Soil Science Society of America Journal
Soil Sci. Soc. Am. J. 80:1121–1134
Received 14 June 2016.
Accepted 22 Aug. 2016.
*Corresponding author (email@example.com; firstname.lastname@example.org).
© Soil Science Society of America, 5585 Guilford Rd., Madison WI 53711 USA. All Rights reserved.
Effect of Enhanced Efciency Fertilizers on Nitrous
Oxide Emissions and Crop Yields: A Meta-analysis
Review & Analysis–Soil Fertility & Plant Nutrition
Enhanced efciency fertilizers (EEFs) have the potential to reduce N2O emis-
sions and improve crop productivity, but the impact of soil and management
conditions on their effectiveness is not clear. We conducted a meta-analysis
to evaluate the effectiveness of different EEF types in reducing N2O emissions
in three cereal production systems: rice (Oryza sativa L.), corn (Zea mays L.),
and wheat (Triticum aestivum L.). We also compared EEF efcacy across soil
and management conditions for corn and wheat systems. Results showed that
the effect of EEFs on N2O emissions and crop yields varied greatly with their
modes of action, soil types, and management conditions. Nitrication inhibi-
tors (NIs), double inhibitors (DIs: urease plus nitrication inhibitors), and
controlled-release N fertilizers (CRFs) consistently reduced N2O emissions
compared with conventional N fertilizers across soil and management condi-
tions (grand mean decreases of 38, 30, and 19%, respectively). The DIs more
effectively reduced N2O emissions in alkaline soils than did NIs, but the trend
was reversed in acidic soils. Urease inhibitors also reduced N2O emissions
compared with conventional N fertilizers in coarse-textured soils and irrigated
systems. Overall crop yields increased by 7% with the addition of NIs alone.
Compared with conventional N fertilizers, DIs also increased crop yields in
alkaline soils, coarse-textured soils, and irrigated systems. However, CRFs had
no effect on crop yields. Overall, this study suggests that NIs or DIs can reduce
N2O emissions while improving crop yields. Growers should select EEFs based
on their soil and management conditions to maximize their effectiveness.
Abbreviations: CI, condence interval; CRF, controlled-release nitrogen fertilizer; DCD,
dicyandiamide; DI, double inhibitor; DMPP, 3,4-dimethylpyrazol phosphate; EEF,
enhanced efciency fertilizer; NBPT, N-(N-butyl)-thiophosphoric triamide; NI, nitrication
inhibitor; UI, urease inhibitor.
Nitrous oxide is a potent greenhouse gas and the single most ozone-layer-
depleting substance (Ravishankara et al., 2009). Atmospheric N2O con-
centrations have risen from about 270 mg L−1 during the preindustrial
era to approximately 327 mg L−1 today (Blasing, 2015). Nitrous oxide is mainly
emitted as an intermediate byproduct from soils during the oxidation of NH4+ to
NO3− by nitrifiers (nitrification) and also during the reduction of NO3− to N2
by denitrifiers (denitrification). Industrial agriculture has made substantial contri-
butions to N2O buildup in the atmosphere, mainly through the production and
consumption of synthetic N fertilizers (Denman et al., 2007; Snyder et al., 2009).
Globally, 50% of synthetic N fertilizers are applied to three major cereal crops (rice,
corn, and wheat), which supply the bulk of food calories and proteins to humans ei-
ther directly as grains or indirectly through livestock products (Ladha et al., 2016).
Even with recent gains in crop productivity, more than a billion persons worldwide
lack access to food (Foley et al., 2011). Meeting the future food demands of an
additional 2 to 3 billion persons by 2050 will require dramatic increases in cereal
crop production, which will further increase the production and consumption of
Dep. of Soil Science
School of Natural Resource Sciences
North Dakota State Univ.
Fargo, ND 58108-6050
Columbia Basin Agricultural
Oregon State Univ.
Adams, OR 97810
Devan A. McGranahan
Range Science Program
School of Natural Resource Sciences
North Dakota State Univ.
Fargo, ND 58108-6050
Dep. of Soil Science
School of Natural Resource Sciences
North Dakota State Univ.
Fargo, ND 58108-6050
•Effectiveness of EEFs varied greatly
with their modes of action, soils, and
•NIs, DIs, and CRFs reduced N2O
emissions by 38, 30, and 19%,
respectively, compared with
conventional N fertilizers.
•NIs increased overall crop yields by
7% compared with conventional N
•DIs might provide added benets
over NIs in alkaline soils, coarse-
textured soils, and irrigated systems.
Published October 13, 2016
1122 Soil Science Society of America Journal
synthetic N fertilizers. Therefore, judicious management of N
fertilizers in rice, corn, and wheat production is essential for re-
ducing N2O emissions and enhancing agricultural sustainability.
Using enhanced efficiency fertilizers (EEFs) instead of
conventional N fertilizers (e.g., urea) can potentially reduce
N2O emissions and improve N use efficiency in cereal produc-
tion. According to the Association of American Plant Food
Control Officials (2013), EEFs are defined as “fertilizer prod-
ucts with characteristics that allow increased plant uptake and
reduce the potential of nutrient losses to the environment (e.g.,
gaseous losses, leaching, or runoff) when compared to an ap-
propriate reference product.” Different EEF products have dif-
ferent modes of action that control the rate of nutrient release
and improve synchronization of soil N availability with crop N
demands (Halvorson et al., 2014; Shaviv, 2001; Trenkel, 2010).
For example, urease inhibitors (UIs) delay the hydrolysis of urea,
nitrification inhibitors (NIs) inhibit the nitrification process by
suppressing the activity of nitrifiers in the soil, and controlled-
release N fertilizers (CRFs) slow the release of nutrients through
coatings (Trenkel, 2010). Combined application of both urease
and nitrification inhibitors (DIs) has the potential to delay urea
hydrolysis as well as inhibit nitrification in soils. Therefore, the
application of EEF products has been proposed to provide agro-
nomic, economic, and environmental benefits over conventional
N fertilizers (conentional N fertilizers hereafter refers to those
N fertilizers without any inhibitors or coatings) (Trenkel, 2010;
Shaviv, 2001; Venterea et al., 2012; Snyder et al., 2009).
