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CROP PHYSIOLOGY & METABOLISM

Maize Kernel Composition and Post-Flowering Source-Sink Ratio

^a Dep. de Producción Vegetal, Fac. de Agronomía, Univ. de Buenos Aires, Av. San Martín 4453, Capital Federal (C1417DSE), Argentina
^b Dep. de Biología Aplicada y Alimentos, 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.), there is little information on how the availability of assimilates during the effective grain-filling period affect final kernel quality. The objective of our research was to analyze the response of kernel starch, protein, and oil to changes in the post-flowering source-sink ratio (i.e., post-flowering shoot biomass increase per kernel). Two commercial hybrids of different kernel weight (KW) and protein content were grown at two stand densities (3 and 9 plants m^-2) during 1998-1999 and 1999-2000. Pollination treatments were used to modify kernel number per plant (KNP). As KNP increased, starch, protein and oil yield per plant increased, but yield per kernel decreased (P < 0.05) in all treatment combinations. In both genotypes, starch, protein, and oil content per kernel varied between 114 to 238, 15 to 48, and 7 to 17 mg kernel^-1, respectively, and concentrations varied between 650 to 700, 80 to 140, and 40 to 60 g kg^-1 dry weight, respectively. Within each hybrid, the post-flowering source-sink ratio explained (P < 0.01) the response of each kernel component content to modifications in KNP and stand density. In both genotypes, kernel starch, protein, and oil content were all maximized at the same post-flowering source-sink ratio (420 and 570 mg kernel^-1 in DK664 and DK752, respectively). A decrease in the source-sink ratio beyond a specific threshold promoted a decrease in the relative protein content and an increase in the relative starch content. Limitations other than assimilates seem to govern the relative oil content of kernels, as no relation with the post-flowering source-sink ratio was found.

Abbreviations: HD, high stand density • KNP, kernel number per plant • KW, kernel weight • LD, low stand density • SNC, soluble nonstructural carbohydrates

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
IN CEREAL CROPS, final KW depends on the relationship between kernel sink capacity and the availability of assimilates to fill this sink. Kernel sink capacity is highly dependent on growth conditions during the early stages of grain filling (Jones et al., 1985, 1996). Nevertheless, final KW of maize reflects the source-sink ratio of the entire grain-filling period (Borrás and Otegui, 2001), and particularly of the grain-filling stage when the kernel accumulates most of its biomass (Egharevba et al., 1976; Tollenaar and Daynard, 1978; Schoper et al., 1982; Cirilo and Andrade, 1996). During this stage of active biomass accumulation, known as the effective grain-filling period, KW responds positively to the assimilate availability per kernel (i.e., the source-sink ratio), but this response holds up to a threshold beyond which no increase is observed in kernel biomass (Borrás and Otegui, 2001). There is little information on how this response may affect final kernel quality (e.g., starch, protein, and oil contents).

