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Crop Science 41:1816-1822 (2001)
© 2001 Crop Science Society of America

CROP PHYSIOLOGY & METABOLISM

Maize Kernel Weight Response to Postflowering Source–Sink Ratio

Lucas Borrás* and María E. Otegui

Cátedra de Cerealicultura, Dep. de Producción Vegetal, Fac. de Agronomía, Univ. de Buenos Aires, Av. San Martín 4453, Capital Federal (C1417DSE), Argentina

* Corresponding author (borras{at}agro.uba.ar)


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
In maize (Zea mays L.), the negative effects of increased stand densities on final kernel weight (KW) are attributed to reductions in the effective grain-filling period, and not in kernel growth rate. This suggests that competition for assimilates among kernels only occurs at the last stages of grain filling. To test this hypothesis, two commercial hybrids of different KW were grown at two stand densities (3 and 9 plants m-2) during 1998 to 1999 and 1999 to 2000. Pollination treatments were performed in order to modify kernel number per plant (KNP) and to obtain a range of source–sink ratios. Pollination treatments altered KNP, and negative relationships were established between KW and KNP, with no differences between years. On the basis of regression analysis of the response of KW to changes in KNP, KW increased between 0.09 to 0.28 mg kernel-1 per unit decrease in KNP, depending on stand density and genotype. The theoretical potential KW was independent of preanthesis plant population effects, which affected ear growth significantly (P <0.01). Kernel weight was closely related to variations in kernel growth rate during the effective grain-filling period (r2 = 0.84; P <0.001), and not to modifications in the duration of this stage. Within each hybrid, the plant source–sink ratio established during the postflowering period explained KW response to modifications in KNP, independently of stand density. Hybrids differed in the capacity to transform biomass produced at the postflowering period into KW. This was in agreement with differences between hybrids in the capacity to sustain KW when the source–sink ratio was reduced. It is concluded that assimilate limitations to kernel growth occur during the whole grain-filling period.

Abbreviations: DAS, d after silking • KNP, kernel number per plant • KW, kernel weight • TT, thermal time


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
GRAIN YIELD IN CEREALS is defined by the number of grains per unit land area and by the individual weight of these grains. In general, grain yield is closely related to the number of grains that reach maturity, and KW is considered a more stable trait. In maize, little knowledge exists on the response of KW to variations in KNP (Jones and Simmons, 1983; Kiniry et al., 1990). The study of this response is important for breeding strategies, because of possible tradeoff relations between the two traits.

In previous research, Jones and Simmons (1983) found no KW response to enhanced assimilate availability per kernel, obtained by reducing KNP at the end of the lag phase (i.e., formative period which takes place soon after ovary fertilization) or during the effective grain-filling period (i.e., after the lag phase). In contrast, Kiniry et al. (1990) reported that KW of grains from the same ear position was increased by reductions in KNP at silking, and that this response was genotype dependent. This finding demonstrated that maize KW could be source-limited during the postflowering period, but did not define when KW was set during the grain filling period. An early study (Reddy and Daynard, 1983) showed that the number of endosperm cells was established during the lag phase, and that this number was related to kernel sink potential (Jones et al., 1985). On the other hand, in an in vitro study, Hanft et al. (1986) observed that assimilate supply during the grain-filling period affected final KW, regardless of endosperm cell number. Similar results were obtained with maize cropped at contrasting sowing dates (Cirilo and Andrade, 1996) or with reductions in KNP at flowering in a related species like sorghum (Sorghum bicolor (L.) Moench; Kiniry, 1988), where significant differences in KW could not be attributed to the number of endosperm cells.

When maize source–sink ratio was altered only during the effective grain-filling period (i.e., after the lag phase), KW varied in relation to the level of assimilate availability per kernel. An increase in assimilates, obtained by thinning the crop 3 wk after flowering (Schoper et al., 1982; Cirilo and Andrade, 1996), promoted a significant increase in KW, with no modifications in KNP. Similarly, KW decreased in response to defoliation treatments performed at different stages of the effective grain-filling period (Egharevba et al., 1976; Tollenaar and Daynard, 1978; Jones and Simmons, 1983). From this evidence it can be inferred that, although the formative period may be critical in the determination of the grain sink capacity (Jones et al., 1985, 1996), conditions during the effective grain-filling period are more important in KW determination.

