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Economic analysis of the role of canola in southern and central NSW farming systems.

J Fiona Scott 1, John P Brennan2 and Khaled Y Faour3

1 NSW Agriculture, RMB 944, Tamworth NSW 2340
2
NSW Agriculture, Wagga AI, PMB, Wagga Wagga NSW 2650
3
NSW Agriculture, Yanco AI, PMB, Yanco NSW 2703

ABSTRACT

Canola has been a significant addition to farming systems in southern and central NSW. The objective of this analysis is to ascertain the farm-level economic impact of the introduction of canola and triazine-tolerant canola into rotations. This paper contains an outline of the cropping system under consideration, a description of the PRISM whole-farm model, analysis of the effect of different yields and price levels on the inclusion of canola and triazine-tolerant canola in rotations and discussion of these results. It will provide useful information for farmers and advisers regarding the yield and price levels at which canola is a viable crop in the rotation system and the potential farm-level economic impacts of the use of triazine-tolerant canola in place of non-triazine tolerant varieties.

KEYWORDS: crop rotations, economics, whole-farm modelling

1. INTRODUCTION

Farming systems in southern NSW have been characterised by two main patterns of land use. Firstly, legume pastures grown in rotation with cereal crops such as wheat and secondly, periods of fallow (primarily for moisture conservation but also weed and disease control) followed by a cereal crop. In the drier areas of southern and central NSW, a common rotation is pasture-fallow-wheat (Poole, 1987).

Since the early 1970’s there has been an intensification of cereal cropping in response to improvement in relative profitability as well as the development of ‘conservation farming’ systems. The expansion of cereal cropping occurred due to opening up of new land and at the expense of pasture and fallow periods (Poole, 1987). Canola has become a commonly grown rotation crop with cereals and pastures. It has the advantages of reducing cereal root diseases, improving soil structure (due to a different root structure to cereals), preventing build up of herbicide resistant weeds and diversifying income.

In this paper we assess the place of canola in the rotation system in the Wagga region of southern NSW in terms of the effects of price changes and relative yield to other crops on the inclusion of canola in the rotation. In addition, we address the use of triazine-resistant canola and it’s effect on rotation choice.

2. THE PRISM MODEL

PRISM is a whole-farm computer model developed to analyse the farming systems of the south-eastern wheat belt of Australia. It was composed in a joint NSW Agriculture and Agriculture Victoria project funded by the Grains Research and Development Corporation. The principal objective of the project was to adapt the Western Australian MIDAS model for use in the wheatbelt of southern Australia. MIDAS (Model of an Integrated Dryland Agricultural System) is a whole-farm linear programming (LP) framework that represents biological and economic aspects of a representative mixed farm (Faour et al., 1997).

Marked differences between the wheatbelt of south-eastern Australia and that of Western Australia required substantial changes from the MIDAS parent model, so the new model was renamed PRISM (Profitable Resource Integration Southern MIDAS). The PRISM model is a Microsoft Excel for Windows workbook of several spreadsheets which uses the LINDO LP solver, What’s Best! to solve the model using a combination of integer and linear programming (Faour et al., 1997).

PRISM is an optimising annual steady state model which allocates available farm resources to maximise farm profit for a representative mixed farm (Faour et al., 1997). There are different versions of PRISM for different regions in south-eastern Australia, including South Australia (Eyre Peninsula), Victoria (Bendigo, Wimmera and Mallee) and southern NSW (Wagga Wagga and Condobolin). The version for the Wagga region is used in this analysis.

Crop yields are determined from growing season rainfall, growing season losses, transpiration, and various weed and disease penalties which vary according to preceding crop history. Monthly live-weight values of livestock are inputs into the model, which determine the animals’ energy requirements. Monthly energy supply by pastures are also inputs into the model. Energy may either be used by the livestock or transferred forward one month (with accompanying quantity and quality penalties).

Outputs from the model include operating cash surplus, optimal area of crop and pasture, the area of each crop grown, the amount of seed to be either purchased or retained, sheep enterprise type (selected from first cross ewes, second cross ewes, merino ewes and merino wethers) and the annual amount of fertiliser required.

3. ANALYSING THE ROLE OF CANOLA

3.1 The representative farm

The representative farm used in this analysis is a 1,000 hectare farm operating an integrated crop and livestock system. Farm revenue is derived from grain, wool and sheep sales as well as interest earned on positive cash flow. Grain may either be sold or fed to livestock as a ration. The model analyses only one soil type (red earth) and does not include cattle. Continuous cropping without a pasture phase was not included as an option as it is not standard district practice (Faour et al., 1997).

