Introduction
From the previous chapters it became clear that the yield responses due to row width, planting density and cultivar treatments applied varies between localities and seasons.
In this chapter an attempt will be made to summarize and analyze the responses. The yield component approach is a popular, crop physiological way to understand yield from simpler attributes (Slafer, 2007). With this approach, grain yield is divided into two major numerical components, the number of kernels m-2 and the average individual kernel weight. The number of kernels m-2 can then be sub-divided into various sub-components such as plants m-2, number of tillers plant-1, number of heads m-2, number of heads plant-1, number of kernels head-1, number of spikelets head-1 and number of kernels spikelet-1.
Of these yield components, a sufficient number of heads per unit area (head population) is widely accepted as one of the most important attributes which can be controlled by cultural practices to optimise the grain yield response (Satorre, 1999). Sufficient head populations can be achieved by ensuring that a sufficient number of seedlings survive and that sufficient resources (water and nutrients), to sustain early growth and development, are supplied. Establishment of sufficient plant populations and therefore heads per unit area, by ensuring sufficient plant establishment, has always been a priority in wheat production in the Western Cape (Laubscher, 1986; Schoonwinkel et al., 1991; Agenbag, 1992). During the mid-eighties when conventional planting methods were almost exclusively used in the Western Cape, seedling survival was considered to be only 50% (Laubscher, 1986). High planting densities (up to 160 kg seed ha-1) were recommended (Agenbag, 1992) to achieve sufficient plant establishment and head populations as spring wheat cultivars have limited tillering ability. Tillering can also be restricted by climatic and soil conditions which are not always optimal due to the fact that the crop is rainfed, especially in seasons when the growing season starts late due to inadequate autumn rainfall. Changes in practices from conventional planting methods (broadcasting and planting in narrow rows in tilled soils) to the no-till planting method, have lead to higher seedling survival rates (Chapter 4) but also the use of wider row widths which can have an influence on yield response to planting density. Changes in
the characteristics of modern-day cultivars could also influence this response. In this chapter the relationships of three important components of yield (number of plants m-2, the number of head bearing tillers m-2 and the number of heads plant-1) between each other and with grain yield itself (ton ha-1), will be discussed. Apart from the following historical comparison, data from all localities in the 2005 and 2006 seasons will be pooled together in order to establish these relationships.
Comparison of yield components in the Western Cape: Historical versus New data Very little data on the components of wheat yield in the Western Cape have been published, except for some work by Laubscher (1986) and Schoonwinkel et al. (1991).
Although production practices of that time differ vastly from those used today, a comparison of yield component data over the 21 year period might give an indication of how changes in production practices influenced the different yield components. For the purposes of this comparison, the average data of only one cultivar, SST 015 in one season (2006) will be used for both the Swartland and the Southern Cape regions. SST 015 was chosen as it was the cultivar in the study most recently released and the 2006 season was chosen as it was a very good rainfall season in the Swartland and a fair season in the Southern Cape. While SST 015 is a very good example of a modern-day cultivar, newly released cultivars at the time (1985) Gamtoos and Palmiet were included in the studies of Laubscher (1986) and Schoonwinkel et al. (1991).
This data will be compared with typical data on producer’s farms in 1985, obtained from Laubscher (1986) and experimental data collected by him in these regions, as well as data published by Schoonwinkel et al. (1991) for the Swartland region (Table 9.1).
Laubscher and Schoonwinkel measured the yield head-1 in their studies, which was not measured in this study.
In order to draw a comparison, the yield head-1 data was calculated from yield data and head count determinations using the equation:
Yield head-1 = yield m-2 (g) / number of heads m-2
Data from this study in the Southern Cape (2006) did not compare favourably with the experimental data of Laubscher for this region in 1985 (Table 9.1). The lower head population (297 vs 364 heads m-2), as well as lower yield head-1 figures (1.04 vs 1.51) resulted in lower grain yields (3.1 vs 3.7 ton ha-1). If the 1985 producer’s figures are compared with experimental data in 2006, it is interesting to note that the number of heads m-2 (283 and 297) and the yield head-1 (1.01 and 1.04) were very similar, but that
substantially. This may indicate that modern day cultivars, such as SST 015 produce fewer kernels head-1 but much greater kernel weight indicated by higher TKM.