Poneleit and Egli (1979) observed that reductions in maize KW promoted by increased stand density were due to reductions in the duration of the effective grain-filing period, and not in kernel growth rate during this stage. Their results suggest that competition for assimilates among kernels occurs mainly late in grain filling, causing reductions in final kernel growth. Moreover, kernel growth rate during the effective grain-filling period was considered to be under genetic control (Cross, 1975; Poneleit and Egli, 1979). Nevertheless, there is no information on how KNP affects kernel growth parameters (i.e., kernel growth rate and grain filling duration) for the same genotype in maize, independent of stand density. For a range of genotypes, Wang et al. (1999) showed that KNP correlated negatively with kernel growth rate and positively with the duration of the effective grain-filling period.

The analysis of postflowering source–sink ratio effects on KW determination will improve our understanding of the magnitude and moment of source limitations during grain filling of commercial maize hybrids. The objectives of this study were (i) to characterize the effects of KNP on kernel growth parameters during the grain-filling period, and (ii) to evaluate KW response to different source–sink ratios. For this purpose, two hybrids of different KWs were studied at two stand densities.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Two F1 commercial hybrids, DK752 and DK664 (Dekalb-Monsanto, Argentina), were sown in October during the growing seasons of 1998 to 1999 (Year 1) and 1999 to 2000 (Year 2) at Salto, Argentina (34°33'S, 60°33'W). The DK752 is a small-kernel hybrid (<250 mg kernel-1) at 70000 plants ha-1, while the DK664 has large kernels (>250 mg kernel-1) under the same growing conditions. Two plant populations were used, 3 plants m-2 (low density) and 9 plants m-2 (high density). They were selected in order to have contrasting vegetative (source) and grain (sink) biomass (Otegui, 1997). Treatments were arranged in a split-plot design with three replicates, where plant populations were the main plots and hybrids the subplots. Experimental plots were kept free of weeds and pests, and experienced no water or nutrient stress.

Three pollination treatments were performed in order to change the number of reproductive sinks per plant: restricted, hand, and open pollination. At least 10 plants per each hybrid stand density x pollination treatment replicate combination were tagged at random 15 d before silking, and were individually identified. The date of silking (first silks visible) of the apical and subapical ears was registered for each tagged plant. The restricted pollination treatment consisted of the controlled pollination of silks from apical ears. It was performed by bagging apical ears 2 d after they silked in order to decrease the number of pollinated ovaries. This manipulation avoided the negative effects observed when ears were cut in order to reduce KNP (Kiniry et al., 1990). In this treatment, the subapical ear was bagged prior to its silking to prevent its pollination. The hand-pollination treatment was aimed to synchronize the pollination of all exposed silks of the two ears 4 d after silking (DAS) of the apical ear (Frey, 1981; Cárcova et al., 2000). In this treatment, both ears of each plant were bagged before silking and were kept covered until 4 DAS, when fresh pollen of the same hybrid was added manually to all exposed silks. This treatment was done to improve KNP (Cárcova et al., 2000). The open-pollinated plants were never bagged and were used as control plants, with an expected intermediate KNP relative to the other two treatments. Plants from all treatments with irregular kernel set along the ear were discarded to avoid the confounded effect of unusually large kernels due to no space restriction.

Beginning 11 DAS, the ears of one plant per replicate were harvested weekly from each treatment combination. Twenty grains were taken from the same ear position (approximately between spikelets 10 and 15, from the bottom of the apical ear), oven-dried in a forced draft oven at 65°C until constant weight, and weighed. Individual KW was determined with these samples, and data were used to estimate grain growth parameters (e.g., rate of grain filling and grain filling duration) as described below (Eq. [1] and [2]). The number of DAS was calculated for each sample, based on the silking date of each plant. Kernel number per plant was counted for all harvested ears. At physiological maturity, final mean KW was calculated as the ratio between total grain weight per plant and KNP.

