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Flowering Calculator: Parameters for predicting flowering dates of new wheat varieties in Western Australia

DL Sharma1, BJ Shackley2, CM Zaicou-Kunesch3 and B Curtis4

1 Centre for Cropping Systems, Department of Agriculture and Food, Lot 12 York Rd, Northam, WA 6401, Australia. Email darshan.sharma@agric.wa.gov.au
2
Department of Agriculture and Food, 10 Dore St, Katanning, WA 6317, Australia. Email brenda.shackley@agric.wa.gov.au
3
Department of Agriculture and Food, 20 Gregory St, Geraldton, WA 6530, Australia.
Email
christine.zaicou-kunesch@agric.wa.gov.au
4
Department of Agriculture and Food, PMB 50 Melijinup Road, Esperance, WA 6450, Australia. Email ben.curtis@agric.wa.gov.au

Abstract

Wheat varieties need to be matched to sowing date so that flowering occurs at an optimum period when the risks of occurrence of damaging low temperature (frost), and high temperature and water stress are minimised. The Flowering Calculator, a computer program previously developed by the Department of Agriculture and Food Western Australia has been available for predictions but is not calibrated for current and new cultivars. Field experiments were conducted with about 50 current varieties over four years (2006-2009) at Geraldton (28.79 S), Northam (31.64S), and Katanning (33.40S) in Western Australia and parameters for different models in this program are presented. Comparison with observed flowering dates revealed that predictions for early sowing dates in southern latitudes were invariably earlier than actual flowering dates with all models – the inability of the model to perform at southern latitudes is the major limitation of this package. However, flowering time in the warmer, northern locations of the wheatbelt could be reasonably predicted and as such, we expect these parameters will be applicable within this region. We have tabulated in this paper the parameters of important varieties that can be used in the Flowering Calculator in the public domain. With these coefficients of parameters and the inbuilt daily average temperatures and photoperiods of the locations predictions of flowering dates can be produced for all these varieties.

Key Words

Phenology, vernalisation, photoperiod, maturity group, frost, screenings, time of sowing

Introduction

Since early part of the 20th century, it was known that sexual reproduction in many plant species is highly influenced by length of the day and prevailing temperature (Garner and Allard 1920). Crop phenology has since then been investigated and exploited to improve productivity in a range of crops.

Flowering date in spring wheat is critical to protect crops from damaging effects of frost (Gott 1961; Anderson 1988) and dry warm finishing conditions (Sharma et al. 2008). Wheat crops are known to yield the most under sowing periods which result in the crop flowering after the danger of frost damage had passed but before the period available for grain growth was significantly shortened (Single 1961; Fischer and Kohn 1966; Syme 1968).

A range of flowering models differing in complexity has been developed over time in Australia (Angus et al. 1981. Perry et al. 1987. Loss and Elliot 1988). Based on these statistical models, Tennant and Tennant (2000) wrote a menu-based program called ‘Flowering Calculator’ which is usable throughout Australia by selecting relevant location and the state. It allows the use of four models which range from simple heatsum accumulation to linear regression of daily development rate (DDR) on day length, mean temperature and their interaction. This software is available on a CD that can be purchased from the Department of Agriculture and Food, Western Australia (Contact: Dr Meredith Fairbanks mfairbanks@agric.wa.gov.au). A particular advantage of this application is that the reporting window graphs historical minimum and maximum temperatures and reports on the frost likelihood with changing sowing date.

However, like any other software program, the Flowering Calculator is usable only for the varieties that have their parameters included in it. Unfortunately, the package has flowering parameters for only 10 varieties (Aroona, Bodallin, Eradu, Gamenya, Miling, Gutha, Sunset, Bencubbin, Spear, WW33), most of which are obsolete. This has rendered this potentially usable tool useless for the want of parameters for current varieties. We present in this paper the parameters that we have developed for current and new wheat cultivars in Western Australia. Users can now update their copy of the program by adding these parameters to the existing ‘Crops-Varieties.dat’ file.

Methods

Unreplicated field experiments were conducted over four seasons (2006-2009) at three locations varying for latitude (Geraldton 28.79 S, Northam 31.64S, and Katanning 33.40S) in the wheatbelt of Western Australia. Each year, seeds were sown in one metre long rows and plant density thinned to 40 plants per linear metre where needed. Sowings in each year were done on 25 April, 16 May, 02 June, 21 June to cover the spread of the sowing period in the WA wheatbelt. Date to anthesis of 50% heads was recorded and parameters of models 1 to 4 were calculated.

Results

Table 1. Parameters for four models in the Flowering Calculator software.

