Heat Stress in Field-Grown Maize: Response of ...

3 downloads 0 Views 1MB Size Report
May 21, 2010 - heat of plant grain yield (PGY) components [ker- nel number per plant (KNP) and individual kernel weight (KW)] and the physiological determi-.

RESEARCH

Heat Stress in Field-Grown Maize: Response of Physiological Determinants of Grain Yield M. Cicchino, J. I. Rattalino Edreira, M. Uribelarrea, and M. E. Otegui*

ABSTRACT Heat stress around flowering has negative effects on maize (Zea mays L.) grain yield. Most research on this topic focused on the response of pollen viability and pollination constraints, and little is known about the relative response to heat of plant grain yield (PGY) components [kernel number per plant (KNP) and individual kernel weight (KW)] and the physiological determinants of grain yield [light interception efficiency (ei), radiation use efficiency (RUE), and harvest index (HI)]. Field experiments were performed to study the response of physiological traits to contrasting air temperature regimes at ear level [nonheated control (TC) and heated (TH; with air temperature >35°C around noon)]. Heating was performed during periods of approximately 15 d at two growth stages [presilking (GS1) and postsilking (GS2)]. All silked ears received fresh pollen. Heating during GS1 caused (i) a larger delay in silking date than in anthesis date, (ii) an increase in male and female sterility, and (iii) a reduction in plant height and leaf area index, but not in ei. Heating always caused a reduction in (i) plant and ear growth rates (EGR) around silking, (ii) RUE around silking, and (iii) HI and KNP. Final PGY was related to KNP (r2 = 0.89, p < 0.001) but not to KW. Variations in KNP were explained (r2 = 0.71, p < 0.0001) by variations in EGR postsilking (EGRPOST ) and not presilking, evidence of long-term effects of heat stress during GS1. Variations in EGRPOST depended on variations in RUE postsilking (RUEPOST ) and not on biomass partitioning to the ear.

Av. San Martín 4453 (ZIP: C1417DSE), Ciudad de Buenos Aires, Argentina. Received 7 Oct. 2009. *Corresponding author ([email protected] agro.uba.ar). Abbreviations: ASI, anthesis–silking interval; ASIIP, anthesis–silking interval of individual plants; ASIPP, anthesis–silking interval of the plant population; EGR, ear growth rate; EGR PRE, EGR presilking; EGR POST, EGR postsilking; EGRCP, EGR critical period; ei, light interception efficiency; GSn, growth stage n; HI, harvest index; IPAR, incident photosynthetically active radiation; IPARi, intercepted IPAR; IPARSB, IPAR immediately below the lowermost green leaves within the shelters; IPARST, IPAR at the top of plants within the shelters; KNP, kernel number per plant; KW, individual kernel weight; PGR, plant growth rate; PGRCP, PGR critical period (between V11 and R 2); PGR POST, PGR postsilking; PGR PRE, PGR presilking; PGY, plant grain yield; RUE, radiation use efficiency; RUECP, RUE critical period; RUEPRE, RUE presilking; RUEPOST, RUE postsilking; TC, nonheated control plot; TH, heated plots; TTS, cumulative stressful temperatures.

T

he effect of heat stress on plant metabolism depends on the intensity and duration of supra-optimum temperatures in combination with the rate of temperature increase (Wahid et al., 2007). The impact on economic yield, however, depends on the developmental stage of the crop at the time of stress (Hall, 1992). High temperature inhibits photosynthesis more than respiration (Hall, 1992), and evidence from field-grown wheat (Reynolds et al., 2007) suggested a decline in radiation use efficiency (RUE, shoot biomass produced per unit of intercepted photosynthetically active radiation, in g MJ−1) for mean maximum temperatures during the cycle between 29.2 and 31.3°C. Nonetheless, the study made no clear distinction between the proportional changes promoted on tissue expansion (the determinant of light interception efficiency; ei, proportion of incident Published in Crop Sci. 50:1438–1448 (2010). doi: 10.2135/cropsci2009.10.0574 Published online 21 May 2010. © Crop Science Society of America | 5585 Guilford Rd., Madison, WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

1438

WWW.CROPS.ORG

CROP SCIENCE, VOL. 50, JULY– AUGUST 2010

photosynthetically active radiation that is intercepted by the crop) and photosynthesis (a determinant of biomass production). For individual maize plants grown in pots, leaf temperature above 30°C affected net photosynthesis because of rubisco inactivation (Crafts-Brandner and Salvucci, 2002), but there was significant acclimation when the increase in temperature was gradual (2.5°C h−1 from 28 to 45°C) rather than abrupt (1°C min−1 for the same temperature range). The former situation is expected in most field conditions, accompanied by a large variation across the canopy due to increased mutual shading from top to bottom leaves that determine a gradual decrease in direct irradiance (Loomis and Connor, 1992). Final effects on RUE and biomass production are not known. Consequently, no inference can be made on the impact of heat stress on established physiological relationships that explain variations in the main determinants of grain yield, that is, kernel number per plant (KNP) and kernel weight (KW). It is well known that maize KNP exhibits a curvilinear response to plant growth rate (PGR) during a critical period (PGRCP) of approximately 30 d centered at silking (Andrade et al., 1999; Vega et al., 2000, 2001), with variations among cultivars and growing conditions attributed to variations in biomass partitioning to ear growth (Echarte and Tollenaar, 2006; Pagano and Maddonni, 2007; D’Andrea et al., 2008). Nevertheless, the general response pattern of KNP to PGRCP, established for varying levels of irradiance per plant obtained by means of a wide range of stand densities (Andrade et al., 1999), held for other abiotic constraints such as water and N deficiencies (Andrade et al., 2002). Similarly, we know that variations in kernel growth rate during active grain filling, the main determinant of final KW (Borrás and Otegui, 2001), are linearly related to variations in PGRCP per kernel (Gambín et al., 2006). Therefore, it is expected that heat stress during the critical period may promote a decline in both grain yield components through reductions in PGR, but its effects on biomass partitioning to the ear are less clear. Evidence indicates that prolonged exposure to temperatures above 32°C can reduce maize pollen germination of many genotypes to levels near zero (Herrero and Johnson, 1980). On one hand, this negative effect on pollen viability may determine a severe decline in KNP due to pollination failure (Uribelarrea et al., 2002). On the other hand, reduced tassel growth and pollen production may promote a decline in apical dominance (Uribelarrea et al., 2008) with the expected increase in biomass allocation to ear growth (Echarte and Tollenaar, 2006). The final impact of their combined effect on the above-described relationships is completely unknown. Field experiments were conducted for elucidating the effects of heat stress around flowering on the physiological determinants of maize grain yield, that is, flowering dynamics, ei, RUE, and biomass partitioning. The experimental design was conceived for evaluating the effects of CROP SCIENCE, VOL. 50, JULY– AUGUST 2010