Gene discovery has been widely used in maize for unveiling traits that resulted in grains with modified oil, protein, and carbohydrate content, which are of special interest in today's breeding programs (Mazur et al., 1999). Nevertheless, data obtained directly from commercial maize hybrids indicate that grain quality can vary significantly depending on the environment for crop growth (Earle, 1977). Even for the same genotype cropped under nonlimiting N conditions in the field in Argentina, protein concentration of the kernels varied drastically among years, with values between 60 and 120 g kg^-1 (Satorre et al., 1998). Field experiments indicated that protein concentration of the kernels was always enhanced when N availability and soluble nonstructural carbohydrate (SNC) supply per kernel were augmented as a result of an increased post-flowering source-sink ratio (Jones and Simmons, 1983; Pearson and Jacobs, 1987; Reed et al., 1988; Pan et al., 1995; Uhart and Andrade, 1995). Enhanced total protein content per kernel was not always correlated with an increase in KW, probably because protein accumulation in maize kernels takes place at source-sink ratios above the threshold that maximizes starch production, and represents a variation in KW too small to be statistically significant. This hypothesis is supported by in vitro studies (Singletary and Below, 1989; Wyss et al., 1991; Faleiros et al., 1996) which determined that N availability per kernel at the saturation point for protein synthesis was greater than N supply for maximum starch accumulation, the main determinant of KW. A similar response was observed in the protein content of the grains of other cereal crops, such as wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.), for which KW remained mostly unchanged in spite of protein increase (Ma et al., 1995; Dreccer et al., 1997; Voltas et al., 1997). This evidence suggests that the protein content of cereals is more source-limited than the starch content, and this difference depends on the supply of starch and protein precursors (Jenner et al., 1991). Consequently, a different post-flowering assimilate availability per kernel is needed to maximize each grain component. Information on this topic is not conclusive for field-grown maize plants, probably because most studies on this species differed in the source-sink ratio range explored after flowering (Jones and Simmons, 1983; Uhart and Andrade, 1995). Moreover, ranges under study were very narrow and did not allow threshold assimilate supply values to be defined for each component. We hypothesize that protein accumulation in maize kernels continues at source-sink ratios above the threshold that maximizes starch production of field-grown plants. There is no information on how oil content may respond to changes in the post-flowering assimilate availability per kernel. Oil is mainly concentrated in the embryo, which is mature for producing a new plant at the end of the lag phase (Watson, 1987). Nevertheless, biomass increase of the embryo continues during the effective grain-filling period (Ingle et al., 1965), and its components may be also affected by the source-sink ratio at this stage. We hypothesized that oil, an energy rich compound (Sinclair and de Wit, 1975), would respond similarly to protein to the post-flowering source-sink ratio.

The objective of our research was to analyze the response of kernel components (starch, protein, and oil) to changes in the post-flowering source-sink ratio. We focused on a possible trade-off between grain yield and grain quality, as reported in wheat (Anderson et al., 1998). Two treatments were combined to obtain a wide source-sink ratio range: stand density (3 and 9 plants m^-2) and kernel set (Kiniry et al., 1990; Cárcova et al., 2000b). Two currently used commercial maize hybrids were tested, which the industry reported to differ in KW and protein content.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
Two widely used F1 commercial hybrids, DK752 and DK664 (Dekalb-Monsanto Argentina), were sown in October during the growing seasons of 1998-1999 (Year 1) and 1999-2000 (Year 2) at Salto (34°33'S, 60°33'W), Argentina. Hybrids were selected because of their contrasting kernel size (Monsanto Argentina, 2001). The hybrid DK752 is a small-kernel hybrid at 70 000 plants ha^-1 (<250 mg kernel^-1) while DK664 has large kernels under the same growing conditions (>250 mg kernel^-1). DK752 is known to have a higher protein concentration than DK664, although both are characterized as red flint hybrids. A multilocation test done at 10 different locations during the growing season of 1999-2000 in Argentina gave the significantly different (P < 0.05) protein concentration of 96.1 vs. 91.3 mg g^-1 for DK752 and DK664, respectively (A. Sanguinetti, Monsanto-Argentina, 1999–2000, personal communication). Two plant populations were used, 3 plants m^-2 (LD: low stand density) and 9 plants m^-2 (HD: high stand density). They were selected 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. Each subplot was eight rows, 0.7 m apart, and 12 m long. Experimental plots were kept free of weeds and pests, and experienced no visible signs of water or nutrient stress. The soil at the experimental site had 50 mg P kg^-1 of soil, and was fertilized with 150 kg of N ha^-1 between the four- and six-leaf stages (ligulated leaves).

Three pollination treatments were performed in each subplot to change the number of reproductive sinks per plant: restricted, hand, and open pollination. At least 10 plants per each hybrid x stand density x pollination treatment combination were tagged at random in each replicate 15 d before silking, and were individually identified. Three plants per treatment combination and replicate were used in the present study. A detailed description of the pollination treatments can be found in Borrás and Otegui (2001). Ears were bagged two days after silking in the restricted pollination treatment. This manipulation avoided the negative effects observed on ear growth when ears were cut to reduce KNP (Kiniry et al., 1990). The hand-pollination treatment was aimed to synchronize the pollination of all exposed silks of the apical and subapical ears 4 d after silking of the apical one to increase KNP (Cárcova et al., 2000b). The open-pollinated plants were never bagged and were used as control plants. Kernel number per plant was expected to be smallest in the restricted pollination treatment and largest in the synchronous pollination one. Plants with irregular kernel set along the ear were discarded to avoid the confounding effect of unusually large kernels because of no space restriction. Kernel number per plant was counted in all harvested ears. Final KW was calculated as the quotient between total plant grain weight and KNP.