Previous studies on the effectiveness of EEFs in reducing
N2O emissions reported mixed results depending on their mode
of action, soil and environmental conditions, and management
factors. For example, in some cases, EEFs reduced N2O emis-
sions by 14 to 61% vs. conventional N fertilizers (Halvorson et
al., 2014), while others showed no effect or even slightly higher
N2O emissions with EEFs (Dell et al., 2014; Parkin and Hatfield,
2014; Sistani et al., 2011; Venterea et al., 2011). Such variability
in the response to EEFs suggests that the effectiveness of EEFs
depends on soils, climate, crop, and management practices.
We used meta-analysis to provide an up-to-date perspective
on EEF efficiency in reducing N2O emissions across EEF types,
crops, soils, and management practices. Meta-analysis is an ana-
lytical technique that combines results from a number of indepen-
dent studies to derive broad conclusions (Rosenberg et al., 2000).
Akiyama et al. (2010) published one such meta-analysis and found
that NIs as well as polymer-coated urea (the most commonly used
CRF), but not UIs, were effective in reducing N2O emissions from
a wide range of agricultural soils, but their analysis considered only
studies published through 2008 and a substantial body of work has
since been published. Moreover, we offer two specific perspectives
not included in previous reviews: (i) a comparison of EEF types un-
der specific soil (soil pH, soil texture) and management (fertilizer
placement and timing of application, tillage, and irrigation) condi-
tions, and (ii) examination of EEFs in reducing N2O emissions, spe-
cifically in the world’s major cereal systems (rice, corn, and wheat).
Therefore, our main objectives were (i) to evaluate the effects of
individual EEFs (UIs, NIs, DIs, and CRFs) on soil N2O emissions
and crop yields in major cereal systems, and (ii) to identify the soil
and management factors in which EEFs are most effective.
MATERIALS AND METHODS
An extensive search of the scientific literature, using Web of
Science (Thompson Reuters) and Google Scholar (Google Inc.)
databases, was conducted in May 2015 for studies that reported
N2O emissions with and without EEFs in major cereal produc-
tion systems. The following key words and their combinations
were used for searching the literature: enhanced efficiency fer-
tilizers, urease inhibitor, nitrification inhibitor, polymer coated
urea, N source, N2O emissions, rice or paddy, wheat, corn or
maize, and cereals. The database search was supplemented by re-
viewing the reference lists of the studies found in our search and
those used in the prior meta-analysis by Akiyama et al. (2010).
Studies were included only if they met the following criteria: (i)
a field study on rice, corn, and/or wheat production (any addi-
tional components such as laboratory incubation or greenhouse
experiments were excluded); (ii) studies measuring N2O emis-
sions for at least one complete growing season without missing
N2O fluxes during the days following fertilization, tillage, and
rainfall or irrigation events; (iii) means and number of replicates
for each treatment comparison reported. We found a total of 43
studies that fulfilled these selection criteria (Table 1).
From each study, data pertaining to the study site location (lon-
gitude and latitude), soil characteristics (pH, texture), management
factors (fertilizer N types, application rates, timing and mode of fer-
tilizer application, tillage, and irrigation), crop types (rice, corn, or
wheat), number of replicates, and the response variables (cumula-
tive N2O emissions and crop yields) were recorded. Graphical data
were extracted using Webplotdigitizer Version 3.8. Each treatment
comparison between EEFs and conventional N fertilizers served
as an observation in our meta-analysis. Conventional N fertilizers
included both organic (pig slurry, poultry manure) and inorganic
(urea, urea–NH4NO3, ammonium sulfate nitrate, KNO3, anhy-
drous NH3) forms of N fertilizers. The EEFs were grouped into
categories based on their modes of action: UIs, NIs, DIs, and CRFs.
In addition, data were categorized by soil characteristics (soil tex-
ture, soil pH) and management practices (time of fertilizer applica-
tion, mode of fertilizer application, tillage, and irrigation) for each
study. Soil texture was subdivided into three categories: fine (>30%
clay), medium (<30% clay and <45% sand), and coarse (>45%
sand). When the soil particle size distribution was not reported, we
classified the soil texture by textural class: fine (clay, silty clay, and
sandy clay), medium (clay loam, loam, silty clay loam, silt, and silt
loam), and coarse (sandy loam, sandy clay loam, and loamy sand)
(Soil Survey Staff, 1999). Studies were also grouped into three soil
pH categories: alkaline (>7.5), neutral (6.5–7.5) and acidic (<6.5).
Similarly, with respect to management practices, we broadly cat-
egorized the studies by the time of N application (single vs. split),
mode of fertilizer application (broadcast vs. banded), tillage (no-till
vs. tilled), and irrigation (irrigated vs. rainfed).
For side-by-side comparisons of EEFs with conventional N
fertilizers, we used the natural log-transformed response ratio
(lnR) as a measure of effect size (Hedges et al., 1999):
( ) ( )
ln ln ln ln
= = −
t and xc are the mean values of cumulative N2O emissions
or crop yields for the EEFs (treatment group) and conventional
N fertilizers (control group), respectively. The variance (v) of
lnR was estimated using
where st and sc represent the standard errors of the EEF treat-
ment and conventional N fertilizer control groups, respectively.
Whenever the standard error was not reported, the average coef-
ficient of variation (CV) was computed, and then the missing
Table 1. Summary of the studies included in the meta-analysis.