Table 9.1 Historical and current data on yield components over a 21 year period in the Swartland and Southern Cape
Typical Experimental data Producers Southern Cape Swartland
1985a 1985a 2006c 1985a 1987b 2006c Heads m-2 283 364 297 415 265 294 Yield head-1 (g) 1.01 1.51 1.04 1.42 1.79 1.43
Kernels head-1 35 42 24 39 - 35
TKM (g) 29 34 44 34 - 41
Grain yield (ton/ha) 2.9d 3.7 3.1 4.0 4.3 4.2
a) Laubscher (1986), Average of cultivars including Palmiet released at the time. Broadcast planting method. Planting density, 500 seeds m-2.
b) Schoonwinkel et al. (1991). Cultivar Palmiet in 175 mm row widths with a planter. Average over planting densities (max 100 kg seed ha-1 used) at Langgewens Research Station, Moorreesburg.
c) Present study. Average data for the cultivar SST 015 in each region over row widths (250-300 mm) and different seeding densities (max 300 seeds m-2) used.
d) Average yield components measured on producers farms in close proximity to experiments in each region in 1985. Grain yield was not measured, but calculated from yield components.
The grain yield measured in the 1985 and 1987 experiments in the Swartland averaged or exceeded 4 ton ha-1 (Table 9.1) which indicates that growing conditions in these seasons favoured high yields and are probably comparable to the 2006 season (4.2 ton ha-1). Average yield calculated for producers was much lower (2.9 ton ha-1) indicating a substantial yield gap of more than one ton ha-1. The reason for this yield gap is not clear, but may have been due to lower planting densities used by producers, or management practices in general. With the use of on-farm, producer managed trials in 2006 (Chapter 3), the yield gap (although not measured) is expected to be much smaller than in 1985.
Results from the present study in the Swartland (2006) compare very favourably to producers data obtained in 1985 (Laubscher, 1986). Although the number of heads m-2 (283 and 294) and the number of kernels head-1 were similar (35), higher yield head-1 (1.43 vs 1.01) caused by the higher TKM (41 vs 29) had a positive impact on grain yield (4.2 ton ha-1) in 2006. These results also compare well to experimental data for 1985 and 1987 (Laubscher, 1986, Schoonwinkel et al., 1991) for the Swartland region. In his studies Laubscher (1986) used very high planting densities with the broadcast method to obtain very high numbers of heads m-2 (415). He also measured fairly high yield head-1 values (1.42 g) and high numbers of kernels head-1 (39) which predicted yield levels of 5.5 ton ha-1 but grain yields of only 4.0 ton ha-1 was realised. Although results from this study (2006) indicated much lower head populations (294 heads m-2), somewhat higher
yield levels (4.2 ton ha-1) were achieved. Once again the higher kernel weight of the modern-day cultivar SST 015 compensated for the lower number of kernels head-1. In 1987, which was also a high yielding season in the Swartland, Schoonwinkel (1991) measured high yields with the cultivar Palmiet planted in narrow (175 mm) rows, at fairly low planting densities of 50-100 kg seed ha-1. Although the average number of heads m-2 was lower than the numbers found in the present study (265 vs 297) very high yield head-1 (1.79 vs 1.43 g) resulted in slightly higher grain yield (4.3 vs 4.2 ton ha-1).
This data confirms to some extent that, wheat yield will be advantaged in some seasons in the Western Cape by high seeding rates and what is called high ratios of rectangularity by Holliday (1963), as it will reduce inter-plant competition in the row at critical growth stages during the season. However, conclusions from these comparisons must be drawn with caution as there may be many factors not taken into account, but in general it seems that grain yields achievable with the current no-till planting method is at least on par with optimum yields achieved under experimental conditions 21 years ago.
