OPDT   OIL & PROTEIN SEEDS DEVELOPMENT TRUST
OAC   OILSEEDS ADVISORY COMMITTEE

OPDT
OIL & PROTEIN SEEDS DEVELOPMENT TRUST

OAC
OILSEEDS ADVISORY COMMITTEE


Income and Cost Budgets for Winter Crops
2020 season

Area coverage

Table 1 and Table 2 provides an overview of the area of coverage for dryland and irrigated winter crops in South Africa's key agro-ecological producing regions. The coordinators of this initiative are sincerely grateful for the interaction and assistance with data, knowledge and other inputs from each organisation, agribusiness and farmers.

Table 1.1: Area coverage – Dryland
Area Dryland crops Source and Collaborators
Southern Cape
Caledon Wheat, barley, canola, oats and lupins Overberg Agri, GSA and BFAP
Bredasdorp Wheat, barley, canola, oats and lupins Overberg Agri, GSA and BFAP
Eastern Ruêns (higher potential) Wheat, barley, canola, oats and lupins SSK, GSA and BFAP
Eastern Ruêns (low to normal potential) Wheat, barley, canola, oats and lupins SSK, GSA and BFAP
Western Cape
Southern Swartland Wheat and canola Kaap Agri, GSA and BFAP
Moorreesburg, Malmesbury and Porterville Wheat, canola and oats Kaap Agri, GSA and BFAP
Darling-vlakte – Hopefield (Sandveld) Wheat, canola and lupins Kaap Agri, GSA and BFAP
Rooi Karoo Wheat and canola Kaap Agri, GSA and BFAP
Free State
Eastern Free State Wheat GSA / VKB / BFAP / Individual farmers
Central Free State Wheat GSA / VKB / BFAP / Individual farmers
Table 1.2: Area coverage – Irrigation
Area Irrigated crops Source and Collaborators
Northern Cape
Northern Cape Wheat, barley and canola GWK, GSA and BFAP
Free State
Eastern Free State Wheat GSA / VKB / BFAP / Individual Farmers
Limpopo
Britz / Northam / Koedoeskop Wheat and barley GSA, Obaro and BFAP

Yield assumptions

Figure 1 and Figure 2 reports the yield assumptions for dryland and irrigated crops. These assumptions represent target yields which were formulated in round table discussions. These levels are based on crop potential in the respective regions, historic trends and expert opinions. It is important to note that intra-regional variations will occur and it is recommended that producers adjust their target yields based on their location and potential. Table 1.3 illustrates descriptive statistics for yield trends and projections over the period from 2005-2020.

Figure 1.1: Dryland winter crop yield assumptions
Figure 1.1: Dryland winter crop yield assumptions
Figure 1.2: Irrigated winter crops yield assumptions
Figure 1.2: Irrigated winter crops yield assumptions
Table 1.3: Industry yield trends: 2005-2021
Wheat:
Winter area
Wheat:
Summer area
Wheat:
Irrigation
Barley:
Winter area
Barley:
Summer area
Canola
Mean: 2005-2021 2.60 2.78 6.22 2.78 6.32 1.32
3-year historic average: 2017-2019 2.18 3.50 6.82 2.90 6.66 1.26
5-year historic average: 2015-2019 2.44 3.12 6.68 3.11 6.33 1.32
Minimum: 2015-2019 1.80 1.53 5.27 1.95 5.19 0.90
Median: 2015-2019 2.50 2.65 6.24 2.80 6.45 1.25
Maximum: 2015-2019 3.40 4.20 7.15 3.65 7.12 1.85

Source: BFAP, 2020

Crop price assumptions

Annually, the Bureau for Food and Agricultural Policy (BFAP) presents a baseline outlook for agricultural production, consumption, prices and trade in South Africa over a 10-year horizon. The outlook is generated within the BFAP system of models and is based on a coherent set of assumptions about a range of economic, technological, environmental, political, institutional, and social factors. Of the range of critical assumptions underpinning the baseline projections, one of the most important is that stable weather conditions will prevail in Southern Africa and around the world; therefore, yields grow constantly over the baseline as technology improves. Consequently, it does not represent a forecast, but rather a single plausible future outcome, based on fundamental factors underpinning markets. It presents a future equilibrium and a benchmark against which further analysis can be measured and understood.

Assumptions related to the future macro-economic environment are based on a combination of projections developed by the International Monetary Fund (IMF), the World Bank and the Bureau for Economic Research (BER) at Stellenbosch University. Baseline projections for world commodity markets were generated by FAPRI at the University of Missouri, as well as the Food and Agriculture Association (FAO) of the United Nations. Once these critical assumptions are captured in the BFAP system of models, the Outlook for all commodities is simulated within a closed system of equations. This captures the interlinkages between sectors and, for example, any shocks in the grain sector are transmitted to the livestock sector and vice versa. For each commodity, important components of supply and demand are identified, after which an equilibrium is established through balance sheet principles by equating total demand to total supply.