Reference Country Cereal type Soil type Soil pH Enhanced efciency fertilizers†
Aita et al. (2014) Brazil corn sandy loam 5.6 DCD, AgrotainPlus
Asgedom et al. (2014) Canada wheat clay loam 7.0 ESN, SuperU
Bastos (2015) USA corn silt loam 7.4 nitrapyrin, ESN
Bhatia et al. (2010) India wheat loam 8.1 DCD, SBT butanoate, SBT furoate
Bremner et al. (1981) USA corn clay loam 6.8 nitrapyrin
Bronson and Mosier (1993) USA corn, wheat clay loam na ‡ nitrapyrin, ECC, DCD
Bronson et al. (1992) USA corn clay loam 7.2 nitrapyrin, ECC
Burton et al. (2008) Canada wheat clay, clay loam na PCU, NBPT
Dell et al. (2014) USA corn silt loam na ESN, SuperU, AgrotainPlus
Ding et al. (2011) China corn sandy loam 8.6 NBPT, DCD, NBPT plus DCD
Ding et al. (2015) China wheat silt loam 8.6 NBPT, DCD, NBPT plus DCD
Drury et al. (2012) Canada corn clay loam na PCU
Fernández et al. (2015) USA corn silt loam 5.9–6.5 ESN
Gao et al. (2015) Canada wheat sand, clay 5.8, 7.1 ESN, SuperU
Ghosh et al. (2003) India rice clay loam 7.6 DCD
Hadi et al. (2008) Indonesia corn sandy loam 4.6 DCD, PoCU
Halvorson et al. (2011) USA corn clay loam 7.6 ESN, Nfusion, SuperU, AgrotainPlus
Halvorson et al. (2010a) USA corn clay loam 7.6 ESN, Duration III, SuperU, AgrotainPlus
Halvorson et al. (2010b) USA corn clay loam 7.6 ESN, SuperU
Halvorson and Del Grosso (2013) USA corn clay loam 7.6 PCU, SuperU
Halvorson and Del Grosso (2012) USA corn clay loam 7.6 ESN, SuperU, AgrotainPlus
Huérfano et al. (2015) Spain wheat clay loam 8.5 DMPP
Ji et al. (2012) China wheat loam na RCU
Jumadi et al. (2008) Indonesia corn na 5.7 DCD, PoCU
Kumar et al. (2000) India rice clay loam 7.8 DCD, thiosulfate
Liu et al. (2013) China corn, wheat na na DCD, DMPP
Ma et al. (2013) China wheat silty clay loam 7.4 DCD, pyridine
Maharjan and Venterea (2013) USA corn silt loam na ESN, SuperU
Majumdar et al. (2000) India rice sandy loam 7.9 DCD, neem
Majumdar et al. (2002) India wheat sandy loam 8.1 DCD, neem, thiosulfate
Malla et al. 2005 India wheat, rice loam 8.0 neem, neem oil, thiosulfate, CaC2, DCD, hydroquinone
Nash et al. (2012) USA corn silt loam 6.2 PCU
Nash et al. (2015) USA corn silt loam 5.7–6.4 PCU
Omonode and Vyn (2013) USA corn silt loam na nitrapyrin
Paniagua (2006) USA corn silt loam 6.7–6.8 ESN
Parkin and Hateld (2010) USA corn silt clay loam 6.9 nitrapyrin
Parkin and Hateld (2014) USA corn silty clay loam 6.7–7.2 ESN, Nutrisphere, SuperU, AgrotainPlus
Sanz-Cobena et al. (2012) Spain corn sandy clay loam 7.9 NBPT, NBPT plus DCD
Sistani et al. (2011) USA corn silt loam 5.8 ESN, SuperU, AgrotainPlus
Sun et al. (2015) China rice na 6.3 N-serve
Venterea et al. (2011) USA corn silt loam na ESN, SuperU
Weiske et al. (2001a) Germany corn, wheat clay loam 6.0–6.8 DCD, DMPP
Yan et al. (2001) Japan corn clay loam 6.1 PoCU
† DCD, dicyandiamide; DMPP, 3,4-dimethylpyrazole phosphate; ECC, encapsulated CaC2; ESN, Environmentally Smart N; NBPT, N-(N-butyl)
thiophosphoric triamide; PCU, polymer-coated urea; PoCU, polyolen-coated urea; RCU, resin-coated urea; SBT, S benzyl thiourea.
‡ na, data not available in the study.
1124 Soil Science Society of America Journal
standard error was estimated by multiplying the reported mean
by 150% of the average CV (Decock, 2014).
Using the response ratio (lnR) and variance (v) from individu-
al studies, MetaWin Version 2.1 statistical software was used to cal-
culate weighted mean effect sizes and generate bias-corrected 95%
confidence intervals (CIs) using a bootstrapping procedure (4999
iterations) for each category (Rosenberg et al., 2000). This software
allowed us to perform categorical random- or fixed-effects meta-
analytic models for the calculation of group effect sizes and/or to
compute the random-effects variance component (pooled study
variance or between-study variance). At first, a categorical random-
effects meta-analytic model was selected. A fixed-effects meta-an-
alytic model was used in place of the random-effects model only
when the estimated pooled variance was £0 (Rosenberg et al.,
2000). For both random- and fixed-effects models, the weighted
mean effect sizes for each category were computed using
where lnRi and wi are the lnR and weighting factor of the ith ob-
servation, respectively. The weighting factor (wi) varied among the
models used. In the case of the categorical random-effects model:
And, in the case of a categorical fixed-effects model:
where vi and s2pooled are the individual study variance (variance
of the ith observation) and pooled study variance (between-
study variance), respectively. Rice systems were poorly represent-
ed in our database (five studies with 19 observations), and the
only EEF that was used in rice was an NI (n = 18) or UI (n = 1)
(Table 1). Given the low number of studies and the fact that N
dynamics in rice systems, which are typically flooded, are differ-
ent than in upland crops, rice systems were analyzed separately
from upland systems and were not included in any analysis of
the effects of soil and management factors. For a more complete
analysis of EEF effects on rice yields, see Linquist et al. (2013).
To facilitate interpretation, the meta-analysis results were
exponentially transformed and graphed as the change (%)
under EEF relative to conventional N fertilizer applications
) − 1]´100%). The mean effect sizes of EEF applica-
tions on N2O emissions and crop yields were considered signifi-
cantly different from conventional N fertilizers when the 95%
CI did not overlap with zero. The mean effect sizes for different
subgroups were considered significantly different from one an-
other only if their 95% CIs did not overlap each other.
