mg) 0 0.05 * 0.152 0.103 0.055
Linoleic Acid (mg) 0 0.19 * 0.694 0.327 0.248
Vitamins
Total Folate (µg) 0 42.8 17 7 8
Niacin (mg) 0 2.41 * 2.11 7.775 9.442
Pantothenic acid (mg) 0 0.638 * 1.399 0.562 0.708
Riboflavin (mg) 0 0.073 * 0.180 0.185 0.228
Thiamin (mg) 0 0.169 * 0.108 0.1 0.108
Vitamin A as RAE (µg) 0 20 27 0 4
Vitamin B6(mg) 0 0.178 * 0.291 0.212 0.238
Vitamin B12 (µg) 0 0 0 2.35 2.35
Vitamin C (mg) 0 1 0 0 0
Vitamin D (µg) 0 0 * 0 0.1 0.1
Vitamin E (mg) 0 0.11 * 1.04 0.17 0.17
Vitamin K (µg) 0 1.7 * 163.7 0.5 1.8
Choline (mg) 0 32.7 * 11.3 56.4 56.4
Minerals
Calcium (mg) 24 27.6 443 11 10
Copper (mg) 0.03 0.251 * 1.33 0.1 0.082
Iron (mg) 0.33 2.6 9.71 1.8 1.8
Magnesium (mg) 1 40.8 171 17 19
Manganese (mg) 0.1 0.494 * 12.75 0.017 0.01
Phosphorous (mg) 0 132 158 136 161
Potassium (mg) 8 274 1329 231 271
Selenium (µg) 0.1 30 * 4.9 12.7 15
Zinc (mg) 0.1 1.15 1.19 4.18 4.58
Nutrients of concern
Total Fat (g) 0 0.55 3.26 24.7 13.68
Trans Fat (g) 0 0.01 * 0 0.61 0.462
Saturated Fat (g) 0 0.15 1.392 10.168 5.462
Cholesterol (mg) 0 0 0 66 60
Sugar (g) 0 0.38 0.64 0 0
Sodium (mg) 38758 6 20 60 63
* Data corresponding to these nutrients were not provided by the independent analysis and was imputed from the
data for boiled lentils from the Canadian Nutrient File (File #3393).
2.3. Calculation of the Nutritional Quality of Burger Patties
By multiplying the ingredient amounts (from Table 1) with their respective nutrient composition
values per g (from Table 2), the amounts of different nutrients in each of the four burger patties were
obtained. The nutritional quality of traditional and reformulated patties was determined using the
Nutrient Balance Concept (NBC) proposed by Fern et al. [
33
] and applied by Chaudhary et al. [
7
] for
their yellow pea reformulation study. The NBC provides an aggregated measure of nutrient density of
the foods by averaging the ratio of amount of qualifying (essential) or disqualifying (of health concern)
nutrients in 2000 kcal of a given food with their daily recommended intake values (DVs). The NBC
consists of three metrics: the Qualifying index (QI), the Disqualifying Index (DI), and the Nutrient
Balance Score (NBS).
Sustainability 2020,12, 6712 5 of 18
The QI is defined as the mean of the ratio of qualifying nutrients contained in 2000 kcal of a given
food relative to their Daily Values (DV) across qualifying nutrients Equation (1).
QIk=
2000 kcal
Ek
×PNq
j=1
ak,j
DVj
Nq(1)
where
QIk
is the QI of an individual food
k
, 2000 kcal represents the total daily energy intake to which
nutrition labelling is based in Canada [
34
], and
Ek
is the amount of calories per serving of food
k
(115 g
for patties here). The amount of each qualifying nutrient arelative to DV is represented by
ak,j/DVj
.
Nq
is the number of qualifying nutrients (q) considered (
Nq
=27) and
ak,j
is amount of nutrient
j
in
the food
k
. When the QI value is >1, the food is considered nutrient dense but if the QI value is <1,
the food is termed as energy dense [33].
The daily recommended intake values (DVs for qualifying nutrients are summarized in Table 3.
DVs are based on Dietary Reference Amounts established by National Academy of Sciences and are
based on the population coverage approach [
35
]. DV for water, protein,
α
-linolenic acid, and linoleic
acid have not been adopted in Canada [
36
]. Therefore, for these nutrients, Dietary Reference Intakes
(DRIs) from the National Academy of Sciences were used and established as the average DVs for men
and women ≥19 years of age [37].
Table 3.
Summary of Daily Values (DV) for qualifying (essential) nutrients and Mean Reference
Values (MRV) for disqualifying nutrients (of health concern) for Canadian Adults used to calculate
the Qualifying Index, Disqualifying Index, and Nutrient Balance Score for reformulated and
traditional foods.
Qualifying Nutrient Daily Value
Macronutrients
Water 3.2 L †
Protein 50 g †
Dietary Fiber 28 g *
α-Linolenic Acid 1.4 g †
Linoleic Acid 14 g †
Vitamins
Total folate/folic acid 400 µg *
Niacin 16 mg *
Pantothenic acid 5 mg *
Riboflavin 1.3 mg *
Thiamin 1.2 mg *
Vitamin A 900 µg *
Vitamin B61.7 mg *
Vitamin B12 2.4 µg *
Vitamin C 90 mg *
Vitamin D 20 µg *
Vitamin E 15 mg *
Vitamin K 120 µg *
Choline 550 mg *
Minerals
Calcium 1300 mg *
Copper 0.9 mg *
Iron 18 mg *
Magnesium 420 mg *
Manganese 2.3 mg *
Phosphorous 1250 mg *
Potassium 4700 mg *
Selenium 55 µg *
Zinc 11 mg *
Sustainability 2020,12, 6712 6 of 18
Table 3. Cont.
Qualifying Nutrient Daily Value
Disqualifying Nutrients Mean Reference Value per day
Sugar 100 g *
Sodium 2300 mg *
Total Fat 75 g *
Saturated Fat 20 g *
Cholesterol 300 mg *
* Government of Canada [
36
].
†
Daily Reference Intakes (DRIs) established by The National Academy of Sciences
were used as Daily Values for water, protein, α-Linolenic Acid, and linoleic acid [37].
The disqualifying index (DI) represents the levels of 5 nutrients of health concern d(sugar, sodium,
total fat, saturated fat, and cholesterol) in a food relative to their daily Maximal Reference Values (MRV):
DIk=
2000 kcal
Ek
×PNd
j=1
ak,j
MRVj
Nd
(2)
DIk
is the disqualifying index for food
k
. Again, 2000 kcal represents the total daily energy
intake, and
Ek
is the energy content of a serving of patty (115 g).
Nd
is the number of disqualifying
nutrients (q) considered (
Nd
=5) and
ak,j
is amount of disqualifying nutrient
j
in the food
k
. MRVs for
the five disqualifying nutrients are summarized in Table 3. Trans fatty acids were not included as a
disqualifying nutrient in this study as levels were not available for lentils in the Canadian Nutrient
File, and the Government of Canada has banned the use of partially hydrogenated oils in Canada [
38
].