The plant source-sink ratio during the effective grain-filling period was defined as aboveground plant biomass increase per kernel during this stage (Uhart and Andrade, 1995), when kernels are the predominant growing sink. Biomass increase was obtained as the difference in plant biomass between physiological maturity and the start of the effective grain-filling period (11 d after silking). Physiological maturity was defined when all the plants had reached between 80 and 100% milk line (Muchow, 1990). In Year 1, plant biomass at 11 d after silking 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, in 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. A description of the allometric model used can be found in Borrás and Otegui (2001).

Total plant kernels were collected at physiological maturity and analyzed for starch, protein and oil concentrations by near-infrared transmittance (Infratec 1227, Tecator, Sweden). The concentration (g kg^-1) of each kernel component was expressed as the concentration on a dry weight basis. Total starch, protein, and oil yield per plant (g plant^-1) were calculated as total grain weight multiplied by the concentration of each component. Starch, protein, and oil content per kernel (mg kernel^-1) were calculated as the quotient between the yield per plant of each component and KNP.

In Year 1, stems from plants at physiological maturity were separated and analyzed for N and total SNC. Stems were sliced lengthwise to achieve a quick and uniform drying, and dried in a forced-draft oven (65°C) until constant weight. After that, they were ground sufficiently to pass through a 1-mm screen and analyzed by the micro-Kjeldahl method for N determination, and a phenol sulfuric acid assay for carbohydrate quantification (Montgomery, 1957).

Three models were used to evaluate the response of kernel components to each independent variable (e.g., KNP, KW, post-flowering source-sink ratio), a linear model (Eq. [1]), a bilinear with plateau model (Eq. [2] and [3]), and a bilinear model (Eq. [2] and [4]).

[1]

[2]

[3]

[4]

where Y stands for the response variable, X for the independent variable, a for the intercept, b and d for the slopes, and c for the threshold between models. The fitting of the models was performed by an optimization technique (Jandel, 1991). The model with the highest r² was always chosen. All model parameters were compared with the confidence interval of the parameter (P < 0.05). The regression slopes between each kernel component and KNP were compared by a t-test of the slopes (P < 0.05; Steel and Torrie, 1960). Normalized contents were calculated as the quotient between each kernel component content and the maximum value estimated with the bilinear with plateau model. The latter was fitted between each component content per kernel and the source-sink ratio during the effective grain-filling period (Eq. [2] and [3]), defined above.

	RESULTS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
Kernel Components and KNP
Pollination treatments modified KNP, and variations in this component affected starch, protein, and oil yield per plant (Fig. 1) . No significant differences were detected between years for any kernel component within each treatment, so data were pooled together. As KNP increased, starch, protein, and oil yield per plant also increased, but the yield per kernel was reduced (P < 0.05). Linear and bilinear models explained the different response of grain components to variations in KNP created with the pollination treatments. The large-kernel hybrid DK664 had a linear response of starch yield to KNP, with no differences between stand densities in the response pattern (Fig. 1A). The hybrid DK752, on the other hand, had significantly (P < 0.05) smaller increases in starch yield when KNP was greater than 336 or 698 at the high or the low stand density, respectively. Protein per kernel was strongly reduced in both hybrids when KNP increased above 245 kernels at high stand density or 509 kernels at low stand density (Fig. 1B). Above these KNP thresholds, the response in protein yield to KNP for both hybrids and stand densities was 83% smaller than below them. The response of oil yield to KNP also decreased at high KNP values (Fig. 1C). Hybrids did not differ at the low stand density, and the threshold for the change in oil yield response was estimated at 772 kernels per plant. The same trend was established for DK752 at the high stand density, with a threshold of 423 kernels per plant. At this stand, oil yield of the DK664 had a linear response to KNP, with a slope smaller than the one at low density for the same KNP range (P < 0.05).

