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Comparison of crop management strategies
involving crop genotype and weed
management practices in conventional and
more diverse cropping systems
Robin Gómez
1
*, Matt Liebman
2
, David N. Sundberg
2
, and Craig A. Chase
3
1
University of Costa Rica, School of Agronomy, Fabio Baudrit Experimental Station, Alajuela, Costa Rica.
2
Department of Agronomy, Iowa State University, Ames, IA 50011, USA.
3
Iowa State University Extension and Outreach, 312 Westbrook Lane, Ames, IA 50014, USA.
*Corresponding author. Universidad de Costa Rica, Escuela de Agronomía, San José, Costa Rica.
gomez.robin@gmail.com
Accepted 14 March 2012 Research Paper
Abstract
Cropping systems that include forage legumes and small grains in addition to corn (Zea mays L.) and soybean [Glycine
max (L.) Merr.] can achieve similar or higher crop productivity and economic return than simpler corn–soybean
rotations. We hypothesized that this rotation effect occurs regardless of the crop genotype planted and the herbicide and
cultivation regime selected for weed management. To test this hypothesis, we conducted a 3-year experiment that
compared three cropping systems: a conventional 2-year corn–soybean rotation, a 3-year corn–soybean–oat (Avena
sativa L.)/red clover (Trifolium pretense L.) rotation, and a 4-year corn–soybean–oat/alfalfa–alfalfa (Medicago sativa L.)
rotation. Within each cropping system, two contrasting sets of management strategies were used: (i) genetically
engineered corn with resistance to insect pests (Ostrinia nubilalis Hübner and Diabrotica spp.) plus the broadcast
application of pre-emergence herbicides, followed in the rotation by a genetically engineered soybean variety with
resistance to the herbicide glyphosate plus the post-emergence broadcast application of glyphosate; and (ii) non-
genetically engineered corn plus the banded application of post-emergence herbicides, followed in the rotation by a non-
genetically engineered soybean and banded application of several post-emergence herbicides. The two management
strategies were identified as ‘GE’and ‘non-GE.’Corn yield was higher in the 3-year (12.51 Mg ha
−1
) and 4-year
(12.79 Mg ha
−1
) rotations than in the conventional 2-year (12.16 Mg ha
−1
) rotation, and was also 2% higher with the GE
strategy than with the non-GE strategy. Soybean yield was similar among rotation systems in 2008, but higher in the
3- and 4-year systems than the 2-year rotation in 2009 and 2010. Soybean yield was similar between management
strategies in 2008, but higher in the GE strategy in 2009, and similar between strategies in the 3- and 4-year rotations in
2010. Increases in rotation length were accompanied by 88–91% reductions in synthetic N fertilizer application, and the
use of the non-GE rather than the GE strategy was accompanied by a 93% reduction in herbicide active ingredients
applied. Averaged over the period of 2008–2010, net returns to land and labor were highest for the 3-year rotation
managed with either the GE ($928 ha
−1
yr
−1
) or non-GE ($936 ha
−1
yr
−1
) strategies, least in the 2-year rotation
managed with the non-GE strategy ($738 ha
−1
yr
−1
), and intermediate in the other rotation × management
combinations. Our results indicate that more diverse crop rotation systems can be as profitable as conventional
corn–soybean systems and can provide farmers with greater flexibility in crop management options.
Key words: diversified cropping systems, forage legumes, crop rotation, weed management, economic return
Introduction
Crop diversity at farm and regional levels in the USA has
diminished markedly during the past 50 years
1,2
, and
monocultures and short rotation sequences are the
prevalent cropping systems there and in many other
developed countries
3,4
. Simplification of cropping systems
has been accompanied by greater reliance on synthetic
Renewable Agriculture and Food Systems: Page 1 of 14 doi:10.1017/S1742170512000142
© Cambridge University Press 2012
pesticides and fertilizers, while conservation practices
have sometimes been abandoned to increase production
5
.
Contamination of underground and surface water by
nitrogen, herbicides and soil sediment is an on-going
concern for agriculturalists
6,7
.
One of the major changes in US agriculture over the
past two decades has been the wide-scale adoption of
genetically engineered crops and associated management
practices, creating ‘technology packages’. In 2011, 94% of
US soybeans were genetically engineered for herbicide
tolerance, principally glyphosate tolerance
8
. Similarly,
in 2011, 72% of the US corn crop was genetically
engineered with traits for herbicide tolerance, insect
resistance, or both
8
. Concomitant with the introduction
of traits for glyphosate tolerance has been a large increase
in the use of glyphosate, making it the most heavily used
agricultural pesticide in the USA
9
.
The rapid increase in the use of transgenic crops has
taken place at the same time as there has been an effort
among researchers and policy-makers to raise awareness
of the environmental, social and economic consequences
of intensive agriculture
10,11
. This effort has led to attempts
to improve agricultural sustainability through the design
and management of agro-ecosystems that exploit ecologi-
cal processes to maintain soil productivity, improve crop
yield, and manage pest and weed populations
12–15
. Some
analysts of genetic engineering for crop production and
protection have argued that it can improve agricultural
sustainability and should be considered for use with other
practices that are common to organic and low-external
input (LEI) production systems
16,17
. Other analysts have
raised concerns over the durability of genetic engineering
approaches, noting the increasing prevalence of weed and
insect pest resistance to genetically engineered corn and
soybean genotypes
18,19
.
LEI cropping systems are intended to reduce environ-
mental, economical and social problems related to
intensive pesticides and fertilizer applications
20,21
. LEI
cropping systems rely on manipulations of ecological
processes, and the agricultural practices performed in
these more diverse systems can lead to improvement in soil
structure
22
, reduction in carbon and nitrogen losses
23,24
,
added organic matter
25
,fixation of atmospheric nitrogen
by legumes
26
, reduction in the incidence and severity of
crop diseases
27,28
, reduction in weed density
29,30
, increase
in soil microbial biomass
31,32
, and higher fossil-energy
efficiency
33
. LEI systems use green and animal manures
and other organic matter amendments as principal
nutrient sources for crops, and to improve soil structure.
Weed management, an important concern in LEI and
organic systems, can be addressed through the application
of small quantities of herbicides, cultivation, and other
cropping practices, which expose weeds to multiple stress
and mortality factors
12
.