This is despite the wider row widths required by the no-till system and lower planting densities currently used. However, it must be taken into account that these comparisons were based on data collected in seasons with high potential and relatively early planting dates which would have benefited tillering. If these comparisons were made for seasons when tillering and/or floret survival was limited due to drought at critical stages, another picture may have emerged. In dry seasons severe interplant competition due to the low ratios of rectangularity in these wide rows would have become a yield reducing factor as reported by Holliday (1963). Therefore the risk of yield loss due to unfavourable climatic conditions at critical stages might be higher than it was 21 years ago. If the expected lower yield gap between experimental data and producer’s yields in the current data is true, this comparison might also indicate that producers are currently better off in terms of yield levels than 21 years ago. This may be due to factors like improved cultivars (for instance higher TKM produced) but also due to improved management practices like plant nutrition, weed control, soil fertility and soil water conservation created by the combination of crop rotation and the no-till planting method.
The relationship between plant population and grain yield
Although high planting densities (up to 160 kg seed ha-1) were recommended by Agenbag (1992) to achieve sufficient plant establishment and head populations, yield responses to different plant populations in terms of grain yield in the present study have been very variable. In Figure 9.1 in which the combined data of all localities in 2005 and 2006 is depicted, it can be seen that seasons and localities had major influences on the
particular season. As discussed in Chapter 6, grain yield was significantly influenced by planting density in one Southern Cape trial (Caledon 2005) when the highest yield was produced by the lowest planting density treatment (100 target (no.) of plants m-2). From the discussion on yield response to planting density in the Swartland (Chapter 8) it can be seen that more positive responses to planting density (up to 175 target (no.) of plants m-2) were found in the majority of the trials.
In general these results indicate that excellent yields can be achieved in some seasons and localities at low planting densities and poor yields in other seasons at high planting densities. This was also the case in the studies of Anderson (1991) who observed that variations in optimum planting density between seasons were far greater than variation between cultivars in a similar Mediterranean environment.
The relationship between plant population and the number of heads plant-1
The high variability of response in grain yield to different plant populations found in this study can, to a large extent, be explained by the relationship between plant population (established number of plants m-2) and the number of heads plant-1 as depicted in Figure 9.2.
In Chapters 5 and 7 it was clearly shown that reduced numbers of heads plant-1 resulted when planting density, and therewith plant population (number of plants per unit area), increased. The same response can also be seen if the data for different localities are pooled for different seasons and cultivars in a regression analysis. Exponential, non-linear curves (y = A + Brx) provide fairly good fits for these responses (Figure 9.2). The constants for these curves (A, B and r) as well as the estimated R2 values are shown in Table 9.2. It can be seen in Figure 9.2 that the lower rainfall received at most localities in 2005 (Chapter 3), resulted in a lower overall number of heads plant-1 for all three cultivars. The number of heads plant-1 of the cultivar SST 57 in particular, was lower than one head per plant when 200 plants m-2 was exceeded, which indicated that some of the plants originally counted, did not survive to become head bearing. The same cultivar produced the highest number of heads plant-1 in the more favourable 2006 season. From these curves, it is clear that cultivars do not only differ in response from each other, but that the same cultivar also differs in response according to the potential of the season.
0 1 2 3 4 5 6 7 8
25 50 75 100 125 150 175 200 225 250 275 300 325 350
.
.
CAL 2005 HPF 2005 MBG 2005 CAL 2006 HPF 2006 MBG 2006 RVD 2006 SWD 2006
Figure 9.1 A scatter plot indicating the relationship between established plants (m-2) and grain yield (ton ha-1) at different localities in the 2005 and 2006 seasons. CAL = Caledon. HPF = Hopefield, MBG = Moorreesburg, RVD = Riversdale and SWD = Swellendam.
0 1 2 3 4 5
50 75 100 125 150 175 200 225 250 275 300 325 350 .
.
