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a Univ. of Saskatchewan, Dep. of Plant Sciences, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
b Univ. of Arkansas, Dep. of Crop, Soil, and Environmental Sciences, 276 Altheimer Drive, Fayetteville, AR 72704 USA
c Univ. of Arkansas, Dep. of Biological and Agricultural Engineering, Northeast Research and Extension Center, P.O. Box 48, Keiser, AR 72351 USA
lpurcell{at}comp.uark.edu
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ABSTRACT |
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 TOPNOTES ABSTRACT INTRODUCTIONMaterials and methodsResultsDiscussionREFERENCES |
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Abbreviations: BM, biomass • CGR, crop growth rate • EFP, effective filling period • 
, partitioning coefficient • HI, harvest index • PGR, plant growth rate • S1, seed Position 1 • S2, seed Position 2 • S3, seed Position 3 • SGR, seed growth rate
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INTRODUCTION |
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TOPNOTESABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionREFERENCES |
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Seed and pod number per plant are typically reduced by increasing plant population, but this reduction is more than offset by the greater number of plants per square meter up to some optimum plant population (e.g., Boquet, 1990). Yield, therefore, may be expressed mathematically by Eq. [1]:
 | (1) |
Conventional full-season soybean production, in the southern USA, is based on sowing maturity group IV, V, VI, and VII cultivars in May or later (Heatherly and Elmore, 1986). Late-sown or double-crop systems are short-season systems that have limited time for development of adequate leaf area (Ball et al., 2000). For late-sown and early-maturing soybean cultivars in the southern USA, we found that populations exceeding current recommendations by almost two fold were necessary for canopy closure and linear biomass production in early reproductive growth for both irrigated and nonirrigated treatments (Ball et al., 2000). For these extremely high populations (>60 plants m-2) in short-season production systems, there is little information on the components of yield described by Eq. [1], or the response of harvest index (HI) to high population when irrigation regime differs.
Although HI is an important descriptor of how vegetative mass is allocated to seed mass at crop maturity (R8, Fehr and Caviness, 1977), it may not accurately reflect partitioning for seed number, which is determined during R3 and R4 and is completed by mid-R5 (Board and Tan, 1995). A theoretical framework for determining seed number per square meter, based upon photosynthate allocation during flowering, was developed by Charles-Edwards et al. (1986). They proposed that seed per square meter was proportional to the daily amount of photosynthate produced by a crop on an area basis during the flowering and seed set periods, multiplied by a partitioning coefficient () that described the fraction of daily photosynthate allocated to seed growth. Seed number per square meter was inversely related to the minimum amount of photosynthate required by an individual seed for growth. Egli and Yu (1991) evaluated this relationship for seed number per square meter by estimating photosynthate production as the crop growth rate (CGR, g m-2 d-1) from flowering to pod set and the photosynthate requirement for seed growth as the seed growth rate (SGR, g seed-1 d-1).
 | (2) |
By varying CGR with shade treatments, Egli and Yu (1991) found that seed per square meter was indeed proportional to CGR but that decreased from about 0.9 to 0.6 as CGR and seed per square meter increased.
The importance of in determining yield responses to population has not been explicitly addressed. Charles-Edwards et al. (1986) modified Eq. [2] to include responses of seed number per plant to population by defining plant growth rate (PGR, g plant-1 d-1) as the quotient of CGR and population.
 | (3) |
Equation [3] indicates that regressing seed per plant against the quotient of PGR and SGR yields a relationship with a slope of . Furthermore, a linear relationship between seed per plant and (PGR x SGR-1) over a wide range of populations indicates a constant .
Since yield results from both the components of seed number and the average seed mass, the nature of seed fill has also been researched to establish the importance of SGR and the effective filling period, (EFP, d). The plant may compensate for differences in individual seed mass by altering SGR and EFP. Water-deficit stress may also affect SGR, EFP, and individual seed mass (Meckel et al., 1984; Egli, 1990). Variation in EFP has also been attributed to genotype, degree of cultivar indeterminacy, irrigation, and environment (Egli et al., 1984; Meckel et al., 1984; Salado-Navarro et al., 1985).
Maintaining the mass of an individual seed is important. Under limited photosynthate availability, such as shading or defoliation during late seed fill, yield can be decreased via lower individual seed mass (Jiang and Egli, 1995; Board and Tan, 1995). Inter- and intraplant competition may also limit carbohydrate availability, but such effects have not been researched for high population in short-season production. While extreme populations may allow for greater seed set, intense inter- and intraplant competition may negate the advantage of increased seed number.
