Page |1
Physiological Responses Related to Increased Grain Yield under Drought in the First
2
Biotechnology-Derived Drought Tolerant Maize1
Accepted Article
1
3 4
Running title: Physiological responses in MON 87460 under drought
5 6
Krishna S. Nemali*, Christopher Bonin, Frank G. Dohleman, Mike Stephens, William R.
7
Reeves, Donald E. Nelson, Joy E. Whitsel, Bernard Sammons, Rebecca A. Silady, Donald
8
Anstrom, Robert E. Sharp, Osric R. Patharkar, David Clay, Marie Coffin, Margaret A. Nemeth,
9
Mark E. Leibman, Michael Luethy and Mark Lawson
10 11
K.S. Nemali, F.G. Dohleman, M. Stephens, W.R. Reeves, J.E. Whitsel, B. Sammons, D.E.
12
Nelson, D. Anstrom, M. Coffin, M.E. Leibman, M. Luethy and M. Lawson: Monsanto Company,
13
800 N. Lindbergh Blvd., St. Louis, MO.
14
C. Bonin: Agrivida, Storrs, CT 06269.
15
R. A. Silady: Biology Department, Southern Connecticut State University, New Haven, CT
16
06515.
17
R. E. Sharp, O.R. Patharkar: Division of Plant Sciences and Interdisciplinary Plant Group, 1-31
18
Agriculture Building, University of Missouri, Columbia, MO 65211.
19
D. Clay: Plant Science Department, Plant Science-Box 2207A, South Dakota State University,
20
Brookings, SD 57007.
21
M. Nemeth: Statistical Consultants Plus, LLC, St. Louis, MO
This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/pce.12446
This article is protected by copyright. All rights reserved.
Page |2
* Corresponding author: Krishna S. Nemali, Monsanto Company, 800 North Lindbergh Blvd.,
2
St. Louis, MO. Tel: 314-694-4263, Email: [email protected].
Accepted Article
1
3 4
Physiological Responses Related to Increased Grain Yield under Drought in the First
5
Biotechnology-Derived Drought Tolerant Maize
6
Krishna S. Nemali*, Christopher Bonin, Frank G. Dohleman, Mike Stephens, William R.
7
Reeves, Donald E. Nelson, Joy E. Whitsel, Bernard Sammons, Rebecca A. Silady, Donald
8
Anstrom, Robert E. Sharp, Osric R. Patharkar, David Clay, Marie Coffin, Margaret A. Nemeth,
9
Mark E. Leibman, Michael Luethy and Mark Lawson
10 11
Abstract: Maize (Zea mays sub sp. mays L.) is highly susceptible to drought stress. This
12
work focused on whole-plant physiological mechanisms by which a biotechnology-derived
13
maize event expressing bacterial cold shock protein B (CspB), MON 87460, increased grain
14
yield under drought. Plants of MON 87460 and a conventional control (hereafter ‘control’) were
15
tested in the field under well-watered (WW) and water-limited (WL) treatments imposed during
16
mid- vegetative to mid-reproductive stages during 2009-11. Across years, average grain yield
17
increased by 6% in MON 87460 compared to control under WL conditions. This was associated
18
with higher soil water content at 0.5 m depth during the treatment phase, increased ear growth,
19
decreased leaf area, leaf dry weight and sap flow rate during silking, increaesed kernel number
20
and harvest index in MON 87460 than the control. No consistent differences were observed
21
under WW conditions. This indicates that MON 87460 acclimated better under WL conditions
22
than the control by lowering leaf growth which decreased water-use during silking, thereby
23
eliciting lower stress under WL conditions. These physiological responses in MON 87460 under
This article is protected by copyright. All rights reserved.
Page |3
WL conditions resulted in increased ear growth during silking which subsequently increased
2
kernel number, harvest index and grain yield compared to the control.
3
Key words: Biotechnology, CspB, drought, ear, harvest index, leaf area, water-use, yield.
Accepted Article
1
4 5 6
Introduction
7 8
Water availability represents the most limiting factor for crop productivity (Bruce et al., 2002).
9
Maize is an economically important crop that is highly susceptible to drought. Recent research
10
indicates that historic maize yield gains with increasing planting densities in the US were
11
accompanied with increased sensitivity to drought in the modern hybrids (Lobell et al., 2014).
