Agro-Input Dealers Train in Spotting Fake Inputs

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The Monitor (Kampala)

Joseph Miti

4 May 2011


As counterfeited agro-inputs float on the Ugandan market, the Uganda National Agro Dealers Association has resolved to train all certified agro dealers countrywide to detect fake inputs.

Mr Wilfred Thembo, Unada Executive Secretary, said the training will also equip dealers with skills of proper marketing and handling of inputs to avoid loses.

“Dealers need skills to detect fake inputs, market new products, handle and maintain their clients especially in this period when prices are skyrocketing,” Mr Thembo said.

It is estimated that 40 per cent of the agricultural inputs on the market are fake. Seeds, fertilisers and agro-chemicals are the most faked products.

Thembo said the trend of counterfeiting seeds and other inputs is affecting the agriculture sector that employs about 80 per cent of Uganda’s population, as farmers suffer heavy financial losses on top of experiencing food shortages as a result of low production.

Mr Thembo attributes the scourge to failure by seed companies to produce or supply enough quality seeds to satisfy the market demand. “Taking advantage of the shortage, some unscrupulous dealers have flooded the market with fake or substandard seeds, for the unsuspecting farmers to buy,” he said.

Unada, funded by Comesa under the Comesa Agro Inputs programme (Comrap) that aim at increasing food production in the region, started off with 90 agro input dealers from Acholi and Lango sub regions, who received training in marketing and customer care last week.

The trainees were taught to identify fake inputs at purchasing point before passing them on to the final users -the farmer.

They were also given tips on accessing loans from commercial banks.

Mwesigwa said after training, the association will make abrupt visits to agro dealers in six months to find out whether the trainees are practicing what they were taught before they are accredited and issued with new licenses.

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Agro-Input Dealers Train in Spotting Fake Inputs