heating on ear growth and kernel set independently of its direct effects on pollen viability and pollination efficiency. Heat levels compatible with plant survival were explored.

MATERIALS AND METHODS Crop Husbandry and Treatment Description Field experiments were conducted during 2006–2007 (Exp. 1) and 2007–2008 (Exp. 2) on a silty clay loam soil (Typic Argiudoll; USDA Natural Resources Conservation Service, 1999) at the experimental unit of the National Institute of Agricultural Technology (INTA) located in Pergamino (33°56′ S, 60°34′ W), Argentina. Details of crop husbandry can be found in Cicchino et al. (2010). Briefly, single-cross maize hybrid Nidera AX 842 MG (RM 119) was sown on 12 December in both experiments at a stand density of 9 plants m−2. Experiments were hand planted at three seeds per hill and thinned to the desired plant population at V3 (Ritchie and Hanway, 1982). The experimental site was surrounded by two lines of the same hybrid planted on 20 December for having abundant pollen availability throughout the flowering period. Fertilizer was applied as urea at a rate of 200 kg N ha−1 at V6. Weeds, pests, and diseases were adequately controlled. Water availability of the uppermost 1 m of soil was kept near field capacity throughout the growing season by means of sprinkler irrigation. Treatments included (i) two temperature conditions [heated (TH) and nonheated control (TC)] between V11 and tasseling (VT; Ritchie and Hanway, 1982) of TC plots in Exp. 1 (ca. 17 d of treatment) and (ii) a factorial combination of two temperature conditions (TH and TC) and two growth stages (GS1, between V11 and VT, and GS2, between VT and silking + 15 d, of TC plots) in Exp. 2. Treatments were distributed in (i) a completely randomized block design in Exp. 1 (i.e., 6 plots) and (ii) a split plot design in Exp. 2, with GSn in the main plot and temperature regime in the subplot (i.e., 12 plots). There were always three replicates. Main plots were 9 rows; rows were 0.7 m apart and 10 m in length. Temperature treatments covered 1.43 m (Exp. 1) or 2.86 m (Exp. 2) along two adjacent rows (i.e., 1.4 m wide). These treatment areas were enclosed with polyethylene fi lm (100-μm thickness) fi xed to wood sticks (laterals and roof ), yielding rigid shelters of 2.3 m height. One shelter was for the TH treatment and had the fi lm reaching the soil surface on all sides, except one side that had a 10-cm opening at the bottom to allow adequate gas exchange. The other shelter was for the TC treatment and had laterals open up to 1.4 m above soil surface, and the south side was completely open. Heating of TH treatments depended exclusively on temperature rise promoted by the greenhouse effect of polyethylene enclosure, a system that allowed reproducing the expected natural variation in temperature associated with varying solar radiation in the region under study. Open shelters were used for avoiding differences in light due to the polyethylene fi lm. Roofs were slightly pierced to avoid water accumulation (all shelters) and facilitate gas exchange at the top of the canopy (TH treatments). These considerations in the design usually grant adequate gas exchange even in actively growing plants (i.e., not affected by abiotic stress), as documented in Cirilo and Andrade (1996). All shelters were removed at the end of each heating period.

WWW.CROPS.ORG

1439

Measurements and Statistical Analysis Incident solar radiation was registered with a CR10X sensor (Campbell Scientific Inc., Logan, UT), installed at the experimental field and converted into incident photosynthetically active radiation (IPAR) by multiplying by 0.45 (Monteith, 1965). Daily IPAR records were corrected for the attenuation promoted by the polyethylene fi lm, which was estimated by measuring IPAR outside the shelter and IPAR at the top of plants within the shelters (IPARST) by means of a line quantum-sensor (Cavabar, Cavadevices, Argentina). Air temperature of each shelter (TH and TC) was registered hourly at ear level throughout the treatment period by means of sensors (TC1047, Microchip Technologies, Chandler, AZ) connected to dataloggers (Temp-Logger, Cavadevices, Buenos Aires, Argentina). Data registered in each sheltered area were used for computing cumulative stressful temperatures (TTS, in °C h above an optimum temperature) based on Eq. [1], n

TTS =

∑ (T

X

– TO ) , for T X > TO, [1]