Establishing which mechanisms are responsible for the greatest yields in short-season soybean production, via high population, may provide insights for management and phenotypic improvement. Therefore, the specific objectives of this research were to: (i) describe seed mass per square meter and seed mass per plant as affected by population density, (ii) investigate the stability of HI at the plant level and at the pod level, (ii) examine the assimilate partitioning relationship for seed number as a function of plant and seed growth, and (iv) evaluate the relative importance of the seed-filling characteristics determining individual seed mass.
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Materials and methods |
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TOPNOTESABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionREFERENCES |
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Data Collection and Calculation
Seed growth analysis was done on samples taken at 10 to 14 d after beginning R5, which corresponds to the beginning of linear seed fill (Salado-Navarro et al., 1985). At 14 d after the initial sample (early R6), and R8 (harvest maturity), additional samples were taken. For each of the three seed growth Harvests, 6 (1997) or 12 (1998) consecutive plants in a row, for each plot, were cut at the base of the shoot and oven dried. Pods were then removed from the plant and bulked for each plot. Pods were divided into two-seeded or three-seeded categories, weighed, counted, and shelled for seed mass. Seed growth rate was calculated as the difference between individual seed mass at Harvests 1 and 2 (during the period of linear seed growth) divided by the time interval between Harvests 1 and 2. Individual seed mass was the individual seed mass at Harvest 3. Effective filling period was calculated as individual seed mass divided by SGR (Egli, 1975). The relationship between seed number and was evaluated on both a crop and plant growth basis by Eq. [2] and[ 3], respectively.
Detailed seed measurements at maturity for pod mass, pod length, pod breadth, shell mass, seed mass per pod, and individual seed mass for seed position in a pod, were taken on a range of population densities, all from irrigated plots, in 1998. Seed position at the distal end of the pod was designated S1. The Position S2 in a three-seeded pod was the middle seed, and in a two-seeded pod this position was closer to the peduncle. For a three-seeded pod, S3 was designated as the position closest to the peduncle.
Yield was harvested from bordered 20-m2 sections of plot with a plot combine. Seed moisture was determined, and yield was expressed at 130 g kg-1 moisture. Mass of a 100-seed subsample was used to calculate the mass of an individual seed and the seed number per square meter. Harvest index was determined from a subsample of six consecutive plants within a row of each plot at R8. The six plants were cut at ground level, bulked and weighed for total biomass (BM). The seed was separated from plants with a single-plant thresher for seed mass, and HI was calculated as the quotient of seed mass and total plant BM.
Statistical Analysis
The relationship between yield per plant and population density was described by an inverse transformation of yield. Relationships between yield and plant population were assessed from covariate analysis and heterogeneity of slopes on the transformed yield variable, using a general linear model (SAS Inst, version 6.12), with each combination of irrigation, and cultivar as the covariate. Outliers were removed after one pass through data on the four separate combinations of cultivar x irrigation regime for each of the 2 yr on the basis Cooks D and Student's residual statistics (Rawlings et al., 1998). A total of 9 plots (initial
) and 6 plots (initial
) were removed as outliers for 1997 and 1998 data sets, respectively. Among these data points were two data points from both irrigated A4922 and irrigated Manokin in 1997, where lodging occurred at the highest density, and the yield curve showed a parabolic decrease. From the transformed data, cultivars were tested against each other for yield differences at populations ranging from 10 to 100 plants m-2 in 10 unit steps, by the use of contrast statements.
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Results |
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TOPNOTESABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionREFERENCES |
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30 plants m-2 in 1997, yields were greater for Manokin than for A4922 mainly because of the ability of Manokin to branch and produce more nodal sites for pod development (Ball, Keisling, Purcell and Vories, 1998, unpublished data). In 1998, yield for the irrigated regime was similar for both cultivars at any plant population, whereas the yield potential for Manokin was higher than for A4922 for all populations used under nonirrigated conditions.
