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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
2019 season

Area coverage

Table 1 and Table 2 indicates the area of coverage and include the dryland and irrigated crops. The source of data and collaborators are also presented. The collaborators 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
Swellendam / Heidelberg Wheat, barley, canola, oats and lupins SSK, GSA and BFAP
Riversdal / Albertina Wheat, barley, canola, oats and lupins SSK, GSA and BFAP
Western Cape
Southern Swartland Wheat and canola Kaap Agri, Overberg Agri, GSA and BFAP
Moorreesburg, Malmesbury and Porterville Wheat, canola and oats Kaap Agri, Overberg Agri, GSA and BFAP
Darling-vlakte – Hopefield (Sandveld) Wheat, canola and lupins Kaap Agri, Overberg Agri, GSA and BFAP
Rooi Karoo Wheat and canola Kaap Agri, Overberg 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
GWK area Wheat, barley and canola GWK / GSA / 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. The yield assumptions represents target yields which were determined in a round table discussion which are based on the 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 respective 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 and projections: 2005-2025
Wheat:
Winter area
Wheat:
Summer area
Wheat:
Irrigation
Barley:
Winter area
Barley:
Summer area
Canola
Mean 2.57 2.43 6.13 2.77 6.21 1.27
3-year average: 2015-2017 2.65 2.37 6.89 3.36 6.45 1.37
5-year average: 2013-2017 2.62 2.59 6.63 3.25 6.23 1.33
Minimum 1.80 1.53 5.27 1.95 5.19 0.90
Median 2.50 2.42 6.13 2.88 6.33 1.20
Maximum 3.40 3.53 7.15 3.65 7.12 1.85

Source: BFAP, 2019

Crop price assumptions

Annually, the Bureau for Food and Agricultural Policy (BFAP) presents an outlook of agricultural production, consumption, prices and trade in South Africa over a 10-year period. The information presented is based on assumptions about a range of economic, technological, environmental, political, institutional, and social factors. The outlook is generated by the BFAP system of models. A number of critical assumptions have to be made for baseline projections. One of the most important assumptions is that normal weather conditions will prevail in Southern Africa and around the world; therefore, yields grow constantly over the baseline as technology improves. Assumptions regarding the outlook of macroeconomic conditions 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. Once the critical assumptions are captured in the BFAP system of models, the Outlook for all commodities is simulated within a closed system of equations. This implies that, for example, any shocks in the grain sector are transmitted to the livestock sector and vice versa. Therefore, for each commodity, important components of supply and demand are identified, after which an equilibrium is established through balance sheet principles by equalling total demand to total supply.

Figure 3 illustrates the commodity price assumptions for wheat, barley and canola that were used as base price for the winter crop budgets for the 2019 production season. Table 1.4 illustrates the standard deduction from the base SAFEX price as presented in Figure 1.3. The sensitivity analysis in the respective crop 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: 2019 X X
(adjusted with price link)
X
– transport differential X X X
(for selective regions)
– grade differential (B1, B2, B3 and UT) Based on historic averages Standard B1
– silo, handling and administration costs X X
– statutory levies X X X
+ price premiums X Back payment calculated at 10% of derived price
Figure 1.3: BFAP average annual commodity price projections: 2016-2019
Source: BFAP, 2018
Figure 1.3: BFAP average annual commodity price projections: 2016-2019

Key input cost trends

Figure 1.4 illustrates the cost trends for fuel, urea, MAP and potassium chloride over the period from January 2017 to February 2019. The cost for nitrogen, phosphates and potassium have reported a decreasing trend since roughly November 2018. The same trend was observed for fuel, however, the projection for 2019 (average) remains higher opposed to the February 2019 price. The average cost of MAP in 2019 is also projected higher compared to February 2019 levels. 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.

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