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Effect of genotype and seeding rate on grain size and uniformity

S.E. Tanaja1, G.D. Batten1, N.A. Fettell2, C.L. Blanchard1, H.M. Allen1, S.R. Openshaw4, A.B. Blakeney5, and R.L. Cracknell6

1E.H. Graham Centre for Agricultural Innovation, Private Mail Bag, Pine Gully Road, Wagga Wagga NSW 2650, Australia.
2
NSWDPI, Agricultural Research & Advisory Station, Condobolin, NSW 2877, Australia
4
AWB Services, 260 Princes Hwy, Werribee, Victoria 3030
5
Cereal Solutions, P.O. Box 201, North Ryde, NSW 1670, Australia
6
Crackers Consulting, 145 Wimbledon Ave, Mount Eliza, Victoria 3930, Australia

Introduction

Wheat grain size is an important wheat quality parameter. Larger grain diameter has been shown to increase flour milling yield, a trait desirable to the flour millers (Yoon, Brorsen & Lyford, 2002). This study also found that increasing grain size uniformity increases milling yield and flour quality.

A number of environmental and genotypic factors have been shown to influence kernel weight (which is a parameter used as an indicator of larger, heavier grain). Environmental conditions such as amount and timing of watering, temperature and daylight hours have been shown to affect kernel weight (Panozzo & Eagles, 1999; Gajri & Prihar, 1983; Nan, Carman & Salisbury, 2002). Variation in grain weight may also result from differences in maturity, grain setting and grain-filling properties of various genotypes. Production of heavier grains has been shown to be associated with lower-floret number per spikelet and the location of the spikelet relative to the ear (distal and proximal spikelets produce smaller grains compared to medial spikelets) (Stoddard, 1999; Fettell & van Herwaarden, 2003; Calderini & Reynolds, 2000). The position of the floret within a spikelet also has a significant impact on the mass of the grain. Second florets are usually the heaviest, followed by the first, third and its subsequent florets if present (Evers, 2004).

Seeding rate is an important factor affecting yield and kernel weight. A study by Nerson (1980) has suggested a parabolic relationship between yield and seeding rate, where optimum seeding rate can be regarded as the minimum seeding density required to achieve maximum yield. Studies by Faris et al (1980) and Anderson (1986) also reported a decrease of thousand kernel weight as seeding rate increases. These studies have found that lower than optimum seeding rates reduce yield potential due to insufficient grain production. The effect of higher than optimum plant/ear density did not reduce yield potential but reduced mean weight of grains (Anderson, 1986) and water use efficiency (Pelton, 1969).

Although the weight per grain is commonly measured, grain dimensions (and size) are often not recorded as measurements are generally time consuming and tedious. Therefore, little is known about the effect of environment, genotype and seeding rate on wheat grain size. These studies have emphasised the importance of average grain size (as indicated by grain weight), and have overlooked the importance of uniformity. This study investigates the effect of site, genotype and seeding rate on grain size and uniformity using rapid digital imaging.

Materials and methods

Materials

Wheat samples (n=240) used in this experiment were grown during the 2003/04 season. Four wheat genotypes (XC01, XD02, XH03 and XS04) were sown at varying seeding rates (60, 100, 140, 180 and 220 viable seeds per m2; vsm-2) at 4 sites across southern New South Wales (Albury, Cootamundra, Finley and Temora). A randomised block design (RBD) was used with three replicates for each site-genotype-seedingrate treatment level.

Sub-samples were cleaned using an aspirator to remove light non-grain materials and broken grains were removed manually.

Measurement of Grain Size and Uniformity

A minimum of 800 individual grains per sample were assessed using single-kernel digital imaging equipment (Cervitec®, Foss Pacific Inc. 2004). Individual images were collected and grain area (GA, unit = pixel) was measured and used as an indicator of grain size. Double and broken grain images were manually identified and discarded. The mean (GAMEAN) was computed for each plot as an indicator of grain size. The standard deviation (GASTV) and coefficient of variance (GACV) of grain area were computed as an indicator of uniformity. GACV is thought to be a more robust parameter (cf. GASTV) of uniformity and is independent of GAMEAN.

Statistical Analysis

GAMEAN, GASTV & GACV values were analysed using a General Linear Model (SPSS for Windows Release 11.5.1, SPSS Inc, 2002). The model was computed using Type III SSE as follows (the symbol * indicates an interaction):

y = Intercept + site + genotype + seedrate + site*block + site*plot + site*genotype + site*seedrate + genotype*seedrate + site*genotype*seedrate + Error

Results and discussion

The effect of site, genotype and seeding rate on grain size and uniformity were found to be highly significant (p<0.05). Site explained the most variation in all three variables measured, followed by genotype and site-genotype interaction (see Table 1). Although seeding rate was found to have a statistically significant effect, the effect was minimal.

Site Effects

The samples from site Temora were found to be the smallest and most uniform grains (GASTV and GACV), followed by Cootamundra, Finley and Albury (see Table 2). Generally, an increase in grain size (GAMEAN) was found to be associated with a reduction in grain uniformity (indicated by an increase in GASTV and GACV). The production of non-uniform larger grain in this study is also associated with the sites of higher yield such as Albury and Finley (Fettell, 2004, unpublished data). The findings indicated that the production of uniform large grains is not possible by site selection alone, due to positive relationship between GAMEAN, GASTV and GACV among the sites.