Harvest Index and Yield Compensation at the Plant or Area Level
Harvest index values ranged from 0.38 to 0.65 over the 2 yr for all treatment combinations (Fig. 2A)
. Although there was a wide range of HI values, we found no consistent relationship between HI and yield. Harvest index decreased for each cultivar under drought conditions. For 0.19-m rows, drought tended to decrease the HI from 0.55 to 0.52 in 1997
and from 0.58 to 0.46
in 1998. The indeterminate cultivar A4922 had a higher HI (0.55) than Manokin in 1997 (0.52;
), but HI of Manokin (0.52) was similar to that of A4922 (0.53) in 1998.
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0.002), and although statistically significant, these differences between treatment combinations did not rank clearly according to density (data not shown). Differences in HI among population densities were generally confined to the highest population when there was lodging. This response was particularly evident for Manokin (irrigated and nonirrigated) in 1997, whereas A4922 was not affected. Harvest index changes were, therefore, minor with regards to changes in yield.
Harvest Index and Yield Compensation at the Pod Level
The ratio of seed-mass to pod-mass for irrigated treatments increased as population density increased for both cultivars (Table 3)
. The increase in the ratio of seed-mass to pod-mass was realized through a lighter shell, and a constant seed mass. For A4922, there was no significant difference in the seed-mass to pod-mass ratio between two-seeded or three-seeded pods, but Manokin three-seeded pods had the higher value of 0.71 compared with 0.69 for a two-seeded pod. Part of the yield compensation mechanism was to maintain seed mass by giving priority to seed filling over making heavier shells, and increasing plant population resulted in more efficient partitioning between shell and seed components within a pod. Pod mass of A4922 was not changed by increasing population, but pod mass of Manokin decreased from 412 mg at 7 plants m-2 to 362 mg at 91 plants m-2. The mass of a two-seeded pod was always significantly less than that of a three-seeded pod for both A4922 and Manokin, and two-seeded pods had shells with lower mass compared with three-seeded pod shells.
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Because less assimilate was required to produce a given seed mass from three-seeded pods than from two-seeded pods, the numbers of pods which are either three-seeded or two-seeded may be important. In 1998, cultivar and the interaction between cultivar and population differed significantly (P < 0.01) in the ratio of number of two-seeded to three-seeded pods (data not shown). The two-seeded to three-seeded pod ratio for A4922 at 20 plants m-2 was 1.28, and this value was reduced significantly to 0.92 at 91 plants m-2, reflecting a shift to more three-seeded pods as population increased. Responses of the two-seeded to three-seeded pod ratio to population in Manokin were opposite to the responses in A4922. At 20 plants m-2, Manokin had a ratio of two-seeded to three-seeded pods of 1.05. At 91 plants m-2, Manokin further shifted to more two-seeded pods with a value of 1.33.
Yield per plant was approximately the same for A4922 and Manokin at any given population for irrigated treatments in 1998 (Table 2), and there was no obvious advantage for A4922 having a greater proportion of three-seeded pods at higher populations than for Manokin. Differences between cultivars for the ratio of two-seeded to three-seeded pods in response to population may be due to crop growth habit. Manokin is a determinate cultivar with flowering spread over a short period whereas A4922 is an indeterminate cultivar with flowering spread over a longer period. Differences in plant architecture and lengths of flowering and pod set periods are important characteristics that affect intraplant competition of pods for assimilate in sequential seed development (Munier-Jolain et al., 1994), and may contribute to the proportion of two-seeded and three-seeded pods.
Crop Growth Rate and Seed Growth Rate Partitioning
Seed number per square meter was directly proportional to the ratio of CGR and SGR (Fig. 3)
. The slope of the line in Fig. 3A had a value of 0.62
, which is an estimate of (Eq. [2]). This value of agreed closely with that found by Egli and Yu (1991) for the highest rates of crop growth. We also evaluated using Eq. [3], by regressing seed plant-1 against the quotient of PGR and SGR (Fig. 3B), which resulted in an estimate of of 0.56. The strong linear relationship
for all the treatments represented indicated that was constant across population density, irrigation regime, and year.
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). In 1998, A4922 also had a higher SGR than Manokin (3.9 mg d-1 and 3.4 mg d-1, respectively;
). Generally, lack of irrigation tended to reduce SGR in A4922 in 1997
but not in 1998, and for Manokin SGR was statistically the same in any irrigation regime (Table 4)
. Averaged over populations in 1997, irrigated A4922 had an SGR of 4.1 mg seed-1 d-1, and irrigated Manokin had an SGR of 3.4 mg seed-1 d-1. With one exception (irrigated A4922 in 1997), plant population did not change SGR for either of the cultivars in irrigated or nonirrigated conditions in 1997 or 1998.