When the DI value is >1, the food is termed as “compromised” because it contains one or more nutrients
of health concern in quantities higher than their maximum recommended amounts [33].
The third metric, the nutrient balance score (NBS) is simply the average of qualifying index values
of all 27 essential nutrients (Nq=27) considered here:
NBSk=100·
PNq
q=1QIq,k
Nq
(3)
NBSk
is the nutrient balance for food
k
.
QIq,k
is the qualifying index for each essential nutrient
q
in food kwhich is basically equal to the numerator term
ak,j/DVj
in Equation (1). Note that when
calculating the NBS, any
QIq,k
>1 is truncated to 1 assuming that if the daily requirement for a
specific qualifying nutrient is already met through a food, any increase in its amount will not improve
the overall nutrient density of the food. This takes care of those scenarios where a food has very
high amount of any one particular nutrient but negligible amounts of all other nutrients. A nutrient
balance score (NBS) of 100% implies that the food contains the 100% of the daily requirement of every
27 essential nutrient in a 2000 kcal diet [33].
2.4. Environmental Footprints of Boneless Beef
The life cycle greenhouse gas emissions, bluewater use, and land use footprint of 1 kg of Western
Canadian bone free beef at packers’ gate were obtained from the recently published report of the
Canadian Roundtable for Sustainable Beef (CRSB) [
16
]. They found that the carbon footprint of
bone free beef at packers’ gate is 24.5 kg of CO
2
eq. At the first life cycle stage “farming or animal
production,” 11.4 kg of CO
2
equivalents are emitted to produce one kg of live cattle weight at the farm
gate. Methane, nitrous oxide, and carbon dioxide are responsible for 57%, 30%, and 13% of the total
emissions. The major GHG sources are enteric fermentation methane emissions due to cattle digestion
(51.5%), manure production, and management (27.7%) and feed production (19.3%). On-farm energy
Sustainability 2020,12, 6712 7 of 18
use and animal transport contribute 1.3% and 0.3% to the total production stage carbon footprint
respectively [16].
After the “farming” stage, the next life cycle stage considered was “transportation between farm
and packers” that considers fuel consumption during transportation, dressing rate, and loss of animal
weight (shrinkage) during transportation. The results after this stage were 18.7 kg CO2eq. per kg of
carcass weight. As of this stage, the animal production accounted for >94% of the GHG emissions and
environmental impact, with fossil fuel consumed during transportation to packers representing about
5.5% [16].
The third life cycle stage considered was “packing” that constitutes environmental impacts due
to the packing of the meat including impacts due to the energy, water, materials such as corrugated
cardboard, polyethylene (PE) film, wood, etc., and chemicals used for cleaning and disinfection and
emitted effluents. As of this stage, the farming stage contributed to 92–95% of total GHG, water,
and land use impacts, while the transportation and packing stage contributed 3–5% and 1–2% of the
total footprint respectively [
16
]. The retail and consumption (food waste by consumers) stages of
beef life cycle were not considered as these are assumed to be same for both traditional and lentil
reformulated beef burgers.
Regarding water depletion, the Canadian Roundtable for Sustainable Beef (CRSB) report found
that on average 235 L of blue water (surface water and groundwater bodies) is required per kg of live
weight at the farm gate for Canadian beef production [
16
]. Water used for irrigation of feed crops
(mainly hay, barley, and maize) represents 81% of the total footprint (indirect footprint), while animal
water consumption (direct footprint) represents 19%. Groundwater, flowing surface water, and lake
water contribute equally about 32% of the animal water consumption.
The land footprint was found to be 93 m
2
of agricultural land per kg of live weight at the farm
gate with pasture-dedicated areas contributing 79% and feed ration (hay and barley) dedicated areas
contribute 21% of the total land footprint. Note that the land footprint varied widely (21 m
2
to 415 m
2
per kg of live weight) among the farms depending upon the grazing surfaces used [16].
The environmental footprints after the first three life cycle stages were 24.5 kg CO2eq., 508.3 L of
water depletion, and 196.4 m
2
of agricultural land occupation per kg of western Canadian bone-free
beef meat at packers’ end gate. These values were used for our regular and lean beef burger patty
environmental analysis.
2.5. Environmental Footprints of Cooked Lentils
Greenhouse gas emissions from the cultivation stage of lentils in western Canada was obtained
from recent reports prepared by (S&T)
2
Consultants Inc. for Canadian Roundtable on Sustainable Crops
(CRSC; [
39
]). They found that the carbon footprint of 1 kg of dry lentils produced in Saskatchewan
province is
−
0.1156 kg CO
2
eq. after accounting for the positive effect of Western Canadian cropping
practices (reduced tillage and reduced summer fallow) on soil organic carbon (SOC). Without accounting
for SOC, the carbon footprint of 1 kg lentils is 0.2152 kg CO2eq.
There were four major sources of production related GHG emissions. Almost 50% of the farming
stage carbon footprint of lentils can be attributed to direct/in-direct nitrous oxide (N
2
O) emissions from
the field, 26% to direct on-farm energy use for cultivation, 18% to fertilizer manufacturing, and 6%
to seeds and pesticide manufacturing. The carbon sequestration associated with SOC due to lentil
cultivation was found to be −0.331 kg CO2eq. per kg of lentil produced.
Since the burger patties contain the cooked lentils, the GHG emissions associated with the cooking
stage of lentils was also included. It was assumed that 6.67 MJ of energy from Canadian natural gas is
required to obtain 1 kg of cooked lentils as mentioned in a recent report [
40
]. The cooking conversion
factor utilized was 2.326 meaning that 1 kg of dry lentils when cooked will yield 2.326 kg of cooked
lentils. The GHG emission factor for Canadian natural gas was taken as 0.04988 kg CO
2
eq. per MJ [
41
].
Summing up the cultivation and cooking stage, the total carbon footprint of 1 kg of cooked lentils
sourced from Saskatchewan province was 0.283 kg CO2eq.
Sustainability 2020,12, 6712 8 of 18
The total water requirement of one 1 kg dry lentils grown in Saskatchewan is 1650 L according to
a recent study by Ding et al. [
42
]. In most of the divisions (census divisions) within Saskatchewan,
the lentils are rain-fed and the bluewater footprint of lentils is zero. However, some farms in division
7 and 11 of Saskatchewan are irrigated through freshwater from Lake Diefenbaker. In the irrigated
areas, around 76% of total water demand of lentils is fulfilled naturally through precipitation and the
rest (24%) through irrigation. The bluewater footprint of irrigated lentils is calculated as 398 L/kg
(
=0.24 ×1650
). The lentil area in division 7 and 11 that are irrigated was derived from a survey of
irrigated producers in Saskatchewan [
43
]. Finally, we calculated the production-weighted bluewater
and land footprint for dry lentils produced in Saskatchewan province of western Canada (detailed
calculations shown in Table 4). On average, 0.67 L of bluewater and 6.67 m
2
of cropland is used to
produce 1 kg of lentils in Saskatchewan. It was assumed that 0.77 L of water is required to obtain 1 kg
of cooked lentils [40].
