Converting harvests into commodities and products that last longer

LACK of capacity to convert harvests into commodities and products that last longer has negatively impacted African food systems for more than five decades. Huge harvests are meaningless if much of the food is not consumed or turned into better livelihoods and employment creation.

If there was serious investment in food preservation, the whole African continent would not be spending US$100 billion importing food annually and post-harvest losses would not be more than the current US$4 billion.

While rainfall is often associated with good harvests, what is becoming clear is that in a changing climate, too much rainfall can have the same negative effect as too little rainfall.

For instance, there are some African communities where once too much rainfall is received, farmers have to forget about growing maize and other crops.

The power of data and participatory value chain mapping

Involving communities in mapping their food systems can be a fundamental starting point in converting harvests into lasting products.

Such a process can also enable communities to tell stories about their local food baskets in ways that reveal opportunities for value addition and preservation.

Through that process, communities can increase their interest in understanding their contribution to the national food basket including surplus going to diverse markets. That level of understanding which informs the whole community’s investment guide cannot be done at individual farmer level.

Data collection and dialogue sessions with communities through participatory value chain mapping can rebuild hope among farming communities back to the time when farmers where able to send their children to school through growing groundnuts, small grains and other commodities.

The communities will also begin to appreciate the value of building enabling market structures and systems. They become conscious of the value of tracking the movement of food from rural areas to urban populations as well as different kinds of losses along the way.

That is also how losses that happen at African mass markets can be discussed and captured as part of managing losses including the role of mass markets in supporting rural livelihoods and rural industrialisation.

In addition to distributing the whole food basket, these markets also support cross-border traders whose contribution to African economies remains unrecognised due to absence of data.

How do African countries measure economic performance without data?

The absence of data on the sources of more than 75% of local food systems renders conventional ways of measuring economic performance unreliable in most African countries. For example, what is the impact of tomato gluts or shortages to communities that heavily depend on tomatoes as sources of income?

For communities that depend on small grains as economic drivers, what is the impact of government imposing prices on grains? What is the implication of some farmers refusing to sell their produce to national buyers like the Grain Marketing Board in preference for mass markets?

Unlike mass markets that try to come up with fair pricing systems based on demand and supply, prices announced by government are often not informed by demand and supply.

When pricing policies are not farmer-friendly, farmers would rather spend time and money going to distant urban mass markets, avoiding a government-controlled grain depot that is located a few kilometres from their home area.

Although blessed with broad food baskets comprising more than 40 diverse commodities, many African countries do not have much data on the majority of food systems and supply chains.

Without data, it is difficult to come up with informed policy interventions.

They end up relying on periodic vulnerability assessments that are often too narrow and skewed towards food aid, not long-term interventions.

By now, all African countries could have invested in analysing the value of small grains regions, fruit regions, livestock regions and other regions dominated by specific agricultural economic drivers.

Without fluid data collection systems along supply chains, it is difficult for policymakers to understand the extent to which agriculture contributes to economic development.

Such understanding can change the role of extension services towards building fluid agricultural data collection systems located at ward level from where production statistics are processed and shared with different agricultural users including diverse markets.