SST 94 2005 SST 57 2005 SST 88 2005 SST 015 2006 SST 57 2006 SST 88 2006
Figure 9.2 Fitted exponential curves for the number of heads plant-1 against plant populations for different cultivars in 2005 and 2006.
These seasonal effects on the number of heads plant-1 was also clearly illustrated by the work of Anderson (1986) who found that in one season (1980-1981) tiller production at low planting densities was large, but that tiller mortality was small and that this resulted in high numbers of heads plant-1 and per unit area. However in the following season, when conditions that favoured tillering were followed by low rainfall during stem elongation, a loss of 21% of the tillers and a reduction in the head population was
Grain yield (ton ha -1 )
Established plants m-2
Number of heads plant -1
Established plants m-2
genotypes and grain yields were accompanied by reduced tiller morality and the ability of plants to produce larger head populations. Anderson (1986) further suggests that the ability of plants to adjust the number of tillers that become head bearing is an important mechanism that allows the wheat crop to optimise its yield under variable seasonal conditions found in Mediterranean environments.
In general, the number of heads plant-1 of all cultivars in all seasons included in this study, approached 1.0 when 250 plants m-2 were exceeded (Figure 9.2). The average calculated number of heads (all cultivars) is 1.39, 1.23, 1.12 and 1.04 heads plant-1 for 175, 200, 225 and 250 established plants m-2 respectively (Table 9.2). This implies that on average, each plant will only produce one head (mono-culm effect) if plant populations of 250 plants m-2 are exceeded and enough resources are available to sustain the population, which was not the case with SST 57 in 2005 (Figure 9.2).
However, with sufficient resources available, greater plant populations (than 250 plants m-2) could be effective in increasing the number of heads per unit area, especially if the competition between plants can be kept to the minimum as was the case with the conventional system (Laubscher, 1986).
During the mid eighties, Laubscher (1986) aimed for head populations of 400 heads m-2 in his experiments from 245-250 plants m-2 (1.6 heads plant-1). He found that seeding densities of 500 seeds m-2 (170-175 kg seed ha-1, TKM=35) were needed to achieve the desired goal, as the seedling survival rate was only 50%. To achieve similar plant populations with a seedling survival rate of 80%, only 109 kg seed ha-1 of the same TKM (35g) will be needed. With the number of heads m-2 approaching 1.0 when the no-till planting method is used at this plant population (Table 9.2) a maximum number of about 250-300 heads m-2 can be expected. However, at a lower seeding density, say 175 established plants m-2 and an average of 1.39 heads plant-1, 243 heads m-2 can be expected, which compares well to the higher plant population, indicating that compensation by increased numbers of heads plant-1 can be effective to maintain sufficient head populations at lower planting densities.
Table 9.2 Non-linear exponential curves (y= A + Brx) fitted for the number of heads plant-1 vs. number of plants m-2 for different cultivars during the 2005 and 2006 season and the average number of heads plant-1 calculated from 175, 200, and 225 plants m-2
These results indicate that lower head populations are generally achieved with the no-till planting method than previously aimed for by Laubscher (1986) with the conventional planting method. Increasing row widths were seen to reduce head populations in this study (Chapters 5 and 7) and were also widely reported by Doyle (1980); Marshall and Ohm (1987); Johnson et al. (1988) and Schoonwinkel et al. (1991). All of these authors indicated that this reduction is caused by increased inter-plant competition at wider row widths which was described by Holliday (1963) and Puckridge and Donald (1967).
The relationship between head population and grain yield
The head population (number of heads per unit area that survive to produce kernels) is considered one of the most important factors that contribute to grain yield (Satorre, 1999). Figure 9.3 clearly shows that there is an increasing trend in grain yield as the head population increases, but that variation in grain yield also increases at higher head populations.
Figure 9.3 The relationship between head population (number of heads m-2) and grain yield (ton ha-1) at all localities (Riversdale, Swellendam, Caledon, Moorreesburg and Hopefield) during the 2005 and 2006 seasons.