Various studies have reported higher crop productivity
and economic return in more diverse crop rotations
than in simpler conventional systems
34,35
, while other
experiments indicated the contrary
36
. Previously, we
reported the results of a multiyear cropping systems
experiment established in Iowa to test the hypothesis that
yield, weed suppression and profit characteristics of
diversified cropping systems can match or exceed those
of conventional systems
37
. The experiment included a
conventional 2-year corn–soybean rotation, and two
more diverse rotations managed with low external inputs:
a 3-year corn–soybean–small grain/red clover system,
and a 4-year corn–soybean–small grain/alfalfa–alfalfa
system. Over a 4-year period (2003–2006), net returns
were highest for the 4-year rotation, lowest for the 3-year
rotation, and intermediate for the 2-year system, with
lower use of synthetic N fertilizer and herbicide in the
more diverse rotations
37
. Within that study, however, corn
and soybean genotypes were not necessarily the same
in the different rotation systems, i.e., rotation systems and
management practices were confounded with crop genetic
identity.
To address this issue, an experiment was initiated to
determine whether effects of cropping system diversity on
crop productivity were similar for management strategies
that differ in the genotypes planted and the weed
management programs implemented. We hypothesized
that: (i) more diverse crop rotations can achieve similar or
higher corn and soybean yields than a conventional,
simpler rotation, regardless of the genotype planted and
the herbicide and cultivation regime selected for weed
management; and (ii) the total economic return of the
more diverse rotations is similar or higher than the
conventional, simpler rotation. There are several impli-
cations of having a similar increase in productivity though
longer rotations, regardless of the genotype sown and
weed management strategy implemented. First, it would
enhance the flexibility of choosing the crop genotype to be
planted according to the needs of each production unit,
either for resistance to insects, diseases, or tolerance to
certain herbicides. Second, it would reduce the inherent
risk of depending on fixed external outputs and conse-
quent price fluctuations. Third, the risk of developing
herbicide resistance in weeds might be minimized
by allowing the use of small quantities of herbicides
with different active ingredients over time. And fourth,
by favoring a more resilient agroecosystem, it might be
possible to reduce the potential negative impacts of
environmental and biotic factors on crop yield.
Materials and Methods
Experimental site
The experiment was conducted at Iowa State University’s
(ISU’s) Marsden Farm, located in Boone County, Iowa.
The site characteristics, management history, and agro-
nomic performance of the crops from 2003 to 2008 are
reported by Liebman et al.
37
and Cruse et al.
33
. Weather
data were collected 1 km from the study site.
2R. Gómez et al.
In 2008–2010, the experiment was arranged as a split-
plot design. Main plot size was 18 m by 85 m. Each crop
within each rotation sequence was grown each year,
constituting nine main plots in each of the four replicate
blocks. The main plots corresponding to corn and
soybean were split in halves and one of two sets of
management strategies (‘GE’or ‘non-GE’) was assigned
to each subplot. For corn, the GE management strategy
consisted of a genetically engineered hybrid plus the
broadcast application of pre-emergence herbicides; the
non-GE strategy consisted of a non-genetically engineered
hybrid plus the application of post-emergence herbicides
in a 38-cm band over the crop row. The GE corn was a
stacked hybrid with genes to control both European corn
borer, Ostrinia nubilalis Hübner, and corn rootworms,
Diabrotica spp. For soybean, the GE strategy used a
genetically engineered variety with resistance to the
herbicide glyphosate plus the post-emergence broadcast
application of that herbicide; the non-GE strategy
consisted of a non-genetically engineered variety and the
application of a mixture of post-emergence herbicides in
a 38-cm-band over the crop row. The details of the corn
hybrids and soybean varieties planted, and the pre-
and post-emergence herbicides applied are provided in
Tables 1 and 2.
Crop management
Tillage operations varied among rotation systems. Fall
chisel plowing occurred in all the rotations after corn
harvest, to partially incorporate corn residue, and a
shallow fall disking was performed after soybean harvest
in the 3- and 4-year rotations to level the plots. Fall
moldboard plowing was carried out in the 3-year rotation
to incorporate the red clover and in the 4-year rotation to
incorporate the second-year alfalfa. Spring cultivation
was performed in all corn plots before planting in 2008–
2010, and in soybean plots in 2009 and 2010.
Oat was planted with red clover in the 3-year rotation
or with alfalfa in the 4-year rotation in the spring of
each year. Oat straw was baled and removed after grain
harvest, and red clover was used as a green manure. First-
year alfalfa was harvested once in each seeding year and
second-year alfalfa was harvested three times in 2008 and
four times in 2009 and 2010. Crop hybrid or cultivar,
planting and harvest dates, seed density, and row spacing
are provided in Table 1.
Soil fertility management differed among rotations: we
applied synthetic fertilizers in the 2-year rotation, whereas
we used composted cattle manure and reduced rates
of synthetic fertilizers in the 3- and 4-year rotations.
Fertilizer rates were based on soil tests from each rotation.
Soil samples (0–20 cm depth) were collected each fall and
submitted to the ISU Soil and Plant Analysis Laboratory
to determine P and K requirements. Synthetic nitrogen
was applied as urea to corn plots in the 2-year rotation
before planting, and the late spring nitrate test was used to
determine rates for post-emergence side-dress N appli-
cations in all corn plots
38
. In 2009 and 2010, no synthetic
nitrogen was applied to corn plots in the 3- and 4-year
rotations due to the presence of adequate amounts of
nitrate in the soil, according to fertilizer recommendations
for Iowa
39
. Composted cattle manure was applied to plots
of red clover and alfalfa preceding corn in the 3- and
4-year rotations at a rate of 16.2 Mg ha
−1
(fresh weight
basis). Synthetic fertilizer rates and total calculated N, P,
and K applied with the composted manure, following
analyses conducted by the ISU Soil and Plant Analysis
Laboratory, are shown in Table 3.
As noted previously, weed management differed among
rotations and management strategies in corn and soybean
plots (Table 2). Banded herbicides were supplemented
with inter-row cultivation for weed control in the non-GE
corn and soybean subplots. This cultivation occurred once
in corn and twice in soybean in 2008, and two times in
corn and soybean in 2009 and 2010. Oat stubble in the
3- and 4-year rotations was mowed 28–35 days after grain
harvest to control weeds (Table 2). No explicit weed
control was performed in established alfalfa plots.
