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Agronomy Journal 92:92-97 (2000)
© 2000 American Society of Agronomy

AGROCLIMATOLOGY

Intercepted Radiation at Flowering and Kernel Number in Maize

Fernando H. Andradea, María E. Oteguib and Claudia Vegaa

a Unidad Integrada INTA Balcarce, Fac. de Ciencias Agrarias UNMP, CC 276, (7620) Balcarce, Buenos Aires, Argentina
b Cereales, Dep. de Producción Vegetal, Fac. de Agronomía, Av. San Martín 4453, (1417) Buenos Aires, Argentina

meotegui{at}mail.retina.ar


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 Materials and methods
 Results and discussion
 Conclusions
 REFERENCES
 
When water and nutrients are not limiting growth, kernel number per plant (KNP) can be calculated for maize (Zea mays L.) using linear models based on intercepted photosynthetically active radiation per plant (IPARP). These models do not include the concept of a threshold IPARP for KNP. Our objective was to study the response of KNP to IPARP in order to improve current models. Published information from several field experiments, performed with two maize hybrids in the temperate region of Argentina, was used for the analysis. Both linear and curvilinear (inverse linear and exponential) models based on IPARP explained more than 75% of the variability in KNP and kernel number per apical ear (KNA). Curvilinear models gave a better fit at low (<0.5 MJ plant-1 d-1) and intermediate (1.3-2 MJ plant-1 d-1) values of IPARP than a simple two-line linear model. Models allowed the estimation of maximum KNA and maximum KNP, and the minimum IPARP to reach them, but only curvilinear models allowed the estimation of a threshold IPARP (0.31-0.37 MJ plant-1 d-1) to avoid plant barrenness. The inverse linear model gave a better prediction of maximum kernel number than the other two models. The exponential model allowed a better estimation of the initial value (2.16 MJ plant-1 d-1) for expressing prolificacy (ears plant-1) > 1. The relationship between KNP and IPARP did not improve when IPARP was expressed on a thermal time basis (photothermal quotient), probably because air temperature did not vary much among the situations explored in this work.

Abbreviations: IPAR, intercepted photosynthetically active radiation • IPARP, intercepted photosynthetically active radiation per plant • IPARPtt, intercepted photosynthetically active radiation per plant and per unit thermal time • KNA, kernel number per apical ear • KNP, kernel number per plant • MRV, mean residual value • PAR, photosynthetically active radiation • PGR, plant growth rate • PPFD, photosynthetic photon flux density • RUE, radiation use efficiency


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
Materials and methods
 Results and discussion
 Conclusions
 REFERENCES
 
MAIZE GRAIN YIELD IS closely associated with kernel number at harvest. Understanding the mechanisms of kernel number determination is therefore of great importance to maize physiologists, modelers, and breeders.

Several reports place the maize growth stage when kernel number is most susceptible to stress in the period bracketing silking (Tollenaar and Daynard, 1978; Fischer and Palmer, 1984; Kiniry and Ritchie, 1985; Aluko and Fischer, 1988; Cirilo and Andrade, 1994b). Thus, the physiological condition of the crop at this stage is critical for kernel set. The number of kernels set is more critical and more affected by environmental conditions than the total number of differentiated spikelets (Goldsworthy, 1984; Otegui, 1995; Uhart and Andrade, 1995b) and the degree of floral differentiation reached by them (Otegui and Melón, 1997; Otegui, 1997). Unfavorable environmental conditions at a period bracketing flowering can cause cessation of ear development and ear abortion (Edmeades and Daynard, 1979; Tollenaar, 1977; Jacobs and Pearson, 1991; Otegui and Melón, 1997) and reduction in the number of viable kernels per ear (Fischer and Palmer, 1984; Kiniry and Ritchie, 1985; Cirilo and Andrade, 1994b). Research on kernel abortion in maize (Boyle et al., 1991; Schussler and Westgate, 1991; Zinselmeier et al., 1995) has indicated that growth cessation is linked to a shortage of assimilate supply to the developing kernels.