RESULTS AND DISCUSSION
Overview of the Data Set
We found 43 studies (Table 1), with a total of 246 obser-
vations, conducted to evaluate the effect of EEFs on soil N2O
emissions in rice, corn, and wheat cropping systems. Thirty-one
studies (172 observations) also documented crop yields. The
studies used here were conducted in South America (Brazil),
North America (USA and Canada), Asia (China, India, Japan,
and Indonesia), and Europe (Germany and Spain) (Fig. 1). The
studies conducted in rice systems were located in China (1) and
India (4). Studies on corn were distributed around the world:
North America (21), Asia (5), Europe (2), and South America
Fig. 1. The global distribution of study sites included in this meta-analysis.
(1). Similarly, the study sites related to wheat systems were dis-
tributed in Asia (7), North America (4), and Europe (2). Further
information on the studies included in this meta-analysis are pre-
sented in Tables 1 and 2.
Effect of Enhanced Efciency Fertilizers
Urease inhibitors delay the hydrolysis of urea into NH4+
by blocking the urease enzyme binding sites (Trenkel, 2010).
The most commonly used UI is N-(N-butyl)-thiophosphoric
triamide (NBPT). In soil, NBPT forms a tridentate ligand
that suppresses the activity of the urease enzyme (Manunza et
al., 1999). By slowing urea hydrolysis, a UI reduces NH3 vola-
tilization and improves the synchronization between soil N
availability and crop N demand (Trenkel, 2010). Moreover, UIs
may reduce N2O emissions by decreasing the availability of an
NH4+ substrate for nitrification. Consistent with the results of
Akiyama et al. (2010), the overall effect of UIs on N2O emis-
sions in the present meta-analysis did not differ from zero (data
When the data were analyzed by individual crop type, soil
texture, and management practice, a significant reduction in
N2O emissions with UIs was observed. For example, UIs signifi-
cantly reduced N2O emissions in corn systems by 36% (CI: −55
to −17%) compared with conventional N fertilizers. Similarly,
N2O emissions were reduced with UI applications in coarse-tex-
tured soils (mean: −28%, CI: −55 to −4%), when fertilizers were
applied in multiple split doses (mean: −19%, CI: −37 to −5%),
and under irrigated field conditions (mean: −32%, CI: −40 to
−23%). However, these results were based on just five studies,
and more field studies are needed to validate these findings.
Nitrification inhibitors are compounds that delay microbial
oxidation of NH4+ to NO2− by inhibiting the activity of nitrifi-
ers in soils (Subbarao et al., 2006; Weiske et al., 2001b). By delay-
ing the first step of nitrification, a NI retains NH4+ for extended
time periods and decreases NO3− contents in soils. Thus, NIs
have the potential to reduce N2O emissions by suppressing both
nitrification and denitrification pathways. Akiyama et al. (2010)
estimated that NIs reduced N2O emissions by 38% (CI: −44 to
−31%) compared with conventional N fertilizers. Our meta-
analysis gave a similar result of 38% N2O (CI: −44 to −33%)
emissions reduced by NIs compared with conventional N fertil-
izers (Fig. 2a).
Application of NIs might also increase N use efficiency and
crop yields by facilitating the uptake of N in the NH4+ form,
which can be assimilated with less energy than NO3− (Subbarao
et al., 2006; Zaman et al., 2009). In this meta-analysis, we ob-
served that NIs significantly increased cereal yields by 7.1% (CI:
4.7–9.5%) compared with conventional N fertilizers (Fig. 2),
consistent with Qiao et al. (2015).
The effectiveness of NIs varied with cereal type (Fig. 2).
Among the three major cereal crops, NIs were more effective
in reducing N2O emissions in corn (mean: −51%, CI: −61 to
−42%) than wheat (mean: −30%, CI: −36% to −24%) or rice
(mean: −27%, CI: −37 to −18%). This indicates that NIs may
reduce N2O emissions more effectively in those cropping systems
that demand higher N inputs and have relatively high mean N2O
emissions from conventional N fertilizers. In the studies includ-
ed in this meta-analysis, more N was applied in corn (mean N ap-
plication rate of 184 kg N ha−1), which ultimately resulted in rel-
atively high mean N2O emissions for conventional N fertilizers
(3.05 kg N2O-N ha−1). In contrast, the mean application rates
and mean N2O emissions from conventional N fertilizers were
relatively low for rice (146 kg N ha−1 and 0.57 kg N2O-N ha−1)
and wheat (135 kg N ha−1 and 1.18 kg N2O-N ha−1). There
was no significant effect of NIs on corn yields. However, NIs sig-
nificantly increased rice and wheat yields by 5.5% (CI: 0.1–12%)
and 7.2% (CI: 4.6–9.6%), respectively, compared with conven-
tional N fertilizers.
Our results also showed that the efficacy of NIs varied with
NI formulations (Fig. 3). Among the most commonly used NIs,
dicyandiamide (DCD) and 3,4-dimethylpyrazol phosphate
(DMPP) significantly reduced N2O emissions and also increased
crop yields compared with conventional N fertilizers (Fig. 3). On
Table 2. Categorization of enhanced efciency fertilizer products evaluated in the studies included based on their mode of action.
Urease inhibitors Nitrication inhibitors Double inhibitors† Controlled-release N fertilizers
dicyandiamide (DCD) NBPT plus DCD polymer-coated urea (PCU), ESN
(Environmentally Smart N), Duration III)
Hydroquinone 3,4-dimethylpyrazole phosphate
SuperU (urea with NBPT and DCD) resin-coated urea (RCU)
nitrapyrin or pyridine or N-serve
AgrotainPlus (NBPT plus DCD) polyolen-coated urea (PoCU)
neem (neem cake, neem-coated urea,
neem oil coated urea, nimin coated
CaC2 or encapsulated CaC2
Nutrisphere (copolymer of maleic
and itaconic acids)
S benzyl thiourea (SBT) butanoate,
† A combination of both urease and nitrication inhibitors.