Model 1: Thermal time to flowering Cd = Σ(Tm-Tb); Tm, mean daily temperature; Tb, base temperature

Model 2: DDR = a + b (Tm - Tb); DDR, daily development rate = 1/days to flower; a, temperature intercept coefficient; b, temperature slope coefficient; Tm, mean seasonal temperature

Model 3: DDR = a + b (Tm - Tb) + c DLm; c, photoperiod coefficient; DLm, mean day length

Model 4: DDR = a + b (Tm - Tb) + c DLm + d (Tm * DLm); d, temperature and photoperiod interaction coefficient

Cultivar

Thermal time for model 1

Parameters of models 2, 3 and 4

[C.d (standard error)]

Model

a

B

c

d

Adjusted R2

Annuello

1348

2

-0.0002

0.0008

   

87.0

 

(18.9)

3

-0.0142

0.0008

0.0013

 

88.5

   

4

-0.0447

0.0032

0.0042

-0.0002

88.4

Arrino

1273

2

0.0002

0.0008

   

84.1

 

(18.1)

3

-0.0146

0.0008

0.0014

 

85.4

   

4

-0.0796

0.0064

0.0075

-0.0005

86.3

Binnu

1326

2

0.0005

0.0007

   

72.8

 

(23.3)

3

-0.0148

0.0008

0.0014

 

74.0

   

4

-0.0674

0.0053

0.0063

-0.0004

74.2

Braewood

1511

2

0.0015

0.0006

   

76.4

 

(30.8)

3

-0.0258

0.0006

0.0025

 

84.8

   

4

-0.0554

0.0029

0.0053

-0.0002

84.5

Bumper

1335

2

0.0021

0.0006

   

74.2

 

(29.2)

3

-0.0342

0.0007

0.0033

 

90.2

   

4

-0.0444

0.0016

0.0042

-0.0001

89.7

Calingiri

1370

2

0.0014

0.0006

   

81.3

 

(18.0)

3

-0.0191

0.0007

0.0019

 

86.0

   

4

-0.0402

0.0024

0.0038

-0.0002

85.9

Carinya

1330

2

-0.0004

0.0008

   

88.7

 

(19.3)

3

-0.0203

0.0008

0.0018

 

91.7

   

4

-0.0874

0.0066

0.0081

-0.0005

92.9

Carnamah

1312

2

0.0013

0.0007

   

82.9

 

(17.4)

3

-0.0106

0.0007

0.0011

 

84.4

   

4

-0.0638

0.0053

0.0061

-0.0004

85.1

EGA 2248

1277

2

0.0006

0.0007

   

76.3

 

(20.4)

3

-0.0140

0.0008

0.0013

 

77.7

   

4

-0.1287

0.0105

0.0121

-0.0009

81.5

EGA Bonnie Rock

1253

2

0.0000

0.0008

   

82.6

 

(19.6)

3

-0.0161

0.0008

0.0015

 

84.1

   

4

0.0093

-0.0013

-0.0009

0.0002

83.8

EGA Eagle Rock

1337

2

-0.0004

0.0008

   

82.2

 

(23.3)

3

-0.0073

0.0008

0.0006

 

82.1

   

4

-0.1124

0.0095

0.0105

-0.0008

85.2

EGA Jitarning

1487

2

0.0035

0.0004

   

58.2

 

(27.1)

3

-0.0181

0.0004

0.0020

 

69.3

   

4

-0.0771

0.0052

0.0075

-0.0004

72.2

EGA Wentworth

1333

2

0.0004

0.0007

   

80.3

 

(20.4)

3

-0.0083

0.0007

0.0008

 

80.6

   

4

-0.1058

0.0088

0.0100

-0.0008

83.9

Endure

1560

2

0.0031

0.0004

   

56.6

 

(32.6)

3

-0.0254

0.0005

0.0025

 

73.5

   

4

-0.0106

-0.0007

0.0012

0.0001

72.8

Fang

1430

2

0.0028

0.0005

   

57.9

 

(37.7)

3

-0.0339

0.0006

0.0033

 

75.5

   

4

-0.0006

-0.0022

0.0002

0.0003

74.8

Fortune

1374

2

0.0013

0.0006

   

70.1

 

(32.1)

3

-0.0220

0.0007

0.0021

 

87.0

   

4

-0.0619

0.0041

0.0058

-0.0003

86.3

GBA Sapphire

1318

2

0.0007

0.0007

   

85.4

 

(17.5)

3

-0.0065

0.0007

0.0007

 

85.6

   

4

-0.0883

0.0073

0.0084

-0.0006

87.6

LongReach Lincoln

1287

2

0.0000

0.0008

   

85.3

 

(21.4)

3

-0.0186

0.0008

0.0017

 

87.5

   

4

-0.0517

0.0037

0.0048

-0.0003

87.4

Mace

1306

2

0.0013

0.0007

   

78.3

 

(28.1)

3

-0.0341

0.0008

0.0032

 

90.0

   

4

-0.0323

0.0006

0.0030

0.0000

89.4

Magenta

1381

2

0.0011

0.0006

   

84.4

 

(18.8)

3

-0.0155

0.0007

0.0015

 

87.6

   

4

-0.0689

0.0051

0.0065

-0.0004

88.8

Spear

1468

2

0.0031

0.0004

   

69.0

 

(24.7)

3

-0.0104

0.0005

0.0012

 

73.4

   

4

-0.0085

0.0003

0.0011

0.0000

72.8

Stiletto

1411

2

0.0045

0.0004

   

67.4

 

(35.9)

3

-0.0084

0.0004

0.0012

 

70.5

   