12
Efforts have been made for decades to enhance drought tolerance through plant breeding
13
techniques (Campos et al., 2006). Some of the gains through breeding have increased maize
14
tolerance to drought stress during flowering, the developmental stage most sensitive to water
15
limitation (Classen and Shaw, 1970; Boyer and Westgate, 2004; Campos et al., 2006). More
16
recently, transgenic approaches have been applied with the hope of modulating endogenous
17
stress pathways through the expression of key genes to accelerate the process of enhancing
18
drought tolerance (Nelson et al., 2007; Castiglioni et al., 2008). Monsanto, in collaboration with
19
BASF, developed the first biotechnology-derived drought-tolerant maize (MON 87460) by
20
expressing bacterial cold shock protein B (CspB) in maize. The purpose of this work was to
21
understand the physiological differences related to grain yield between MON 87460 and the
22
control.
This article is protected by copyright. All rights reserved.
Page |4
Cold shock proteins (CSP) contain RNA binding sequences referred to as cold shock
2
domains (CSD) and are well known to act as RNA chaperones (Horn et al., 2007). The CSD-
3
containing proteins transiently and non-specifically bind to RNA (Hofweber et al., 2005; Horn et
4
al., 2007). The most well characterized CSP proteins are the orthologs CspA from Escherichia
5
coli and CspB from Bacillus subtilis. The role of CSP in bacterial adaptation to cold stress is
6
discussed in Horn et al., 2007 and Barria et al., 2013. Cold shock proteins in bacteria have a
7
potential to completely inhibit translation at high concentrations (Horn et al., 2007). When
8
bacteria are exposed to cold stress, CSP synthesis is favored while non-CSP synthesis and
9
bacterial growth are transiently inhibited (Horn et al., 2007). After acclimation to cold stress is
10
complete, non-CSP synthesis and bacterial growth are restored at a slower rate (Horn et al.,
11
2007). Plant CSD-containing proteins share a high level of similarity with the bacterial CSPs
12
and were shown to share in vitro and in vivo functions with bacterial CSPs (Karlson and Imai,
13
2003; Kim et al, 2007; Nakaminami et al., 2005 and 2006; Chaikam and Karlson, 2008; Fusaro
14
et al., 2007). Plant CSD-containing proteins have generally been reported to respond to abiotic
15
stresses (Karlson et al., 2002; Fusaro et al., 2007; Castiglioni et al., 2008; Chaikam and Karlson,
16
2008; Juntawong et al., 2013). The CSPs accumulate to high amounts in recently divided, not
17
yet expanded plant cell types that exhibit meristematic activity (Nakaminami et al., 2006;
18
Chaikam and Karlson, 2008). In such cell types, the combination of water deficit that generally
19
slows global translation and comparatively high CSP accumulation may result in reduced cellular
20
expansion.
Accepted Article
1
21
Knowledge of component physiological processes can aid in understanding mechanisms
22
related to grain yield differences under WL conditions. Grain yield in maize can be determined
23
as the product of the plant dry matter and harvest index (Monteith, 1977; Passioura, 1996).
This article is protected by copyright. All rights reserved.
Page |5
Genetic improvement for grain yield in the US and Canada was associated with increase in plant
2
dry matter production without a change in harvest index (Tollenaar and Lee, 2006). However in
3
Argentina, where drought stress can significantly affect crop production, genetic improvement
4
for grain yield was associated with improvement in harvest index without a change in plant dry
5
matter production (Edmeades et al., 1999; Echarte et al., 2004; Tollenaar and Lee, 2006).
6
Increase in harvest index was associated with increased kernel set at harvest and specific increase
7
in ear growth/dry matter partitioning to ear at silking (the first reproductive stage) in the modern
8
Argentinean hybrids (Echarte et al., 2004). An association between ear size at silking and kernel
9
set at harvest was reported elsewhere (Fisher and Palmer, 1983; Echarte et al., 2004; Severini et
10
al, 2011). Thus, it appears that increased ear size at silking is a mechanism to increase kernel set,
11
harvest index and grain yield in maize under WL conditions.
Accepted Article
1
12
The objective of the current work was to understand the physiological responses related to
13
grain yield differences between MON 87460 and the control under WL conditions by testing
14
hypotheses on mechanisms that affect grain yield and yield components.
15 16 17
Materials and methods
18 19
Plant materials, planting details and water treatments:
20
Transgenic maize (MON 87460) and control (Monsanto hybrid NH6212) were tested in the field
21
trials from 2009 to 2011 in Woodland, CA, US. The relative maturity of the control was 110
22
days and is suitable for cultivation in CA, US. Both the control and MON 87460 were F1
23
hybrids with same genetic background except for the absence of transgene in the control. MON
This article is protected by copyright. All rights reserved.