1

where TTS represents cumulative stressful temperatures on a per hour basis during the treatment period (n) of each plot, T X is mean hourly air temperature, and TO is optimum air temperature. A TO value of 33.9°C was used, the average of estimates obtained in previous research (Cicchino et al., 2010). Nine (Exp. 1) or at least eighteen (Exp. 2) plants were tagged within each shelter at V11. The dates of anthesis (i.e., at least one extruded anther visible) and silking (i.e., at least one extruded silk visible) were recorded on all tagged plants and used for computing the anthesis–silking interval (ASI) on a per plant basis (ASIIP). Additionally, the anthesis–silking interval was calculated for each plot as the difference in days between 50% silking and 50% anthesis dates, that is, on a plant population basis (ASIPP). These dates were obtained from a sigmoid logistic function (Eq. [2]) fitted to the whole data set of each flowering event and temperature regime in GS1 (Lizaso et al., 2003). Pop = a/{1 + exp[–(X – b)/c]}; [2] where Pop is the proportion of plant population that reached the stage, a is the maximum proportion of plant population that reached the stage, b is time to 50% of the event (in days), and c is a parameter governing maximum slope (in days). If maximum observed Pop = 1, then a = 1 and Eq. [2] had only two estimated parameters (b and c). Adequate pollination and fertilization of all plants was granted in the experiments. For TH plots of GS1 treatments, there was abundant pollen from surrounding plants and other maize crops at time of shelter removal before anthesis (VT of TC plots). For TH plots of GS2 treatments, fresh pollen was collected daily from nontreated plants (i.e., outside shelters) and was added manually to silks exposed from all silked ears. Silks were pollinated by hand between 1000 and 1100 h. For pollen collection, tassels with anthers visible only in the main branch were bagged late in the afternoon and sampled for pollen the next morning. Pollination continued until no new silks were exposed from among the husks, and the arrest of silk elongation 24 h after pollination was evidence of a successful procedure (Bassetti and Westgate, 1993a, b). Leaf number along the stem was identified at the start of GS1 treatment (V11) for quantification of differences in leaf area promoted by temperature regimes during GS1. Total leaf 1440

area was measured at silking on all tagged plants as the sum of all green leaves, and leaf area above the eleventh leaf was identified. Individual leaf area was computed as lamina length × maximum width × 0.75 (Montgomery, 1911; Stewart and Dwyer, 1999). Leaf area index was calculated as the product of leaf area per plant and number of plants per unit land. Light interception efficiency (ei) was estimated at V11, VT, silking, and R 2 (Ritchie and Hanway, 1982). Measurements were performed at midday, between 1130 and 1430 h, on clear days, using the above-mentioned line quantum-sensor. One meter of the sensor was placed (i) at the top of the canopy and outside the shelters of each plot for IPAR determination and (ii) diagonally across sheltered rows (i.e., centered at the interrow space) and immediately below the lowermost green leaves of the canopy (IPARSB). Values of IPAR were corrected for the attenuation produced by the polyethylene fi lm for obtaining IPARST. Four measurements were performed in each shelter and were averaged for computing IPARSB. Equation [3] was used for calculating ei. ei = 1 – (IPARSB/IRARST); [3] Daily ei was estimated by linear interpolation between observation dates. Daily intercepted IPAR (IPARi) was estimated as the product between daily values of IPAR (with or without correction, depending on the date) and ei. Shoot biomass was estimated for each tagged plant on several dates (always referred to growth stages of TC plots): V11, V15 (only in Exp. 2), VT, silking, and R 2. Estimations were based on allometric linear models established at each sampling date for each treatment combination. Details of this technique can be found elsewhere (Borrás and Otegui, 2001; Maddonni and Otegui, 2004; Echarte and Tollenaar, 2006; D’Andrea et al., 2008). Models were based on the relationship between plant biomass and morphometric variables, and values for each parameter were developed using destructive harvests of at least 10 plants for each treatment combination. The morphometric variables used were plant height from ground level to the uppermost visible ligule, stalk diameter at the base of the plant, and maximum apical ear diameter at silking (only in Exp. 2) and R 2. Shoot biomass estimates for each tagged plant were used to calculate PGR (in g pl−1 d−1) during (i) the whole critical period for kernel set, that is, between V11 and R 2 (PGRCP), (ii) the presilking period of active ear elongation (Otegui and Bonhomme, 1998), that is, between V11 and silking (PGRPRE), and (iii) the postsilking period of ear elongation and lag phase of grain fi lling (Westgate et al., 2004), that is, between silking and R 2 (PGRPOST). Ear growth rate (EGR) was computed as the daily increase in ear biomass accumulation during different growth stages. In Exp. 1 it was obtained only for the critical period (EGRCP, between silking –15 d and silking +15 d). In Exp. 2 it was analyzed for the presilking period (EGRPRE, between 15 d before silking and silking), the postsilking period (EGRPOST, between silking and silking +15 d), and the critical period. Ear biomass was set to zero on 15 d before silking of TC plots (Otegui and Bonhomme, 1998). Estimates of PGRs and EGRs were averaged for each plot. Radiation use efficiency (RUE, in g MJ−1) was computed as (i) the relationship between cumulative shoot biomass and cumulative IPARi for the critical period (RUECP, between silking –15 d and silking +15 d) and the presilking period (RUEPRE, between 15 d before silking and silking) or (ii) the quotient between biomass

WWW.CROPS.ORG

CROP SCIENCE, VOL. 50, JULY– AUGUST 2010

increase and IPARi increase between silking and R 2 (RUEPOST), as described in Eq. [4]. RUEPOST = (BiomassR2 – BiomassSilking)/(IRARi R2 – IPARiSilking); [4] where BiomassR2 and BiomassSilking represent shoot biomass per m 2 at R 2 and silking, respectively, and IRARi R2 and IPARiSilking represent IPARi at R 2 and silking, respectively. All tagged plants were harvested at physiological maturity (i.e., when black layer was visible in the base of grains of the mid portion of the apical ear). Each harvested ear was separated into husks and cob plus kernels. All plant material was oven dried at 65°C until constant weight and then weighed. The ears of each tagged plant were individually hand shelled, and kernel number was counted for each ear. Prolificacy was computed as the number of grained ears per plant, and KNP was calculated by adding the kernels counted in the apical and the subapical ears (when present). Plant grain yield (PGY, in g plant−1) was determined and final individual kernel weight (KW) computed as the quotient between PGY and KNP. The plant source–sink ratio during the effective grain-filling period (EGF; Eq. [5]) was computed as aboveground plant biomass increase per kernel (Borrás and Otegui, 2001). Biomass increase was obtained as the difference in plant biomass between physiological maturity (BiomassPM) and R2 (BiomassR2). Source–sink ratio during EGF = (BiomassPM – BiomassR2)/KNP; [5] Harvest index (HI) was estimated for each plot as the quotient between PGY and plant shoot biomass at physiological maturity. All data were analyzed by ANOVA to evaluate the effects of treatments and their interactions. A t test was used to determine significant differences (p < 0.05) between means. Regression analysis was used for evaluating the relationship between (i) KNP and estimated PGRs, (ii) KNP and estimated EGRs, (iii) estimated EGRs and estimated PGRs, and (iv) fi nal KW and estimated source–sink ratio during the effective grain-fi lling period. An exponential function of the type indicated in Eq. [6] was fitted to the relationships indicated in (i) and (ii), as suggested by Andrade et al. (1999). Y = d – e exp(–X/f ); [6] where the coefficient d represents the plateau of the function (i.e., max. KNP) and coefficients e (in KNP) and f (in g plant−1 d−1) determine the slope.