Figure 3 illustrates the commodity price assumptions for wheat, barley and canola that were used as a reference point in generating the commodity price assumptions for the 2020 production season. These levels take into consideration global market conditions, the macro-economic landscape and domestic balance sheet principles. Table 1.4 illustrates the standard operating procedure in calculating a reference point at farm gate. The sensitivity analysis in the respective regional commodity enterprise budgets makes provision for variation in price and yield and indicates the gross margin under each price and yield combination.

Table 1.4: Deductions from SAFEX price to derive a farm gate price per region
Wheat Barley Canola
SAFEX / Derived Price: 2020 X X X
– transport differential X X X
(for selective regions)
– grade differential, premiums (BS, B1, B2, B3 and COW) and price factors Based on historic averages Regional price factors
– silo, handling and administration costs X X X
– statutory levies X X X
+ price premiums Nitrogen sliding scale premium (50% of production qualifies for this premium) Back payment calculated at 10% of derived price
Figure 1.3: BFAP average annual commodity price projections: 2016-2019
Source: BFAP, 2020
Figure 1.3: BFAP average annual commodity price projections: 2017-2021

Key input cost trends

Figure 1.4 illustrates the domestic cost trends for fuel, urea, MAP and potassium chloride over the period from January 2017 to April 2020. Since October 2019, the major fertilisers have reported a decreasing trend until roughly February 2020. The rapid depreciation in the Rand/US dollar exchange rate resulted in the cost of fertilisers to increase in March and April 2020. Persistent uncertainty in the macro-economic environment could entail continuous volatility in the Rand/USD exchange rate, which could impact the cost of imported inputs such as fuel, fertilisers, chemicals and machinery / implements. The agricultural input cost assumptions in this report have been adjusted according to in-depth analytical analysis on existing prices, movements in the Rand/US dollar exchange rate, the oil price and forward-looking scenarios.

Figure 1.4: Fertiliser and fuel cost trends: January 2017 to April 2020
Source: Grain SA and BFAP, April 2020
Figure 1.4: Fertiliser and fuel cost trends: January 2017 to February 2019 and 2019 projections

Methodology, approach and definitions

  • A standard operating procedure was used across all crops and regions for generating the cost and income budgets for the 2020 production season.
  • Deterministic or targeted yields were based on industry discussions which refers to a yield that should be obtained given a normal production season with normal weather in the respective agro-ecological production regions.
  • The farm gate price for each crop was calculated by deducting transport differential, grade differential, handling fees, commission and levies (statutory) from the simulated SAFEX or derived price.
  • The grade differential for wheat was calculated according to historic averages for protein levels at national level. The adjusted grading criteria was incorporated in the commodity enterprise budgets for the 2020 production season which assumes a premium of 2% will be received for protein levels exceeding 12.5%, a zero differential of wheat of a protein level between 11.5-12.4%, a 1% grade differential deduction of protein levels between 10.5-11.4% and a 4% deduction of protein levels between 9.5-10.4%. For simplification purpose, Class Other Wheat (COW) was not accounted for in the enterprise budgets.
  • The gross production value is then calculated by multiplying the yield with the farm gate price.
  • The direct costs are calculated by multiplying the cost per unit by the estimated quantity of input use or application rate.
  • For the majority of the crops, it was assumed that own machinery was used, except for speciality operations that is coupled with economies of scale. In such cases, a contracting cost item was allocated. For the majority of crops, provision was made for fire and SASRIA insurance.
  • Fertiliser and lime application will vary significantly in regions and across crops, however, an attempt was made to follow a standardised approach across the regions. Micro-elements and foliar feed for selective crops are included in the total fertiliser cost.
  • Fuel consumption is based on the prevalence production system in each region.
  • For plant protection, herbicide, insecticide and fungicides are accounted for based on interaction with industry experts and producers. For instance, in certain regions provision was made for fungicide sprays, but for others where the practise is not common, fungicides were excluded from plant protection costs.
  • Repairs and maintenance costs are calculated based on the production system operations.
  • For irrigated crops, the cost of water and electricity was calculated according to typical irrigation application rates at their respective regional costs per millimetre. For instance, variations will occur in the cost for water in areas where predominantly boreholes are used compared to irrigation/water scheme areas.
  • The gross margin was calculated by subtracting the direct cost from the gross production value.
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