Page |6
87460 was produced by Agrobacterium-mediated transformation. The genetic insert in MON
2
87460 contains the rice actin1 promoter (McElroy et al., 1990), linked to a rice actin1 intron
3
(McElroy et al., 1991).
4
U58859) was introduced with the exception that for cloning convenience the codon for the
5
second amino acid was modified, changing the encoded amino acid from Leucine to Valine.
6
MON 87460 also contains the coding sequence for neomycin phosphotransferase II (NPTII)
7
which was used as a selectable marker (Monsanto Company, 2009).
Accepted Article
1
The native coding region for CspB (GenBank accession number
8
For all years, seed was planted at a density of approximately 88,000 plants per hectare into
9
raised beds approximately 0.10 m high, with row spacing of 0.76 m. Irrigation tape was buried
10
under soil between beds for sub-surface water application. The soil type was silty clay with 1.5
11
to 2% organic matter and a pH of 6.9 to 7.0. At any site, two treatment blocks (WW and WL)
12
were planted each year. Treatment blocks were separated by a four-row buffer of conventional
13
maize.
14
contained randomized MON 87460 and control plots. Details on the number of replications, row
15
number per replication, row length, and row spacing for different years are shown in table 1.
Each treatment block was divided in to several replications and each replication
16
Daily meteorological data were collected to calculate daily reference evapo-transpiration
17
(ET) using calculations described by Monteith (1965). Crop ET, estimated from reference ET
18
and crop coefficient values for California were used to estimate daily water consumption by the
19
crop to determine the amount of irrigation needed for each treatment. The WW treatment was
20
managed to provide optimal grain yield by targeting replacement of 100% crop ET from planting
21
through physiological maturity. The WL treatment was managed to impose drought conditions
22
by withholding irrigation during the mid vegetative to mid reproductive stages (~V10 – R3
23
stages). Rescue irrigations were provided as needed in the WL treatment to prevent crop failure.
This article is protected by copyright. All rights reserved.
Page |7
The cumulative irrigation volumes applied to WW and WL treatments during 2009 and 2010 are
2
shown in supporting information figure S1. Throughout the remainder of the growing season
3
(i.e. before stress and after stress), irrigation targeted 100% ET replacement in the WL treatment.
4
Minimal precipitation occurred at any site during the treatment phase (~V10-R3 stages).
5
Measurements:
6
Details about measurements conducted during different years and number of replicates analyzed
7
for each measurement are shown in table 1.
8
(Table 1 will be inserted here)
Accepted Article
1
9
2009: Physiological responses were measured during the treatment phase and at harvest
10
under WL and WW conditions.
11
conductance, leaf area and leaf dry weight per plant during the treatment phase, ear diameter
12
during silking, ear number, kernel number, single kernel weight, harvest index and grain yield at
13
harvest.
Measurements included leaf photosynthesis rate, stomatal
14
Leaf photosynthesis rate and stomatal conductance to H2O were measured around mid-day
15
on multiple days during the treatment phase in the WW and WL treatments. Measurements were
16
collected on sunlit leaves from one plant per replication using a portable open path gas exchange
17
system (Li-Cor 6400; Li-Cor, Inc., Lincoln, NE USA). Environmental conditions maintained
18
inside the cuvette included a CO2 concentration of 380 µmol mol-1, photosynthetic photon flux of
19
1000 µmol m-2 s-1 and a relative humidity of the sample chamber at 50%. Leaf area and leaf dry
20
weight were measured at multiple time points during the treatment phase from 4-6 plants in each
21
replication. Leaves were separated from the plants and their total area was measured using an
22
area meter (LiCor 3100 C, LiCor, Lincoln, NE). Then leaf dry weight was measured by drying
23
separated leaves in a forced air oven at 80 °C until constant weight was reached. From this data, This article is protected by copyright. All rights reserved.
Page |8
leaf area and leaf dry weight per plant were calculated. Diameter of the primary ear on 10 plants
2
per replication was measured at multiple times during silking. From this data, average ear
3
diameter per plant was calculated. Ear diameter was measured at the midpoint between the tip
4
and the base of the ear. At harvest, plants from 2 rows were cut at the ground level and separated
5
into vegetative material and ears. The ears on plants were counted. Fresh weight of the
6
vegetative material and ears was measured. A sub-sample of vegetative material and ears were
7
dried separately in a forced air oven at 80 °C until constant weight was reached. The relation
8
between fresh and dry weights was calculated from sub-sample material. This relation was used
9
to estimate dry weight of the vegetative material and ears collected from 2 rows. Plant dry
10
weight was measured as the sum of vegetative and ear dry weight. Kernels on the ears were
11
shelled, their moisture content and weight were determined.