RESULTS Growing Conditions and Heat Stress Differences in temperature and IPAR between years and growth stages (Fig. 1) caused differences in heat stress levels represented by TTS for both periods under analysis. Based on a constant optimum temperature of 33.9°C, higher air temperatures registered during January of Exp. 2 determined larger TTS values during GS1 of this experiment than of Exp. 1 (Table 1). For both periods under analysis (GS1 and GS2), cumulative heat stress was larger for heated than for control plots (Table 1) and for GS1 than for GS2 in Exp. 2 (p = 0.076).

CROP SCIENCE, VOL. 50, JULY– AUGUST 2010

Flowering Dynamics All flowering events were delayed in response to supraoptimum temperatures applied during GS1 (Fig. 2), but the effect was larger on 50% silking date (p < 0.05 in Exp. 1; p EGRPOST TH (1.30 g plant−1 d−1) > EGRPRE TC (0.40 g plant−1 d−1) > EGRPRE TH (0.01 g plant−1 d−1) for heating applied exclusively during GS1 in Exp. 2 (data of EGR across subphases was not available for GS1 in Exp. 1). Preanthesis heating caused a reduction of EGRPOST of the same magnitude as that observed for heat stress performed during silking (1.31 g plant−1 d−1 for plots heated during GS2). Variations in EGRCP were explained (r 2 > 0.53, p  0.10).

– – 19 283 – 0.015 –

0.91 (in the heated plots of GS1) and 1.08 (in the heated plots of GS2). The only difference among fitted models was for ordinate values (p  0.10).



p values of main and interaction effects.

the critical period for temperature regimes applied during GS1 established a significant (p < 0.001) year × subphase × temperature regime interaction for RUE. The outstanding trend of this result was that negative effects of preanthesis heat stress on RUE held after heat stress removal and determined a decline in RUEPOST even larger than observed for plots heated during silking. Estimated values of RUEPRE ranged between 4.33 (in Exp. 1) and 2.52 (in Exp. 2) g MJ−1 for control plots of GS1 and between 1.31 (in Exp. 1) and 0.91 (in Exp. 2) g MJ−1 for plots heated during this stage. Estimates of RUEPOST obtained for these same plots ranged between 3.57 (in Exp. 1) and 3.90 (in Exp. 2) g MJ−1 for control plots and between 1.02 (in Exp. 1) and 1.21 (in Exp. 2) g MJ−1 for heated plots. For the latter, RUEPOST values were smaller than those computed for heated plots of GS2 (1.62 g MJ−1). Variations in RUE explained observed variations in PGR of all evaluated

Table 3. Intercepted incident photosynthetically active radiation (IPARi) between V11 and R2, plant biomass at different growth stages [silking (R1), silking +15 d (R2), and physiological maturity (PM)], and radiation use efficiency (RUE) between V11 and R2 for two treatment periods (during GS1 and GS2) and two experiments (Exp. 1 and Exp. 2). IPARi Experiments and temperature regime

GS1

GS1

−2



277 274

– –

272 275 ns† ns ns

277 277 ns ns ns

GS1

GS2

Biomass PM GS1

RUE

GS2

GS1

−1

––––– MJ m ––––– Exp. 1 Control Heated Exp. 2 Control Heated Year effect (GS1) or GS effect (Exp. 2) Temperature effect Interaction effect§

Biomass R2

Biomass R1 GS2

–––––––––––––––––––––– g plant –––––––––––––––––––––– 121 51

169 68

– –

136 65 0.06‡ 0.0006 ns

165 76

156 139 0.0017 0.0002 0.0006

ns 0.0003 ns

226 118

GS2

–––––– g MJ

– –

−1

––––––

4.01 1.19

– –

261 242 3.84 151 188 1.19 0.05 ns ns 0.003 0.0009 < 0.0001 ns 0.01 ns

3.65 3.21 0.0003 < 0.0001 0.0001

ns, not significant (p > 0.10).



p values of main and interaction effects.

§

For Year × Temperature effect during GS1 or for GS × Temperature effect during Exp. 2.

Table 4. Plant (PGRCP) and ear (EGRCP) growth rates during the critical period, plant grain yield (PGY), harvest index (HI), and grain yield components [Prolificacy (in grained ears per plant), kernel number per plant (KNP), and individual kernel weight (KW)] for two treatment periods (GS1 and GS2) and two experiments (Exp. 1 and Exp. 2). Experiments and temperature regime

EGRCP

PGRCP GS1

GS2

GS1

PGY

GS2

–––––––– g plant−1 d−1 –––––––– Exp. 1 Control Heated Exp. 2 Control Heated Year effect (GS1) or GS effect (Exp. 2) Temperature effect Interaction effect¶

GS1

– –

0.86 0.26

– –

113 56

4.21 0.92 ns‡

3.80 3.14 0.003§

1.30 0.49 0.003

1.36 0.74 0.031

139 49 ns

0.0008 0.0003 ns ns

GS2

GS1

GS2

––– g plant−1 –––

3.90 1.06

0.0001 0.0005 ns 0.0008

Prolificacy †

HI

GS1

GS2

KNP GS1

KW

GS2

– ears plant−1 –

GS1

GS2

––––– mg –––––

– –

0.478 0.352

– –

1 0.89

– –

490 236

– –

230 250

– –

129 52 ns

0.533 0.343 ns

0.530 0.263 ns

1 0.67 ns

1 1 0.0007

478 188 ns

446 175 ns

291 248 ns

291 283 ns

0.001 ns

0.0005 ns

0.005 0.0007 ns 0.0007

0.002 0.0002 ns ns

0.002 0.0001 ns ns

ns 0.07

0.02 ns



ANOVA performed on data transformed to arcsin.



ns, not significant (p > 0.10).

