Selected crop value chains in Kenya: current conditions and outlook to 2035

Reported crop production in each of Kenya’s 47 counties. Counties without a reported value stay grey; they are not treated as zero.

The trade tables include many smaller oilseed and nut products that drop out when the analysis focuses on palm, sunflower and soybean. Each is shown here with physical volume on the left scale and trade value on the right.

• 9 of 10

  crops have Base domestic capacity at or above modelled 2035 demand

  For these crops the defined market, not land or yield, becomes the binding constraint under the assumed area and yield path. It does not make the production target certain.

• 1.6%

  of Base 2035 palm-oil demand is covered domestically

  Base demand reaches about 1.04M t CPO-equivalent while domestic capacity reaches 16.5k t.

• +71%

  Base macadamia demand growth, 2024–2035

  The fastest-growing Base demand path in the portfolio, driven by the 5% export-demand scenario.

• 6

  crops carry an explicit maturity lag

  Perennial supply does not appear immediately after planting; each crop’s lag is listed under its projection below.

1. Forecast demand

   Each crop uses a demand method suited to its market: import substitution, export growth, industrial capacity, or a domestic or export proxy.

2. Build domestic capacity

   Area moves toward scenario targets, new perennial area waits until bearing age, and yield moves toward a potential yield.

3. Convert to the market unit

   Seed is converted to oil, fresh fruit bunches to crude palm oil and seed cotton to lint, so supply and demand are compared in the same unit.

4. Compare demand with local supply

   Local supply gap = max(demand − domestic supply capacity, 0). Imports are not counted as supply in this comparison.

Observed years sit on white; the shaded zone is modelled, starting at the 2025 model year. The teal line is the Base path and the band spans the Low and High scenarios.

The Low, Base and High demand paths for each crop, and the domestic supply-capacity assumptions used to judge whether those markets could be served from Kenyan production.

Change the demand and supply assumptions for a crop and compare your 2035 result with the published Base scenario, which stays fixed on the chart.

• Scenario, not certainty. Low, Base and High are conditional sensitivity paths, not P10/P50/P90 probability bands. The methodology requires backcasting and at least 10,000 Monte Carlo draws before probabilistic fan charts are reported.
• Edible-oil supply follows the PE physical identity. Area, yield, post-harvest loss, oil content, extraction efficiency and refining loss are separate inputs in the calculator; full county-level Nerlovian estimation and crusher-capacity constraints need the external estimation dataset.
• Demand is crop-specific. Sunflower and canola use direct oil imports as a narrow demand floor; cotton uses spinning capacity; coffee and tea use export-demand growth. Where imports help define the demand market, they are not counted as domestic supply when the local supply gap is calculated.
• Land envelopes differ in evidence quality. Some are official cultivation envelopes; others are analyst or programme planning assumptions and should not be read as national suitability maps.
• Perennial timing matters. New avocado, macadamia, cashew and palm area does not become productive straight away.

The full 2025–2035 Low, Base and High series with the input register behind the charts, and every observed series used in Part I.