12
adjusting kernel moisture to 15.5% as total kernel weight/ m2 and converted to Mg ha-1. Later,
13
kernels were dried in a forced air oven at 80 °C until constant weight was reached. The dry
14
weight of 1000 kernels was measured from which single kernel weight was calculated. Kernel
15
number was estimated as the ratio of kernel dry weight to single kernel weight. From this,
16
number of kernels per ear was estimated as the ratio of kernel number to ear number. Harvest
17
index was calculated as the ratio of kernel dry weight to plant (vegetative material + ear) dry
18
weight.
Accepted Article
1
Grain yield was measured after
19
2010: Physiological responses were measured at silking and harvest growth stages in the WL
20
and WW treatments. At silking, leaf area, ear and plant dry weights were measured per plant.
21
Measurements at harvest included plant dry weight, kernel number/m2, single kernel weight,
22
harvest index and grain yield.
This article is protected by copyright. All rights reserved.
Page |9
Leaf area was measured as described in 2009 from 6 plants per replicate to determine leaf
2
area per plant. At silking, plants from 1 m length of the designated row were cut at the ground
3
level. Vegetative and ear material separated and dried in a forced air oven at 80 °C until constant
4
weight was reached to determine their dry weights. Plant dry weight was determined as the sum
5
of vegetative and ear dry weights. Grain yield was measured from separate rows as described for
6
2009. In addition, plants from 1 m length of the designated row were cut at the ground level and
7
separated into vegetative material and the primary ear at harvest.
8
separately in a forced air oven at 80 °C until constant weight was reached. Plant dry weight,
9
single kernel weight, kernel number and harvest index were measured as described in 2009.
Accepted Article
1
The material was dried
10
2011: Physiological responses were measured during silking under WW and WL conditions.
11
Plant and ear dry weights at silking, number of days to reach 50% silking, sap flow rate during
12
the treatment phase and soil profile water content were measured. Although not a focus, grain
13
yield was measured at harvest.
14
Ear and plant dry weights at silking were measured as describe din 2010. Sap flow rate was
15
used to measure plant water-use (Dynagauge sensors; FLOW-32, Dynamax, Houston, TX)
16
during the treatment phase in the WL and WW treatments. Sap flow rate was measured based on
17
manufacturer guidelines on a single plant per replication that was close to the soil water content
18
monitoring probe (described below). The measurements were made once every 10 min and
19
averaged to out put daily values. Soil water content was measured using 1.6 m long capacitance
20
probes (Enviroscan, Sentek Sensor Technologies, Stepney SA, Australia) during the season.
21
Probes were installed in the soil at the center of the two rows after plant establishment. The
22
scaled frequency data generated by the probes was collected continuously (every two minutes)
23
using a data logger from plant establishment until harvest. Scaled frequencies were converted to
This article is protected by copyright. All rights reserved.
P a g e | 10
estimate soil water content (expressed as meter of water per meter of soil, m.m-1) using the
2
standard conversion formula provided by the vendor (Sentek Sensor Technologies).
3
minute interval data was averaged to calculate daily average soil water content for the entire
4
season in the WL and WW treatments. Average soil water content at different depths and
5
percent change in daily average soil water content relative to the start of the treatment at a depth
6
of 0.5 m were calculated for WL treatment during the treatment phase.
7
Experimental design and statistical analyses:
8
The WW and WL treatment blocks were planted and analyzed as separate experiments. For both
9
treatments and all years, the experimental design was a randomized complete block (RCBD).
10
The number of replications within a treatment varied by the year and measurement type. The
11
two plant materials, MON 87460 and control, were assigned randomly to separate plots within
12
each replication.
Accepted Article
1
The two-
13
Measured responses were analyzed using ANOVA (SAS Version 9.2, SAS Institute, Inc.
14
2002-2008) and means were separated using t-tests. Comparisons for measured responses were
15
made between MON 87460 and the control for each year within a treatment. A combined-site
16
analysis was used in 2009 and 2010 as data were collected from two different sites in each year.