§

p values of main and interaction effects.



For Year × Temperature effect during GS1 or for GS × Temperature effect during Exp. 2.

CROP SCIENCE, VOL. 50, JULY– AUGUST 2010

WWW.CROPS.ORG

1443

periods (r 2 ≥ 0.87, n = 18, p < 0.001), and a significant (r 2 = 0.765, n = 18 , p < 0.001) negative relationship of the type RUE = 5.56 – 0.68 ln TTS was established using RUE and TTS values of the corresponding heated subphase (i.e., RUEPRE for GS1 and RUE POST for GS2).

Grain Yield and Grain Yield Components Heating always affected PGY (Table 4), and there were no differences in this trait between years for heat stress applied during GS1. Similarly, there were no differences in PGY between plots heated during GS1 or GS2. In spite of the variation in heat stress level reached at different growth stages in Exp. 2 (TTS GS1 > TTS GS2; Table 1), PGY of each temperature regime did not differ between these periods. Contrasting temperature regimes promoted a significant (p = 0.005) variation in prolificacy during GS1 but had no effect on this trait when performed during GS2 (no barren ear was detected for this treatment period). Final kernel number, however, always decreased in heated plots (Table 4). Treatments had no clear effect on final KW (Table 4), which increased (8.7%) in heated plots of Exp. 1 but decreased (14.8% for GS1 and 2.75% for GS2) in those heated during Exp. 2. No trend could be established between this trait and the source–sink ratio computed for the critical period (PGRCP per kernel or EGRCP per kernel) or for the effective grain-fi lling period. Variation in grain yield was well explained by final total biomass (r 2 = 0.83, n = 18, p < 0.001), but temperature regimes affected the relationship between these traits (i.e., individual HI; Table 4). A strong linear relationship was established between HI and reproductive sink size represented by the final number of kernels (HI = 0.18 + 0.0007 KNP, r 2 = 0.85, n = 18, p < 0.001), which improved with a curvilinear fit that gave an ordinate close to zero (HI = 0.08 + 0.0015 KNP – 0.000001 KNP2, r 2 = 0.86, n = 18, p < 0.001). The variation in PGY, therefore, was largely explained by the variation in KNP (r 2 = 0.89, n = 161, p < 0.001) and not by the variation in KW (r 2 = 0.08, n = 150). For GS1 data, mean KNP had a negative response to the increase in mean ASIIP (KNP = 454 exp(−0.2882 ASI), r 2 = 0.62, n = 12 , p < 0.001), but no trend could be established when individual plant data (n = 100) were used for the analysis. Similarly, KNP had no clear response to biomass production during the studied period (V11 to R 2), represented by PGR (Fig. 4A) and EGR (Fig. 4B). The relationship did not improve when rates obtained during the presilking phase (data not shown) or each heated phase were included in the analysis (Fig. 4C and 4D). Robust relationships (r 2 ≥ 0.64, p < 0.0001) were established when postsilking growth rates were evaluated (Fig. 4E and 4F), especially EGR POST. Using these functions, minimum rates of −0.121 g plant−1 d−1 for PGR POST and 0.355 g plant−1 d−1 for EGR POST were estimated as thresholds for avoiding plant barrenness. 1444

Fig. 3. Relationship between ear growth rate (EGR) and plant growth rate (PGR) during the period between silking – 15 d and silking + 15 d (A), the presilking phase spanning approximately 15 d before 50% silking (B), and the postsilking phase spanning approximately 15 d after 50% silking (C). Data correspond to heated (TH) and nonheated (TC) plots during 17 d before anthesis (GS1) or during 15 d after 50% silking (GS2) in two experiments (Exp. 1 and Exp. 2). Solid lines represent different partitioning ratios.

DISCUSSION Heat stress applied during late vegetative growth of maize (GS1) produced a negative effect on all physiological determinants of biomass production and grain yield (flowering dynamics, tissue expansion, and RUE). Some responses, however, differed from trends established for other major abiotic stresses (e.g., water and N deficiencies). Most of the tissue expansion that determined final plant height and leaf area took place during GS1, but heating during this stage had a smaller effect on these traits than on biomass production. On one hand, this result contrasted with most evidence obtained from research on water (Boyer, 1970; NeSmith and Ritchie, 1992; Sadras and Milroy, 1996) and N (Sinclair and Horie, 1989; Uhart and Andrade,

WWW.CROPS.ORG

CROP SCIENCE, VOL. 50, JULY– AUGUST 2010

Fig. 4. Response of kernel number per plant (KNP) to plant (PGR) and ear (EGR) growth rates during the period between silking – 15 d and silking + 15 d (A and B), the heating period (GS1 or GS2) of each treatment (C and D), and the postsilking phase spanning approximately 15 d after 50% silking (E and F). Data correspond to heated (TH) and nonheated (TC) plots during 17 d before anthesis (GS1) or during 15 d after 50% silking (GS2) in two experiments (Exp. 1 and Exp. 2). The lines in E and F represent fitted models.