To control soybean aphid (Aphis glycines Matsumura),
we applied the insecticides lambda-cyhalothrin
(0.027 kg a.i. ha
−1
) on August 13, 2008 and chlorpyrifos
(0.531 kg a.i. ha
−1
) on August 14, 2009 to all soybean
plots; no insecticide was applied in 2010.
Yield determination and data analysis
Six rows (382 m
2
) of each corn and soybean subplot were
harvested using a combine and grain yield was measured
in a weigh wagon. Corn weight was adjusted to reflect a
moisture concentration of 155 g kg
−1
, whereas soybean
weight was adjusted to a moisture concentration of
130 g kg
−1
. Oat grain was harvested from entire plots
(1530 m
2
) using a combine, and the weight was adjusted
to a moisture concentration of 140 g kg
−1
. Alfalfa and oat
straw were clipped and baled from entire plots, and the
weight of the bales was determined and adjusted to a
moisture concentration of 150 g kg
−1
and 100 g kg
−1
,
respectively.
Yield of each crop was analyzed separately. Analyses
of variance (ANOVAs) of corn and soybean yields were
performed using the MIXED procedure of SAS, specified
for analysis of a split-plot experiment repeated over
3 years
40
. Rotation and management strategy were
considered fixed factors, and replication and year as
random factors. Orthogonal contrasts were used to
analyze corn and soybean yield of: (i) the 2-year rotation
versus the average of the 3- and 4-year rotations (simple
versus more diverse systems); and (ii) the 3-year rotation
versus the 4-year rotation (comparison between diverse
rotations). Oat yield was analyzed using the GLM
procedure of SAS, with rotation as a fixed factor and
replication and year as random factors. Alfalfa yield over
the 3 years was analyzed using the GLM procedure.
3Comparison of crop management strategies
Weed biomass sampling and data analysis.
In corn plots, above-ground weed biomass in eight 3.05 ×
0.76 m areas per sub-plot was clipped on September 30,
2008, September 23, 2009 and September 14, 2010, and
then dried and weighed. The same methodology was used
to determine weed biomass in soybean sub-plots on
October 2, 2008, September 24, 2009 and September 30,
2010. In oat stubble with red clover, oat stubble with
alfalfa, and second year alfalfa plots, weed biomass was
collected, and then dried and weighed, from eight 0.25 m
2
randomly placed quadrats per plot on October 10, 2008,
October 6, 2009 and October 15, 2010. Weed biomass
values were transformed (ln [x+ 1]) to meet the ANOVA
requirement for normal distribution. The same ANOVA
and orthogonal contrasts performed in the crop yield
analyses were used to test for differences in weed biomass,
within the same crop, among years, rotations and
management strategies.
Economic analysis
Labor requirements, costs and returns for the different
rotation system and management strategy combinations
were assessed using data from various sources. Labor
times for machinery operations were based on values
presented by Hanna
41
and costs for labor and machinery
wear and maintenance were assigned based on reports
by Duffy
42–44
. Costs for fertilizer, seed, pesticides,
interest on loans, crop insurance and miscellaneous
items were estimated using data from Duffy
42–44
and
local agricultural dealers. We considered an integrated
low-external-cropping system representative of the region,
where the crops are fed to livestock and cattle manure
Table 1. Hybrid or cultivar grown, planting and harvest date, seed density, seed mass and inter-row spacing used in contrasting crop
rotations.
Crop
1
Year
Management
strategy
Hybrid or
cultivar
Planting
date Harvest date
Seed density
(seeds ha
−1
)
Seed mass
(kg ha
−1
)
Inter-row
spacing
(cm)
Corn 2008 Post/non-GE Agrigold 6395 May 19 November 3 79,530 –76
Corn 2009 Post/non-GE Agrigold 6395 April 23 October 21 79,530 –76
Corn 2010 Post/non-GE Agrigold 6395 April 20 October 8 79,530 –76
Corn 2008 Pre/GE Agrigold
6395BtRW
May 19 November 3 79,530 –76
Corn 2009 Pre/GE Agrigold
6395BtRw
April 23 October 21 79,530 –76
Corn 2010 Pre/GE Agrigold
6395BtRW
April 20 October 9 79,530 –76
Soybean 2008 GLY/GE Kruger 287RR May 21 October 6 382,850 –76
Soybean 2009 GLY/GE Kruger 287RR May 12 October 27 395,200 –76
Soybean 2010 GLY/GE Kruger 287RR May 19
2
October 5 395,940 –76
Soybean 2008 MIX/non-GE Kruger 2918 May 21 October 6 382,850 –76
Soybean 2009 MIX/non-GE Kruger 2918 May 12 October 27 395,200 –76
Soybean 2010 MIX/non-GE Kruger 2918 May 19
2
October 5 395,940 –76
Oat 2008 –IN09201 April 16 August 4 –83 20
Oat 2009 –IN09201 April 1 July 20 –78 20
Oat 2010 –IN09201 April 1 July 16 –81 20
Red
clover
2008 –Cherokee April 16 ––13 20
Red
clover
2009 –Duration April 1 ––13 20
Red
clover
2010 –Medium April 1 ––13 20
Alfalfa 2008 –FSG 400LH April 16 June 20, August 1,
September 17
–17 20
Alfalfa 2009 –Freedom LH April 1 June 3, July 6,
August 17,
September 15
–17 20
Alfalfa 2010 –Freedom LH April 1 May 28, July 12,
August 20,
November 30
–17 20
1
Corn and soybean were planted in all the rotation systems, oat was planted with either red clover in the 3-year rotation or with
alfalfa in the 4-year rotation.
2
In 2010, soybean was planted on May 19 in blocks 1–3 and on May 25 in block 4.
4R. Gómez et al.
is applied to the crop fields. Manure was assumed to be
generated by on-farm livestock and therefore free, but the
costs of spreading it, i.e., labor and machinery, were
calculated using data from Hanna
41
and Duffy
42–44
. Iowa
market year crop prices were obtained from the USDA
National Agricultural Statistics Service
45
.
We placed primary emphasis on determining the
economic performance characteristics of the whole
rotation systems under contrasting management strat-
egies, rather than the economic performance of individual
crop phases within the different rotations. Consequently,
we evaluated gross revenue and net returns to land and
Table 2. Weed management practices for each crop rotation from 2008 to 2010. Rate (kg ha
−1
) of herbicide active ingredients shown in
parentheses.