17
Leaf area, leaf dry weight and ear diameter were also analyzed by the measurement time. Daily
18
average sap flow rate and percent change in daily average soil water content at 0.5 m depth
19
during the treatment phase were analyzed by repeated measures. For all analyses, a p-value
Physiological Responses Related to Increased Grain Yield under Drought in the First
2
Biotechnology-Derived Drought Tolerant Maize1
Accepted Article
1
3 4
Running title: Physiological responses in MON 87460 under drought
5 6
Krishna S. Nemali*, Christopher Bonin, Frank G. Dohleman, Mike Stephens, William R.
7
Reeves, Donald E. Nelson, Joy E. Whitsel, Bernard Sammons, Rebecca A. Silady, Donald
8
Anstrom, Robert E. Sharp, Osric R. Patharkar, David Clay, Marie Coffin, Margaret A. Nemeth,
9
Mark E. Leibman, Michael Luethy and Mark Lawson
10 11
K.S. Nemali, F.G. Dohleman, M. Stephens, W.R. Reeves, J.E. Whitsel, B. Sammons, D.E.
12
Nelson, D. Anstrom, M. Coffin, M.E. Leibman, M. Luethy and M. Lawson: Monsanto Company,
13
800 N. Lindbergh Blvd., St. Louis, MO.
14
C. Bonin: Agrivida, Storrs, CT 06269.
15
R. A. Silady: Biology Department, Southern Connecticut State University, New Haven, CT
16
06515.
17
R. E. Sharp, O.R. Patharkar: Division of Plant Sciences and Interdisciplinary Plant Group, 1-31
18
Agriculture Building, University of Missouri, Columbia, MO 65211.
19
D. Clay: Plant Science Department, Plant Science-Box 2207A, South Dakota State University,
20
Brookings, SD 57007.
21
M. Nemeth: Statistical Consultants Plus, LLC, St. Louis, MO
This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/pce.12446
This article is protected by copyright. All rights reserved.
Page |2
* Corresponding author: Krishna S. Nemali, Monsanto Company, 800 North Lindbergh Blvd.,
2
St. Louis, MO. Tel: 314-694-4263, Email: [email protected].
Accepted Article
1
3 4
Physiological Responses Related to Increased Grain Yield under Drought in the First
5
Biotechnology-Derived Drought Tolerant Maize
6
Krishna S. Nemali*, Christopher Bonin, Frank G. Dohleman, Mike Stephens, William R.
7
Reeves, Donald E. Nelson, Joy E. Whitsel, Bernard Sammons, Rebecca A. Silady, Donald
8
Anstrom, Robert E. Sharp, Osric R. Patharkar, David Clay, Marie Coffin, Margaret A. Nemeth,
9
Mark E. Leibman, Michael Luethy and Mark Lawson
10 11
Abstract: Maize (Zea mays sub sp. mays L.) is highly susceptible to drought stress. This
12
work focused on whole-plant physiological mechanisms by which a biotechnology-derived
13
maize event expressing bacterial cold shock protein B (CspB), MON 87460, increased grain
14
yield under drought. Plants of MON 87460 and a conventional control (hereafter ‘control’) were
15
tested in the field under well-watered (WW) and water-limited (WL) treatments imposed during
16
mid- vegetative to mid-reproductive stages during 2009-11. Across years, average grain yield
17
increased by 6% in MON 87460 compared to control under WL conditions. This was associated
18
with higher soil water content at 0.5 m depth during the treatment phase, increased ear growth,
19
decreased leaf area, leaf dry weight and sap flow rate during silking, increaesed kernel number
20
and harvest index in MON 87460 than the control. No consistent differences were observed
21
under WW conditions. This indicates that MON 87460 acclimated better under WL conditions
22
than the control by lowering leaf growth which decreased water-use during silking, thereby
23
eliciting lower stress under WL conditions. These physiological responses in MON 87460 under
This article is protected by copyright. All rights reserved.
Page |3
WL conditions resulted in increased ear growth during silking which subsequently increased
2
kernel number, harvest index and grain yield compared to the control.
3
Key words: Biotechnology, CspB, drought, ear, harvest index, leaf area, water-use, yield.
Accepted Article
1
4 5 6
Introduction
7 8
Water availability represents the most limiting factor for crop productivity (Bruce et al., 2002).
9
Maize is an economically important crop that is highly susceptible to drought. Recent research
10
indicates that historic maize yield gains with increasing planting densities in the US were
11
accompanied with increased sensitivity to drought in the modern hybrids (Lobell et al., 2014).