View larger version (30K): [in this window] [in a new window]   Fig. 1. Starch (A), protein (B) and oil (C) yield per plant for varying KNP values of hybrids DK664 and DK752 grown at the stand densities of 3 (LD) and 9 (HD) plants m-2. Parameters ± standard errors of the fitted linear and bilinear models are shown in the inserts of each figure with the corresponding symbols.

Kernel Components and KW
All kernel components were highly affected by variations in KW, but no significant differences were detected between experimental years or stand densities within each hybrid. Starch content per kernel was strongly (P < 0.001) correlated with KW in both hybrids (Fig. 2A , slope = 0.64 mg mg^-1). Starch concentration decreased when KW increased, as indicated by the significantly positive (P < 0.05) intercept of the linear regression in both genotypes.

View larger version (31K): [in this window] [in a new window]   Fig. 2. Starch (A), protein (B) and oil (C) content per kernel (mg kernel-1) in relation to kernel weight (KW; mg kernel-1) for hybrids DK664 and DK752. The gray dotted lines within each graphic show the concentration of the component as reference. Inserts within each figure show the parameters ± the standard error of the fitted linear and bilinear models.

Bilinear models also gave the best fit to the response of oil content to variations in KW of both hybrids (P < 0.001, Fig. 2C). Unlike protein, the slope of the relationship was always larger below the breakpoint than above it (P < 0.10 for DK752 and P < 0.05 for DK664). Interestingly, KW threshold values for having a change in the response of oil content (207 and 258 mg kernel^-1 for DK752 and DK664, respectively) did not differ significantly from threshold values calculated for protein content.

Source-Sink Ratio Effects on Kernel Components
Variations in kernel starch, protein, and oil contents were correlated (P < 0.01) to changes in plant weight gain per kernel during the effective grain-filling period (i.e., the post-flowering source-sink ratio). Stand densities and years showed no differences in the response of each kernel component to the source-sink ratio, so data were pooled for the analysis within each hybrid. Bilinear models with plateaus always gave the best fit (Fig. 3) . Starch, protein, and oil content values were normalized to the maximum component value (i.e., fitted plateau of the bilinear model between the kernel content of each component and the post-flowering source-sink ratio) to compare fitted parameters (e.g., slopes, breakpoints) among components. No significant differences (i.e., mean value ± confidence interval) were detected between kernel components in the assimilate availability per kernel necessary for maximizing each kernel component content in either hybrid. In the range of response (i.e., below the breakpoints), significant (P < 0.05) differences were evident between components when assimilate availability per kernel increased. For both hybrids, starch and oil had significantly (P < 0.05) larger intercepts (Parameter a) and smaller slopes (Parameter b) than protein in the response range of the relationship. Protein was the component most affected (i.e., largest slope) by the post-flowering source-sink ratio when assimilate availability per kernel declined below the threshold that maximized its content, and it exhibited the largest variation in normalized content values (65% variation in protein as compared with 53% in oil and 49% in starch).

View larger version (37K): [in this window] [in a new window]   Fig. 3. Normalized protein, starch and oil variations in response to the post-flowering source-sink ratio of hybrids DK664 and DK752. Model parameters ± standard errors are shown in the insert. The post-flowering source-sink ratio was calculated as plant biomass increase per kernel during the effective grain-filling period (mg kernel-1).

View larger version (35K): [in this window] [in a new window]   Fig. 4. Response of starch, protein and oil concentration to variations in the post-flowering source-sink ratio of hybrids DK752 and DK664. Model parameters ± standard errors are shown in the insert. The post-flowering source-sink ratio was calculated as plant biomass increase per kernel during the effective grain-filling period (mg kernel-1).

Post-Flowering Source-Sink Ratio and Assimilate Availability per Kernel
At physiological maturity, residual stem SNC available per kernel was enhanced only when assimilate availability per kernel was higher than 220 mg kernel^-1, and residual stem N available per kernel was enhanced only when the assimilate availability per kernel was above 332 mg kernel^-1 (Fig. 5) . Stem N content per kernel was more stable than SNC content per kernel over a wider range of assimilate availability per kernel at physiological maturity.

View larger version (22K): [in this window] [in a new window]   Fig. 5. Residual stem N and soluble nonstructural carbohydrates (SNC) (mg kernel-1) at physiological maturity (PM) of hybrids DK664 and DK752 in response to the post-flowering source-sink ratio. Model parameters ± standard errors are shown in the insert. The post-flowering source-sink ratio was calculated as plant biomass increase per kernel during the effective grain-filling period (mg kernel-1).