Table 4.
Summary of lentil production, land footprint (yield), and bluewater footprint in each census
division of Saskatchewan for the year 2017.
Saskatchewan
Census
Division
Lentil
Production
(Tonnes)
Lentil Acres
(Harvested)
Yield
(Tonnes/Acre)
Irrigated/
Rain-Fed
Bluewater
Footprint (L/Kg)
Production ×Bluewater
Footprint
2 164,200 383,800 0.43 Rain fed 0 0
3 233,400 475,500 0.49 Rain fed 0 0
4 140,800 326,200 0.43 Rain fed 0 0
6 222,500 369,800 0.60 Rain fed 0 0
7 352,485 600,814 0.59 Rain fed 0 0
7 2515 4286 0.59 Irrigated 398 1,000,790
8 505,800 813,800 0.62 Rain fed 0 0
11 169,590 246,938 0.69 Rain fed 0 0
11 1210 1762 0.69 Irrigated 398 481,507
12 220,300 285,700 0.77 Rain fed 0 0
13 198,900 273,700 0.73 Rain fed 0 0
P=2,211,700 P=1,482,297
Weighted average Bluewater footprint for dry Saskatchewan lentils (L/kg)
1,482,297–2,211,700 =0.67
Data taken from crop production statistics of Saskatchewan government [44].
The environmental footprints from transportation, packaging, retail, and post-consumer recycling
stage of lentil life cycle were not taken into account as the impact of these stages is highly site-dependent
and within the LCA, these stages often contribute very little to the total footprint of the plant-based
foods relative to the production stage [45].
2.6. Water Scarcity Assessment
For assessing the impact of beef and lentil production on regional water scarcity, the Available
Water Remaining (AWARE) method recently proposed by Boulay et al. [
29
] was applied. This method
is an outcome of a two-year consensus building process by the Water Use in Life Cycle Assessment
(WULCA), a working group of the UNEP-SETAC Life Cycle Initiative [
28
]. The recommended method,
AWARE, is based on the quantification of the relative available water remaining per area once the
demand of humans and aquatic ecosystems has been met, answering the question: What is the potential
to deprive another user (human or ecosystem) when consuming water in this area? The resulting
characterization factor (CF) ranges between 0.1 and 100 and can be used to calculate water scarcity
footprints of agricultural products.
The total bluewater footprint of a food product is multiplied with the AWARE agricultural
characterization factor for the region where the product was produced to calculate the water
scarcity footprint:
Water Scarcity Footprint =Water consumption ×CFAWARE (4)
The unit of water scarcity footprint is m3world eq./m3consumed. The characterization factor is
limited to a range from 0.1 to 100, with a value of 1 corresponding to a region with the same amount of
Sustainability 2020,12, 6712 9 of 18
remaining water per area within a certain period of time as the world average, values <1 for regions
with less problems of scarcity than the world average and a value of 10, for example, representing
a region where there is 10 times less water remaining per area within a certain period of time as the
world average, or that it takes 10 times more surface time to generate an amount of unused water in
this region than the world average, assuming a given level of water demand [29].
The AWARE characterization factors are available at the sub-watershed level and monthly time
step, globally. The characterization factors values can be aggregated to country or county level and/or
annual time step for use with other data at the respective resolutions. Rather than using country or
province average values, we therefore derived the AWARE characterization factors at the Saskatchewan
census division level to be consistent with the crop production data that is also available at this
geographic resolution (Table 4). Since some divisions are drier and water scarce than others, using
spatially explicit characterization factors will result in more accurate results.
To this end, the Saskatchewan census divisions’ boundary shape files were overlaid with
the AWARE characterization factor shape files that provide one characterization factor for each
sub-watershed globally. The AWARE characterization factor for a particular division was then
calculated by taking the area-weighted average of characterization factors for all sub-watershed
occurring in that division. All calculations were performed in Google Earth online.
Table 5shows the calculated AWARE characterization factors per census division of Saskatchewan
along with the production-weighted average water scarcity (AWARE) footprint for Saskatchewan beef,
which came out to be 21.34 m3world eq./m3.
Table 5.
Summary of cattle production and water scarcity footprint of beef in each census division
of Saskatchewan.
Saskatchewan Census
Division
Total Cattle Production
(in Numbers of Cow) AWARE CF Production ×CF
1 72,500 3.12 226,200
2 81,900 13.4245 1,099,466
3 92,500 75.705 7,002,712
4 115,000 41.0785 4,724,027
5 75,000 3.12 234,000
6 81,900 3.12 255,528
7 85,000 41.736 3,547,560
8 70,000 35.9015 2,513,105
9 42,500 3.12 132,600
10 30,000 3.265 97,950
11 60,000 4.028 241,680
12 42,500 33.767 1,435,097
13 47,500 20.26 962,350
14 32,500 7.033 228,572
15 37,500 6.02 225,750
16 60,000 6.974 418,440
17 97,500 6.5447 638,108
18 0 5.559 0
P=1,123,800 P=23,983,148
Weighted average water scarcity (AWARE) footprint for Saskatchewan beef (m3
world eq./m3)23,983,148–1,123,800 =21.34
Cow production data taken from Statistics Canada [46].
Using a similar approach and the census division-specific production statistics of lentils from
Table 4, the average water scarcity (AWARE) footprint for Saskatchewan lentils was calculated as
0.01 m
3
world eq./m
3
. However, since the water used in irrigation of lentils comes from Lake
Diefenbaker which falls under the watershed with AWARE characterization factor as 6.02 m
3
world
eq./m
3
, this characterization factor was used to multiply the bluewater footprints of lentils to get their
water scarcity footprints.
Sustainability 2020,12, 6712 10 of 18
2.7. Biodiversity Impact Assessment
To translate the land footprint into impacts on biodiversity, the ecoregion-specific characterization
factor values provided by Chaudhary & Brooks [
30
] were used. These characterization factors give the
potential species extinctions (mammals, birds, amphibians, reptiles, and plants combined) due to per
m
2
of cropland and other land uses in each of the 804 terrestrial ecoregions of the world and were
calculated through the countryside species-area relationship model (cSAR) [30].
The characterization factors take into account the number of species within a region per unit
area (higher species density means higher projected impact due to human land use), the affinity of all
species present in the region to different land use types (higher affinity means species can survive in
human land uses and thus lower species loss) and the current extent of human encroachment of the
natural habitat of all species within the region (higher encroachment means higher projected loss) [
30
].