1126 Soil Science Society of America Journal
the other hand, nitrapyrin reduced N2O emissions by 43% (CI:
−54 to −27%) but had no effect on crop yields (mean: 3.2%, CI:
−7.9 to 11%). Among these, three commonly used NIs, DMPP
(the most recently developed nitrification inhibitor) is assumed
to inhibit nitrification more effectively than DCD and nitra-
pyrin (Subbarao et al., 2006) because DMPP has similar mobil-
ity in soil as NH4+ (Pasda et al., 2001). In contrast, the relative
mobility of DCD is higher, and that of nitrapyrin lower, than
that of NH4+ (Pasda et al., 2001). Our analysis, however, showed
that DCD, DMPP, and nitrapyrin were equally effective in re-
ducing N2O emissions from conventional N fertilizers (Fig. 3a).
Despite these benefits, large-scale application of DCD should be
viewed with caution because low levels of DCD residues were
detected in milk products and the use of DCD was suspended in
New Zealand in 2012 (Astley, 2013). Thus, a complete life-cycle
assessment of these NI products in addition to their toxicity ef-
fects on plant growth and human health needs to be conducted.
Double (Both Urease and Nitrication) Inhibitors
Double inhibitors (DIs) may be more effective than UIs or
NIs alone because the combined application of both a UI and an
NI not only increases crop NH4+ availability by delaying urea
hydrolysis but also prolongs NH4+ retention by inhibiting nitri-
fication in the soil. The conservative release of N by DIs can re-
Fig. 2. The effect of nitrication inhibitors (Nis) on (a) N2O emissions and (b) crop yields relative to conventional N fertilizers for different cereal
types, soil types, and management conditions. Studies in rice systems were not included in any analysis of the effects of soil and management
factors. Mean effect sizes and 95% (condence intervals) CIs are shown. Numbers in parentheses indicate the sample size (the number of pairwise
comparisons). The mean effect sizes were considered signicantly different only when the 95% CIs did not overlap with zero. The mean effect
sizes for different subgroups are considered signicantly different from one another only if their 95% CIs do not overlap.
duce all possible N losses (NH3 and N2O emissions and NO3−
leaching) and improve the N use efficiency of crops. Our results
indicated that DIs and NIs were equally effective in reducing
N2O emissions compared with conventional N fertilizers (Fig.
2a and 4a), which suggests that the supplemental addition of a
UI to an NI did not necessarily mitigate direct N2O emissions
more effectively. However, the presence of UIs in DIs may en-
hance their efficacy in reducing indirect N2O emissions, which
occur via NH3 volatilization (Kim et al., 2012). Application of
an NI alone has been shown to significantly increase NH3 vola-
tilization by prolonging NH4+ retention in the soil, which in
turn leads to greater indirect N2O emissions (Kim et al., 2012;
Thapa et al., 2015). When data were categorized based on the in-
dividual cereal types, DIs were equally effective in reducing N2O
emissions under both corn (mean: −30%, CI: −37 to −21%) and
wheat (mean: −34%, CI: −53 to −10%) compared with conven-
tional N fertilizers (Fig. 4a).
There was no overall effect of DIs on crop yields across soil
types (Fig. 4b). For DIs, significant yield benefits were found
only in alkaline soils (mean: 2.0%, CI: 0.5–3.7%), medium
(mean: 2.3%, CI: 0.3–4.7%) to coarse-textured (mean: 5.7%,
CI: 1.4–9.9%) soils, and under irrigation (mean: 2.0%, CI:
0.5–1.9%). The inconsistent response of crop yields to DIs sug-
gests that the current combination of a UI (NBPT) and an NI
(DCD) might be unable to synchronize soil N release with crop
N demands. More research is needed to determine the optimum
combination of NBPT and DCD within a DI to optimize both
economic and environmental benefits.
Controlled-Release Nitrogen Fertilizers
Controlled-release N fertilizers include coated or encapsu-
lated fertilizers with inorganic or organic materials that control
the rate, pattern, and duration of nutrient release (Shaviv, 2001;
Chien et al., 2009). These products are designed to release nutri-
Fig. 3. The effect of individual enhanced efciency fertilizers on (a) N
O emissions and (b) crop yields relative to conventional N fertilizers for
different cereal types, soil types, and management conditions. Studies in rice systems were not included in any analysis of the effects of different
EEF products. Mean effect sizes and 95% condence intervals (CIs) are shown. Numbers in parentheses indicate the sample sizes (the number of
pairwise comparisons). The mean effect sizes were considered signicantly different only when the 95% CIs did not overlap with zero. The mean
effect sizes for different subgroups are considered signicantly different from one another only if their 95% CIs do not overlap.
1128 Soil Science Society of America Journal
ents by diffusion through a semipermeable polymer membrane
coating (e.g., polymer-coated urea) in a controlled manner such
that the release of the nutrient is better matched with crop de-
mands (Blaylock et al., 2004). Thus, a CRF limits the availability
of the N fertilizer to nitrifiers and denitrifiers, potentially reducing
N2O emissions. Our analysis indicated that CRFs reduced N2O
emissions by 19% relative to conventional N fertilizers in cereal
systems (Fig. 5a), which is lower than the 35% reduction reported
by Akiyama et al. (2010). This difference could be due to the dif-
ferences in the size of the data sets (89 comparisons in this study vs.
20 comparisons by Akiyama et al. ). In addition, Akiyama
et al. (2010) included two studies (Ball et al., 2004; Dobbie and
Smith, 2003) conducted on grasslands in Scotland where mean
N2O emissions were relatively high (5.63 kg N2O-N ha−1 for con-
ventional N fertilizers) due to high N application rates and high
rainfall. The greater N2O emissions of these two studies prob-
ably skewed their results toward greater observed effectiveness of
CRFs. However, we focused on studies in corn and wheat fields in
which mean N2O emissions were relatively low even with conven-
tional N fertilizers (3.56 kg N2O-N ha−1).