12
Efforts have been made for decades to enhance drought tolerance through plant breeding
13
techniques (Campos et al., 2006). Some of the gains through breeding have increased maize
14
tolerance to drought stress during flowering, the developmental stage most sensitive to water
15
limitation (Classen and Shaw, 1970; Boyer and Westgate, 2004; Campos et al., 2006). More
16
recently, transgenic approaches have been applied with the hope of modulating endogenous
17
stress pathways through the expression of key genes to accelerate the process of enhancing
18
drought tolerance (Nelson et al., 2007; Castiglioni et al., 2008). Monsanto, in collaboration with
19
BASF, developed the first biotechnology-derived drought-tolerant maize (MON 87460) by
20
expressing bacterial cold shock protein B (CspB) in maize. The purpose of this work was to
21
understand the physiological differences related to grain yield between MON 87460 and the
22
control.
This article is protected by copyright. All rights reserved.
Page |4
Cold shock proteins (CSP) contain RNA binding sequences referred to as cold shock
2
domains (CSD) and are well known to act as RNA chaperones (Horn et al., 2007). The CSD-
3
containing proteins transiently and non-specifically bind to RNA (Hofweber et al., 2005; Horn et
4
al., 2007). The most well characterized CSP proteins are the orthologs CspA from Escherichia
5
coli and CspB from Bacillus subtilis. The role of CSP in bacterial adaptation to cold stress is
6
discussed in Horn et al., 2007 and Barria et al., 2013. Cold shock proteins in bacteria have a
7
potential to completely inhibit translation at high concentrations (Horn et al., 2007). When
8
bacteria are exposed to cold stress, CSP synthesis is favored while non-CSP synthesis and
9
bacterial growth are transiently inhibited (Horn et al., 2007). After acclimation to cold stress is
10
complete, non-CSP synthesis and bacterial growth are restored at a slower rate (Horn et al.,
11
2007). Plant CSD-containing proteins share a high level of similarity with the bacterial CSPs
12
and were shown to share in vitro and in vivo functions with bacterial CSPs (Karlson and Imai,
13
2003; Kim et al, 2007; Nakaminami et al., 2005 and 2006; Chaikam and Karlson, 2008; Fusaro
14
et al., 2007). Plant CSD-containing proteins have generally been reported to respond to abiotic
15
stresses (Karlson et al., 2002; Fusaro et al., 2007; Castiglioni et al., 2008; Chaikam and Karlson,
16
2008; Juntawong et al., 2013). The CSPs accumulate to high amounts in recently divided, not
17
yet expanded plant cell types that exhibit meristematic activity (Nakaminami et al., 2006;
18
Chaikam and Karlson, 2008). In such cell types, the combination of water deficit that generally
19
slows global translation and comparatively high CSP accumulation may result in reduced cellular
20
expansion.
Accepted Article
1
21
Knowledge of component physiological processes can aid in understanding mechanisms
22
related to grain yield differences under WL conditions. Grain yield in maize can be determined
23
as the product of the plant dry matter and harvest index (Monteith, 1977; Passioura, 1996).
This article is protected by copyright. All rights reserved.
Page |5
Genetic improvement for grain yield in the US and Canada was associated with increase in plant
2
dry matter production without a change in harvest index (Tollenaar and Lee, 2006). However in
3
Argentina, where drought stress can significantly affect crop production, genetic improvement
4
for grain yield was associated with improvement in harvest index without a change in plant dry
5
matter production (Edmeades et al., 1999; Echarte et al., 2004; Tollenaar and Lee, 2006).
6
Increase in harvest index was associated with increased kernel set at harvest and specific increase
7
in ear growth/dry matter partitioning to ear at silking (the first reproductive stage) in the modern
8
Argentinean hybrids (Echarte et al., 2004). An association between ear size at silking and kernel
9
set at harvest was reported elsewhere (Fisher and Palmer, 1983; Echarte et al., 2004; Severini et
10
al, 2011). Thus, it appears that increased ear size at silking is a mechanism to increase kernel set,
11
harvest index and grain yield in maize under WL conditions.
Accepted Article
1
12
The objective of the current work was to understand the physiological responses related to
13
grain yield differences between MON 87460 and the control under WL conditions by testing
14
hypotheses on mechanisms that affect grain yield and yield components.
15 16 17
Materials and methods
18 19
Plant materials, planting details and water treatments:
20
Transgenic maize (MON 87460) and control (Monsanto hybrid NH6212) were tested in the field
21
trials from 2009 to 2011 in Woodland, CA, US. The relative maturity of the control was 110
22
days and is suitable for cultivation in CA, US. Both the control and MON 87460 were F1
23
hybrids with same genetic background except for the absence of transgene in the control. MON
This article is protected by copyright. All rights reserved.