	DISCUSSION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

When KNP increased, the small kernel hybrid DK752 exhibited a greater source limitation for starch yield per plant than the large kernel hybrid DK664. This finding gives support to the same trend observed in the response of KW to KNP of these genotypes (Borrás and Otegui, 2001). The decrease observed in oil content per kernel in response to increase KNP (Table 1) was similar for both hybrids under study. Although there were differences between hybrids in the protein content and concentration (Table 1), these differences were small relative to the large treatment differences in protein content and concentration that treatments allowed to test (Fig. 2B and 4).

There was no significant difference between the two stand densities in the theoretical potential starch, protein, or oil content per kernel (Table 1). This result supports the similar response for potential KW reported by Borrás and Otegui (2001) for the same data set. Pan et al. (1995) showed that variations in stand density did not create differences in the protein content per kernel when the assimilate availability per kernel was enhanced within each stand density, but differences between stand densities in their study (4.5 and 5.5 plants m^-2) were quite small relative to those in the present study (3 and 9 plants m^-2). Our results provide evidence of the lack of preovary fertilization effects, which are set by different stand densities and affect ear growth rate (Andrade et al., 1999), on final kernel size and kernel quality for a large range of post-flowering source-sink ratios.

The concentration of each kernel component was modified as the number of sinks per plant increased. A decrease in the source-sink ratio beyond a given threshold promoted a decrease in the protein concentration and an increase in starch concentration, but had no effect on the relative oil content (Fig. 4). The response of protein concentration to the post-flowering source-sink ratio was in agreement with data obtained in previous research (Jones and Simmons, 1983; Pearson and Jacobs, 1987; Reed et al., 1988; Pan et al., 1995; Uhart and Andrade, 1995). Nevertheless, we detected a saturation point for protein accumulation which had not been reported before, probably because previous experiments on this topic (Uhart and Andrade, 1995) only explored source-sink ratios within the response range of our bilinear with plateau model. We showed that total protein accumulation in the kernels slowed when the assimilate availability per kernel was beyond 430 mg of biomass increase per kernel during the effective grain-filling period. This threshold was above the post-flowering source-sink ratios usually experienced by maize crops, which are in the range between 100 and 400 mg kernel^-1 even for contrasting environments, stand densities, and genotypes (Uhart and Andrade, 1995; Cirilo and Andrade, 1996; Maddonni et al., 1998; Cárcova et al., 2000a). Values between 100 and 400 mg kernel^-1are within the range in which modifications in the post-flowering source-sink ratio were correlated with changes in kernel composition (Fig. 3 and 4). This evidence indicates that the genetic potential for kernel protein content is not usually reached in most growing conditions. There is room, therefore, for improving protein yield in this species through genotypes (Swank et al., 1982) and agronomic practices aimed to increase the post-flowering source-sink ratio. Among the genotypes, research should focus on reducing the decrease in radiation use efficiency usually observed after silking (Otegui et al., 1995), which has been mainly attributed to reductions in leaf N because of kernels demand (Sinclair and Muchow, 1998).