1995) deficiencies experienced by plants during vegetative growth, which established a larger resource availability threshold for affecting tissue expansion than for reducing carbon assimilation ( Jones and Kiniry, 1986). On the other hand, there was agreement with many of these studies on the fact that negative effects of stress on leaf expansion during late vegetative growth did not cause proportional reductions in ei and IPARi but may produce a marked decline in RUE. Another distinctive aspect of heat stress was the effect on late development of tassels and ears. Research on this subject in maize usually took place from anthesis onward (Herrero and Johnson, 1980; Schoper et al., 1987; Fonseca and Westgate, 2005) and highlighted the negative effects of above-optimum temperature on pollen viability. No CROP SCIENCE, VOL. 50, JULY– AUGUST 2010

information was available on the response of flowering dynamics to these types of temperatures, and no distinction was ever made between pollen and pistil effects on kernel set. Heat stress during GS1 caused a larger delay in silking date than in anthesis date, in agreement with evidence obtained under water (Herrero and Johnson, 1981; Hall et al., 1982; Bolaños and Edmeades, 1993) and N ( Jacobs and Pearson, 1991; Uhart and Andrade, 1995; D’Andrea et al., 2006) deficiencies during a similar period. Two related aspects, however, departed from the expected behavior: ASI values and proportion of malesterile plants. The delay registered in silking date was similar to reports from mentioned literature but did not promote a large increase in ASI (max. mean value of 4 d). Similarly, most reports on abiotic stress in this species

WWW.CROPS.ORG

1445

indicated a larger negative effect on female fertility (represented by silked ears) than on male fertility (represented by pollen-producing anthers), which was not observed in our research. Heat stress performed during GS1 determined a similar proportion of sterile tassels and nonsilked ears, a phenomenon never reported for maize. In spite of these results, and the relationship established between KNP and ASIIP, pollen availability was not the cause of reduced KNP under heat stress, because of (i) abundant pollen availability from surrounding plots at silking of heated plants in GS1 (i.e., after shelter removal) and (ii) manual addition of fresh pollen to silks of heated plants in GS2. Moreover, our results suggested that most of the reduction in KNP observed in silked ears might be related to abortion of fertilized structures and not to pollination and/or fertilization problems, because exposed silks did not continue elongation after exposure to fresh pollen and many silked ears did not produce kernels. This result is in agreement with previous evidence of kernel abortion in fertilized ovaries from tip ear positions under water deficit, despite fresh pollen addition to their late-appearing silks (Otegui et al., 1995). In spite of heat stress removal before anthesis in GS1 plots, many fertilized ovaries might have experienced the general process of cell disorganization and final kernel abortion (Westgate and Boyer, 1986), evidence of indirect effects of heat stress on kernel set. In contrast with previous research on maize kernel number determination under abiotic stress (Andrade et al., 2002; Echarte and Tollenaar, 2006; D’Andrea et al., 2008), variation in PGR and EGR during the critical period spanning from the start of ear elongation to ovary fertilization (Otegui and Bonhomme, 1998; Westgate et al., 2004) did not give an adequate explanation to the variation observed in KNP. In the present study, final KNP responded almost exclusively to plant and EGRs during the postsilking phase of the mentioned critical period and had no clear link with presilking growth rates. Moreover, it did not depend on growth rates during the occurrence of heat stress. Obtaining this additional detail on the relative importance of growth rates during the critical period was possible by the way temperature regimes were managed across subperiods (GS1 and GS2), yielding a large range of pre- and postsilking combinations. Important outputs of this manipulation were the assessment of (i) mentioned indirect effects of heat stress on kernel set, which could not be attributed to pollen viability and pollination dynamics and seemed mediated by EGR during the period of silk pollination and ovary fertilization, and (ii) variation in biomass partitioning to the ear between pre- and postsilking, which was low and variable for the former but high and stable for the latter. These findings are supported by previous evidence obtained in controlled conditions on the importance of current assimilate availability during silking for maize 1446

kernel set (Schusler and Westgate, 1991a, b, 1995; Boyle et al., 1991). There were, however, some interesting aspects of heat stress effects on ear growth during this period that deserved attention: (i) temperature did not affect biomass partitioning to the ear after silking, and almost all plant growth was dispensed to ear growth during this stage; previous temperature regime had no effect on this partitioning pattern, (ii) large negative effects on kernel set of presilking heat stress were not due to reduced EGR PRE of this treatment and could be attributed to long-term, indirect effects of heating on EGR POST, and (iii) RUEPOST was the only physiological trait that explained the observed variations in biomass production across treatments, with the concomitant effects on EGR POST and consequently on the main determinant of grain yield. These findings support the conceptual model developed by Reynolds et al. (2007) for breeding wheat cultivars aimed to hot environments, which highlighted the importance of RUE and RUE-related traits (e.g., photoprotective mechanisms) for those growing conditions. Nevertheless, we call attention to the interpretation of partitioning effects (or its surrogate HI in the general physiological model) on final grain yield. Variation in HI among treatments was very large but promoted by the variation in sink activity summarized in final KNP, which was chiefly the result of variations in EGR POST caused by temperature effects on RUEPOST, and not on biomass partitioning to the ear during this stage. Moreover, part of the variation in RUEPOST depended on temperature effects on RUEPRE, because of long-term effects of heating on the photosynthetic system. In our research, temperature effects on biomass partitioning took place exclusively during the presilking period, a response that suggested an indirect rather than a direct effect of temperature on this trait. Before silking, organs other than the ear were also undergoing expansion and might have exerted a strong dominance in the distribution of the few photoassimilates produced by a heated plant, with a negative consequence on the final reproductive fate of the ear (Otegui, 1997). Barren plants were present only in plots heated during GS1. Concerning the direct effect of heating on ear metabolism, evidence from studies on maize ear temperature shows the buffering capacity of the canopy and the husks (Khabba et al., 2001; Cárcova and Otegui, 2001), which almost eliminate the negative effects of direct solar radiation typical of crops with grains located in an apical inflorescence (Ploschuk and Hall, 2001; Passarella et al., 2002; Reynolds et al., 2007). Finally, no clear trend in KW was detected due to contrasting temperature regimes during the period under analysis. The result, however, did not disagree with current evidence on KW determination in this species (Gambín et al., 2006), which highlighted the response of this grain yield component to variations in the source–sink ratio during the critical period (i.e., PGRCP per set kernel

WWW.CROPS.ORG

CROP SCIENCE, VOL. 50, JULY– AUGUST 2010

or EGRCP per set kernel). This ratio did not differ markedly between temperature regimes evaluated in the current research. An analysis of heat stress on kernel growth, therefore, should combine treatments evaluated in the present study (i.e., during the period that controls potential KW and kernel growth rate) with heating performed during the effective grain-fi lling stage (i.e., the period that modulates grain-fi lling duration).