A bilinear model was fitted to compare grain growth parameters between treatments on a thermal time (TT; in °C days) basis (Eq. [1] and [2]):

[1]

[2]
where a is the intercept (mg), b is the rate of grain filling (mg °C day-1), and c is the total duration of grain filling (in °C days). The bilinear model was fitted with an optimization technique (Jandel Scientific, 1991). Thermal time computations started at silking of each plant, using mean daily air temperature and a base temperature of 0°C (Muchow, 1990). For KW comparisons at equal kernel developmental stages, TT calculations for hand-pollinated plants started at pollination (i.e., 4 DAS). Mean daily air temperature was calculated as the average between daily maximum and minimum air temperatures, registered at the experimental site during both years. The duration of the lag phase was calculated as the cumulative TT from silking until KW equaled zero. This calculation was performed by transposing the axis in Eq. [1] instead of interpolating the linear model, in order to have the confidence interval of the lag phase duration.

The rate of grain-filling during the effective grain-filling period, b in the model, was compared by a t-test of the slopes (Steel and Torrie, 1960). Differences among treatments in TT duration of the lag phase and of the whole grain-filling period (i.e., from silking until physiological maturity) were based on the confidence interval of the parameters (P < 0.05). For the analysis of kernel growth parameters, KNP data were grouped in three ranges within each sampling date and hybrid x stand density combination, independently of pollination treatments. We distinguished plants with (i) high kernel number, (ii) intermediate kernel number, and (iii) low kernel number. This was done because of the variations in KNP within each pollination treatment.

The plant source–sink ratio during the effective grain-filling period was defined as aboveground plant biomass increase per kernel during this stage (Cirilo and Andrade, 1996), when kernels are the only growing sink. Biomass increase was obtained as the difference in plant biomass between physiological maturity and the start of the effective grain-filling period ({approx}11 DAS). In Year 1, plant biomass at 11 DAS was estimated as the average weight of three plants sampled at each subplot, independently of the pollination treatment. In Year 2, a nondestructive allometric model was used for plant biomass estimation, with a modified version of the Vega et al. (2000) model. This model allowed the estimation of biomass increase of tagged plants that remained in the field until physiological maturity. The allometric model was based on stem volume (f, in m3) and apical ear diameter (e, in mm) (Eq. [3]) of three plants per subplot. Stem volume was calculated using plant height from ground level up to the ligule of the flag leaf (g, in m) and stem diameter at the base of the plant (h, in m) (Eq. [4]):

[3]

[4]

The model was fitted using a multiple regression analysis. A single model described shoot biomass of both hybrids and both plant populations (Eq. [3]). The relationship between actual and estimated shoot biomass did not differ from 1 (Fig. 1) . In both years, plant biomass at physiological maturity was determined by individual sampling of all tagged plants with grain-bearing ears.



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  		Fig. 1. Relationship between plant biomass estimated from stem volume and apical ear diameter and observed plant biomass, 11 d after silking, of hybrids DK752 and DK664 grown at 3 and 9 plants m-2. The dotted line shows the 1:1 ratio, and the solid line shows the fitted model. Each point represents one plant.

 
A bilinear model was also fitted between the plant source–sink ratio and KNP (Eq. [5] and [6]):

[5]

[6]
where Y is the source–sink ratio (mg kernel-1), i is the intercept, j and l are the two different slopes (mg kernel-1 KNP-1) of the relationship, and k is the break point between the slopes.

Total soluble nonstructural carbohydrates were analyzed from the apical ear internodes of plants harvested at physiological maturity in Year 1. Internodes were cut lengthwise in order to have a quick and uniform drying, and dried in a forced-draft air oven until constant weight. Oven-dried internodes were ground sufficiently to pass through a 1-mm screen, and analyzed using the phenol sulfuric acid assay (Montgomery, 1957).

A bilinear model of the type described in Eq. [1] and [2] was used to relate final mean KW to (i) plant weight gain per kernel during the effective grain-filling period, and to (ii) soluble nonstructural carbohydrate concentration at physiological maturity.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Kernel Weight and Kernel Number per Plant
Pollination treatments modified KNP, and variations in this component affected KW significantly (Fig. 2) . Reductions in KW were closely related to increases in KNP in all treatment combinations, even at the very low stand density of 3 plants m-2. No significant differences were established between years, so a single relationship was fitted to each stand density x hybrid combination. Plant population had a significant (P < 0.01) effect on ear biomass at silking (data not shown) and on the response of KW to KNP in both hybrids. In both stand densities, increased KNP promoted a steeper decrease in KW in the smaller kernel hybrid DK752 than in the DK664, and slopes were significantly different at the high stand density (P < 0.05) and at the low stand density (P < 0.10). Interestingly, there were no differences between stand densities in the intercept of the relationship for the two hybrids studied. Therefore, the theoretical maximum KW was the same for all treatments. When final (i.e., at physiological maturity) KW of grains from positions 10 to 15 of the apical ear was related to final mean KW, the regression never differed from the 1:1 line in any hybrid (Fig. 3) , indicating that KW had been affected similarly at all kernel positions along the ear.