In many studies conducted to analyze kernel set in maize, intercepted photosynthetically active radiation (IPAR) at a period bracketing (Otegui and Bonhomme, 1998) or close to (Kiniry and Knievel, 1995) silking was used as the determinant variable. These studies indicate that a simple linear relationship would be suitable to explain kernel set response to IPAR per plant (IPARP) during the critical period, with kernel set reaching a different plateau depending on the potential seed number of each hybrid. However, data from Andrade et al. (1993b) suggest that the response function of kernel set is curvilinear. This curvilinear response has been observed also for the relationship between kernel number per plant (KNP) and plant growth rate (PGR) around silking (Tollenaar et al., 1992; Andrade et al., 1999). Calculations based on data by Tollenaar et al. (1992) also support findings by Andrade et al. (1993b), under the assumption of a constant radiation use efficiency (RUE = grams of shoot biomass formed/MJ of intercepted solar radiation). These curvilinear functions also define a plateau when the potential seed number is reached, and introduce the concept of a threshold of IPARP or PGR for kernel production. In severely stressed environments, these threshold-based curvilinear models should predict kernel set better than linear models with positive or zero y-intercepts.

Our objective was to study the response of KNP to IPARP, in order to improve current models. Published information from several field experiments (Andrade, 1995; Otegui et al., 1995b; Otegui and Bonhomme, 1998) was used to calculate and compare linear and curvilinear models based on the KNP–IPARP relationship. Estimates of IPARP corresponded to a 30-d period centered on silking.


   Materials and methods
TOP
 ABSTRACT
 INTRODUCTION
 Materials and methods
Results and discussion
 Conclusions
 REFERENCES
 
Field Plots and Treatments
Data presented in this work were obtained from 14 experiments (Table 1) conducted at the INTA Balcarce Experiment Station (37°45' S, 58°18' W) and at the Salto-Rojas experiment site (34°08' to 34°33' S, 60°33' to 60°59' W). Eight growing seasons were included in the analysis, from 1989–1990 to 1996–1997 (Table 1). At both sites, soils were silty clay loam soils (Typic Argiudolls, in the USDA taxonomy), with a minimum effective soil depth of 1.5 m (Balcarce) or 2.0 m (Salto-Rojas) and with an organic matter content of 5.6% (Balcarce) or 3% (Salto-Rojas) in the first 0.25 m of depth. The Balcarce area is characterized by lower average air temperatures during the growing season than the Salto-Rojas area. The frost-free period is about 150 d in Balcarce and 185 d in Salto-Rojas. More details about climatic data of the Balcarce and Salto-Rojas regions were presented by Andrade (1995) and Otegui et al. (1995b). Maize hybrids Dekalb 636 (in most experiments) or DK 639 (in two experiments) were sown in mid-September or mid-October. Both hybrids are closely related (they have one line in common), with similar cycle length, endosperm type, and other agronomic traits. Plots were overplanted and desired densities were obtained by thinning after seedling emergence. A uniform plant-to-plant distance within the row was obtained in all plots. The experiments were conducted with three or four replications. In general, the size of the plots was four to five rows, 0.70 m apart and 12 to 15 m long. Plots were fertilized with 10 to 42 kg P ha-1 and 140 to 202 kg N ha-1, depending on the soil analysis for each experiment site, to provide adequate mineral nutrition. Soil water in the 1-m depth was kept above 50% of maximum available water by sprinkler (Balcarce and Rojas) or furrow (Salto) irrigation during the entire growing season. During a 31-d period bracketing silking (from silking minus 10 d to silking plus 20 d), rainfall plus irrigation was always greater than 150 mm, in order to satisfy mean evaporative demand ({cong}5 mm d-1) mostly with water from the uppermost soil layer (Otegui et al., 1995a). Weeds and insects were adequately controlled.


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  		Table 1 Conditions of experiments for studying kernel number in maize (two locations in Argentina)

 
In five of these experiments (Exp. 1 to 5), incident irradiance was modified by shading. Plots were shaded during the 31-d period mentioned above. Plots were shaded with neutral black synthetic cloth of different mesh, stretched at approximately 0.05 to 0.10 m above the crop on cane and wire structures. Shading level of each mesh was determined with a LI-COR 191 SB line quantum sensor (LI-COR, Lincoln, NE) connected to a LI-COR 188B radiometer. Photosynthetically active radiation (PAR) intercepted by the shading cloths was measured by placing the line quantum sensor 15 cm above and below the cloths from 0900 to 1600 h for the entire duration of the treatment (Uhart and Andrade, 1995a). Shading levels across experiments were 0, 20, 32, 45, 50, 55, and 88% (Table 1). Daily mean air temperature within the canopy (i.e., not under direct sunlight) was monitored to determine any effect of shade on this variable. Only in one experiment (Exp. 6) was the amount of solar radiation intercepted by the plants modified through defoliation. In the plots subjected to defoliation, all ligulated leaves were cut at the ligule level approximately 10 d before silking. Defoliated plants were checked daily up to anthesis, to remove the leaves that completed their expansion after the first cutting. In the other five experiments (Exp. 7 to 11), plant density was varied from 2.1 to 40 plants m-2 (total range across experiments) to provide a wide range of crop and plant growth rates (Table 1). All plant densities and defoliation levels were included in the data set for analysis (Table 1). Only early (mid-September) and normal (October) planting dates were considered (Table 1). Very early (late August-early September) and late (November) plantings were not included in the analysis, to avoid the effect of low temperature on radiation use efficiency (Andrade et al., 1993a; Wilson et al., 1995) and biomass partitioning (Wilson et al., 1995), which may affect kernel set independently of light interception (Cirilo and Andrade, 1994a, 1994b; Otegui et al., 1995b).