Similar to the AWARE model for assessing water scarcity footprint of products and processes,
the above characterization factors have been recommended as “best practice” for assessing the
biodiversity footprint of products and processes within life cycle assessment (LCA) studies by the land
use working group of the UNEP-SETAC Life Cycle Initiative [
28
]. The methodology to calculate the
biodiversity characterization factors is described below.
The characterization factors are derived using the cSAR model for each ecoregion jand for five
different human land uses (cropland, pasture, urban, plantations, and managed forests) (Equation (2)).
The characterization factors are provided separately for three levels of management intensity (light,
medium, and intense) for each land use type as more intense use implies higher impact on biodiversity
of the region. See the supplementary Table S1 of Chaudhary & Brooks [
30
] for definitions of light,
medium, and intense use cropland.
In the first step, the total number of species of taxon g(mammals, birds, amphibians, reptiles,
and plants) projected to go extinct (
Sloss,g,j
) due to human land use in each ecoregion jare calculated
using the cSAR model [30]:
Sregional
loss,g,j=Sorg,g,j·
1−
Anew,j+P16
i=1hg,i,j·Ai,j
Aorg,j
zj
(5)
where
Sorg,g,j
is the total number of species occurring in each ecoregion’s area (
Aorg,j
) before any human
intervention,
Anew,j
is the remaining natural habitat area in the ecoregion currently (in m
2
),
Ai,j
is the
current area of land use type
i
(
i
=1:16) in m
2
,
zj
is the SAR exponent for the ecoregion, and
hg,i,j
is the
affinity of the taxon gto the land use type
i
in ecoregion j. See Chaudhary & Brooks [
30
] for full details
on the model.
The model above provides projected extinctions from a particular ecoregion only, but it might be
that species occur elsewhere. In order to translate it into global extinctions, in step 2, the projected
regional extinctions from Equation (5) are multiplied with a vulnerability score (0 <VS
g,j
<1) that
takes into account the proportion of all species’ global habitat range occurring within that ecoregion
and the current International Union for Conservation of Nature (IUCN) threat status of all species in
that ecoregion. In other words, the VS accounts for the endemicity and threat status of species hosted
by a region. A VS equal to one implies that all species in the region are endemic to it and are threatened
with extinction according to IUCN Red List [47].
Sglobal
loss,g,j=Sregional
loss,g,j×VSg,j(6)
Sustainability 2020,12, 6712 11 of 18
In the third and final step, the total projected species loss in each ecoregion calculated through
Equation (6) (
Sglobal
loss,g,j
) is allocated to each individual land use type based on their area share and the
taxon affinity to them through an allocation factor ai,jsuch that 0 <ai,j<1 and 16
P
i=1
ai,j=1.
Sglobal
loss,g,i,j=Sglobal
loss,g,j∗ai,j(7)
ai,j=Ai,j(1−hg,i,j)
P16
i=1Ai,j(1−hg,i,j)(8)
When the allocated species loss for a particular taxon gEquation (6) is divided by the area of that
land use type (
Ai,j
), it provides the characterization factors reflecting projected species loss due to
1 m2of land use in ecoregion j.
The updated characterization factors of Chaudhary & Brooks [
30
] were used to compare the
biodiversity impact of traditional and reformulated beef burger patties’ life cycle. Canada has
over 50 terrestrial ecoregions differing largely in terms of species richness per unit area, amount of
remaining natural habitat, and the intensity of human land uses. Therefore, using a country-average
characterization factor might under or overestimate the impact of crop production on biodiversity.
Similar to water scarcity characterization factors, the census division-specific characterization
factors were derived by taking the area-weighted average of characterization factors for all ecoregions
occurring in that division. These characterization factors were divided by the yield of lentils in each
division to get the characterization factors in the unit–potential species loss per kg of dry lentils grown
in the division. The calculated biodiversity characterization factors for lentils per census division for
five taxa-mammals, birds, amphibians, plants, and taxa-aggregated characterization factors are shown
in Table 6. Similar to lentil (crop land use), the biodiversity characterization factors for pasture land
use in each of the census division of Saskatchewan were calculated (see Table 7).
Table 6.
Characterization factors (in potential species loss per kg
×
10
−12
) for assessing the biodiversity
footprint of lentils grown in different census divisions of Saskatchewan, Canada. The characterization
factors are zero for census divisions 5, 14, and 18 because the lentil production in these divisions is
zero. The aggregated characterization factors are in the unit–potentially disappeared fraction (PDF) per
kg ×10−12. See Chaudhary & Brooks [30] for details.
Census
Division
Mammals
(PSL/Kg)
Birds
(PSL/Kg)
Amphibians
(PSL/Kg)
Reptiles
(PSL/Kg)
Plant
(PSL/Kg)
Aggregated
(PDF/Kg)
1 4.25 11.6 0.857 0.375 39.6 0.127
2 10.7 23.4 1.82 1.12 64.3 0.268
3 12 20.9 1.58 1.18 30.3 0.25
4 12.4 23.6 1.81 1.25 47 0.277
5 0 0 0 0 0 0
6 4.87 13.2 0.992 0.454 46 0.145
7 8.88 17.3 1.33 0.902 36.8 0.202
8 9.28 16.5 1.25 0.922 25.6 0.197
9 4.75 12.7 0.845 0.215 29.7 0.137
10 3.48 9.46 0.644 0.233 28.1 0.103
11 5.00 13.8 1.09 0.546 52.5 0.151
12 4.59 11.9 0.931 0.482 42.1 0.132
13 5.33 12.3 0.93 0.524 35 0.138
14 0 0 0 0 0 0
15 2.99 8.02 0.545 0.166 21 0.0867
16 2.61 6.92 0.465 0.102 14.6 0.0744
17 3.10 8.17 0.551 0.109 16.1 0.0877
18 0 0 0 0 0 0
Sustainability 2020,12, 6712 12 of 18
Table 7.
Characterization factors (in potential species loss per kg
×
10
−12
) for assessing the
biodiversity footprint of beef grown in different census divisions of Saskatchewan province of Canada.
The aggregated characterization factors are in the unit–potentially disappeared fraction (PDF) per
kg ×10−12.