If a simple linear regression (red line A-B) is fitted to this data, only 31.7% of the variation is accounted for. The equation for this line is as follows:
Yield (ton/ha-1) = 0.0011312x + 0.18, R2 = 31.7%
x = number of heads m-2
Variation in this dataset would have been caused by many factors that could have
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0
0 50 100 150 200 250 300 350 400 450 500
.
.
A
B
C
D A-B: Yield=0.0011312X +0.18. Est. R2=31.7%
C-D: Yield (max)=0.0246X -1.2376
Grain yield (ton ha -1 )
Number of heads m-2
cultivars, plant populations and row widths included. As all these factors may influence producers differently in every season, it is impossible to develop an accurate model with which yield can be predicted from any given head population, that will be true for a wide set of circumstances. However, the hand drawn yellow line (C-D) may be of some value in determining the maximum yield (Yield (max)) that has been achieved in this study at given head populations. The equation of this line was calculated with simple mathematics to be:
Yield (max) (ton/ha-1) = 0.0246x - 1.2376
x = number of heads m-2
The maximum yield (Yield (max)) which was achieved in this study according to this equation at different head populations is shown in Table 9.3.
Table 9.3 Yield (max) values for this study calculated with Yield (max) = 0.0246x - 1.2376 at different head populations
Head population (heads m-2)
Yield (max)
(ton ha-1)
150 2.452
175 3.067
200 3.682
225 4.297
250 4.912
275 5.527
300 6.142
350 7.372
Table 9.3 shows that maximum yields of not more than 2,452 ton ha-1 were achieved with low head populations of 150 heads m-2. In the range of 250-300 heads m-2, it was possible to achieve yield levels of 4.912 to 6.124 ton ha-1. According to these calculations, to have achieved very high yield levels (above 7 ton ha-1) more than 350 heads m-2 would have been needed, but such yield levels were only achieved in a few single plots (Figure 9.3). This figure also indicates that when high head populations in the region of 400 heads m-2 were achieved (as aimed for by Laubsher, 1986), the yields realised, were not as high as would be expected. This is most probably due to the high levels of inter-plant competition created by wide row widths at such high head populations (large sink) and not enough resources available (limited source) to reach the full potential created by the large number of heads.
Planting density recommendations
The trial design used in the study (factorial experiments including row widths and planting densities) has limitations in terms of planting density recommendations, as only three planting density treatments were used in each experiment. In order to determine optimum planting densities with the no-till planting method, a wider range of planting densities would have produced more specific results. However, analysis of the yield components above does give some indicators which can be used to make preliminary recommendations. From the discussion above it is clear that with the no-till planting method head populations of 250-300 heads m-2 are sufficient to create a yield potential (Yield (max)) of between 4.9 and 6.1 ton ha-1. Such high yields in commercial fields will only be achievable in the most excellent of seasons when almost no drought stress occurs at any time during the season and all management practices are optimal. To achieve such head populations, at least 175 established plants m-2 will be needed (175 plants m-2 x 1.39 heads plant-1= 243 heads m-2).
To ensure at least 175 established plants m-2, at an 80% seedling survival (Chapter 4), 25% more seeds (219 seeds m-2) must be placed by the planter (see planting density calculations in Chapter 3). At a very low TKM of 32 g, 70 kg of seed ha-1 will be required and with a high TKM of 40 g, 87.5 kg seed ha-1 will be required. These planting density requirements are somewhat lower than recommended by the owners of current cultivars, which range from 100-140 kg seed ha-1. If it is taken into account that the recommendations by cultivar owners are made for conventional planting methods where
To ensure at least 175 established plants m-2, at an 80% seedling survival (Chapter 4), 25% more seeds (219 seeds m-2) must be placed by the planter (see planting density calculations in Chapter 3). At a very low TKM of 32 g, 70 kg of seed ha-1 will be required and with a high TKM of 40 g, 87.5 kg seed ha-1 will be required. These planting density requirements are somewhat lower than recommended by the owners of current cultivars, which range from 100-140 kg seed ha-1. If it is taken into account that the recommendations by cultivar owners are made for conventional planting methods where