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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 | 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
Table 1.3 illustrates descriptive statistics for yield trends over the period from 2005-2022 (2022 assumes trend yields). 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.
Wheat: Winter area |
Wheat: Summer area |
Wheat: Irrigation |
Barley: Winter area |
Barley: Summer area |
Canola | |
---|---|---|---|---|---|---|
Mean (2005-2022) | 2.67 | 2.88 | 6.25 | 2.89 | 6.40 | 1.39 |
3-year average (2020-2022) | 3.31 | 3.86 | 6.71 | 3.66 | 7.05 | 2.01 |
5-year average (2018-2022) | 2.95 | 3.60 | 6.70 | 3.31 | 6.94 | 1.74 |
Minimum (2005-2022) | 1.80 | 1.53 | 5.27 | 1.95 | 5.19 | 0.90 |
Median (2005-2022) | 2.59 | 2.71 | 6.31 | 3.04 | 6.45 | 1.28 |
Maximum (2005-2022) | 3.60 | 4.40 | 7.15 | 3.95 | 7.12 | 2.25 |
Source: BFAP, 2022
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.
Wheat | Barley | Canola | Oats | |
---|---|---|---|---|
SAFEX / Derived Price: 2022 | 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 | BS calculated at 2% premium | X | Back payment calculated at 10% of derived price | – |
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 2022 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.
Source: BFAP, 2022
Global agricultural commodity prices have increased rapidly since the final quarter of 2020 with renewed hikes following the Russian invasion into Ukraine. A number of underpinning factors, beyond the Russia-Ukraine conflicts, have driven agricultural markets in recent months. Structural shifts on the demand side provided support for international markets. These include China's recovering pork sector, along with expanded poultry production which is driving high import volumes of maize and soybeans and a renewed drive towards renewable energy which is increasing the demand for biodiesel and vegetable oils used to manufacture it. Supply pressure is caused by aging oil palm plantations in Malaysia which results in low yields and limited reinvestment which was exacerbated by labour shortages and heavy rainfall in Malaysia, which resulted in sub-optimal harvesting and further reducing palm oil stock levels. The war in Ukraine has exacerbated many of the vegetable oil and oilseed supply constraints. Weather concerns in key production regions, some as a result of the current La Nina system, is driving further uncertainty as to the ability to recover low stock levels in 2022. Generally, 2022 is set to be the third consecutive year of strong growth in the agricultural sector, supported by high global prices and strong output volumes.
Key input cost trends
Soaring fertiliser and other agricultural inputs costs around the globe has been a concern for months and there are no signs of abating yet. Various agricultural input product prices reached unprecedented heights in 2022, underpinned by a multitude of factors that combined to create a perfect storm. Figure 1.4 shows a calendar year-on-year percentage change for key agricultural inputs over the period from 2020 to 2022. The weighted cost for fertiliser (combination between nitrogen, phosphorus and potassium) has increased by 51% in 2021 and is projected to increase by 62% in 2022. Urea, LAN28, MAP and potassium are projected to increase by 55%, 55%. 61% and 108% respectively in 2022 (total for 2021 and 2022 = 110%, 101%, 115% and 147%). Herbicides projected to increase by 26% in 2022 (37% in 2021). Administered cost such as wages and electricity projected to increase on average by 10% in 2022.
The hikes in the cost of agricultural inputs were driven by a combination of supply and demand factors. For fertilisers in particular, a perfect storm was created underpinned by tight supplies, rising raw material cost (oil and gas) increasing demand (high commodity prices) and global logistics constraints and freight rates. Certain events in 2021 has exacerbated this situation such as hurricane Ida's impact on supply and transport in Louisiana and nutrient export restrictions from China and Russia. Rising coal prices and power rationing in China forced producers to cut production and exports. The Russia-Ukraine conflict contributed significantly towards rising prices where Russia is the 2nd largest producer of ammonia, urea and potash and the 5th largest producer of processed phosphates (Grain SA, 2022). Belarus is also a major exporter of fertilisers. The cost of chemicals was impacted by raw material shortages, COVID related slowdown in production, Chinese regulation, increase demand / stocks and shipping costs and US manufacturing downtime due to mechanical failure. The global logistical constraints further fuelled rising costs and delays.
Source: Grain SA and BFAP, updated September 2022
The year-on-year inflation will vary significantly depending on when inputs were purchased. Figure 1.5 shows the period inflation depending on when inputs were purchased. The graphs show the percentage change for the cost of specific inputs for various periods in 2021 and 2022: Calendar year: January-December 2020 vs. 2021 vs. 2022; September 2020 (2021)-August 2021 (2022) is indicative for the summer rainfall production region; Average from August-December 2020 (2021) vs. the same periods in 2021 and 2022; Average from January-May 2020 (2021) vs. the same periods in 2021 and 2022; indicative of the typical winter crop season.
Source: Grain SA and BFAP, updated September 2022
Great uncertainty remain regarding the full impact of the Russia-Ukraine conflict in coming months underpinned by the uncertainty on how long the conflicts will last. Recent market dynamics suggested that demand for certain fertiliser types (e.g. urea) came under pressure due to continuous high prices, resulting in lower international prices. Although the cost for certain international fertiliser products indicated some declines in recent weeks, the rapid depreciation in the Rand-US$ has offset the lower prices.