Crop
Management
strategy 2008 2009 2010
---------------- --- ----------------2-year rotation - - - - - - ---------------- --- --- ---
Corn Pre/GE PRE, broadcast: S-metolachlor
(1.981), isoxaflutole (0.088)
PRE, broadcast: S-metolachlor
(1.820), isoxaflutole (0.070)
PRE, broadcast: S-metolachlor
(1.820), isoxaflutole (0.070)
Corn Post/non-GE POST, banded: nicosulfuron
(0.013), rimsulfuron (0.007),
mesotrione (0.053); inter-row
cultivation (1)
POST, banded: nicosulfuron
(0.013), rimsulfuron (0.007),
mesotrione (0.053); inter-row
cultivation (2)
POST, banded: nicosulfuron
(0.013), rimsulfuron (0.007),
mesotrione (0.053); inter-row
cultivation (1)
Soybean GLY/GE POST, broadcast: glyphosate
(1.121)
POST, broadcast: glyphosate
(1.121)
POST, broadcast: glyphosate
(1.401)
Soybean MIX/non-GE POST, banded: clethodim
(0.051), lactofen (0.053),
flumiclorac pentyl ester
(0.015); inter-row
cultivation (2)
POST, banded: clethodim
(0.051), lactofen (0.070),
flumiclorac pentyl ester
(0.015); inter-row
cultivation (2)
POST, banded: clethodim
(0.051), lactofen (0.088),
flumiclorac pentyl ester
(0.023); inter-row
cultivation (2)
---------------- --- ----------------3-year rotation ---------------- --- ----------------
Corn Pre/GE PRE, broadcast: S-metolachlor
(1.981), isoxaflutole (0.088)
PRE, broadcast: S-metolachlor
(1.820), isoxaflutole (0.070)
PRE, broadcast: S-metolachlor
(1.820), isoxaflutole (0.070)
Corn Post/non-GE POST, banded: nicosulfuron
(0.013), rimsulfuron (0.007),
mesotrione (0.053); inter-row
cultivation (1)
POST, banded: nicosulfuron
(0.013), rimsulfuron (0.007),
mesotrione (0.053); inter-row
cultivation (2)
POST, banded: nicosulfuron
(0.013), rimsulfuron (0.007),
mesotrione (0.053); inter-row
cultivation (1)
Soybean GLY/GE POST, broadcast: glyphosate
(0.121)
POST, broadcast: glyphosate
(1.121)
POST, broadcast: glyphosate
(1.401)
Soybean MIX/non-GE POST, banded: clethodim
(0.051), lactofen (0.053),
flumiclorac pentyl ester
(0.015); inter-row
cultivation (2)
POST, banded: clethodim
(0.051), lactofen (0.070),
flumiclorac pentyl ester
(0.015); inter-row
cultivation (2)
POST, banded: clethodim
(0.051), lactofen (0.088),
flumiclorac pentyl ester
(0.023); inter-row
cultivation (2)
Oat + red
clover
–Stubble mowing (1) Stubble mowing (1) Stubble mowing (1)
---------------- --- ----------------4-year rotation ---------------- --- ----------------
Corn Pre/GE PRE, broadcast: S-metolachlor
(1.981), isoxaflutole (0.088)
PRE, broadcast: S-metolachlor
(1.820), isoxaflutole (0.070)
PRE, broadcast: S-metolachlor
(1.820), isoxaflutole (0.070)
Corn Post/non-GE POST, banded: nicosulfuron
(0.013), rimsulfuron (0.007),
mesotrione (0.053); inter-row
cultivation (1)
POST, banded: nicosulfuron
(0.013), rimsulfuron (0.007),
mesotrione (0.053); inter-row
cultivation (2)
POST, banded: nicosulfuron
(0.013), rimsulfuron (0.007),
mesotrione (0.053); inter-row
cultivation (1)
Soybean GLY/GE POST, broadcast: glyphosate
(0.121)
POST, broadcast: glyphosate
(1.121)
POST, broadcast: glyphosate
(1.401)
Soybean MIX/non-GE POST, banded: clethodim
(0.051), lactofen (0.053),
flumiclorac pentyl ester
(0.015); inter-row
cultivation (2)
POST, banded: clethodim
(0.051), lactofen (0.070),
flumiclorac pentyl ester
(0.015); inter-row
cultivation (2)
POST, banded: clethodim
(0.051), lactofen (0.088),
flumiclorac pentyl ester
(0.023); inter-row
cultivation (2)
Oat + alfalfa –Stubble mowing; hay
removal (1)
Stubble mowing; hay
removal (1)
Stubble mowing; hay
removal (1)
Alfalfa –Hay removal (3) Hay removal (4) Hay removal (4)
5Comparison of crop management strategies
Table 3. Fertilization regimes for crops grown in contrasting crop rotations from 2008 to 2010.
Crop 2008 2009 2010
--- ---------------- --- --- ----------------2-year rotation - - - - - - ------------------
Corn 20 kg P + 49 kg K ha
−1
as TSP
1
and KCl before planting;
114 kg N ha
−1
as urea at planting; 102 kg N ha
−1
after planting as UAN
2
112 kg N ha
−1
as urea at planting;
56 kg N ha
−1
after planting as UAN
178 kg K ha
−1
before planting as KCl; 59 kg P ha
−1
before
planting as TSP; 112 kg N ha
−1
as urea at planting;
63 kg N ha
−1
after planting as UAN
Soybean 20 kg P + 49 kg K ha
−1
as TSP and KCl before planting None 178 kg K ha
−1
before planting as KCl; 59 kg P ha
−1
before
planting as TSP
-- ---------------- --- --- ----------------3-year rotation - - - - - -------------- --- ---
Corn 119 kg N + 69 kg P + 92 kg K ha
−1
as composted manure before
planting; 102 kg N ha
−1
after planting as UAN
122 kg N + 52 kg P + 113 kg K ha
−1
as
composted manure before planting
83 kg N + 43 kg P + 73 kg K ha
−1
as composted manure
before planting; 90 kg K ha
−1
before planting as KCl
Soybean None None 90kg K ha
−1
before planting as KCl
Oat + red clover None None 90 kg K ha
−1
before planting as KCl
------------- --- --- ----------------4-year rotation - - - - --------------- --- --- ------
Corn 20 kg P + 49 kg K ha
−1
as TSP and KCl before planting; 119 kg
N + 69 P + 92 kg K ha
−1
as composted manure before
planting; 102 kg N ha
−1
after planting as UAN
122 kg N + 52 kg P + 113 kg K ha
−1
as
composted manure before planting
83 kg N + 43 kg P + 73 kg K ha
−1
as composted manure
before planting; 178 kg K ha
−1
before planting as KCl
Soybean 20 kg P + 49 kg K ha
−1
as TSP and KCl before planting None 178 kg K ha
−1
before planting as KCl
Oat + alfalfa 20 kg P + 49 kg K ha
−1
as TSP and KCl before planting None 178 kg K ha
−1
before planting as KCl
Alfalfa 20 kg P + 49 kg K ha
−1
as TSP and KCl before planting none 178 kg K ha
−1
before planting as KCl
1
TSP: triple super phosphate.