The major barrier to widespread adoption of CRFs over
conventional N fertilizers is cost. To be economically feasible,
the use of CRFs must increase crop yields such that the added
costs are compensated. However, CRFs consistently showed no
or a negative effect on crop yields in this meta-analysis (Fig. 5b).
uemada et al. (2013) also reported that CRFs had a negative
effect on crop yields, although the NO3− leaching losses were
significantly reduced compared with conventional N fertilizers.
Therefore, a new generation of CRF products is needed to re-
duce N losses in an economically sustainable manner.
Fig. 4. The effect of double inhibitors (DIs) on (a) N
O emissions and (b) crop yields relative to conventional N fertilizers for different cereal (corn
and wheat) types, soil types, and management conditions. Only studies from corn and wheat systems were included in the analysis of the effects of
soil and management factors. Mean effect sizes and 95% condence intervals (CIs) are shown. Numbers in parentheses indicate the sample sizes
(the number of pairwise comparisons). The mean effect sizes were considered signicantly different only when the 95% CIs did not overlap with
zero. The mean effect sizes for different subgroups are considered signicantly different from one another only if their 95% CIs do not overlap.
Factors Affecting the Effectiveness of Enhanced
Soil pH. Soil pH greatly influenced EEF efficacy by regulating
N loss mechanisms. In general, the rates of NH3 volatilization
(Francis et al., 2008) and nitrification (Norton, 2008; ŠImek and
Cooper, 2002) following urea fertilization increases with increas-
ing soil pH. Thus, the benefit of using EEFs might be greater in
soils with higher pH values. Linquist et al. (2013) observed that
EEFs increased crop yields and N uptake in rice systems only in
neutral (pH = 6.5–7.5) to alkaline (pH > 7.5) soils but not in
acidic (pH < 6.5) soils. Conversely, Abalos et al. (2014) observed
that the overall effect of EEFs (urease and nitrification inhibi-
tors) on crop yields and N uptake decreased in neutral to alkaline
soils compared with acidic soils.
Given that EEF products differ in their mode of action, the
effectiveness of these products might vary in soil depending on
pH values. In acidic soils, only NIs significantly reduced N2O
emissions (mean: −59%, CI: −77 to −40%) compared with con-
ventional N fertilizers (Fig. 2a). Neither DIs nor CRFs reduced
N2O emissions compared with conventional N fertilizers in
acidic soils (Fig. 4a and 5a). In alkaline soils, DIs (mean: −43%,
CI: −47 to −38%) more effectively reduced N2O emissions than
NIs (mean: −21%, CI: −27 to −16%) (Fig. 2a and 4a). This
could be attributed to the rapid hydrolysis of NIs at high soil pH,
which in turn leads to reduced efficacy of the NIs in inhibiting
Fig. 5. The effect of controlled-release N fertilizers (CRFs) on (a) N2O emissions and (b) crop yields relative to conventional N fertilizers for
different cereal (corn and wheat) types, soil types, and management conditions. Only studies from corn and wheat systems were included in the
analysis of the effects of soil and management factors. Mean effect sizes and 95% condence intervals (CIs) are shown. Numbers in parentheses
indicate the sample sizes (the number of pairwise comparisons). The mean effect sizes were considered signicantly different only when the 95%
CIs did not overlap with zero. The mean effect sizes for different subgroups are considered signicantly different from one another only if their
95% CIs do not overlap.
1130 Soil Science Society of America Journal
nitrification in alkaline soils (Briggs, 1975). In addition, the ef-
fectiveness of NIs in improving crop yields and N uptake may be
further reduced in alkaline soils due to their tendency to increase
N losses via NH3 volatilization by prolonging NH4+ retention
in soil (Kim et al., 2012; Thapa et al., 2015; Qiao et al., 2015).
Higher soil pH leads to an overall increase in NH3 loss by favor-
ing the conversion of NH4+ to NH3 due to a decrease in H+
activity. Therefore, a DI—which has the ability to inhibit both
N loss mechanisms—might be the most effective form of EEF in
alkaline soils. However, the results from this analysis indicated
that both NIs and DIs were equally effective in increasing crop
yields compared with conventional N fertilizers (Fig. 2b and 4b).
Soil Texture. Soil texture affects gas diffusivity, controls
soil moisture loss, and influences N2O production (Del Grosso
et al., 2008; Skiba and Ball, 2002; Rochette et al., 2004). Fine-
textured, poorly drained soils tend to remain wetter and an-
aerobic longer after rainfall or irrigation, thereby facilitating
denitrification (Del Grosso et al., 2008). In contrast, the higher
aeration in coarse-textured, well-drained soils facilitates nitrifica-
tion. Therefore, applied fertilizers are more susceptible to N2O
emissions in fine- and medium-textured, poorly drained soils. In
these soils, the application of EEFs may efficiently reduce N2O
emissions. However, Bundy and Bremner (1973) observed that
a NI was considerably more effective in inhibiting nitrification
in coarse-textured soils than in fine-textured soils. Slangen and
Kerkhoff (1984) also concluded that the mobility, bioactivity,
and effectiveness of inhibitors are lower in fine-textured soils
than in coarse-textured soils due to greater adsorption of the in-
hibitors by clays in fine-textured soils. In this meta-analysis, NIs,
DIs, and CRFs significantly reduced N2O emissions compared
with conventional N fertilizers in all soil types, but their respons-
es did not vary with soil texture (Fig. 2a, 4a, and 5a).