Page |6
87460 was produced by Agrobacterium-mediated transformation. The genetic insert in MON
2
87460 contains the rice actin1 promoter (McElroy et al., 1990), linked to a rice actin1 intron
3
(McElroy et al., 1991).
4
U58859) was introduced with the exception that for cloning convenience the codon for the
5
second amino acid was modified, changing the encoded amino acid from Leucine to Valine.
6
MON 87460 also contains the coding sequence for neomycin phosphotransferase II (NPTII)
7
which was used as a selectable marker (Monsanto Company, 2009).
Accepted Article
1
The native coding region for CspB (GenBank accession number
8
For all years, seed was planted at a density of approximately 88,000 plants per hectare into
9
raised beds approximately 0.10 m high, with row spacing of 0.76 m. Irrigation tape was buried
10
under soil between beds for sub-surface water application. The soil type was silty clay with 1.5
11
to 2% organic matter and a pH of 6.9 to 7.0. At any site, two treatment blocks (WW and WL)
12
were planted each year. Treatment blocks were separated by a four-row buffer of conventional
13
maize.
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contained randomized MON 87460 and control plots. Details on the number of replications, row
15
number per replication, row length, and row spacing for different years are shown in table 1.
Each treatment block was divided in to several replications and each replication
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Daily meteorological data were collected to calculate daily reference evapo-transpiration
17
(ET) using calculations described by Monteith (1965). Crop ET, estimated from reference ET
18
and crop coefficient values for California were used to estimate daily water consumption by the
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crop to determine the amount of irrigation needed for each treatment. The WW treatment was
20
managed to provide optimal grain yield by targeting replacement of 100% crop ET from planting
21
through physiological maturity. The WL treatment was managed to impose drought conditions
22
by withholding irrigation during the mid vegetative to mid reproductive stages (~V10 – R3
23
stages). Rescue irrigations were provided as needed in the WL treatment to prevent crop failure.
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The cumulative irrigation volumes applied to WW and WL treatments during 2009 and 2010 are
2
shown in supporting information figure S1. Throughout the remainder of the growing season
3
(i.e. before stress and after stress), irrigation targeted 100% ET replacement in the WL treatment.
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Minimal precipitation occurred at any site during the treatment phase (~V10-R3 stages).
5
Measurements:
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Details about measurements conducted during different years and number of replicates analyzed
7
for each measurement are shown in table 1.
8
(Table 1 will be inserted here)
Accepted Article
1
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2009: Physiological responses were measured during the treatment phase and at harvest
10
under WL and WW conditions.
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conductance, leaf area and leaf dry weight per plant during the treatment phase, ear diameter
12
during silking, ear number, kernel number, single kernel weight, harvest index and grain yield at
13
harvest.
Measurements included leaf photosynthesis rate, stomatal
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Leaf photosynthesis rate and stomatal conductance to H2O were measured around mid-day
15
on multiple days during the treatment phase in the WW and WL treatments. Measurements were
16
collected on sunlit leaves from one plant per replication using a portable open path gas exchange
17
system (Li-Cor 6400; Li-Cor, Inc., Lincoln, NE USA). Environmental conditions maintained
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inside the cuvette included a CO2 concentration of 380 µmol mol-1, photosynthetic photon flux of
19
1000 µmol m-2 s-1 and a relative humidity of the sample chamber at 50%. Leaf area and leaf dry
20
weight were measured at multiple time points during the treatment phase from 4-6 plants in each
21
replication. Leaves were separated from the plants and their total area was measured using an
22
area meter (LiCor 3100 C, LiCor, Lincoln, NE). Then leaf dry weight was measured by drying
23
separated leaves in a forced air oven at 80 °C until constant weight was reached. From this data, This article is protected by copyright. All rights reserved.
Page |8
leaf area and leaf dry weight per plant were calculated. Diameter of the primary ear on 10 plants
2
per replication was measured at multiple times during silking. From this data, average ear
3
diameter per plant was calculated. Ear diameter was measured at the midpoint between the tip
4
and the base of the ear. At harvest, plants from 2 rows were cut at the ground level and separated
5
into vegetative material and ears. The ears on plants were counted. Fresh weight of the
6
vegetative material and ears was measured. A sub-sample of vegetative material and ears were
7
dried separately in a forced air oven at 80 °C until constant weight was reached. The relation
8
between fresh and dry weights was calculated from sub-sample material. This relation was used
9
to estimate dry weight of the vegetative material and ears collected from 2 rows. Plant dry
10
weight was measured as the sum of vegetative and ear dry weight. Kernels on the ears were
11
shelled, their moisture content and weight were determined.