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  		Fig. 2. Relationship between kernel weight (KW) and kernel number per plant (KNP) of hybrids DK752 and DK664 grown at 3 and 9 plants (pl) m-2. Fitted regressions between KW and KNP were: DK752, 3 pl m-2, KW = 357 ± 9 - 0.12 ± 0.01 x KNP, r2 = 0.70***; DK752, 9 pl m-2, KW = 371 ± 12 - 0.28 ± 0.03 x KNP, r2 = 0.67***; DK664, 3 pl m-2, KW = 349 ± 6 - 0.09 ± 0.01 x KNP, r2 = 0.77***; DK664, 9 pl m-2, KW = 342 ± 12 - 0.18 ± 0.03 x KNP, r2 = 0.55***. ***Significant at the 0.001 probablility level.

 


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  		Fig. 3. Relationship between final kernel weight (KW) of grains from positions 10 to 15 (counted from the bottom of the apical ear) and final mean KW (calculated as the ratio between total grain weight per plant and kernel number per plant), of hybrids DK752 and DK664. The dotted line shows the 1:1 ratio.

 
When plants were sorted into three KNP categories within each hybrid and stand density, it could be observed clearly that modifications in KW were achieved only through variations in kernel growth rate during the effective grain-filling period (Table 1). Each year, the highest kernel growth rates corresponded to the lowest KNP range, while the lowest values were obtained with kernels that corresponded to ears that had set the largest number of kernels. For a given KNP range (i.e., high, intermediate, or low), no differences were detected in kernel growth rate between stand densities of the same hybrid. The only exception was the low kernel number per plant range of the DK664 in Year 1, with the highest kernel growth rate of the experiment (45 mg °C day-1) at low stand density and a significantly smaller rate (39 mg °C day-1) at high stand density. There was no significant trend, however, in the duration of the grain-filling period, nor of the lag phase between KNP ranges (Table 1). Significant differences (P < 0.05) were detected only between a few treatments of each hybrid. For the DK664, differences occurred in total grain-filling duration at low stand density during Year 1. For the DK752, differences in this parameter were observed in Year 2 between stand densities, but only for the high kernel number per plant group. Thus, enhanced KNP did not promote a consistent shortening of grain filling, and final KW was mostly related to kernel growth rate during the effective grain-filling period (Fig. 4) . A single significant trend could be established for all treatments and years (P < 0.001; Fig. 4A).


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  		Table 1. Kernel growth rate (KGR) during the effective grain-filling period, and duration of the grain-filling period and the lag phase of hybrids DK752 and DK664, cropped at two stand densities (3 and 9 plants m-2). Three ranges of kernel number per plant (KNP) were identified (high, intermediate, and low).

 


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  		Fig. 4. A, relationship between kernel weight (KW) and kernel growth rate during the effective grain-filling period for hybrids DK752 and DK664 grown at 3 and 9 plants (pl) m-2. B, relationship between KW and duration of the effective grain-filling period for the same hybrids and stand densities.

 
Kernel Weight and Postflowering Source–sink Ratio
Modifications in KNP at flowering altered the source–sink ratio established for the postflowering period. With the modifications in KNP at flowering, both stand densities exhibited a similar range of source–sink ratios (Fig. 5) . A single bilinear model described both years within each stand density of each hybrid. Two response patterns were found for each treatment combination; one, in which large reductions in KNP caused only slight increases in biomass availability per kernel, and the other one, in which small reductions in KNP promoted large increases in this variable. For similar KNP values, biomass availability per kernel was always larger at the lower stand density. Models fitted to low and high stand densities differed significantly for each hybrid (P < 0.05). On the other hand, models did not differ significantly between hybrids within a stand density, but the DK752 tended to have higher values of plant weight gain per kernel during the postflowering period than the DK664.