2
UAN: urea ammonium nitrate.
6R. Gómez et al.
management on a unit land area basis, with land units
divided into two equal portions for corn and soybean in
the 2-year rotation; three equal portions for corn,
soybean, and oat with red clover in the 3-year rotation;
and four equal portions for corn, soybean, oat with
alfalfa, and alfalfa in the 4-year rotation. Net returns to
land and management represented returns to a farm
operation calculated without accounting for costs of land
(e.g., rent or mortgage payments) or management time
(e.g., marketing). Split-plot ANOVAs were conducted to
examine variation in gross revenue and net returns, using
year and block as random factors and rotation system
(main plot) and management strategy (sub-plot) as fixed
factors. Orthogonal contrasts were conducted to examine
rotation effects, as described above for corn and soybean
yield analyses. Treatment interactions with year were
significant for both gross revenue and net returns, causing
us to analyze results separately by year. However, we also
evaluated these response variables averaged over the
period of 2008–2010, as a means of examining economic
performance over a longer time frame. For simplicity in
presentation, we evaluated mean costs for each rotation
system and management strategy combination by cat-
egory averaged over the period of 2008–2010.
Results
Weather conditions
Air temperature did not differ from the long-term mean
in any of the 3 years (Table 4). Precipitation fluctuation
in 2008 and 2010 was significant. May, June and July 2008
were very wet months (Table 4), some plots were
occasionally flooded for 2–3 days during those months.
Very wet conditions also occurred in June and August of
2010 (Table 4).
Nitrogen fertilizer and herbicide use
The quantity of synthetic nitrogen applied in the corn
phase of the 3- and 4-year rotations was five times lower
than in the corn phase of the conventional 2-year rotation
(Table 5). Likewise, the overall synthetic nitrogen used in
the 3- and 4-year rotations was 88 and 91% lower than
in the 2-year rotation, respectively (Table 5). There were
no differences in nitrogen use among management
strategies.
Table 4. Mean monthly air temperature and precipitation determined 1km from the study site in Boone, IA.
Month
Mean monthly air
temperature (°C)
Long-term mean
1
Total monthly
precipitation (mm)
Long-term mean
1
2008 2009 2010 2008 2009 2010
April 8.4 8.9 13.0 9.8 133 116 93 90
May 15.2 15.7 16.1 16.1 216 96 92 115
June 21.3 21.1 21.7 21.2 271 104 284 124
July 23.3 20.4 23.7 23.2 236 70 171 103
August 21.6 20.2 24.0 21.9 53 123 285 106
September 17.9 18.1 17.7 17.6 78 24 167 80
October 11.6 7.3 12.6 11.2 92 186 14 63
November 2.4 6.5 3.4 2.8 66 35 59 42
1
Long-term mean for 1951–2010.
Table 5. Mean herbicide and synthetic nitrogen fertilizer use
over 2008–2010 in the three crop rotations.
Rotation
Herbicides (kg
a.i. ha
−1
yr
−1
)
N fertilizer (kg
Nha
−1
yr
−1
)
2-year
Corn pre/GE 1.950 186.3
Corn post/non-GE 0.073 186.3
Soybean GE 1.214 0.0
Soybean non-GE 0.139 0.0
Rotation average
GE strategy
1.582 93.2
Rotation average
non-GE strategy
0.106 93.2
3-year
Corn pre/GE 1.950 34.0
Corn post/non-GE 0.073 34.0
Soybean GE 1.214 0.0
Soybean non-GE 0.139 0.0
Oat/red clover 0.000 0.0
Rotation average
GE strategy
1.055 11.3
Rotation average
non-GE strategy
0.071 11.3
4-year
Corn pre/GE 1.950 34.0
Corn post/non-GE 0.073 34.0
Soybean GE 1.214 0.0
Soybean non-GE 0.139 0.0
Oat/alfalfa 0.000 0.0
Alfalfa 0.000 0.0
Rotation average
GE strategy
0.791 8.5
Rotation average
non-GE strategy
0.053 8.5
7Comparison of crop management strategies
Herbicide use was lower in the non-GE strategy than
in the GE strategy in all the rotations due to banded
applications (Table 5). Similarly, less herbicide was
applied in the longest, most diverse rotation (Table 5)
because weed control was done mechanically in the oat
+ alfalfa and alfalfa phases.
Crop yields
Corn. The main effect of year was not significant
(P= 0.2743), and no interactions were detected among
years, rotations or management strategies. In 2008,
standing water in one plot corresponding to the 3-year
rotation with the GE management strategy caused a
reduction in plant density and therefore a reduction in
corn yield. This particular value was considered an outlier
in the dataset after testing the normality of the distri-
bution. We then performed an ANOVA and orthogonal
contrasts with and without the outlying observation,
and with the data transformed (log
e
x) and untrans-
formed. The outlier made the rotation main effect in the
ANOVA not significant, whether or not the data were
transformed. However, this value was not removed
from the dataset because the significant rotation main
effect remained evident through orthogonal contrasts
(Table 6).
Corn yield was highest in the 4-year rotation
(mean = 12.79 Mg ha
−1
), lowest in the 2-year rotation
(mean = 12.16 Mg ha
−1
) and intermediate in the 3-year
rotation (mean = 12.51 Mg ha
−1
)(Table 6). There were
significant differences in corn yield between the con-
ventional 2-year rotation and the more diverse 3- and
Table 6. Mean corn yield over the years 2008–2010.
Management strategy
GE Non-GE
--- --- ----------------Mgha
−1
------------------
Rotation system
2-year 12.49 11.82
3-year 12.59 12.43
4-year 12.82 12.75
SE 0.24 0.24
--- --- ----------------P----------------------
Effects
Rotation 0.08
Management 0.03
Rotation*Management 0.29
Contrasts
2-year versus (3-year + 4-year)/2 0.04
3-year versus 4-year 0.4
Table 7. Soybean yield from 2008 to 2010 involving three rotations and two management strategies.
