What a Baseline Survey of 3,650 Farmers Tells Us About Nigeria’s Agricultural Problem

By Munachiso Elekwa and Juliet Ihuoma

Nigeria’s agricultural challenge is mostly framed as a production problem. Yields are too low. Inputs are too expensive. Farmers lack access to improved seeds, mechanisation, and irrigation. All of this is true, and none of it is new. But the SAPZ baseline assessment we conducted across five states, Cross River, Imo, Kaduna, Ogun, and Oyo, presents a finding that deserves far more attention: the deeper constraint in Nigeria’s agricultural economy is not what happens on the farm, but what happens after it.

The SAPZ, or Special Agro-Industrial Processing Zones, is an African Development Bank-funded programme designed to transform Nigeria’s rural economy through agro-industrial hubs that integrate production, processing, storage, and distribution. Before implementation began, our team conducted a baseline assessment across the five participating states to establish pre-intervention benchmarks. We surveyed 3,650 respondents, including farmers, enterprises, and farmer organisations, across treatment and comparison locations. What emerged was a rural economy overwhelmingly made up of primary producers, with very few of the downstream actors that give agricultural production commercial value.

Across the five states, 78% of respondents were classified as farmers only. The remaining 22% included agro-processors, traders, service providers, and aggregators, the range of value-chain actors that, in a functioning agro-industrial system, connect farms to markets. Agro-processors accounted for 10.6% of the total sample, followed by traders at 6.9% and service providers at 2.8%. Aggregators, who collect and consolidate produce from multiple farmers and channel it into supply chains, were almost entirely absent. Across 3,650 respondents and five states, only 14 people identified as aggregators. That represents just 0.4% of the sample.

This is not a minor detail. Aggregators are often the first link between a farmer and an organised market. Without them, farmers sell at the farm gate, typically to whoever arrives at harvest and at whatever price is offered. There is little consolidation of supply, limited bargaining power, inconsistent quality, and no reliable pathway through which produce can move into processing or formal trade. When this link is missing at scale, as the data suggest it is across most of the SAPZ communities surveyed, the effects are felt throughout the value chain.

The picture varied across states. Ogun stood out as the most economically diversified, with nearly half of its respondents engaged in non-farmer value-chain roles. It also recorded the highest share of households earning more than two million naira annually at 22% and was the only state where processing and enterprise income appeared with any regularity. Imo, Oyo, and Cross River occupied a middle ground, with a visible presence of agro-processors and traders but still a strong concentration of primary producers. Kaduna and Cross River were the most production-dominated, with 88.6% and 85.3% of respondents classified as farmers only and very limited representation from downstream actor categories.

What Ogun represents in these data is worth examining more closely. The distinction is not simply that the state has more traders and processors than the others. It is that this diversification appears to be associated with better economic outcomes. The income data reflect this clearly. In Imo, nearly half of respondents reported total household income below ₦250,000 in the previous year, equivalent to less than ₦700 per day for an entire household. In Kaduna, almost one-third of respondents fell into the same category. Ogun’s income distribution, by contrast, was spread more evenly across higher income bands, with a meaningful share of households reporting earnings from processing and trading activities rather than crop sales alone. The states with more developed value-chain ecosystems are also the states where household incomes are higher.

This relationship matters for how we think about SAPZ’s objectives. The programme aims to increase agricultural productivity by more than 60%, reduce post-harvest losses, and create over 500,000 jobs (AfDB, 2025). Nigeria spent $4.7 billion on food imports in 2025, a figure that reflects not a lack of agricultural production capacity but a shortage of the infrastructure and market systems needed to convert that capacity into processed, storable, and tradeable food products (SAPZ Baseline Assessment, 2025). The baseline findings suggest that achieving these objectives will require more than building processing facilities. It will require developing the human and commercial systems that make those facilities viable.

The training data reinforce this point. Across all five states, 78.4% of respondents had received no agribusiness or value-chain training of any kind. Among those who had received training, the overwhelming focus was on crop production, ranging from 65% of trained respondents in Imo to 89.2% in Kaduna. Training in business and entrepreneurship was far less common, reaching only 3.9% of trained respondents in Ogun and peaking at 26.5% in Kaduna. Training in processing and value addition was reported by roughly one-third of trained respondents in Kaduna and Ogun but by far fewer respondents in Cross River and Imo. The current capacity-building landscape has largely prepared people to produce crops, not to build enterprises around them.

None of this diminishes the importance of production-side interventions. The baseline documented substantial farm-level constraints, including heavy reliance on rain-fed agriculture, limited access to inputs, and small farm sizes across all states. These challenges are real and must be addressed. But the evidence consistently points to a structural gap beyond the farm gate: the thin or absent layer of processors, aggregators, traders, and service providers through which agricultural output acquires commercial value. The SAPZ programme was designed to strengthen that layer. The baseline provides a clear account of how much of that work remains to be done, and where.