4

-0.0115

0.0006

0.0015

0.0000

68.8

Tammarin Rock

1214

2

0.0015

0.0007

   

87.3

 

(14.8)

3

-0.0070

0.0007

0.0008

 

87.7

   

4

-0.0752

0.0063

0.0073

-0.0005

88.8

Wedgetail

1691

2

0.0051

0.0002

   

26.5

 

(44.4)

3

-0.0178

0.0002

0.0021

 

50.4

   

4

-0.0670

0.0039

0.0066

-0.0003

53.4

Westonia

1221

2

-0.0002

0.0008

   

87.4

 

(17.3)

3

-0.0084

0.0009

0.0008

 

87.4

   

4

-0.0978

0.0084

0.0092

-0.0007

88.9

Wyalkatchem

1288

2

0.0002

0.0008

   

84.5

 

(18.0)

3

-0.0122

0.0008

0.0011

 

85.4

   

4

-0.0541

0.0043

0.0051

-0.0003

85.6

Wylah

1715

2

0.0065

0.0001

   

0.4

 

(66.3)

3

-0.0232

0.0000

0.0028

 

43.0

   

4

-0.0131

-0.0008

0.0019

0.0001

39.3

Yandanooka

1307

2

0.0016

0.0006

   

83.0

 

(16.7)

3

-0.0162

0.0007

0.0016

 

86.6

   

4

-0.0380

0.0025

0.0037

-0.0002

86.6

Yitpi

1454

2

0.0030

0.0004

   

63.4

 

(25.7)

3

-0.0123

0.0005

0.0014

 

67.9

   

4

-0.0509

0.0037

0.0050

-0.0003

68.3

Young

1210

2

-0.0002

0.0008

   

79.6

 

(25.6)

3

0.0066

0.0008

-0.0006

 

79.0

   

4

-0.1680

0.0147

0.0159

-0.0013

84.6

Zippy

1178

2

-0.0006

0.0009

   

85.3

 

(28.5)

3

-0.0247

0.0010

0.0022

 

87.3

   

4

-0.0796

0.0059

0.0074

-0.0005

87.2

Parameters for different models in respect of current and new wheat cultivars are given in Table 1.

In order to check the reliability of the models, predictions of flowering time were made for the Geraldton site in the north and Katanning in the south using the temperature datasets of year 2007 and comparisons made with the actual flowering dates. These comparisons revealed that the model predicted flowering date with a RMSE error of 7 days for all sowing dates in the north (Geraldton) and June sowing in the south (Katanning) but deviations from expected date were high for early sowing dates (RMSE = 16 days) at southern latitudes. All the models tended to under-predict flowering date at the southern location (Katanning). We anticipate that vernalisation requirement of the varieties and the hourly temperature profile to be the likely causes.

Conclusion

Parameters to predict flowering times using the Flowering Calculator are now available for new and current wheat cultivars grown in Western Australia. The predictions at southern latitudes (33S) showed large deviation from observed dates. However, flowering dates in northern, warmer locations at latitudes around 29S could be reasonably predicted and thus might have application in other Australian states with similar location attributes. Given the location related observed limitations of the current model, we have now initiated the development of an improved model.

References

Anderson WK (1988). Minimizing frost damage in Western Australia: a phenological approach. In: Paper presented at the ‘Frost injury of wheat’ workshop. Wheat Research Council, Sydney 26 July1988.

Angus JF, Mackenzie DH, Morton R and Schafer CA (1981). Phasic development in field crops II. Thermal and photoperiodic responses of spring wheat. Field Crops Research 4, 269-283.

Fischer RA and Kohn GD (1966). The relationship of grain yield to vegetative growth and post-flowering leaf area in the wheat crop under condition of limited soil moisture.Australian Journal of Agricultural Research 17,281–295.

Garner WW and Allard HA (1920). Effect of the relative length of day and night and other factors of the environment on growth and reproduction in plants. Journal of. Agricultural Research (USDA) 18, 558-606.

Gott MB (1961). Flowering of Australian wheats and its relation to frost injury.Australian Journal of Agricultural Research 12,547–565.

Loss SP and Elliott GA (1988). FLOWER: A model predicting flowering times of cereals. Users' manual. Tech. Rep. 14, Div. Plant Res., W.A. Dep. of Agric., Australia.

Perry MW, Siddique KHM and Wallace JF (1987). Predicting phenological development for Australian wheats. Australian Journal of Agricultural Research 38, 809-819.

Sharma DL, D’Antuono MF, Anderson WK, Shackley BJ, Zaicou-Kunesch CM and Amjad M (2008). Variability of optimum sowing time for wheat yield in Western Australia. Australian Journal of Agricultural Research 59, 958-970.

Single WV (1961). Studies on frost injury in wheat. 1. Laboratory freezing tests in relation to the behaviour of cultivars in the field.Australian Journal of Agricultural Research 12,767–782.

Syme JR (1968). Ear emergence of Australian, Mexican and European wheats in relation to time of sowing and their response to vernalization and day length.Australian Journal of Experimental Agriculture and Animal Husbandry 8,578–581.

Tennant S and Tennant D (2000) Flowering Calculator Version 0.91. Agriculture Western Australia.

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