Light Interception Measurements
Percent radiation interception was estimated from photosynthetic photon flux density (PPFD) measurements as [1 - (It/I0)] x 100, where It is the incident PPFD above senesced leaves and below the green leaves and I0 is the incident PPFD at the top of the canopy. At least five measurements of PPFD were made in each plot weekly or fortnightly. The values for It and I0 were obtained between 1100 and 1400 h (standard time), with a line quantum sensor. These measurements were taken along the cycle of the crop or started a few days after treatment application (shading and defoliation). The amount of PAR intercepted by each plant (IPARP) was calculated based on incident radiation per unit land area (considering the effects of shades), percent interception and plant density. The period from silking minus 10 d to silking plus 20 d was included in the analysis, and the IPARP was expressed on a daily basis. Climatic records were obtained from weather stations located always at less than 1 km from the experiments, where air temperature at 1.8 m was registered.

The calculated IPARP was divided by daily thermal time during the above-mentioned period to calculate the photothermal quotient (i.e., the amount of radiation intercepted per plant per unit thermal time; here symbolized as IPARPtt) (Fischer, 1985; Cantagallo et al., 1997). Daily thermal time was computed as the difference between daily mean air temperature (24-h average) and a base temperature of 8°C (Ritchie and NeSmith, 1991).

Grain Yield and Kernel Set
At Balcarce, total grain yield (0% moisture) was determined at physiological maturity (black layer in the grains of the midportion of the ear; Daynard and Duncan, 1969) by hand harvesting all ears in 7.15 m of the two center rows of the plot (or the remaining ears at low densities). At Salto-Rojas, ears in 1 m2 (at plant populations of 7 to 8 plants m-2) or 2 m2 (at plant populations of 5.5 and 9.5 plants m-2) were sampled at physiological maturity. At Balcarce, the number of kernels per unit area was calculated based on kernel weight and grain yield of individual ears. At Salto-Rojas, the number of kernels of each ear (apical and subapical) was always counted. Kernel weight was determined by weighing two samples of 500 kernels each (Balcarce) or as the quotient of plant grain yield and KNP (Salto-Rojas).

Daily values of IPARP and IPARPtt were averaged for the whole period under analysis, and KNA and KNP were related to these irradiance indicators.

Statistical Analyses
Data were processed by analysis of variance procedures and/or by linear regression analysis using the routines included in SAS/STAT (SAS, 1987). Appropriate standard errors of the means were calculated. Models were fitted with TBLCURVE (Jandel, 1992).


   Results and discussion
TOP
 ABSTRACT
 INTRODUCTION
 Materials and methods
 Results and discussion
Conclusions
 REFERENCES
 
Environmental conditions experienced by the crops during the months when the critical period for kernel set usually took place are listed in Table 2 . In general, both air temperature and irradiance were higher at Salto-Rojas than at Balcarce. On the other hand, the within-year variation for irradiance was larger at Balcarce than at Salto-Rojas. Daily mean air temperature within the crop did not differ in more than 1°C between shading and control treatments, as mentioned in Andrade and Ferreiro (1996). Nevertheless, KNP for IPARP within 0.6 and 1 MJ plant-1 d-1 tended to be larger (up to 30%) for shaded than for control plots, as indicated by Andrade et al. (1993b). This difference may be related to increased RUE due to reduced vapor pressure deficit (Stockle and Kiniry, 1990), which may have taken place under shading but was not measured in our experiments.