The effect of NIs and DIs on crop yields varied with soil
type. In coarse-textured soils, both NIs and DIs significantly
increased crop yields by 5.5% (CI: 2.5–8.7%) and 5.7% (CI:
1.4–9.9%), respectively, compared with conventional N fertiliz-
ers (Fig. 2b, 4b). In medium-textured soils, only DIs significantly
increased crop yields (mean: 2.3%; CI: 0.3–4.7%), whereas in
fine-textured soils, only NIs significantly increased crop yields
(mean: 8.7%; CI: 4.7–11.4%) compared with conventional N
fertilizers. In contrast, CRFs showed no and a negative effect
on crop yields in medium- to coarse-textured and fine-textured
soils, respectively (Fig. 5b). Based on these results, the positive
response of crop yields to EEF application seems to be more con-
sistent in coarse-textured soils.
Timing of Fertilizer Application
The timing of fertilizer application to synchronize soil N
release with crop N demand is essential for improving the yield
and quality of crops. This can be achieved through split applica-
tion of N fertilizers in multiple doses throughout the growing
season. The enhanced efficiency of crops to recover fertilizer
N with split N applications might help to reduce unwanted N
losses, including N2O emissions, and reduce the environmental
impact of fertilization (Velasco et al., 2012). Our meta-analysis
suggests that the agronomic and environmental benefits of split
N applications could be further improved by amending conven-
tional N fertilizers with NIs in corn and wheat systems (Fig. 2a
and 2b). When split applied, the addition of NIs significantly re-
duced N2O emissions by 53% (CI: −62 to −46%) and increased
crop yields by 7.3% (CI: 4.9–9.5%) compared with conventional
N fertilizers. Even when all N fertilizers were applied at or be-
fore planting as a single dose, the addition of NIs significantly
reduced N2O emissions by 26% (CI: −33 to −19%) compared
with conventional N fertilizers (Fig. 2a). However, the reduction
in N2O emissions with NIs during single N applications was not
sufficient to significantly increase crop yields (Fig. 2b).
Mode of Fertilizer Application
Subsurface placement of fertilizers in bands is often pro-
moted to enhance agronomic efficiency or N fertilizer recovery
efficiency of crops compared with broadcast applications (Malhi
et al., 2001; Yadvinder-Singh et al., 1994; Zhu and Chen, 2002).
However, there is a discrepancy in the literature on the effect of
fertilizer placement on soil N2O emissions. The EEF effective-
ness is also impacted by its mode of application. Subbarao et al.
(2006) suggested greater effectiveness of EEFs when applied as
banded than broadcast fertilizers. In this meta-analysis, we ob-
served greater effectiveness of DIs in reducing N2O emissions
when applied as banded (mean: −45%, CI: −53 to −36%) fertil-
izers than broadcast (mean: −14%, CI: −22 to −5%) fertilizers
(Fig. 4a), but the overall effect of NIs and CRFs on N2O emis-
sions did not vary between broadcast and banded applications
(Fig. 2a and 5a). Slangen and Kerkhoff (1984) reported that
nitrapyrin (NI form) is not effective as coatings on broadcast
fertilizers because of its relatively high vapor pressure. Therefore,
nitrapyrin should be incorporated or injected into the soil to
enhance its effectiveness. As such, we separately evaluated the
efficacy of nitrapyrin but found a similar response under both
broadcast (mean: −40%, CI: −50 to −21%) and banded (mean:
−43%, CI: −55 to −26%) fertilizer applications.
No-till or minimal tillage management practices are pro-
moted to reduce soil erosion, enhance agricultural sustainability,
build soil health, and reduce greenhouse gas emissions through C
sequestration (Cole et al., 1997; Six et al., 2004), but the effect of
no-till on N2O emissions is highly variable. No-till management
can enhance N2O emissions by increasing soil moisture content
and bulk density (Liu et al., 2007; Rochette, 2008) or decrease
N2O emissions by lowering soil temperature and improving soil
structure (Six et al., 2002; Venterea et al., 2011). Also, by regulat-
ing soil moisture and soil temperature, tillage practices affect the
mobility, persistence, and effectiveness of inhibitors in the soil.
The relative effectiveness of most NI products decreases with
increasing soil temperature (Bundy and Bremner, 1973) due to
increased activity of nitrifiers and therefore a decrease in the per-
sistence of the inhibitors (Slangen and Kerkhoff, 1984). In this
context, NIs should be more effective in reducing N2O emis-
sions and enhancing crop yields under no-till than tilled soils.
Results from this meta-analysis, however, indicated that
the overall effect of NIs on N2O emissions and crop yields did
not vary between no-till (mean N2O: −46%, CI: −58 to −34%;
mean yield: 9.6%, CI : 6.6–12.8%) and tilled (mean N2O: −42%,
CI: −55 to −30%; mean yield: 6.9%, 3.8–10.3%) soils (Fig. 2).
Similarly, DIs also showed similar reductions in N2O emissions
under both no-till (mean: −26%, CI: −37 to −14%) and tilled
(mean: −34%, CI: −44 to −23%) soils (Fig. 4a). In contrast,
CRFs significantly reduced N2O emissions compared with con-
ventional N fertilizers only when soils were tilled (mean: −28%,
CI: −36 to −19%) (Fig. 5a).
Irrigating fields shortly after fertilizer application fa-
cilitates the incorporation of broadcast fertilizers into the soil,
which reduces N losses through NH3 volatilization (Holcomb
et al., 2011). However, irrigated systems are more prone to
NO3− leaching losses than rainfed systems (Follett et al., 1991;
uemada et al., 2013). Moreover, irrigated systems are vulner-
able to denitrification-induced N2O emissions due to the fact
that irrigated systems tend to have a higher soil water-filled pore
space for most of the growing season. By reducing the availabil-
ity of NO3− substrate for denitrification and leaching losses, the
positive benefits of EEF applications might be more prominent
under irrigated than rainfed systems.
Results from this meta-analysis showed that the benefits of
different EEF products were more pronounced in irrigated than
rainfed systems. The UIs significantly reduced N2O emissions
in irrigated (mean: −30%, CI: −45 to −11%) systems, but the
effect was nonsignificant in rainfed systems (data not shown).