When Jones and Simmons (1983) enhanced the assimilate availability per kernel, both absolute and relative protein contents increased without concomitant increases in KW, suggesting that kernels achieved the potential protein content at post-flowering source-sink ratios larger than those needed to maximize the starch content (i.e., the main determinant of KW). They also showed a slight reduction in the relative starch content when the post-flowering source-sink ratio was increased. Jenner et al. (1991) proposed that the main limitation to protein accumulation in grains during the post-flowering period was the supply of protein precursors, which is usually less than the precursors needed for maximum starch accumulation. In our study, assimilates needed to maximize kernel protein or starch content were found to occur at the same source-sink ratio during the effective grain-filling period for both genotypes (Fig. 3). Nevertheless, our data also indicated that protein content experienced a larger source limitation effect than the other kernel components (Fig. 1 and 3). When the post-flowering source-sink ratio was increased, the availability of stem SNC and N per kernel increased. The source-sink ratio for excess stem N per kernel, however, was higher than the source-sink ratio for excess stem SNC per kernel (Fig. 5). This result leads us to speculate that the availability of N to the kernels during grain filling was more limiting than the availability of SNC. Below et al. (1981) also found that the plant N supply capacity to the ear was more limited than its carbohydrate supply capacity. Uhart and Andrade (1995) showed that this limitation became more important as the post-flowering source-sink ratio decreased, probably because a limited carbon supply to the roots hindered N uptake during grain filling (Pan et al., 1995). In our study, values of stem N content per kernel set found at physiological maturity included the range reported by Jones and Simmons (1983), Pearson and Jacobs (1987), and Uhart and Andrade (1995). Our data revealed that N content in the stem at physiological maturity increased only when the maximum protein content per kernel had been achieved. This result indicates that maize is highly efficient in the use of postsilking available N for kernel formation, and explains the high N harvest index (grain N per total shoot N) usually found for this crop (Pearson and Jacobs, 1987).

In experiments where the assimilate availability per kernel was enhanced during the whole post-flowering period (Reed et al., 1988; Pan et al., 1995), differences in N content of kernels from plants with contrasting KNP values were not evident at mid grain filling but were significant at physiological maturity. Moreover, protein fractions (e.g., zeins, albumins) are formed unevenly during grain filling. Zeins exhibit the largest increase during the last phases of kernel development (Ingle et al., 1965), and increases in total protein content have always been matched by a rise in the zein fraction (Tsai et al., 1978; Singletary and Below, 1989; Singletary et al., 1990). Conversely, structural proteins (e.g., albumins and globulins) are mostly deposited during the early stages of grain filling (Tsai et al., 1978). On the basis of these reports, it can be speculated that the zein fraction was responsible for the rapid increase in protein content when KW increased beyond the threshold that determined the breakpoint in the bilinear model (Fig. 2B), and that structural proteins predominated at low KW ranges (Singletary et al., 1990). These possible differences among protein fractions in the response to KW should be verified because of their commercial and nutritional importance. The zein fraction is known to be of very poor nutritional value, but to have significant positive effects on kernel physical parameters, such us decreased kernel susceptibility to breakage (Dombrink-Kurtzman and Bietz, 1993).

Finally, oil content did not respond the same as protein to the post-flowering source-sink ratio. Results have shown that oil content per kernel was source limited (Table 1), but there was no relationship between oil concentration and KW (Fig. 2), KNP (Table 1), or the post-flowering source-sink ratio for either genotype. These results indicate that, although oil is an energy-rich compound, increased assimilate availability per kernel will not increase the oil content per kernel if KW is not increased as well. Results are probably related to oil distribution within the kernel [oil being mostly located in the embryo (Ingle et al., 1965)], and to the constant embryo-endosperm ratio found for a wide range of kernel weights within the same genotype (Paddick and Sprague, 1939). A constant oil concentration within the embryo should result in an almost constant oil concentration for the whole kernel in a wide range of KW. This response pattern was probably the cause of the stable oil concentration observed in our work.

	CONCLUSIONS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
When KW was altered because of differences in the post-flowering source-sink ratio, starch, protein, and oil responded differently to the modifications in the assimilate availability per kernel. Stand density did not induce any permanent preovary fertilization effect on kernel capacity to achieve the maximum starch, protein, or oil content. Differences among treatments appeared to be related to the post-flowering source-sink ratio only. Results from the present research showed that starch, protein, and oil content were maximized at the same level of assimilate availability per kernel. But, at lower levels of assimilate supply, protein was more source limited than the other kernel components. Variation in kernel oil concentration was not related to the post-flowering source-sink ratio.

	ACKNOWLEDGMENTS

 
Authors wish to thank R. Savin, A. Sanguinetti, D. Diz and C.L. Ballaré for their valuable help. This work was supported by Fundación Antorchas (A-13622/1-79), Dekalb-Monsanto Argentina, and the Agencia Nacional de Promoción Cientfica y Tecnológica (PICT-99 Nro. 08-06608). L. Borrás has a grant of, and J.A. Curá and M.E. Otegui are members of CONICET, the Research Council of Argentina.

Received for publication May 25, 2001.

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TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 

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