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  		Table 2 Daily (24 h) mean air temperature and incident solar irradiance when the critical period for maize kernel number usually takes place at Balcarce and Salto-Rojas

 
Kernel set per plant and per uppermost ear were significantly related to the daily IPARP during the critical period around silking (Fig. 1 and Table 3) . Both linear (Fig. 1a and c) and curvilinear (Fig. 1b and d) models based on IPARP explained more than 74% of the variability in kernel number (Table 3). Though both approaches yielded an excellent fit, models differed in their prediction capacity of KNA and KNP. At low values of IPARP (IPARP < 0.5 MJ plant-1 d-1, 6% of the data set), mean residual values (MRV equals measured minus calculated kernel number) for KNA obtained with the exponential and the inverse-linear models were closer to zero than those obtained with the two-line linear model . A similar trend was observed at high IPARP values. When IPARP > 1.41 MJ plant-1 d-1 (break point of the two-line linear model for KNA; Table 3), both the exponential and the inverse linear models gave better predictions than the two-line linear model . When the whole plant was considered (KNP), only the exponential model gave MRV close to zero at extreme values of IPARP.



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  		Fig. 1 Linear (a and c) and curvilinear (b and d) relationships between kernel number per plant (KNP) or per apical ear (KNA) and intercepted photosynthetically active radiation per plant (IPARP) for the maize hybrids DK 636 and DK 639 cropped at Balcarce (squares) and at Salto-Rojas (triangles);

 

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  		Table 3 Regression equations, 95% confidence limits of coefficients, and r2 values describing the response of kernel number per apical ear (KNA) and per plant (KNP) to intercepted photosynthetically active radiation per plant (IPARP, in MJ plant-1 d-1) during a 30-d period centered on silking. All models included 182 data points

 
Curvilinear models indicated that a threshold IPARP of 0.31 to 0.37 MJ plant-1 d-1 must be reached for having any kernel set (both on a whole-plant or on an uppermost-ear basis). On the other hand, the ordinate values obtained with the two-line linear model did not differ significantly from zero (Table 3). Similarly, the simple linear models calculated by Kiniry and Knievel (1995) and Otegui and Bonhomme (1998) did not detect a threshold IPARP for starting kernel set. Moreover, the threshold calculated with the curvilinear models (exponential and inverse-linear) allowed the estimation of a minimum PGR for kernel set. If a RUE of 3 g MJ-1 (Andrade et al., 1993a; Otegui et al., 1995b) is considered, minimum PGR during the critical period to avoid plant barrenness should be approximately 0.93 to 1.10 g plant-1 d-1. Similar threshold values were reported by Andrade et al. (1999) for the same hybrid. These values are also included in the range of PGR threshold values for kernel set (0.38–1.29 g plant-1 d-1) calculated by Tollenaar et al. (1992) for a set of nine hybrids representing different breeding eras in Canada.

Models also allowed the estimation of maximum kernel set per uppermost ear and the minimum IPARP to reach it (Fig. 1). Calculations made with the two-line linear model indicated that maximum kernel set in the uppermost ear (540 kernels ear-1) was obtained when IPARP was >= 1.41 MJ plant-1 d-1, and that kernel set increased at a rate of 410 kernels MJ-1. The exponential model calculated a similar plateau for maximum kernel set in this earshoot (518 kernels ear-1), with 95% of this maximum value reached at IPARP equal to 1.75 MJ plant-1 d-1. For the inverse linear model, calculated maximum kernel set in the uppermost ear (597 kernels ear-1) was slightly larger than for the other two models, but closer to actual maximum values obtained with this hybrid (Otegui, 1995). On the other hand, this model calculated 95% of maximum kernel set in this earshoot at extremely large values of IPARP (>=7.05 MJ plant-1 d-1), which were always double the measured IPARP values in our experiments. For all models, calculated maximum kernel set in the uppermost ear was below the plateau suggested by Cirilo and Andrade (1994b) and Otegui (1995) for the same hybrid (spikelets per apical ear = 600 to 700), which was defined as the total number of differentiated spikelets in the apical ear (Otegui and Melón, 1997). This uppermost plateau was reached or slightly exceeded only in cases with prolificacy (ears plant-1) > 1 (Fig. 1c and d), which occurred when IPARP values were greater than 2.16 MJ plant-1 at very low plant populations (2.2 plants m-2) tested at Balcarce.

When kernel set in the whole plant was considered, model parameters were almost identical to those observed for models fitted to apical ear data (Table 3). This result was probably due to low mean kernel number in the second earshoot, which at a plot level was the result of averaging plants that showed and did not show prolificacy > 1. Nevertheless, this result differed from observations made on other hybrids by Otegui (1995), who determined that KNP (averaged at a plot level) could exceed the potential set by the uppermost earshoot by up to 30%. These differences would be mostly related to the intrinsic capacity to set kernels by the subapical earshoot of each hybrid. This capacity is apparently very low for the cultivars used in this study (Otegui, 1995).