3.2 PRISM model settings

PRISM-Wagga was run for the representative farm with various yield and price combinations for standard and triazine tolerant (TT) canola. For standard canola, yield was varied across a range of outcomes, from 1.4 to 2.8 t/ha in 0.2 tonne increments. For TT canola, a 20% yield penalty was assumed, so yields were varied from 1.12 to 2.24 t/ha. For each yield level, a price sensitivity analysis was conducted where the farm gate price was altered from $240 to $450 per tonne in $10 increments. For each combination of yield and price, the PRISM model identified the rotation which maximised the operating cash surplus of the farm.

All parameters for other crops were not altered since the effects of relative yield of and price differences for canola were being tested. On-farm price levels for the various crops were wheat $140/t, lupins $290/t and oats $100/t. Yield levels for other crops varied according to the rotation (the model takes soil fertility, disease and weed effects into account) but were in the order of wheat 2.8 t/ha, barley 2.0 t/ha and oats 3.1 t/ha.

Canola yield was lower where canola was cropped after wheat compared to after pasture due to weed and soil fertility penalties. The model allowed for yield benefits to wheat crops following canola. It was assumed that no fertiliser nitrogen was added to grain crops so there was some yield reduction from the potential in canola.

4. RESULTS

4.1 Variation in yields and prices

When canola was not included in the available set of crop options, the rotation selected was 600 ha of crop and 400 ha of pasture. The model reports the selected rotation(s) in acronym form where P represents sub-clover pasture, W for wheat, L for lupins, Ca for canola and O for oats. The rotations selected were PPWLW (942 ha) and PPOLW (58 ha) with 200 ha of lupins, 388 ha of wheat, 12ha of oats and 2,600 second cross ewes. The operating cash surplus was $164 466. Canola was not selected as part of the rotation until the canola yield and/or on-farm price was high enough to increase the operating cash surplus above this level.

When canola was included in the crop options, the rotations selected were PPCaW (4 year rotation, canola 25% of farm area) and PPPCaWLW (7 year rotation, canola 13% of farm area). Figure 1 summarises the results in terms of percentage of farm area sown to canola at different yield and price levels. The maximum percentage of farm area allowed to be sown to canola was 25%, meaning that canola is only grown one year in four at the most. This was to minimise weed and disease problems.

Low yielding (1.4 t/ha) canola was not included in the optimal rotation until the price became relatively high ($410/t). Conversely when canola yields were very high (2.8 t/ha) it was always selected as part of the rotation.

4.2 Herbicide resistant canola

Currently, the only herbicide resistant canola released in Australia is triazine tolerant (TT) canola. Triazine herbicides are residual herbicides, mostly used for the control of mustard, radish and turnip weeds. Previously control of these weeds in canola was difficult because canola belongs to the same botanical family (Brassicaceae) and thus was susceptible to the same herbicides. Current TT canola varieties are Pinnacle, Karoo, Drum, Clancy, Hylite 200TT and Surpass 600TT (Colton et al., 1999). The triazine herbicides that may be used on these varieties are atrazine and simazine (Mullen and Dellow, 1998).

Currently, the permit for using triazine herbicides on TT canola specifies that only a single atrazine or simazine application or a single application combining atrazine and simazine is permitted. The maximum total amount allowed to be applied to the crop in the growing season is 4 litres per hectare of either chemical or a combination of both chemicals (Mullen and Dellow, 1998).

The non-TT variety Oscar has been used as a benchmark by the industry for comparing average yields with the TT varieties. Trials have shown that the TT variety Pinnacle returns 80-85% the yield of Oscar. Pinnacle is usually recommended over the other TT varieties because Drum and Karoo have poorer blackleg resistance, and Clancy has substantially lower average yield. Pinnacle also has a marginally better average oil percentage than the other three TT varieties (Colton et al., 1999). There may be some price penalties for oil percentages below an acceptable level.

For the purposes of this analysis, the standard canola input costs in the PRISM-Wagga model were altered to suit the Pinnacle variety, with the ‘standard’ variety being Oscar. This included altering the seed cost, herbicide treatments (see Table 1) and average yield. It was assumed that a 20% yield penalty was incurred compared to the standard canola variety.