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adjusting kernel moisture to 15.5% as total kernel weight/ m2 and converted to Mg ha-1. Later,
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kernels were dried in a forced air oven at 80 °C until constant weight was reached. The dry
14
weight of 1000 kernels was measured from which single kernel weight was calculated. Kernel
15
number was estimated as the ratio of kernel dry weight to single kernel weight. From this,
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number of kernels per ear was estimated as the ratio of kernel number to ear number. Harvest
17
index was calculated as the ratio of kernel dry weight to plant (vegetative material + ear) dry
18
weight.
Accepted Article
1
Grain yield was measured after
19
2010: Physiological responses were measured at silking and harvest growth stages in the WL
20
and WW treatments. At silking, leaf area, ear and plant dry weights were measured per plant.
21
Measurements at harvest included plant dry weight, kernel number/m2, single kernel weight,
22
harvest index and grain yield.
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Page |9
Leaf area was measured as described in 2009 from 6 plants per replicate to determine leaf
2
area per plant. At silking, plants from 1 m length of the designated row were cut at the ground
3
level. Vegetative and ear material separated and dried in a forced air oven at 80 °C until constant
4
weight was reached to determine their dry weights. Plant dry weight was determined as the sum
5
of vegetative and ear dry weights. Grain yield was measured from separate rows as described for
6
2009. In addition, plants from 1 m length of the designated row were cut at the ground level and
7
separated into vegetative material and the primary ear at harvest.
8
separately in a forced air oven at 80 °C until constant weight was reached. Plant dry weight,
9
single kernel weight, kernel number and harvest index were measured as described in 2009.
Accepted Article
1
The material was dried
10
2011: Physiological responses were measured during silking under WW and WL conditions.
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Plant and ear dry weights at silking, number of days to reach 50% silking, sap flow rate during
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the treatment phase and soil profile water content were measured. Although not a focus, grain
13
yield was measured at harvest.
14
Ear and plant dry weights at silking were measured as describe din 2010. Sap flow rate was
15
used to measure plant water-use (Dynagauge sensors; FLOW-32, Dynamax, Houston, TX)
16
during the treatment phase in the WL and WW treatments. Sap flow rate was measured based on
17
manufacturer guidelines on a single plant per replication that was close to the soil water content
18
monitoring probe (described below). The measurements were made once every 10 min and
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averaged to out put daily values. Soil water content was measured using 1.6 m long capacitance
20
probes (Enviroscan, Sentek Sensor Technologies, Stepney SA, Australia) during the season.
21
Probes were installed in the soil at the center of the two rows after plant establishment. The
22
scaled frequency data generated by the probes was collected continuously (every two minutes)
23
using a data logger from plant establishment until harvest. Scaled frequencies were converted to
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P a g e | 10
estimate soil water content (expressed as meter of water per meter of soil, m.m-1) using the
2
standard conversion formula provided by the vendor (Sentek Sensor Technologies).
3
minute interval data was averaged to calculate daily average soil water content for the entire
4
season in the WL and WW treatments. Average soil water content at different depths and
5
percent change in daily average soil water content relative to the start of the treatment at a depth
6
of 0.5 m were calculated for WL treatment during the treatment phase.
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Experimental design and statistical analyses:
8
The WW and WL treatment blocks were planted and analyzed as separate experiments. For both
9
treatments and all years, the experimental design was a randomized complete block (RCBD).
10
The number of replications within a treatment varied by the year and measurement type. The
11
two plant materials, MON 87460 and control, were assigned randomly to separate plots within
12
each replication.
Accepted Article
1
The two-
13
Measured responses were analyzed using ANOVA (SAS Version 9.2, SAS Institute, Inc.
14
2002-2008) and means were separated using t-tests. Comparisons for measured responses were
15
made between MON 87460 and the control for each year within a treatment. A combined-site
16
analysis was used in 2009 and 2010 as data were collected from two different sites in each year.
17
Leaf area, leaf dry weight and ear diameter were also analyzed by the measurement time. Daily
18
average sap flow rate and percent change in daily average soil water content at 0.5 m depth
19
during the treatment phase were analyzed by repeated measures. For all analyses, a p-value