2008 2009 2010
GE Non-GE GE Non-GE GE Non-GE
-----------------------------------Mgha
−1
-------------------------------------
Rotation system
2-year 3.61 3.32 3.56 3.24 2.83 1.45
3-year 3.73 3.58 4.18 3.43 3.64 3.73
4-year 3.94 3.99 4.05 3.85 3.69 3.59
SE 0.18 0.26 0.44
----------------------------------------P-----------------------------------
Effects
Rotation 0.0968 0.1046 0.0003
Management 0.0580 0.0307 0.0034
Rotation*Management 0.1308 0.3941 0.0012
Contrasts
2-year versus (3-year + 4-year)/2 0.0819 0.0460 <0.0001
3-year versus 4-year 0.1508 0.5315 0.82
8R. Gómez et al.
4-year rotations, but no differences were detected
between the 3- and 4-year systems (Table 6). We also
detected higher corn yield in the GE management
strategy (mean = 12.63 Mg ha
−1
) compared with the
non-GE management strategy (mean = 12.33 Mg ha
−1
),
in all the rotations (Table 6), although this difference was
small.
Soybean. Soybean yield was affected by a significant
three-way interaction among year, rotation and manage-
ment strategy (P= 0.0022), therefore, soybean yiel d was
analyzed separately by year. Orthogonal contrasts high-
lighted the higher soybean yield in the longer rotations
versus the conventional corn–soybean rotation in 2009
and 2010 (Table 7).
The ANOVA for each year detected significant differ-
ences in soybean yield between management strategies in
2009 and 2010 (Table 7). These differences could be the
result of abiotic and biotic factors affecting the soybean
plants in those years. In 2009, we observed severe
temporary defoliation in the non-GE subplots sprayed
with lactofen, but no precise quantification was made
on each plot. In 2010, low soil temperatures at planting
and high soil moisture during the summer favored the
attack of the soil-borne pathogen Fusarium virguliforme
Aoki & T. Aoki, which caused the disease known
as sudden death syndrome (SDS). In the 2-year rotation,
this attack affected 96% of the soybean plants in
the non-GE management strategy and 27% of the
soybean plants in the GE strategy
46
. In contrast, in the
3- and 4-year rotations, fewer than 9% of the soybean
plants of either management strategy were affected by
SDS
46
.
Oat and alfalfa. Oat grain yield was similar between
rotations (P= 0.1018) and between years 2008 and
2010, but higher in 2009 (P= 0.0250) (Table 8).
Alfalfa hay yield differed among years (P< 0.0001): it
was highest in 2010 (12.12 Mg ha
−1
), lowest in 2009
(5.48 Mg ha
−1
), and intermediate in 2008 (9.96 Mg ha
−1
)
(Table 8). The differences in alfalfa yield among
years could be attributed to extreme environmental
conditions, such as flooding in spring of 2008 and summer
of 2009.
Weed biomass. Overall, weed biomass in all the corn
and soybean plots was very low (Table 9). Because of the
few weeds present and their patchy distribution, the data
were not normally distributed and the variability was
high. This situation is common in agricultural fields with
low weed density
47
. The dominant weeds were Taraxacum
officinale F.H. Wigg. aggr., Setaria faberi R.A.W.
Herrm., Amaranthus rudis J.D. Sauer, Abutilon theo-
phrasti Medik. and Chenopodium album L. The triple
interaction of year, rotation and management strategy
was significant for weed biomass in corn plots
(P= 0.0079), therefore weed biomass was analyzed by
year. Weed biomass in corn was greater in the 4-year
rotation with the non-GE management strategy in 2008,
and in the 2-year rotation with the GE strategy in 2010.
Higher weed biomass was detected in the non-GE than
GE corn subplots in 2009 (Table 9). In soybean plots, no
differences in weed biomass were evident among rotations
or between management strategies (Table 9). Weed
biomass in oat intercropped with a legume was affected
by the interaction between year and rotation (P= 0.0289).
Weed biomass in oat did not differ between rotations in
2008 and 2010, but was lower in the 3-year rotation in
2009 (Table 9).
Economic analysis. In 2008, gross revenue was higher in
the 2-year rotation ($1623 ha
−1
yr
−1
) than in the 3-year
($1472 ha
−1
yr
−1
) and 4-year ($1526 ha
−1
yr
−1
) rotations,
but was unaffected by management strategy (Fig. 1A;
Table 10). Similarly, in 2009, gross revenue was higher in
the 2-year rotation ($1474 ha
−1
yr
−1
) than in the 3-year
($1284 ha
−1
yr
−1
) and 4-year ($1210 ha
−1
yr
−1
) rotations,
but it was also greater with the GE ($1353 ha
−1
yr
−1
) than
the non-GE ($1292 ha
−1
yr
−1
) management strategy
(Fig. 1B; Table 10). In 2010, gross revenue was affected
by an interaction between rotation system and manage-
ment strategy such that gross revenue was greatest in the
2-year rotation managed with the GE strategy ($1806
ha
−1
yr
−1
), least in the 2-year rotation managed
with the non-GE strategy ($1466 ha
−1
yr
−1
) and inter-
mediate in the other rotation and management combi-
nations (Fig. 1C; Table 10). Average gross revenue for
the period of 2008–2010 was greatest for the 2-year
rotation managed with the GE strategy ($1662 ha
−1
yr
−1
),
least for the 3-year rotation managed with the non-
GE strategy ($1422 ha
−1
yr
−1
), and intermediate for the
other rotation and management combinations (Fig. 1D;
Table 10).
Two general patterns were evident for total production
costs (Fig. 2). First, total production costs were highest for
the 2-year rotation (mean = $780 ha
−1
yr
−1
), least for the
3-year rotation (mean = $511 ha
−1
yr
−1
) and intermediate
for the 4-year rotation (mean = $620 ha
−1
yr
−1
). Second,
the GE management strategy was slightly more costly
Table 8. Oat grain and alfalfa hay yield from 2008 to 2010.