Census
Division
Mammals
(PSL/Kg)
Birds
(PSL/Kg)
Amphibians
(PSL/Kg)
Reptiles
(PSL/Kg)
Plant
(PSL/Kg)
Aggregated
(PDF/Kg)
10.69 1.88 0.14 0.06 5.85 0.02
21.14 2.48 0.19 0.11 6.24 0.03
31.46 2.56 0.19 0.13 3.37 0.03
41.33 2.53 0.19 0.12 4.59 0.03
50.54 1.45 0.09 0.03 3.68 0.02
60.73 1.98 0.15 0.06 6.27 0.02
71.30 2.52 0.19 0.12 4.89 0.03
81.44 2.55 0.19 0.13 3.61 0.03
90.55 1.49 0.10 0.02 3.13 0.02
10 0.57 1.56 0.11 0.04 4.24 0.02
11 0.86 2.35 0.18 0.09 8.18 0.03
12 0.88 2.29 0.18 0.08 7.36 0.03
13 0.97 2.21 0.17 0.09 5.78 0.02
14 0.56 1.52 0.10 0.02 2.58 0.02
15 0.57 1.55 0.10 0.03 3.66 0.02
16 0.55 1.51 0.10 0.02 2.83 0.02
17 0.56 1.52 0.10 0.02 2.64 0.02
18 0.46 1.44 0.08 0.0004 0.79 0.01
Out of a total of 7.55649 million hectares of land devoted to cattle production in Saskatchewan,
88% is for grazing (pasture) and 12% is for growing cattle feed crops (see Figure 3.5 on page 109
of report by CRSB [
16
]). For calculating the characterization factors per kg beef, the area-weighted
average of crop and pasture characterization factors for each census division were taken. Finally,
the production-weighted characterization factors for Saskatchewan province were calculated for each
taxa for use in biodiversity assessment of a typical beef burger patty (see Table 8).
Table 8.
Production-weighted average characterization factors (CFs in potential species loss per
kg ×10−12
) for assessing the biodiversity footprint of beef and lentils in Saskatchewan province of
Canada. The taxa aggregated characterization factors are in the unit—potentially disappeared fraction
(PDF) per kg
×
10
−12
. These characterization factors were multiplied by amounts of lentil, wheat,
and beef in the products to calculate the biodiversity footprint of traditional and reformulated foods.
Taxon Biodiversity CFs Lentils (PLS/Kg) Biodiversity CFs Beef (PLS/Kg)
Mammals 8.05 182.71
Birds 16.44 407.39
Amphibians 1.26 29.90
Reptiles 0.81 14.86
Plants 38.33 912.21
Taxa aggregated
0.19 4.59
3. Results
3.1. Nutritional Quality Comparison of Traditional and Reformulated Beef Burgers
It is clear from Table 2that the amounts of essential nutrients such as dietary fiber, folate,
thiamin, vitamins A, C, and minerals such as calcium, iron, magnesium, manganese, and selenium
are much higher in lentils compared with beef. On the other hand, the amounts of calories, protein,
niacin, riboflavin, Vitamin B6, B12, D, E, and choline are higher in the beef than lentils. Importantly,
the amounts of nutrients of health concern such as sodium, fat, and cholesterol are several times higher
Sustainability 2020,12, 6712 13 of 18
in beef than lentils. Also, the amounts of essential nutrients in lean beef are in general higher than
regular beef.
Table 9shows that replacing a portion of beef with lentils improves the nutrient density (measured
through nutrient balance score, NBS [
33
], Equation (3)) by >20% compared with traditional beef burger.
Highest NBS of 64 is for lean beef burger reformulated with cooked lentil puree while the lowest NBS
of 46 is for regular beef burger.
Table 9.
Nutrient balance score (NBS [
33
], Equation (3)) for traditional and lentil reformulated
beef burgers.
Type of Burger (One Serving =115 g) Nutrient Balance Score
Regular beef burger 45.62
Regular beef burger with lentil puree 56.18
Lean beef burger 54.77
Lean beef burger with lentil puree 63.86
In terms of individual nutrients, replacing regular beef with cooked lentils increased the amount
of 21 out of 27 essential nutrients considered while the amount of six essential nutrients were similar
in both traditional and reformulated burgers. In particular, the reformulated burger has 60
×
higher
dietary fiber, three times higher total folate, five times higher manganese, and 1.6 times higher selenium
than a regular beef burger.
The amounts of disqualifying nutrients (fat, trans fat, saturated fat, and cholesterol) in lentil
reformulated burger were ~17% less than the regular beef burger while the amounts of sugar and
sodium in regular and reformulated burgers were almost at the same level. The results therefore
show that beef burgers reformulated with cooked lentils are much more nutrient dense than regular
beef burgers.
3.2. Environmental Characterization Factors for Ingredients of Beef Burgers
Table 10 presents the carbon, bluewater, water scarcity, land use, and biodiversity characterization
factors (CFs per kg) of dry lentils, cooked lentils, and boneless beef produced in Saskatchewan province
of western Canada. It can be seen that the biodiversity footprint of 1 kg boneless beef is 32
×
higher
than that of 1 kg of cooked lentils. The land used to produce 1 kg of boneless beef is ~40
×
higher than
land used to produce 1 kg of cooked lentils.
Table 10.
Environmental characterization factors (CFs) of ingredients (per kg) used to make the
traditional and reformulated beef burgers. Biodiversity footprint is in taxa-aggregated potentially
disappeared fraction (PDF).
Product Greenhouse Gas (kg
CO2eq.) Bluewater (L) Water Scarcity
(m3World eq.) Land (m2)Biodiversity
(PDF)
Dry lentils at farm, 1 kg −0.1156 0.67 4.033 6.6736 1.90 ×10−13
Lentils, cooked, 1 kg 0.283 0.29 1.734 2.8691 1.43 ×10−13
Boneless beef at packers
end gate, 1 kg 24.5 508.30 10847 196.4 4.59 ×10−12
For the beef production, the farming or animal production stage contributed to 92–95% of total
GHG, water, and land use impacts, while the transportation and packing stage contributed 3–5% and
1–2% of the total footprint respectively (see CRSB report [
16
] for full LCA). In contrast, the cooking
stage contributed almost 100% to the total carbon footprint of cooked lentils while the lentil cultivation
stage contributed almost no GHG emissions (see report hosted by Canadian roundtable for sustainable
crops [
39
]. Also, in contrast with beef, the blue water footprint of the cultivation stage of lentil
production is almost zero because the majority of lentils are rain-fed in Saskatchewan.
Sustainability 2020,12, 6712 14 of 18
These characterization factors from Table 10 were multiplied with amounts of each ingredients in
each product (see Table 1) to get the final environmental footprint of burgers presented in Table 11.
The footprints of other burger ingredients such as black pepper and salt are negligible due to very
small amounts used and thus were not considered here.
Table 11.
Environmental footprints one serving (115g) of traditional and lentil reformulated beef
burgers. Biodiversity footprint is in taxa-aggregated potentially disappeared fraction (PDF).
Type of Burger (One
Serving =115 g)
Greenhouse Gas
(Kg CO2eq.) Bluewater (L) Water Scarcity
(m3World eq.) Land (m2)Biodiversity
(PDF)
Regular beef burger
with lentil puree 1.87 38.59 823 14.98 3.53 ×10−13
Regular beef burger 2.79 57.83 1234 22.34 5.22 ×10−13
% reduction 33.03 33.31 33.33 32.95 32.50
3.3. Environmental Footprint Comparison of Traditional and Reformulated Beef Burgers
Table 11 presents the per serving environmental footprint comparison of traditional and lentil
reformulated beef burgers. It can be seen that the environmental footprints reduce by ~33% when the
beef burgers are reformulated with cooked lentils.
