User Information
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.
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 (high potential) | Wheat, barley, canola, oats and lupins | SSK, GSA and BFAP |
Eastern Ruêns (normal potential) | Wheat, barley, canola, oats and lupins | SSK, GSA and BFAP |
Eastern Ruêns (low potential) | 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 |
Area | Irrigated crops | Source and Collaborators |
---|---|---|
Northern Cape | ||
GWK Area | 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 1.1 and Figure 1.2 reports the yield assumptions for dryland and irrigated crops. The yield assumptions represent 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 2005-2021.
Wheat: Winter area |
Wheat: Summer area |
Wheat: Irrigation |
Barley: Winter area |
Barley: Summer area |
Canola | |
---|---|---|---|---|---|---|
Mean (2005-2021) | 2.60 | 2.86 | 6.21 | 2.83 | 6.37 | 1.34 |
3-year average (2019-2021) | 2.68 | 3.65 | 6.55 | 3.13 | 7.12 | 1.69 |
5-year average (2017-2021) | 2.53 | 3.80 | 6.75 | 3.16 | 6.85 | 1.51 |
Minimum (2005-2021) | 1.80 | 1.53 | 5.27 | 1.95 | 5.19 | 0.90 |
Median (2005-2021) | 2.50 | 2.65 | 6.25 | 2.97 | 6.45 | 1.27 |
Maximum (2005-2021) | 3.40 | 4.40 | 7.15 | 3.95 | 7.20 | 2.25 |
Source: BFAP, 2021
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 1.3 illustrates the commodity price assumptions for wheat, barley, canola and oats that were used as base price for the winter crop budgets for the 2021 production season. Table 1.4 illustrates the standard deduction from the base SAFEX or derived 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.
Wheat | Barley | Canola | Oats | |
---|---|---|---|---|
SAFEX / Derived Price: 2021 | X | X (adjusted with price link for Southern Cape and Northern producing regions) |
X | X |
– transport differential | X | X | X (for selective regions) |
Standard wheat transport differential + transport to processing facilities (estimate R200-R250 per ton) |
– grade differential (BS, B1, B2, B3 and COW) | Based on historic averages; updated with new grading system | – | – | – |
– silo, handling and administration costs | X | X | – | – |
– statutory levies | X | X | X | X |
+ price premiums | – | X | Back payment calculated at 10% of derived price | – |
Global agricultural commodity prices have increased rapidly since the final quarter of 2020. The price of oilseeds has reached levels last seen in 2012, due to low supply and high demand, and global stocks are expected to reach a 5-year low at the end of the season. Supply has been limited due to weather concerns and disruptions in palm oil production due to lack of foreign labour (in an effort to contain COVID-19). While China has been rebuilding its pig herd following African Swine Fever, driving up demand. Tight oilseed supplies are expected to ease as Southern hemisphere soybeans become available.
These global price dynamics have also spilled over into South African markets. South Africa is still a net importer of vegetable oil, hence prices tend to trade at import parity and consequently international prices are key to determining local levels. The same is true for wheat, where South Africa typically imports up to 50% of the domestic requirement.
Key input cost trends
Figure 1.4 illustrates the cost trends for fuel, urea, MAP and potassium chloride over the period from January 2019 to February 2021. Around the time of the hard lockdown in South Africa (February to May 2020) the fertiliser cost reported an increase, and decreased again from May to July 2020. After the July decrease, the cost of nitrogen and phosphates never returned back to their original pre-lockdown levels, and continued to report an increasing trend. The cost of potassium continued to decrease after May 2020. The opposite lockdown trend was observed for fuel, the price decreased during the lockdown period and increased again after May 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. If inflationary pressures in the US persist, this would likely force the US Reserve to increase interest rates leading to a stronger US dollar and consequently a weaker Rand.