CONCLUSIONS Heat stress during late vegetative growth and the silking– pollination periods had severe negative effects on kernel set and fi nal grain yield of maize crops. The outstanding aspects of the current research were (i) the identification of EGR during the period of silk pollination and ovary fertilization (EGR POST) as the main determinant of final kernel numbers, (ii) the detection of the main physiological trait that modulated the observed variations in EGR POST under heat stress, which was RUE and not biomass partitioning to the ear, and (iii) the assessment of long-term effects of heat stress on RUE. Results presented in this paper support the importance of biomass production during the period immediately after silking on kernel number determination of maize, traditionally used in important crop simulation models ( Jones and Kiniry, 1986). Nevertheless, we also call attention to (i) presilking effects of heat stress on biomass partitioning to the ear, which were of indirect nature and determined ear reproductive fate (i.e., a barren or prolific plant), and (ii) the long-term effects of abiotic stresses during late-vegetative growth, especially those related to heat damage to the photosynthetic system that may affect postsilking RUE. Acknowledgments The authors wish to thank L. Blanco, M. Chintio, W. Miranda, M. Rossini, A. Severini, and W. Tanaka for their invaluable help with field work. This research was fi nanced by Agro Fresh (Rohm and Haas), the CONICET, and the Regional Fund for Agricultural Technology (FONTAGRO). M. Cicchino has a graduate’s scholarship from INTA, and J.I. Rattalino-Edreira has a graduate’s scholarship from CONICET. M.E. Otegui is a member of CONICET.

References Andrade, F.H., L. Echarte, R. Rizzalli, A. Della Maggiora, and M. Casanovas. 2002. Kernel number prediction in maize under nitrogen or water stress. Crop Sci. 42:1173–1179. Andrade, F.H., C.R.C. Vega, S.A. Uhart, A.G. Cirilo, M. Cantarero, and O.R. Valentinuz. 1999. Kernel number determination in maize. Crop Sci. 39:453–459. Bassetti, P., and M.E. Westgate. 1993a. Emergence, elongation, and senescence of maize silks. Crop Sci. 33:271–275. Bassetti, P., and M.E. Westgate. 1993b. Senescence and receptivity of maize silks. Crop Sci. 33:275–278. Bolaños, J., and G.O. Edmeades. 1993. Eight cycles of selection for drought tolerance in lowland tropical maize. II. Responses in CROP SCIENCE, VOL. 50, JULY– AUGUST 2010

reproductive behavior. Field Crops Res. 31:253–268. Borrás, L., and M.E. Otegui. 2001. Maize kernel weight response to postflowering source-sink ratio. Crop Sci. 41:1816–1822. Boyer, J.S. 1970. Leaf enlargement and metabolic rates in corn, soybean, and sunflower at various leaf water potentials. Plant Physiol. 46:233–235. Boyle, M.G., J.S. Boyer, and P.W. Morgan. 1991. Stem infusion of liquid culture medium prevents reproductive failure of maize at low water potential. Crop Sci. 31:1246–1252. Cárcova, J., and M.E. Otegui. 2001. Pollination asynchrony and kernel abortion in maize. Crop Sci. 41:1809–1815. Cicchino, M., J.I. Rattalino Edreira, and M.E. Otegui. 2010. Heat stress during late vegetative growth of maize: Effects on phenology and assessment of optimum temperature. Crop Sci. 50: (in press). Cirilo, A.G., and F.H. Andrade. 1996. Sowing date and kernel weight in maize. Crop Sci. 36:325–331. Crafts-Brandner, S.J., and M.E. Salvucci. 2002. Sensitivity of photosynthesis in a C4 plant, maize, to heat stress. Plant Physiol. 129:1773–1780. D’Andrea, K.E., M.E. Otegui, A.G. Cirilo, and G.H. Eyhérabide. 2006. Genotypic variability in morphological and physiological traits among maize inbred lines. I. Response to nitrogen availability. Crop Sci. 46:1266–1276. D’Andrea, K.E., M.E. Otegui, and A.G. Cirilo. 2008. Kernel number determination differs among maize hybrids in response to nitrogen. Field Crops Res. 105:228–239. Echarte, L., and M. Tollenaar. 2006. Kernel set in maize hybrids and their inbred lines exposed to stress. Crop Sci. 46:870–878. Fonseca, A.E., and M.E. Westgate. 2005. Relationship between desiccation and viability of maize pollen. Field Crops Res. 94:114–125. Gambín, B.L., L. Borrás, and M.E. Otegui. 2006. Source–sink relations and kernel weight differences in maize temperate hybrids. Field Crops Res. 95:316–326. Hall, A.E. 1992. Breeding for heat tolerance. Plant Breed. Rev. 10:129–168. Hall, A.J., F. Vilella, N. Trapani, and C. Chimenti. 1982. The effects of water stress and genotype on the dynamics of pollenshedding and silking in maize. Field Crops Res. 5:349–363. Herrero, M.P., and R.R. Johnson. 1980. High temperature stress and pollen viability of maize. Crop Sci. 20:796–800. Herrero, M.P., and R.R. Johnson. 1981. Drought stress and its effects on maize reproductive systems. Crop Sci. 21:105–110. Jacobs, B.C., and C.J. Pearson. 1991. Potential yield of maize, determined by rates of growth and development of ears. Field Crops Res. 27:281–298. Jones, C.A., and J.R. Kiniry. 1986. CERES-Maize: A simulation model of maize growth and development. Texas A&M Univ. Press, College Station, TX. Khabba, S., J.-F. Ledent, and A. Lahrouni. 2001. Maize ear temperature. Eur. J. Agron. 14:197–208. Lizaso, J.I., M.E. Westgate, W.D. Batchelor, and A. Fonseca. 2003. Predicting potential kernel set in maize from simple flowering characteristics. Crop Sci. 43:892–903. Loomis, R.S., and D.J. Connor. 1992. Crop ecology. Productivity and management in agricultural systems. Cambridge Univ. Press, Cambridge, UK. 538 pp. Maddonni, G.A., and M.E. Otegui. 2004. Intra-specific competition in maize: Early-determined hierarchies among plants affect fi nal kernel set. Field Crops Res. 85:1–13. Monteith, J.L. 1965. Radiation and crops. Exp. Agric. 1:241–251.