4. Discussion
Results from this study demonstrate that 33% replacement of ground beef with cooked lentil
puree can decrease the environmental footprint by ~33% and concurrently increase the nutritional
density (nutrient balance score) of beef burgers by ~20%. These results contribute to the growing body
of scientific evidence on the potential for pulses to improve the nutritional and environmental profile
of individual foods, diets, and national food systems [1,4,7].
Although the calorie and protein content per unit weight is higher for beef (Table 2), the overall
nutrient density is higher for lentil reformulated burger than regular beef burger (Table 9). The increase
in nutrient density is primarily due to much higher levels of dietary fiber, manganese, and selenium in
lentils than in beef. Thus, our analysis shows the importance of considering all essential nutrients when
comparing the nutritional implications of dietary change or food substitutions. Focusing solely on
calories or protein can provide misleading results with negative consequences on nutritional security
of the region.
The major strength of this environmental footprint analysis is that rather than using site-generic or
globally/country averaged emission factors from different databases, we used Saskatchewan-specific
datasets for lentil and beef production. For example, as shown in Table 5, the country-average AWARE
characterization factor for water scarcity in Canada is 6.578 m
3
world eq./m
3
[
29
], which is almost three
times less than the average characterization factor for Saskatchewan beef (21.34 m
3
world eq./m
3
).
This is because Saskatchewan is drier than the majority of other regions in Canada. Even within the
province of Saskatchewan, the water scarcity characterization factors varied over 20 times from 3.12 m
3
world eq./m
3
in divisions 1, 5, 6, and 9 to 75.7 m
3
world eq./m
3
in division 3. The bluewater footprint
of Saskatchewan lentils is almost zero (Table 4) because they are produced through rain-fed agriculture.
This is in striking contrast with the global average bluewater footprint of lentils which is 489 L/kg
according to Mekonnen & Hoekstra [10].
Similarly, the biodiversity characterization factors also vary considerably across Canada, and using
a country-average value is not appropriate. Even within the Saskatchewan province, the biodiversity
characterization factors vary by a factor of two across the 18 census divisions (Table 7). Regarding our
carbon footprint analysis, we relied on a report that takes into account the positive effect of Western
Canadian cropping practices (reduced tillage and reduced summer fallow) on soil organic carbon
(SOC) which is often absent in other parts of the world. This shows the importance of including
all stages when carrying out LCA of food products. Even without accounting for SOC effects, the
carbon footprint of 1 kg lentils in Saskatchewan is 0.2152 kg CO
2
eq. which is about five times lower
Sustainability 2020,12, 6712 15 of 18
than the world average value provided in other studies [
8
]. Compared to beef produced in the USA,
the environmental footprints of Canadian beef are much lower. For example, Rotz et al. [
48
] found
that the carbon and water depletion footprint of US beef to be 29.1 kg CO
2
eq. and 2221 litres per
kg of bone-free beef meat at packers’ end gate. The corresponding values for Canadian beef are
24.5 kg CO
2
eq. and 508 L per kg. This demonstrates the importance of working with high geographic
resolution and site-specific values when conducting the environmental footprint analysis of food
products. Using country or global average values from existing meta-analysis or literature can lead to
misleading results in the case of food products’ environmental footprints [9].
Nutritional and environmental benefits of lentil reformulated burger might not be sufficient
for its widespread adoption because cost is perceived as a major factor for many consumers [
6
,
49
].
However, the price of lean ground beef and raw lentils in Canada is 5.79 US$ per kg and 3.41 US$ per
kg respectively, meaning that the cost per serving (115 g) of regular and reformulated beef burgers is
0.65$ and 0.48$ respectively. Therefore, the lentil reformulated burger is 26% cheaper than regular beef
burger. Partial replacement of beef with lentils in a burger demonstrates a win-win scenario for all
three dimensions (nutrition, environment, and economics) of sustainability.
One of the limitations of our biodiversity analysis is that our characterization factors reflect the
negative impact of conversion of native forests or grasslands to agriculture and pasture land use on
plants and terrestrial vertebrates (mammals, birds, amphibians, and reptiles) only and do not take
into account the impact on other species groups such as invertebrates, soil bacteria, fungi, etc. This is
because the underlying data to calculate the characterization factor for invertebrates, soil bacteria,
and fungi are not available yet through the International Union for Conservation of Nature (IUCN) [
47
].
In addition, a method adapted to Canadian agro-ecosystems and considering multiple species groups
may better reflect the differences in biodiversity impact between pasture and cultivated crops [
16
].
Impact on other indicators of biodiversity such as evolutionary history loss should also be studied [
50
].
Regardless, since the objective was to calculate the relative impact of regular and lentil-reformulated
burger, the selected biodiversity characterization factors are able to achieve this.
Since the environmental impacts calculated or compiled here for Saskatchewan were so different
than national or world average values, future studies should carry out similar comparisons of regular
and reformulated beef burgers based on data from other major beef and lentil producing regions and
production systems. Using beef and lentil production data from other regions might change the relative
difference in environmental impacts of the two burgers as calculated here using Saskatchewan-specific
values. In this study, five indicators of environmental impact are calculated but it should be expanded
in future to also include other indicators such as human toxicity, air, water pollution, or impact on
ecosystem services. A widespread adoption of lentil reformulated burger would entail cutting down
on production of beef and increasing the production of lentils worldwide. A global scale feasibility
study is therefore needed that can also model the consequences of such a production shift on social,
environmental, and economic dimensions of sustainability. Instead of lentils, future studies might also
explore the sustainability implications of incorporating other plant-based foods in beef burgers.
5. Conclusions
Overall, our analysis demonstrates the potential of food innovation and reformulation of existing
recipes to contribute towards multiple sustainable development goals and complement other efforts
such as reducing food waste [
1
], dietary behaviour change [
4
], and others [
1
]. Our multi-dimensional
quantitative sustainability analysis can provide a template for future studies looking at benefits of
partial or full substitution of animal sourced food products with plant-based products in different
regions of the world. To conclude, inclusion of higher amounts of pulses in traditional meat-based
products could bring substantial environmental advantages and a more nutritionally balanced diet
without jeopardizing the affordability or nutrient composition.
Author Contributions:
A.C. and D.T. contributed to the study design, data analysis, interpretation, and writing
of the manuscript. Both authors critically reviewed the manuscript for intellectual content. Conceptualization,
Sustainability 2020,12, 6712 16 of 18
A.C. and D.T.; methodology, A.C. and D.T.; software, A.C.; validation, A.C. and D.T.; formal analysis, A.C.;
investigation, A.C. and D.T.; resources, A.C. and D.T.; data curation, A.C. and D.T.; writing—original draft
preparation, A.C.; writing—review and editing, A.C. and D.T.; visualization, A.C.; supervision, A.C. and D.T.;
project administration, A.C. and D.T.; funding acquisition, A.C. and D.T. All authors have read and agreed to the
published version of the manuscript.