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  		Fig. 5. Relationship between plant weight gain per kernel during the postflowering period and kernel number per plant (KNP) for hybrids DK752 and DK664 cropped at 3 and 9 plants m-2. The inserts show the parameters ± the standard error of the bilinear model, where i is the intercept, j and l are the slopes of the two lines, and k is the break-point between the slopes. The dotted curves show lines of equal aboveground biomass production (g plant-1) during the effective grain-filling period.

 
Modifications in KNP at flowering not only changed the total number of sinks per plant, but also the source activity after flowering. Increased KNP resulted in heavier plants at physiological maturity in all treatments and years (P < 0.01, Fig. 5). These modifications in plant biomass production buffered the variations in plant source–sink ratio due to modifications in KNP at flowering.

A different bilinear model could be fitted for each hybrid between KW and the source–sink ratio established for the postflowering period, but no difference was detected between stand densities or years within each hybrid (Fig. 6) . Plants that gained more than 414 mg of biomass per kernel for DK664, and 588 mg of biomass per kernel for DK752 reached maximum KW independently of the stand density. For both hybrids, the source–sink ratio that maximized KW was greater than the 1:1 relationship, especially in the DK752. There was large variability among plants in KW at the remobilization range (i.e., at the left side of the 1:1 ratio), which cannot be explained from differences between years.



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  		Fig. 6. Relationship between kernel weight and plant weight gain per kernel during the postflowering period (source–sink ratio) for hybrids DK752 and DK664. The dotted line shows the 1:1 ratio. The inserts show the parameters ± the standard error of the bilinear model, where a is the intercept (mg), b is the slope for source–sink ratios below the break-point, and c is the break-point between lines.

 
For both hybrids, KW could be significantly (P <= 0.005) explained by soluble nonstructural carbohydrate concentration in the apical ear internode at physiological maturity. The response pattern was similar to that observed between KW and plant weight gain per kernel. For soluble nonstructural carbohydrates, DK664 exhibited a range between 33.6 and 346.6 mg g-1, with a threshold at 139 ± 24 mg g-1 for reaching maximum KW. For DK752, nonstructural soluble carbohydrates ranged from 46.5 to 450 mg g-1, and the threshold was estimated at 217 ± 35 mg g-1. Below the thresholds, KW decreased at a different rate between hybrids. This rate was 0.81 ± 0.27 mg and 0.60 ± 0.16 mg KW per unit concentration of stem soluble nonstructural carbohydrates (mg g-1) for DK664 (r2 = 0.61; P < 0.005) and DK752 (r2 = 0.80, P < 0.0001), respectively.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
CONCLUSIONS
 REFERENCES
 
As observed in previous research (Jacobs and Pearson, 1991; Otegui, 1997), increased plant population promoted a reduction in ear growth around silking, but this effect did not modify potential KW. This result leads to the conclusion that there are no prefecundation effects on KW determination in maize. This finding contrasts with recent research on wheat (Triticum aestivum L.), where KW responded to preanthesis assimilate availability per kernel (Calderini and Reynolds, 2000). In the present work, KW of each hybrid appeared to be related only to the plant postflowering source–sink ratio, independent of stand density. On the other hand, maximum KW was obtained only at source–sink ratio values above the 1:1 ratio, contrary to data obtained by Cirilo and Andrade (1996). Our results indicate that KW is maximized only when there is biomass accumulation in organs other than kernels during the effective grain-filling period, but hybrids differ in the response.

The response of KW to biomass availability per kernel is supported by soluble nonstructural carbohydrate concentration data at physiological maturity. Internode nonstructural carbohydrate concentrations were in agreement with data obtained by Kiniry et al. (1992). In their unshaded plants without ear (i.e., highest source–sink ratio), soluble nonstructural carbohydrate concentration reached maximum values of 360 ± 20 mg g-1 (i.e., slightly above maximum values registered for the DK664). On the other hand, this concentration was between 30 ± 10 and 110 ± 20 mg g-1 in their shaded plants with ear (i.e., lowest source–sink ratio). Lowermost values for our hybrids were within this range. The response pattern established in our work (bilinear with plateau) helps to explain apparent discrepancies found in the literature, like the lack of response of KW to enhanced soluble nonstructural carbohydrate concentration observed in the reduced KNP treatment by Jones and Simmons (1983). In their work, the concentration in the stems of the control plants at physiological maturity was always above the thresholds established in the present study. The different thresholds for maximum KW between hybrids (i.e., DK752 > DK664) suggest a different capacity to support high KW values when the availability of assimilates is reduced (i.e., DK752 < DK664), in agreement with the observed response of KW to increased KNP.