WWW.CROPS.ORG

1447

Montgomery, E.G. 1911. Correlation studies in corn. Neb. Agric. Exp. Stn. Annu. Rep. 24:108–159. NeSmith, D.S., and J.T. Ritchie. 1992. Short- and long-term responses of corn to a preanthesis soil water deficit. Agron. J. 84:107–113. Otegui, M.E. 1997. Kernel set and flower synchrony within the ear of maize. II – Plant population effects. Crop Sci. 37:448–455. Otegui, M.E., F.H. Andrade, and E.E. Suero. 1995. Growth, water use, and kernel abortion of maize subjected to drought at silking. Field Crops Res. 40:87–94. Otegui, M.E., and R. Bonhomme. 1998. Grain yield components in maize. I – Ear growth and kernel set. Field Crops Res. 56:247–256. Pagano, E., and G.A. Maddonni. 2007. Intra-specific competition in maize: Early established hierarchies differ in plant growth and biomass partitioning to the ear around silking. Field Crops Res. 101:306–320. Passarella, V.S., R. Savin, and G.A. Slafer. 2002. Grain weight and malting quality in barley as affected by brief periods of increased spike temperature under field conditions. Aust. J. Agric. Res. 53:1219–1227. Ploschuk, E.L., and A.J. Hall. 2001. Capitulum position in sunflower affects grain temperature and duration of grain fi lling. Field Crops Res. 44:111–117. Reynolds, M.P., C. Saint Pierre, A.S.I. Saad, M. Vargas, and A.G. Condon. 2007. Evaluating potential genetic gains in wheat associated with stress-adaptive trait expression in elite genetic resources under drought and heat stress. Crop Sci. 47(S):172–189. Ritchie, S.W., and J.J. Hanway. 1982. How a corn plant develops. Spec. Rep. 48. Iowa State Univ. of Sci. and Technol., Coop. Ext. Serv., Ames, IA. Sadras, V.O., and S.P. Milroy. 1996. Soil-water thresholds for the responses of leaf expansion and gas exchange: A review. Field Crops Res. 47:253–266. Schoper, J.B., R.J. Lambert, and B.L. Vasilas. 1987. Pollen viability, pollen shedding, and combining ability for tassel heat tolerance in maize. Crop Sci. 27:27–31. Schusler, J.R., and M.E. Westgate. 1991a. Maize kernel set at low water potential: I. sensitivity to reduced assimilates during early kernel growth. Crop Sci. 31:1189–1195.

1448

Schusler, J.R., and M.E. Westgate. 1991b. Maize kernel set at low water potential: II. sensitivity to reduced assimilates at pollination. Crop Sci. 31:1196–1203. Schusler, J.R., and M.E. Westgate. 1995. Assimilate flux determines kernel set al low water potential in maize. Crop Sci. 35:1074–1080. Sinclair, T.R., and T. Horie. 1989. Leaf nitrogen, photosynthesis, and crop radiation use efficiency: A review. Crop Sci. 29:90–98. Stewart, D.W., and L.M. Dwyer. 1999. Mathematical characterization of leaf shape and area of maize hybrids. Crop Sci. 39:422–427. Uhart, S.A., and F.H. Andrade. 1995. Nitrogen deficiency in maize: I. Effects on crop growth, development, dry matter partitioning, and kernel set. Crop Sci. 35:1376–1383. Uribelarrea, M., J. Cárcova, L. Borrás, and M.E. Otegui. 2008. Enhanced kernel set promoted by synchronous pollination determines a tradeoff between kernel number and kernel weight in maize. Field Crops Res. 105:172–181. Uribelarrea, M., J. Cárcova, M.E. Otegui, and M.E. Westgate. 2002. Pollen production, pollination dynamics, and kernel set in maize. Crop Sci. 42:1910–1918. USDA Natural Resources Conservation Service. Soil taxonomy: A basic system of soil classification for making and interpreting soil surveys. Second edition, USDA Agriculture Handbook 436. Washington, DC: US Gov. Print. Office, 1999. Vega, C.R.C., F.H. Andrade, V.O. Sadras, S.A. Uhart, and O.R. Valentinuz. 2001. Seed number as a function of growth. A comparative study in soybean, sunflower and maize. Crop Sci. 41:748–754. Vega, C.R.C., V.O. Sadras, F.H. Andrade, and S.A. Uhart. 2000. Reproductive allometry in soybean, maize and sunflower. Ann. Bot. (London) 85:461–468. Wahid, A., S. Gelani, M. Ashraf, and M.R. Foolad. 2007. Heat tolerance in plants: An overview. Environ. Exp. Bot. 61:199–223. Westgate, M.E., and J.S. Boyer. 1986. Reproduction at low silk and pollen water potentials in maize. Crop Sci. 26:951–956. Westgate, M.E., M.E. Otegui, and F.H. Andrade. 2004. Physiology of the corn plant. In W.C. Smith, F.J. Betran, and E. Runge (ed.) Corn: Origin, history, technology, and production. John Wiley & Sons, Oboken, NJ, p. 235–271.

WWW.CROPS.ORG

CROP SCIENCE, VOL. 50, JULY– AUGUST 2010

Suggest Documents