Funding:
The present study was funded by Pulse Canada. A.C. acknowledges funding from the Initiation Grant
of IIT Kanpur, India (project number 2018386). D.T. acknowledges funding from the Canadian Agricultural
Partnership from the Government of Canada.
Conflicts of Interest: D.T. is an employee of Pulse Canada. A.C. declares no conflict of interest.
References
1.
Willett, W.; Rockström, J.; Loken, B.; Springmann, M.; Lang, T.; Vermeulen, S.; Garnett, T.; Tilman, D.;
de Clerck, F.; Wood, A.; et al. Food in the Anthropocene: The EAT–Lancet Commission on healthy diets from
sustainable food systems. Lancet 2019,393, 447–492. [CrossRef]
2.
Adhikari, L.; Tuladhar, S.; Hussain, A.; Aryal, K. Are Traditional Food Crops Really ‘Future Smart
Foods?’A Sustainability Perspective. Sustainability 2019,11, 5236. [CrossRef]
3.
Kim, D.; Parajuli, R.; Thoma, G.J. Life Cycle Assessment of Dietary Patterns in the United States: A Full Food
Supply Chain Perspective. Sustainability 2020,12, 1586. [CrossRef]
4.
Chaudhary, A.; Krishna, V. Country-specific sustainable diets using optimization algorithm.
Environ. Sci. Technol. 2019,53, 7694–7703. [CrossRef] [PubMed]
5.
Weinrich, R. Opportunities for the adoption of health-based sustainable dietary patterns: A review on
consumer research of meat substitutes. Sustainability 2019,11, 4028. [CrossRef]
6.
Blanco-Murcia, L.; Ramos-Mej
í
a, M. Sustainable Diets and Meat Consumption Reduction in Emerging
Economies: Evidence from Colombia. Sustainability 2019,11, 6595. [CrossRef]
7.
Chaudhary, A.; Marinangeli, C.; Tremorin, D.; Mathys, A. Nutritional combined greenhouse gas life cycle
analysis for incorporating Canadian yellow pea into cereal-based food products. Nutrients
2018
,10, 490.
[CrossRef]
8.
Clune, S.; Crossin, E.; Verghese, K. Systematic review of greenhouse gas emissions for different fresh food
categories. J. Clean. Prod. 2017,140, 766–778. [CrossRef]
9.
Poore, J.; Nemecek, T. Reducing food’s environmental impacts through producers and consumers. Science
2018,360, 987–992. [CrossRef]
10.
Mekonnen, M.M.; Hoekstra, A.Y. The Green, Blue and Grey Water Footprint of Crops and Derived Crop Products;
Report No. 47; UNESCO-IHE Institute for Water Education: Delft, The Netherlands, 2010.
11.
Mekonnen, M.M.; Hoekstra, A.Y. A global assessment of the water footprint of farm animal products.
Ecosystems 2012,15, 401–415. [CrossRef]
12.
Eshel, G.; Shepon, A.; Makov, T.; Milo, R. Land, irrigation water, greenhouse gas, and reactive nitrogen
burdens of meat, eggs, and dairy production in the United States. Proc. Natl. Acad. Sci. USA
2014
,111,
11996–12001. [CrossRef] [PubMed]
13.
Selinske, M.J.; Fidler, F.; Gordon, A.; Garrard, G.E.; Kusmanoff, A.M.; Bekessy, S.A. We have a steak in it:
Eliciting interventions to reduce beef consumption and its impact on biodiversity. Cons. Lett.
2020
, e12721.
[CrossRef]
14.
Dalin, C.; Outhwaite, C.L. Impacts of Global Food Systems on Biodiversity and Water: The Vision of Two
Reports and Future Aims. One Earth 2019,1, 298–302. [CrossRef]
15.
Steinfeld, H.; Mooney, H.; Schneider, F.; Neville, L. Livestock in a Changing Landscape, Volume 1: Drivers,
Consequences, and Responses; Island Press: Washington, DC, USA, 2013.
16.
Canadian Roundtable for Sustainable Beef. National Beef Sustainability Assessment—Environmental and Social
Life Cycle Assessments; Deloitte: Calgary, AB, Canada, 2016. Available online: https://crsb.ca/assets/Pages/
Sustainability-Benchmarking/Assessment/8e68cb86c3/NBSA-EnvironmentalAndSocialAssessments.pdf
(accessed on 15 November 2019).
17.
Marinangeli, C.P.; Curran, J.; Barr, S.I.; Slavin, J.; Puri, S.; Swaminathan, S.; Tapsell, L.; Patterson, C.A.
Enhancing nutrition with pulses: Defining a recommended serving size for adults. Nutr. Rev.
2017
,75,
990–1006. [CrossRef] [PubMed]
Sustainability 2020,12, 6712 17 of 18
18.
MacWilliam, S.; Parker, D.; Marinangeli, C.P.; Tr
é
morin, D. A meta-analysis approach to examining the
greenhouse gas implications of including dry peas (Pisum sativum L.) and lentils (Lens culinaris M.) in crop
rotations in western Canada. Agric. Syst. 2018,166, 101–110. [CrossRef]
19.
Angadi, S.V.; McConkey, B.G.; Cutforth, H.W.; Miller, P.R.; Ulrich, D.; Selles, F.; Volkmar, K.M.; Entz, M.H.;
Brandt, S.A. Adaptation of alternative pulse and oilseed crops to the semiarid Canadian Prairie: Seed yield
and water use efficiency. Can. J. Plant Sci. 2008,88, 425–438. [CrossRef]
20.
Lupwayi, N.Z.; Kennedy, A.C. Grain Legumes in Northern Great Plains. Agron. J.
2007
,99, 1700–1709.
[CrossRef]
21.
Mitchell, D.C.; Lawrence, F.R.; Hartman, T.J.; Curran, J.M. Consumption of dry beans, peas, and lentils could
improve diet quality in the US population. J. Am. Diet. Assoc. 2009,109, 909–913. [CrossRef]
22.
Mudryj, A.N.; Yu, N.; Hartman, T.J.; Mitchell, D.C.; Lawrence, F.R.; Aukema, H.M. Pulse consumption in
Canadian adults influences nutrient intakes. Br. J. Nutr. 2012,108 (Suppl. S1), S27–S36. [CrossRef]
23.
Yadav, S.S.; McNeil, D.; Stevenson, P.C. (Eds.) Lentil: An Ancient Crop for Modern Times; Springer Science &
Business Media: Berlin/Heidelberg, Germany, 2007; Available online: https://link.springer.com/content/pdf/
10.1007/978-1-4020-6313-8.pdf (accessed on 10 November 2019).
24.