At a plant level, the ordinate fitted by the two-line linear model did not differ significantly from zero (Table 3), and kernel set increased at a rate of 410 kernels MJ-1. The IPARP at the break point when maximum kernel set is reached (1.44 MJ plant-1 d-1) did not differ significantly (P < 0.05) from that obtained for the uppermost ear.

For the inverse-linear model, neither the threshold to avoid plant barrenness nor the plateau of maximum kernel set differed significantly from values obtained for kernel set in the uppermost ear (Table 3). Also at a whole-plant level, 95% of maximum kernel set was reached at extremely large values of IPARP (>=7.3 MJ plant-1 d-1).

Results obtained using the exponential model to calculate kernel set in the whole plant indicated that (i) maximum kernel set per plant was significantly (P < 0.05) larger (582 kernels) than that estimated for the uppermost ear (518 kernels); (ii) 95% of maximum kernel set in the whole plant was reached when IPARP equaled 2.17 MJ plant-1 d-1; and (iii) the threshold IPARP to avoid plant barrenness (0.31 MJ plant-1 d-1) was similar to that obtained with the model fitted to the uppermost ear data set. The IPARP value for obtaining 95% of maximum kernel set was close to the observed threshold value (2.16 MJ plant-1 d-1) for expressing prolificacy (ears plant-1 > 1) in this study. When converted to PGR, the prolificacy threshold value of 6.48 g plant-1 d-1 obtained agreed closely with measurements made by Andrade et al. (1999), who detected a threshold of approximately 6 g plant-1 d-1 for the expression of prolificacy > 1 in the same hybrid. Similar PGR threshold values were found by Tollenaar et al. (1992) for a different set of hybrids.

The relationship between KNP and IPARP did not improve when IPARP was expressed on a thermal time basis (data not shown). This is probably because monthly mean air temperature did not vary much among the different situations explored in this work. When night temperature was artificially modified by heating (Andrade et al., 1999), expression of PGR per unit thermal time provided a better prediction of KNP. Thus, another variable that must be taken into account to understand kernel set is the duration of the critical period of kernel number determination. This period is under temperature control, and recent studies (Otegui and Melón, 1997; Otegui and Bonhomme, 1998) have established that active ear elongation takes place over a fairly constant thermal time period, which may vary widely among sites when expressed in terms of days. Hence, a photothermal quotient of the type used in wheat (Triticum spp.; Fischer, 1985) and sunflower (Helianthus spp.; Cantagallo et al., 1997) could be a useful tool to correct for the effect of temperature on the extension of the critical seed set period (Otegui et al., 1996) and, consequently, the resulting amount of intercepted solar radiation assigned to assimilate production for kernel set. For maize, the beneficial effects of warm (>20°C) temperature on radiation use efficiency (Andrade et al., 1993a) and biomass partitioning to the ear (Wilson et al., 1995) must be also considered.


   Conclusions
TOP
 ABSTRACT
 INTRODUCTION
 Materials and methods
 Results and discussion
 Conclusions
REFERENCES
 
Kernel set per plant and per apical ear were well explained by the IPARP during a 30-d period bracketing silking. At low values of IPARP, curvilinear models could give more accurate calculation of KNP (MRV <= 22 ± 103) than simple linear models . Using curvilinear models, the relationship between these two variables is characterized by (i) threshold IPARP values for having plant barrenness, (ii) a plateau indicating potential kernel number, and (iii) an initial response of KNP to IPARP. These model attributes improve our understanding of kernel set in maize with respect to simple linear models proposed previously. Nevertheless, differences among hybrids in the response of KNP to IPARP (Kiniry and Knievel, 1995; Otegui and Bonhomme, 1998) are still to be solved, and models should consider this restriction if accurate kernel set is to be foreseen.Jandel Scientific 1992; SAS Institute 1987


   ACKNOWLEDGMENTS
 
Thanks go to A. Cirilo, M. Cantarero, G. Maddonni, R. Ruiz, S. Uhart, and O. Valentinuz, who provided part of the data used in this work. This work was supported by Instituto Nacional de Tecnología Agropecuaria (INTA); Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET); Facultad de Ciencias Agrarias Universidad Nacional de Mar del Plata; Facultad de Agronomía Universidad de Buenos Aires (UBACyT AG04); Fundación Antorchas; and Dekalb Argentina S.A.

Received for publication December 4, 1998.
   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 Materials and methods
 Results and discussion
 Conclusions
 REFERENCES
 




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