Biomass production during grain filling was under control of the source–sink ratio established after pollination, and hybrids differed in the response. At both stand densities, a reduction in sink size promoted a decrease in aboveground biomass production, as observed by Kiniry et al. (1992) and Rajcan and Tollenaar (1999). Differences between the hybrids in the response of biomass production to sink size could be related to different end product inhibition of photosynthesis, as suggested by some authors (Rajcan and Tollenaar, 1999). This hypothesis needs to be tested with photosynthesis measurements. Differences between hybrids in KW response to the plant source–sink ratio is evidence of a variable capacity to transform plant biomass produced after pollination in KW. Hybrid DK664 had a smaller biomass availability threshold in order to maximize KW than hybrid DK752. This contrast between hybrids may be due to differences in the response of kernel composition to postflowering assimilate availability (e.g., photosynthesis or remobilization).

The variation in KNP, with the concomitant effect on plant source–sink ratio, controlled final KW through modifications in kernel growth rate during the effective grain-filling period. Neither the duration of grain filling nor the length of the effective grain-filling period were affected by treatments. Differences within hybrids in kernel growth rate during the grain-filling period support that it is not only a genotype-dependent trait, as has been hypothesized (Cross, 1975; Poneleit and Egli, 1979). Our results clearly indicate that competition for assimilates among kernels takes place during the whole grain-filling period, and not only at its last phase, as suggested in previous experiments (Poneleit and Egli, 1979). These results are in agreement with data obtained in sorghum (Kiniry, 1988), where reductions in KNP around flowering enhanced KW through modifications in kernel growth rate, and not in the duration of the effective grain-filling period.

Reddy and Daynard (1983) and Capitano et al. (1983) showed that both maximum endosperm cell number and the number of starch granules per kernel had important roles in the determination of maize KW. It is known that maize endosperm consists of a cell population of different ages (Shannon, 1974), with young cells being smaller and having smaller starch granules than the older ones (Boyer et al., 1976). Consequently, the whole endosperm is a population of starch granules of variable sizes (Boyer et al., 1976), although there exists a great homogeneity among starch granules from the same endosperm cell (Shannon, 1974). It can be hypothesized that endosperm cell development would depend upon plant source–sink ratio, and kernels from plants with a large ratio are likely to have a greater number of starch granules or granules of larger size than those with a low ratio. This trait could also explain the large sink capacity of maize kernels, which are able to profit from any improvement in the source–sink ratio, regardless of the time when this improvement takes place during the grain-filling period (Schoper et al., 1982). Research in sorghum (Kiniry, 1988) supports this hypothesis. In this species, the number of starch granules explained differences in final KW when the postflowering source–sink ratio was modified, although there were no treatment effects on endosperm cell number, starch granule number, or kernel weight at the end of the lag phase.


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
REFERENCES
 
Stand density effects on prefecundation ear growth had no consequences on KW, which appeared to be related only to the postflowering source–sink ratio. Stand density effects on prefecundation ear growth had no consequences on the theoretical potential KW. Final KW appeared to be related only to the postflowering source–sink ratio. This ratio controlled biomass production during the effective grain-filling period, and hybrids differed in the capacity to transform plant biomass produced after pollination in kernel biomass, with the concomitant effect on final KW. Differences in KW resulted from changes in kernel growth rate, indicating that competition for assimilates among kernels took place during the whole grain-filling period.


   ACKNOWLEDGMENTS
 
Authors wish to thank A. Curá, M. Ducasse, M. Gerbaldo, F.G. Gonzalez, and M. Uribelarrea for their valuable help. This work was supported by Fundación Antorchas (A-13622/1-79), Dekalb-Monsanto Argentina, the Univ. of Buenos Aires (UBACyT JG 20), and the Agencia Nacional de Promoción Científica y Tecnológica (PICT-99 Nro. 08-06608). L. Borrás has a grant of and M.E. Otegui is a member of CONICET.

Received for publication December 11, 2000.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 




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L. Borras, J. A. Cura, and M. E. Otegui
Maize Kernel Composition and Post-Flowering Source-Sink Ratio
Crop Sci., May 1, 2002; 42(3): 781 - 790.
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