Heller, M.C.; Keoleiank, G.A. Beyond Meat’s Beyond Burger Life Cycle Assessment: A Detailed Comparison
between a Plant-based and an Animal-Based Protein Source. CSS18-10. Available online: https://css.umich.
edu/sites/default/files/publication/CSS18-10.pdf (accessed on 25 July 2019).
25.
Verbeke, M. Functional foods: Consumer willingness to compromise on taste for health? Food Qual. Prefer.
2006,17, 126–131. [CrossRef]
26.
Tobler, C.; Visschers, V.H.M.; Siegrist, M. Eating green. Consumers’ willingness to adopt ecological food
consumption behaviors. Appetite 2011,57, 674–682. [CrossRef] [PubMed]
27.
Tulchinsky, T.H. Micronutrient deficiency conditions: Global health issues. Public Health Rev.
2010
,32, 243.
[CrossRef]
28.
UNEP/SETAC Life Cycle Initiative. Global Guidance for Life Cycle Impact Assessment Indicators—Volume
1, Chapter-6; United Nations Environment Programme: Paris, France, 2016. Available online: http:
//www.lifecycleinitiative.org/training-resources/global-guidance-lcia-indicators-v-1/(accessed on 19 October
2019).
29.
Boulay, A.M.; Bare, J.; Benini, L.; Berger, M.; Lathuilli
è
re, M.J.; Manzardo, A.; Margni, M.; Motoshita, M.;
N
ú
ñez, M.; Pastor, A.V.; et al. The WULCA consensus characterization model for water scarcity footprints:
Assessing impacts of water consumption based on available water remaining (AWARE). Int. J. LCA.
2018
,23,
368–378. [CrossRef]
30.
Chaudhary, A.; Brooks, T.M. Land use intensity-specific global characterization factors to assess product
biodiversity footprints. Environ. Sci. Technol. 2018,52, 5094–5104. [CrossRef] [PubMed]
31.
Saskatchewan Pulse Growers. Classic Beef Lentil Burger Recipe. Available online: https://www.lentils.org/
recipe/classic-beef-lentil-burger/(accessed on 18 October 2019).
32.
Government of Canada. Canadian Nutrient File. Government of Canada. Available online: https:
//food-nutrition.canada.ca/cnf-fce/index-eng.jsp (accessed on 18 October 2019).
33.
Fern, E.B.; Watzke, H.; Barclay, D.V.; Roulin, A.; Drewnowski, A. The Nutrient Balance Concept: A New
Quality Metric for Composite Meals and Diets. PLoS ONE 2015,10, e0130491. [CrossRef] [PubMed]
34.
The Canadian Food Inspection Agency. Food Labeling for Industry: Information within the Nutrition
Facts Table—Daily Value and % Daily Value. Available online: http://www.inspection.gc.ca/food/
labelling/food-labelling-for-industry/nutrition-labelling/information-within-the-nutrition-facts-table/eng/
1389198568400/1389198597278?chap=0(accessed on 12 October 2019).
35.
Government of Canada. Regulations Amending the Food and Drug Regulations (Nutrition Labelling, Other
Labelling Provisions and Food Colours); Government of Canada: Gatineau, QC, Canada, 2016.
36. Government of Canada. Table of Daily Values. Available online: https://www.canada.ca/en/health-canada/
services/technical-documents-labelling-requirements/table-daily- values.html (accessed on 2 October 2019).
37.
National Academy of Sciences. Table: DRI Values Summary. Available online: http:
//www.nationalacademies.org/hmd/~{}/media/Files/Activity%20Files/Nutrition/DRI-Tables/5Summary%
20TableTables%2014.pdf?la=en (accessed on 4 October 2019).
Sustainability 2020,12, 6712 18 of 18
38.
Government of Canada. Notice of Modification—Prohibiting the Use of Partially Hydrogenated Oils
(PHOs) in Foods. Available online: https://www.canada.ca/en/health-canada/services/food-nutrition/
public-involvement-partnerships/modification-prohibiting-use-partially-hydrogenated-oils-in-foods/
information-document.html (accessed on 17 October 2019).
39.
Canadian Roundtable for Sustainable Crops. GHG Emissions & Air Quality. Available online: https:
//crsccsmp.azurewebsites.net/home/criterion/2(accessed on 17 October 2019).
40.
Dettling, J.; Tu, Q.; Faist, M.; DelDuce, A.; Mandlebaum, S. A Comparative Life Cycle Assessment of Plant-Based
Foods and Meat Foods; Quantis USA: Boston, MA, USA, 2016. Available online: https://www.morningstarfarms.
com/content/dam/morningstarfarms/pdf/MSFPlantBasedLCAReport_2016-04-10_Final.pdf (accessed on 5
October 2019).
41.
Canada Energy Regulator. Greenhouse Gas (GHG) Emissions Overview. Available online: https://www.cer-
rec.gc.ca/nrg/sttstc/lctrct/rprt/2017cndrnwblpwr/ghgmssn-eng.html (accessed on 5 October 2019).
42.
Ding, D.; Zhao, Y.; Guo, H.; Li, X.; Schoenau, J.; Si, B. Water Footprint for Pulse, Cereal, and Oilseed Crops in
Saskatchewan, Canada. Water 2018,10, 1609. [CrossRef]
43.
Saskatchewan Irrigation Crop Diversification Corporation. Irrigation Crop Survey. Available online:
https://irrigationsaskatchewan.com/icdc/irrigation-crop-survey/(accessed on 5 October 2019).
44.
Saskatchewan Crop District Production Statistics. Available online: https://www.saskatchewan.ca/
business/agriculture-natural-resources-and-industry/agribusiness-farmers-and-ranchers/market-and-
trade-statistics/crops-statistics/crop-district-production (accessed on 29 October 2019).
45.
Roy, P.; Nei, D.; Orikasa, T.; Xu, Q.; Okadome, H.; Nakamura, N.; Shiina, T. A review of life cycle assessment
(LCA) on some food products. J. Food Eng. 2009,90, 1–10. [CrossRef]
46.
Statistics Canada. Total Beef Cows by Census Division (CD). 2016. Available online: https://www150.statcan.
gc.ca/n1/pub/95-634-x/2017001/article/54906/catm-ctra-308-eng.htm (accessed on 15 October 2019).
47.
International Union for Conservation of Nature (IUCN) Red List. Available online: https://www.iucnredlist.
org/(accessed on 25 October 2019).
48. Rotz, C.A.; Asem-Hiablie, S.; Place, S.; Thoma, G. Environmental footprints of beef cattle production in the
United States. Agric. Syst. 2019,169, 1–13. [CrossRef]
49.
Hirvonen, K.; Bai, Y.; Headey, D.; Masters, W.A. Affordability of the EAT–Lancet reference diet: A global
analysis. Lancet Glob. Health 2020,8, e59–e66. [CrossRef]
50.
Chaudhary, A.; Mooers, A. Terrestrial vertebrate biodiversity loss under future global land use change
scenarios. Sustainability 2018,10, 2764. [CrossRef]
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