Genotypic Effects

The genotypic influence on uniformity is shown graphically in figure 1 as differences in the gradient line of each genotype. Wheat genotype XS04 was found to produce the smallest grains with the highest uniformity (GASTV) (see Table 2). Genotype XH03 also produced small grains but with the least uniformity. Genotype XD02 produced the largest grain, but with a high level of uniformity (similar GACV to XS04).

Table 1. Sources of variations in GAMEAN, GASTV and GACV.

Sources of Variation

Variation Explained

GAMEAN

GASTV

GACV

SITE

89.82%

68.89%

33.46%

GENOTYPE

4.73%

17.02%

22.92%

SEEDRATE

0.09%

2.53%

2.15%

SITE * BLOCK

0.17%

0.95%

2.06%

SITE * GENOTYPE

3.39%

4.35%

8.49%

SITE * SEEDRATE

0.41%

0.93%

2.38%

GENOTYPE * SEEDRATE

0.22%

n.s.

n.s.

SITE * GENOTYPE * SEEDRATE

0.32%

n.s.

n.s.

SITE*PLOT

n.s.

n.s.

6.02%

Note: all sources of variation are significant (p<0.05). Non-significant figure reported as n.s.

The genotypic effect may be attributed to the origin of grain in relation to the ear, spikelet as well as floret. One aspect which may reduce the uniformity of XH03 is its capacity to set a higher number of florets per spikelets. Evers (2004) has reported significant differences in weight of grains obtained from different florets.

Figure 1. Scatter plot (n=240) of GAMEAN and GASTV from different cultivars.

Seeding Rate Effects

Samples from plots sown at the lowest seeding rate (60vsm-2) were characterised by being large and non-uniform (see Table 2). Higher seeding rate impacted minimally on reducing the overall grain size but significantly improved uniformity.

The reduction in uniformity observed at the lowest seeding rate could be due to the type of tillers the grains were produced from. Lower seeding rate were found to have a higher number of tillers per plant (Fettell, 2004, unpublished results), increasing the proportion of secondary and tertiary tillers. However, no relationship between ear number per plant and GACV were noted (R=0.1), possibly due to the relatively small effect of seeding rate. In the sample set studied, the presence of smaller grains is likely to be associated with variation within the ear (different floret and spikelets), rather than between different ears. Further work is needed to acertain a better understanding of these effects.

Table 2. Mean effects of site, genotype and seeding rate on grain area variables.

   

GAMEAN

GASTV

GACV

Site

 

 

 

 

 

 

 

 

Temora

2693

a

392

a

0.135

a

 

Cootamundra

3018

b

408

b

0.146

b

 

Finley

3189

c

524

c

0.165

c

 

Albury

3584

d

579

d

0.162

c

Genotype

 

 

 

 

 

 

 

XS04

3015

a

424

a

0.141

a

 

XH03

3118

b

530

d

0.169

c

 

XC01

3126

b

490

c

0.156

b

 

XD02

3223

c

458

b

0.141

a

Seedrate

 

 

 

 

 

 

 

60

3138

b

503

c

0.159

c

 

100

3123

ab

480

b

0.153

b

 

140

3110

a

469

ab

0.150

ab

 

180

3118

ab

463

a

0.148

a

 

220

3113

a

464

a

0.148

a

All significance tested using Tukey's HSD test; a=0.05

Significance denoted by different subscripts

Conclusion

The production of large, uniform grains is desirable to increase milling yield and quality. Targeting high uniformity through site selection alone appears to be ineffectual; however, genotype selection appears to be a more viable strategy. By utilising genotypes such as XD02, better uniformity can be achieved without reducing average grain size. More research into cultivar variability may lead to better selection in breeding programmes. We have also found that the lowest seeding rate in the study reduces the level of uniformity in wheat grains.

References

Anderson. W. K. (1986). Australian Journal of Agricultural Research. 37. pp. 219-33.

Calderini. D. F. & Reynolds. M. P. (2000). Australian Journal of Plant Physiology. 27(3). pp.183-191.

Evers. A. D. (2004). A Short Course on Grain Morphology. Canberra. Australia.

Faris. D. G. & De Pauw. R. M. (1980). Field Crops Research. 3. pp. 289-301.

Fettell. N. A. & van Herwaarden. A. F. (2003). in Proceeding of the 11th Australian Barley Technical Symposium.

Gajri. P. R. & Prihar. S. S. (1983). Agricultural Water Management. 6(1). pp. 31-41.

Nan. R.. Carman. J. G. & Salisbury. F. B. (2002). Journal of Plant Physiology. 159(3). pp. 307-312.

Nerson. H. (1980). Field Crops Research. 3. pp. 225-234.

Panozzo. J. F. & Eagles. H. A. (1999). Australian Journal of Agricultural Research. 50(6). pp.1007-1015.

Pelton. (1969) W. L. Canadian Journal of Plant Science. 49. pp. 607-614.

Stoddard. F. L. (1999). Cereal Chemistry. 76(1). pp.139-144.

Yoon. B. S.. Brorsen. B. W. & Lyford. C. P. (2002). Journal of Agricultural and Resource Economics. 27(2). pp.481-494.

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