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to CGR or PGR. From covariate analysis and heterogeneity of slopes, where cultivar was the covariate, was regressed against each of PGR, CGR, PGR x SGR-1, or CGR x SGR-1. In this analysis, was derived for each data point from measured values of PGR, CGR, SGR and seed number per square meter. We found to be similar for both cultivars for all these regressions. However, estimates of are typically associated with cumulated error from the measurements SGR, PGR, and seed number per square meter. Egli and Yu (1991) also reported that they found no evidence for genotypic differences in partitioning by cultivars. Therefore, with the constancy of over the range of our data, and being similar for A4922 and Manokin, we concluded that seed number per square meter was determined primarily by differences in CGR (from the factors present in the empirical model) for the population and irrigation treatments. A constant , for both irrigation treatments and over a wide range of populations, indicates that seed number was directly dependent upon carbon available from crop growth. Therefore, high CGR results in a high seed number and, for short-season production, this is associated with high plant population (Ball et al., 2000).
Seed Filling and Individual Seed Mass
Data for seed mass in two-seeded and three-seeded pods from 1998, with eight irrigated plant populations represented, are presented in Table 5
. Several points can be made from the grand means for each pod category and seed position within a pod. The first point is that A4922 had the greater seed mass (total seed mass, S1, S2 and S3) compared with Manokin in either two-seeded or three-seeded pods. The second point is that in a two-seeded pod, the individual seed mass at S2 (closer to the peduncle) was significantly less than individual seed mass at Position S1 (P 0.05) for both cultivars. Individual seed mass of A4922 was 140 mg at Position S1 compared with 120 mg at S2, and individual seed mass of Manokin was 122 mg at S1 and 103 mg at S2. Thirdly, in the three-seeded pod, A4922 had the larger seeds of the two cultivars, but respective pods of both A4922 and Manokin had similar individual seed mass at Positions S1 and S2. Individual seed mass for A4922 was 139 mg at both S1 and S2, and for Manokin, 117 mg at both S1 and S2. Finally, the three-seeded pods exhibited significantly lower seed mass for Position S3, closest to the peduncle, when compared with seed at S1 and S2.
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The above detailed seed position measurements (Table 5) were only taken on irrigated treatments. With water deficit during pod fill, seed filling may be decreased and individual seed mass would be expected to vary (Purcell et al., 1997). Additionally, the effects of water deficit may cause variation in individual seed mass by an interaction with the effects of population density. By maintaining individual seed mass for specific seed positions in response to high population, the crop had the ability to increase yield by increasing seed number without a detrimental reduction in seed mass.
For both cultivars, individual seed mass of the nonirrigated treatment generally decreased compared with the irrigated treatment (Table 4). Irrigated Manokin, in 1997, showed a tendency for decreased seed mass at the highest plant populations, which may have been due to deleterious effects of lodging. The greater seed mass in 1997 of nonirrigated Manokin at 12 plants m-2 compared with greater populations may be due to decreased competition among plants for soil water and resulting in seed mass being similar to the irrigated treatment. Otherwise, there were no obvious effects of population on individual seed mass.
Seed Filling and Effective Filling Period
Response of EFP to irrigation treatment interacted with cultivar in 1997 (
, Table 4). For A4922, EFP was unaffected by irrigation treatment with values of 30 and 32 d for irrigated and nonirrigated treatments, respectively. For Manokin, EFP was decreased from 31 d in the irrigated treatment to 26 d for the nonirrigated treatment. In 1998, EFP of cultivars responded similarly to irrigation regime with irrigated treatments having the higher EFP of 31 d compared with an EFP for nonirrigated treatments of
. Differences between cultivars in the response of EFP may be due to slight differences in phenology when exposed to drought during seed fill (Ball et al., 2000).
Within the eight combinations of year x irrigation regime x cultivar, EFP was remarkably constant for any combination of treatments across plant population (Table 4). The only significant effect of population on EFP was for irrigated Manokin grown at 64 plant m-2 in 1997, which had a lower EFP value of 25 d compared with the 12 plant m-2 treatment. For 1997 irrigated Manokin, EFP and individual seed mass values tended to decrease as plant population increased, but no other clear relationships were evident.