Crop Year
Rotation system
2-year 3-year 4-year SE
--------------Mgha
−1
--------------
Oat
1
2008 –3.17 3.30 0.15
Oat
1
2009 –3.56 3.69 0.10
Oat
1
2010 –3.23 3.50 0.13
Alfalfa
2
2008 ––9.96 0.35
Alfalfa
2
2009 ––5.48 0.17
Alfalfa
2
2010 ––12.12 0.35
1
Mean yield of harvested oat straw in the 3-year rotation was
2.82, 2.81 and 1.86 Mg ha
−1
in 2008, 2009 and 2010, respect-
ively, and 2.59, 2.67 and 1.74Mg ha
−1
in the 4-year rotation.
2
Alfalfa hay yield for second-year stands. Mean first-year
alfalfa hay yield was 1.03, 1.21 and 1.13 Mg ha
−1
in 2008,
2009 and 2010, respectively.
9Comparison of crop management strategies
than the non-GE strategy in each rotation
(mean difference = $44 ha
−1
yr
−1
). With regard to cost
categories, higher synthetic fertilizer costs were incurred
by the 2-year rotation ($278 ha
−1
yr
−1
) than in the 3-year
($57 ha
−1
yr
−1
) and 4-year ($142 ha
−1
yr
−1
) rotations.
Higher quantities of synthetic nitrogen in the 2-year
Figure 1. Annual and mean gross revenue and net returns of crop management strategies in each rotation system.
Table 9. Weed biomass in crop rotations involving two management strategies from 2008–2010. Transformed (ln [x+ 1]) means are in
parentheses.
Crop Rotation system Management strategy
Year
2008 2009 2010
---------------------gm
−2
------------------------
Corn 2-year GE 0.26 (0.22) 0.23 (0.20) 1.18 (0.71)
Corn 2-year Non-GE 0.11 (0.10) 0.65 (0.44) 0.18 (0.15)
Corn 3-year GE 6.18 (0.96) 0.28 (0.24) 0.17 (0.15)
Corn 3-year Non-GE 2.81 (0.78) 1.15 (0.73) 0.70 (0.44)
Corn 4-year GE 0.16 (0.15) 0.40 (0.32) 0.17 (0.15)
Corn 4-year Non-GE 2.24 (1.09) 1.44 (0.85) 0.25 (0.22)
SE
1
(0.39) (0.13) (0.15)
Soybean 2-year GE 0.06 (0.06) 0.25 (0.22) 0.17 (0.16)
Soybean 2-year Non-GE 0.50 (0.40) 0.26 (0.22) 0.40 (0.32)
Soybean 3-year GE 0.37 (0.28) 0.22 (0.19) 0.05 (0.05)
Soybean 3-year Non-GE 0.26 (0.21) 4.48 (0.85) 0.25 (0.21)
Soybean 4-year GE 0.07 (0.07) 0.06 (0.06) 0.02 (0.02)
Soybean 4-year Non-GE 0.24 (0.17) 0.07 (0.06) 0.24 (0.20)
SE (0.09) (0.28) (0.07)
Oat 3-year –10.09 (2.17) 0.31 (0.26) 9.12 (1.77)
Oat 4-year –7.04 (1.82) 6.88 (2.04) 10.14 (2.38)
SE (0.40) (0.11) (0.51)
Alfalfa 4-year –1.27 (0.76) 51.50 (3.93) 7.93 (2.18)
SE (3.81) (3.81) (3.81)
1
Transformed (ln[x+ 1]) standard error of the mean.
10 R. Gómez et al.
rotation, and lower quantities of P and K applied in the
3-year rotation explain these differences (Table 3). Seed
costs were higher with the GE (mean = $162 ha
−1
yr
−1
)
than the non-GE (mean = $114 ha
−1
yr
−1
) strategies. Pre-
harvest machinery and operations costs differed little
among rotations, but greater harvest expenses were
incurred in the 4-year rotation (mean = $164 ha
−1
yr
−1
)
than the 3-year (mean = $125 ha
−1
yr
−1
) and 2-year (mean
= $122 ha
−1
yr
−1
) systems due to harvest of alfalfa.
Expenses for pesticides decreased with rotation
length and increased with the use of the GE manage-
ment strategy. Conversely, labor costs increased with
rotation length, reflecting added work in plowing legume
sod and spreading manure before planting corn, but
decreased with the use of the GE management strategy,
reflecting the absence of inter-row cultivation in corn and
soybean with the GE strategy. Labor costs were, however,
relatively small (< 6.5%) in all rotation × management
combinations. Insurance and miscellaneous expenses were
lower in the more diverse rotation systems than in the
conventional 2-year system.
Despite differences among rotation systems and man-
agement strategies in gross returns and production costs,
net returns to land and management were unaffected by
rotation and management in 2008 (Fig. 1A; Table 10).
However, in 2009, net returns were higher in the 2-year
(mean = $819 ha
−1
yr
−1
) and 3-year (mean = $818 ha
−1
yr
−1
) rotations than in the 4-year (mean = $739 ha
−1
yr
−1
) rotation, though they remained unaffected by
management strategy (Fig. 1B; Table 10). In 2010, net
returns were affected by a strong interaction between
rotation system and management strategy (Fig. 1C;
Table 10). Net returns in 2010 were greatest in the 3-
year rotation and did not differ within that system
between non-GE ($937 ha
−1
yr
−1
) and GE strategies
($891 ha
−1
yr
−1
). The 4-year rotation provided lower net
returns than did the 3-year rotation in 2010 and there was
no difference between the non-GE ($743 ha
−1
yr
−1
) and
GE ($728 ha
−1
yr
−1
) management strategies. A significant
difference was detected in 2010 between management
strategies for the 2-year rotation, with lower net returns
generated by the non-GE system ($442ha
−1
yr
−1
) than
the GE strategy ($692 ha
−1
yr
−1
). Average net returns for
the period of 2008–2010 were greatest in the 3-year
rotation regardless of whether it was managed with the
non-GE ($937 ha
−1
yr
−1
) or GE strategy ($928 ha
−1
yr
−1
)
(Fig. 1D; Table 10). The other rotation systems produced
significantly lower net returns with significant differences
between management strategies evident in both the 4-year
rotation (non-GE: $847 ha
−1
yr
−1
; GE: $823 ha
−1
yr
−1
)
and the 2-year rotation (non-GE: $738 ha
−1
yr
−1
;GE:
$831 ha
−1
yr
−1
)(Fig. 1D: Table 10).