The NIs also significantly reduced N2O emissions compared
with conventional N fertilizers, but the effect size did not vary
between irrigated and rainfed systems (Fig. 2a). However, com-
bined application of both urease and nitrification inhibitors (DI)
reduced N2O emissions more effectively in irrigated systems
(mean: −45%, CI: −51 to −39%) than rainfed systems (mean:
−17%, CI: −29 to −5%) (Fig. 4a). Additionally, the use of an
EEF significantly reduces NO3− leaching losses compared with
conventional N fertilizers in irrigated systems (uemada et al.,
2013), which were generally the most dominant N loss process.
Thus, the application of EEF products may consistently increase
crop yields in irrigated systems. In support of this hypothesis,
we found that NIs and DIs significantly increased crop yields
by 5.2% (CI: 2.1–8.1%) and 2.0% (CI: 0.5–3.8%), respectively,
compared with conventional N fertilizers in irrigated systems
(Fig. 2b and 4b). However, the effect of NIs and DIs on crop
yields was nonsignificant in rainfed systems.
Knowledge Gaps and Future Considerations
Soil N2O emissions have a high degree of spatial (hotspots)
and temporal (hot moments) variability (Groffman et al., 2009).
The most commonly accepted snapshot measurements of N2O
emissions include closed chambers at weekly intervals (as used in
most of the studies included in this meta-analysis except that of
Liu et al. ) and are more prone to missing short-term emis-
sion peaks (hot moments). Moreover, some of these studies de-
ployed only one chamber within a plot, which might have missed
potential hotspots of N2O fluxes. Missing hotspots and hot mo-
ments of N2O fluxes can mask treatment effects. Moreover, cap-
turing such hotspots and hot moments of N2O fluxes will fur-
ther improve our understanding of the biogeochemical processes
of N2O emissions. Therefore, it is necessary to capture spatial,
temporal, and diurnal variability in N2O emissions to elucidate
the effects of agricultural products and management practices.
This could be achieved by collecting continuous N2O measure-
ments with multiple automated chambers over small areas or by
using micrometeorological methods coupled with optical ana-
lytical techniques across wide areas (Rapson and Dacres, 2014).
Until now, most studies have focused on determining the
impact of EEFs at the field scale during the crop growing season,
but the positive benefits of EEF application may extend beyond
the end of the growing season. Thus, future research should con-
sider year-round measurements of N2O emissions at a landscape
scale even outside the crop’s growing season. Similarly, the agro-
nomic and environmental benefits associated with fall applica-
tion of EEFs need to be evaluated because fall application mini-
mizes early spring operations close to planting. Little research has
evaluated fall-applied nitrapyrin (the most commonly used NI
in North America) compared with fall-applied conventional N
fertilizers in croplands. For example, Parkin and Hatfield (2010)
found that fall-applied nitrapyrin had no effect on annual N2O
emissions but significantly increased crop yields compared with
conventional N fertilizers. Similarly, Goos and Johnson (1999)
also observed that amending fall-applied anhydrous NH3 with
nitrapyrin increased wheat growth, N uptake, and grain yields.
Nearly 63% of the studies included in our analysis did not
report any measure of variance such as standard deviation, stan-
dard error, coefficient of variation, etc., and crop yields were not
reported in 28% of the studies. Future studies should clearly re-
port sample sizes and some measure of variability while reporting
mean cumulative N2O emissions as well as information pertain-
ing to the production and quality of the crops. Future studies
should also report information on other factors that could affect
the effectiveness of EEFs, such as soil temperature, soil organic
C, cation exchange capacity, and other environmental variables.
This will facilitate comparative data analysis and aid in formu-
lating the most effective and economically feasible management
To estimate the overall effect of EEFs on total N2O emis-
sions, results obtained in our meta-analysis must be accompa-
nied with information on indirect N2O emissions that occur
via NH3 volatilization, NO3− leaching, and runoff and erosion
losses. The short- and long-term effects of the continuous use
of EEFs on targeted and non-targeted soil microorganisms and
biogeochemical processes, plant growth and metabolism, human
1132 Soil Science Society of America Journal
and animal health, and biodiversity should be evaluated. Future
studies should also consider new-generation EEF products that
could effectively reduce N losses under the most vulnerable
environmental conditions (high temperature, alkaline pH) in
a cost-effective manner. A complete life-cycle assessment and
cost–benefit analysis is needed to assess the net benefits of these
new products ahead of widespread adoption.
Ensuring global food security while reducing environmen-
tal costs associated with N fertilizer application is a major chal-
lenge in the 21st century. Among the 4 Rs of nutrient steward-
ship to achieve sustainable intensification is the selection of the
right N source, which might be EEFs instead of conventional N
fertilizers. As anticipated, EEFs showed variable effects on N2O
emissions depending on soil (soil pH, texture) and management
(timing and mode of fertilizer application, tillage, irrigation)
factors. Urease inhibitors significantly reduced N2O emissions
compared with conventional N fertilizers only in coarse-tex-
tured soils and under irrigated conditions. Nitrification inhibi-
tors consistently reduced N2O emissions, but their effectiveness
was more pronounced in neutral soils, coarse-textured soils, and
under irrigated conditions. Combined application of both UIs
and NIs (DIs) were more effective in alkaline soils, medium- to
coarse-textured soils, irrigated field conditions, and when the
fertilizer was applied in bands. Controlled-release N fertilizers
significantly reduced N2O emissions across a wide range of soil
and management conditions but had no or negative effects on
crop yields. Based on our findings, NIs can be recommended
as a potential option for N2O mitigation while sustaining crop
yields. Alternatively, applications of DIs in alkaline soils, coarse-
textured soils, and irrigated systems would provide an additional
advantage over NIs in terms of reducing direct as well as indirect
N2O emissions. Future work should be directed toward develop-
ing new-generation EEF products that work effectively under a
wide range of soils, crops, climates, environments, and manage-
ment conditions to ensure widespread sustainability.
We are grateful to the authors of all those studies from which data were
extracted. We also express our sincere thanks to the associate editor and
two anonymous reviewers for their valuable comments that improved
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