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Discussion |
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TOPNOTESABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionREFERENCES |
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By and large, yield response to population was due to an increased plant mass per unit area at maturity. Our data indicate that HI was relatively stable and was not affected by population except when lodging occurred. Similarly, partitioning during the season, as estimated by , was relatively constant. Previous research also found HI to be relatively stable within a variety except for conditions of extreme interplant competition (Spaeth and Sinclair, 1984b) that occur at high populations. Although we found that HI decreased under water deficit, this effect was rather small, perhaps because water deficit occurred during early stages of pod fill. In a previous study at the same location (Purcell et al., 1997), water-deficit stress during late seed fill accounted for approximately 90% of the yield decrease in a nonirrigated treatment compared with the well-watered treatment.
Yield compensation in this study was primarily associated with decreased yield per plant as population increased. The decreased yield per plant was more than offset by population, resulting in yield per square meter increasing to an asymptote as population increased.
At the pod level, a decreased photosynthate availability per plant at high populations was compensated by selectively partitioning more assimilate into seed mass relative to the shell mass, resulting in a greater ratio of seed to shell mass. This was partially responsible for soybean maintaining a high HI as population increased. The combined findings of the seed growth analysis indicated that SGR, EFP, and individual seed mass did not vary appreciably across population density. Both water availability and cultivar affected individual seed mass, but there was no effect of population density per se. Differences in compensation, in response to high population, were not evident with regard to decreasing individual seed mass, or changing the components affecting seed mass (SGR and EFP). This led us to conclude that seed number per square meter, which is determined before R5, was the main mechanism determining differences in yield in this population study. For a short-season production system, with adequate water and high plant populations, these findings are in agreement with seed number being the main component driving yield in full-season production (e.g., Board et al., 1999; Jiang and Egli, 1995). Therefore, a strategy of high population will not compromise the ability of the crop to fill the seeds it sets.
Seed number per square meter was directly proportional to the ratio of CGR to SGR. The partitioning coefficient, , was estimated at 0.62 on an area basis and 0.58 on a plant basis, and was constant across 0.19 m row treatments. Within the errors of measurement, A4922 and Manokin had similar partitioning for seed number despite a lesser SGR of Manokin than A4922. Neither plant population nor irrigation affected partitioning of assimilate to seed. Because SGR was fairly constant for 1997 and 1998 for population and irrigation treatments, seed number was determined mainly by CGR.
The empirical model of Charles-Edwards et al. (1986) indicates that seed number per square meter is associated with crop growth during flowering to pod set (R1 to late R4 or early R5). This corresponds to evidence that seed number per square meter is related to canopy photosynthesis during the same period (e.g., Heitholt et al., 1986; Egli et al., 1985; Jones et al., 1984; Egli and Yu, 1991). Seed number per square meter is determined prior to the period of linear seed growth for any particular pod (Pigeaire et al., 1986; Duthion and Pigeaire, 1991). The sequential fruiting characteristic of soybean results in a range of developmental stages of reproductive organs on the same plant (e.g., Spaeth and Sinclair, 1984a). While early fruiting sites are accumulating mass linearly, other sites may be producing flowers or developing young pods. The assimilate demand by reproductive organs of diverse developmental stages on a plant is likely to be different. Models which incorporate crop growth and seed growth with respect to sequential pod development may better explain the complexities of assimilate allocation in crops that have nonsynchronous reproductive growth (e.g., Board and Tan, 1995). Fruiting patterns and crop growth habit may be important factors determining differences among cultivars in intraplant competition and response to population.
In summary, the results from our study evaluated the importance of population to yield compensation for short-season production in the mid South. Results were similar to conclusions drawn from full-season production systems (Board et al., 1999) and earlier work based on wide rows (Lehman and Lambert, 1960), or in more northern latitudes (Lueschen and Hicks, 1977). We found that high rates of crop growth resulted in increased seed number and final plant biomass, which were the predominant factors determining yield. In that both HI and were fairly constant, our study indicates the importance of maximizing crop growth and final crop biomass. Logically then, maximizing CGR and biomass by every means possible should result in greater yielding capabilities if serious water-deficit stress during the later part of seed fill is avoided. High rates of crop growth require full light interception which, in turn, necessitates early canopy establishment. In short-season, time-constrained production systems, high plant population is a key way of ensuring that soybean has maximum light interception, CGR, and biomass.
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ACKNOWLEDGMENTS |
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NOTES |
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TOPNOTESABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionREFERENCES |
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Received for publication October 14, 1999.
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