Discussion
This study and previous publications
33,37
have been
consistent in showing higher productivity of corn and
soybean in rotations that are more diverse than the
conventional corn–soybean system that is prevalent in the
US Midwest, despite the lower use of synthetic fertilizer
and herbicides. In the present study, composted manure
Table 10. ANOVA of economic returns.
ANOVA
2008 2009 2010 Mean, 2008–2010
Gross
revenue
Net
returns
Gross
revenue
Net
returns
Gross
revenue
Net
returns
Gross
revenue
Net
returns
Effects ---- ---------------- --- --- ----------P--- --- ---------------- --- -- --
Rotation 0.0360 0.1644 0.0005 0.0761 0.4451 0.0018 0.0063 0.0062
Management 0.0668 0.7632 0.0186 0.8707 < 0.0001 0.0013 < 0.0001 0.0069
Rotation*Management 0.1064 0.3221 0.2770 0.4696 < 0.0001 < 0.0001 < 0.0001 < 0.0001
Contrasts
2-year versus (3-
year + 4-year)/2
0.0171 0.0825 0.0002 0.1978 0.4668 0.0013 0.0022 0.0077
3-year versus 4-year 0.2700 0.4615 0.0620 0.0490 0.3055 0.0153 0.6707 0.0155
Figure 2. Production costs of crop management strategies in
each rotation system.
11Comparison of crop management strategies
and legume residues provided sufficient quantities of
nitrogen so that no synthetic fertilizer was applied to the
3- and 4-year rotations in 2009 and 2010. The N made
available from legume residues and composted manure in
more diverse rotations is likely to be released more slowly
than N provided by commercial fertilizers and may
therefore be less susceptible to leaching into subsurface
drainage lines that discharge into streams and lakes
24
.
This represents an important potential advantage at a
time when reducing water contamination by nitrate
comprises an important goal for the design of sustainable
agricultural systems
10
. In the present study, the net
economic returns from the more diverse rotation systems
were high or higher than the conventional 2-year rotation,
even when the labor requirement was higher in the more
diverse systems. Higher economic return in the 3-year
rotation than the 4-year rotation was due to the
application of lower quantities of P and K in the 3-year
rotation. The alfalfa hay harvested from plots of the
4-year rotation removed P and K that was not offset
sufficiently by manure application, while the red clover
was not removed but incorporated into the soil in the
3-year rotation.
We also found that in the more diversified 3- and 4-year
rotation systems it was possible to implement manage-
ment strategies that differ in crop genotypes and weed
management activities, including the herbicides applied,
without altering substantially the net economic returns of
the cropping system. In the conventional 2-year rotation
system, in contrast, choice of management strategy
strongly affected net returns. It is important to note that
these two management strategies do not constitute an
extensive comparison between genetically engineered and
conventional crop performance, but rather an evaluation
of two specific sets of management tactics in which
particular genotypes were coupled with chemical and/or
physical weed control practices.
More diverse cropping systems that include crops with
different botanical characteristics and the addition of
organic matter increase microbial biomass and enhance
the functional diversity of microbial communities that
affect multiple processes within the soil, limiting the
impact of some crop pathogens
28,48
and potentially
making the system more resilient. As an example, in the
present work, we observed in 2010 a severe outbreak of
SDS of soybean, in the 2-year rotation. The appearance of
this disease was widespread in soybean fields in Iowa in
2010 and favored by certain weather and soil conditions
46
.
In the soybean plants of the 3- and 4-year rotations,
however, SDS incidence was much lower and similar
between management strategies, suggesting a rotation
effect that operates similarly regardless of the crop
genotype planted
46
. In a similar cropping systems
experiment, Porter et al.
1
suggested an association
between higher disease incidence observed in a 2-year
corn–soybean rotation with lower soybean yield, com-
pared to a 4-year corn–soybean–oat/alfalfa–alfalfa
rotation, although they did not identify the diseases
affecting soybean plants or quantify disease incidence or
severity.
Having similar economic return regardless of the
management strategy implemented gives the farmer
higher flexibility when choosing the corn and soybean
genotype to be planted and the herbicides to be applied,
and decreases the risk associated with depending on a
specific management strategy over time. Similarly, the N
supplied by composted manure and legumes made the
more diverse rotation systems less reliant on synthetic N,
and therefore less affected by the variability in fertilizer
prices.
Oat productivity in the 3- and 4-year rotations and
alfalfa productivity in the 4-year rotation had important
impacts on the rotation total economic return. Oat grain
and alfalfa hay yields varied significantly among years,
and both were less profitable than corn or soybean (data
not shown). In order to maintain high rotation economic
return, it is important to maximize the productivity of
oat and alfalfa. Although weed biomass was low in both
crops, when cold weather conditions reduced the alfalfa
stand in 2009, weed seedlings emerged and colonized
empty spaces, affecting crop growth. Weed biomass was
significantly higher in 2009 because of the successful
colonization of T. officinale in certain areas of the plots
where the alfalfa plants were damaged. Nonetheless, weed
management was generally successful in both conven-
tional and more diverse systems, and in both management
strategies. The implications of these results are that
farmers who plant non-genetically engineered genotypes
in more diverse cropping systems may achieve the same
weed control as with genetically engineered crops, and
would be less likely to depend on a single herbicide as the
control method, thereby reducing the risk of selection for
herbicide resistant weeds.
We conclude that diversified cropping systems can be as
profitable as simpler, conventional systems, require less
synthetic nitrogen and herbicide use, give greater crop
management flexibility to farmers, and can be more
resilient to biotic factors that affect crop performance. We
acknowledge, however, that broad-scale shifts to diver-
sified systems from the conventional corn–soybean system
will favor changes in crop prices, due to changes in
supply, which may create economic forces that counter-
vail diversification. Policy and economic incentives
that encourage cropping system diversification as a
means of reducing agrichemical use, retarding the
evolution of herbicide resistance in weeds, and improving
environmental quality will likely be required to promote
substantial change on a landscape level.
Acknowledgements. We thank L. Leandro for assistance with
field evaluation of SDS of soybeans, B. Hartzler and S. Goggi
for their comments and suggestions on the manuscript, and
J. Anderson, B. Beelner, M. Cruse, M. Fiscus, B. North
and A. Phillips for assistance with field operations. Funding for
12 R. Gómez et al.
this study was provided by the USDA National Research
Initiative (Project 2006-35320-16548) and the Leopold
Center for Sustainable Agriculture (Projects 2007-E09 and
E-2010-02).
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