Table 1: Differences between standard canola and TT canola in the PRISM model

 

Standard canola (Oscar)

TT canola (Pinnacle)

 

Input rate/ha

Cost $/ha

Input rate/ha

Cost $/ha

Herbicides

Fusilade 0.25 L, Lontrel 0.3 L, trifluralin 2.0 L

$63.30

atrazine 2L, simazine 2L

$23.50

Seed price

$3.10/kg @ 4 kg/ha

$12.40

$3.32/kg @ 4 kg/ha

$13.28

 

Total

$75.70

 

$ 36.78

Difference in costs (TT compared to standard)

-$38.92

The herbicide costs for Pinnacle were less than for Oscar, while seed costs for Pinnacle were slightly higher. All other costs were assumed to remain the same. As illustrated in Table 1, there was a net reduction in input costs (of $38.92) for Pinnacle. However, the value of the 20% yield penalty varied from $67.20/ha (for 1.12 t/ha @ $240/t) to $252/ha (for 2.24 t/ha @ $450/t), which in all cases was greater that the reduction in costs, resulting in a lower relative gross margin for Pinnacle.

If the achievable yields of Pinnacle were the same as for Oscar there would be a net improvement in gross margin from Pinnacle, due it’s relatively lower input costs. If Pinnacle had the same yield potential relative to Oscar, it would be included in the rotation at lower on-farm prices than Oscar. For example, at 1.6 t/ha, Pinnacle is first incorporated in the rotation at an on-farm price of $340/t (Figure 2), while at the same yield Oscar is not included until the price reaches approximately $370/t.

5. DISCUSSION OF RESULTS

The analysis of canola in the rotations of a representative farm in the Wagga region of southern NSW revealed that provided canola yield and/or on-farm canola price is adequate, it has a significant place in the rotation. This situation appears the have been the case since the mid-1980’s, with canola increasing notably in the Murrumbidgee region from 1,773 hectares in 1983 to 72,597 hectares in 1996, according to Australian Bureau of Statistics data. However, at lower prices or in lower yielding areas canola has a more limited role in the rotation system.

Compared to the results for standard canola, TT canola requires higher yields and/or prices to be included in the rotation. The assumed yield penalty of 20% for TT canola outweighed it’s lower herbicide costs. However, currently standard canola and TT canola are not in competition for the same crop area, since TT canola is usually grown only when there is a need to control the Brassicacae family weeds and it is impractical to grow standard canola due to the weed problem. TT canola provides the option to grow canola where the farmer would not have otherwise had the option. In the analysed example, the farmer who could only grow TT canola due to a brassica weed problem would wait for higher prices (of the order of $30-$40/t) before growing it than a farmer who could grow ‘standard’ canola.

The implications of these results for canola breeding programs and the industry are that if the comparably lower yields of TT canola can be improved to equate that of the ‘standard’ varieties, TT canola would replace standard canola, due to the formers lower input costs.

Acknowledgments

The assistance of Latarnie McDonald and Greg Condon (both of NSW Agriculture) on agronomic matters is gratefully acknowledged. The views expressed in this paper are those of the authors and do not necessarily represent those of NSW Agriculture.

References

1. Colton, R., Wratten, N., Mailer, R and Parker, P. (1999) Canola variety and management guide 1999. NSW Agriculture Agnote DPI 229, NSW Agriculture.

2. Faour KY, Brennan JP, Scott BJ and Armstrong EL (1998) Analysing the Rate of Adoption of Pulse Crops in Southern NSW, Contributed paper to the 42nd Annual Conference of the Australian Agricultural and Resource Economics Society Inc., Armidale NSW.

3. Faour KY, Butler, GJ, Robinson JB, Wall LM, Brennan JP, and Scott BJ (1997) PRISM-Wagga Manual, Version 1.0 NSW Agriculture, Wagga Wagga.

4. Mullen, C.L. and Dellow, J.J. (1998) Weed Control in Winter Crops 1998, NSW Agriculture, Agdex 100/682

5. Poole, M. (1987) “Tillage practices for crop production in winter rainfall areas.” in Tillage, PS Cornish and JE Pratley (eds), Inkata Press.

6. Schilizzi, SGM and Kingwell, RS. (1998) The effect of weather-year and price uncertainty on the profitability of legume crops: Preliminary investigations. Contributed paper to the 42nd Annual Conference of the Australian Agricultural and Resource Economics Society Inc., Armidale NSW.

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