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Cassava; A Tuber Whose Potential Is Not Yet Tapped

by Harvest Money Editor
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At 60 years of age, Augustine Akutu looks younger than his actual age. He is healthy and relatively well off, thanks to his farming activities, which earn him some good money every season.

A resident of Akumangor village, Asamuk sub-county, Amuria district, Akutu grew up in poor family background.

“I do not even remember attending any school, but surprisingly today, people call me the ‘Professor of cassava farming’,” he says. 

Akutu owns over 400 acres of cassava, which he has planted in rented plots of land across sub-counties in the district with the hope of planting up to 1,000 acres in the next few years.

“I locate a good piece of land and then I ask the owner to rent it to me,” he says. This is how his acreage has developed to the current 400 acres.

Akutu is a fairly large-scale cassava farmer. However, majority of cassava farmers are not large-scale. In fact, according to a survey carried out by the Economic Policy Research Centre (EPRC), the average acreage for medium-scale cassava farmers in Uganda is around 10 acres. But for the last few years, cassava has gradually grown from a simple food to an industrial crop.

President Yoweri Museveni has always reiterated the potential of cassava. He, for example, pointed out that cassava can be processed into high-grade starch that is used for processing medicines.

“We have got a young growing pharmaceutical sector, but we are importing starch that is used for processing medicines. We should get this from our cassava,” he said.

The President also pledged government support for a project in the northern part of the country that produces denatured ethanol stoves and that is intended, in the long-term, to establish cassava derived from ethanol as a sustainable alternative cooking fuel.

Museveni said if such projects obtained a firm footing, Uganda would be able to export fuel and starch made from cassava to other countries in the region.

Positively though, production of cassava has been growing gradually. In 2013, for example, the country produced 2.3 million tonnes of cassava, 2.4 million in 2015; however, by the end of 2019, Uganda produced at least 4.1 million tonnes of cassava per year. Most of this is consumed locally, mainly through steaming (cooking), roasting and dried cassava that is turned into flour. 

Less value addition

Good cassava can be preserved in mainly two ways; either as wet/flash dried, direct sun-dried or solar-dried.

“Majority of farmers cut the cassava into pieces and dried it directly under the sun. This obviously affects the quality of the flour,” Prof. Otim Nape, a veteran crop scientist, says. However, there are some for example in Lira, Apac, Tororo and Nakasongola, who are practiding good post-harvest handling. But there is still a big need for proper equipment.

“There are 5-10 good solar driers in Uganda, while there are only two good fresh driers,” the EPRC survey says. A good flash drier costs about sh400m. Farmers think that the first step by the Government must be to invest in processing.

“If each region can have a good drying unit, then losses can be reduced and the things that the President is talking about like starch can be collected,” Christine Okot, a cassava farmer in Lira, says.

Threatened by diseases
Dr Titus Alicai, a principal scientist at the National Agricultural Research Organization (NARO), contends that any reduction in cassava production due to cassava mosaic disease (CMD) and cassava brown streak disease (CBSD) threatens not only food security, but would also play havoc with government plans to support a project that seeks to utilise cassava pulp for ethanol production.
But that depends on a consistent supply of cassava, which has struggled to overcome disease issues. CMD and CBSD still remain a threat and the status quo has not been helped by poor farmer practices, such as recycling seed cuttings beyond recommended times.
“On the CMD and CBSD mitigation front, there have been inroads made in recent years, principally with the development and distribution of improved cassava varieties such as NASE14, NASE 19 and NARO CASS 1 to farmers by the National Agricultural Research Organization,” Alicai says.

In Uganda, CMD accounts for an estimated annual yield loss of more than $60m and it has, by all accounts, been singled out as the biggest economic constraint to the production of cassava in sub-Saharan Africa.

The impact of CMD on Uganda’s cassava production was not considered grave until the late 1980s, when its devastating effect was experienced in the north-west of the country. The outbreak caused the disappearance of a cassava landrace called Ebwanatereka, which was widely distributed in the country in the 1980s.
Cassava brown streak disease, on the other hand, is thought to be the most devastating cassava disease in southern, eastern and central Africa. It reportedly can cause up to 100% yield loss.
As a means of combating CMD, a Ugandan computer scientist, Dr Jennifer Rose Aduwo, has developed a computer application based on an artificial neural network that can automatically detect the disease.
Aduwo, the dean of the Uganda Management Institute’s School of Distance Learning and Information Technology, says the application has already provided an accuracy rate of 97.2% for CMD’s classification and 88% for the disease’s severity grading.

“This model will help reduce the high cassava yield losses Uganda suffers annually due to CMD,” she says.

“What is expected is that timely and fast information provided by the model from farmers or agricultural extension workers, at the click of a button from an internet-connected smartphone which has captured cassava leaf images from gardens for the disease’s detection/classification, will be sent to a team at the National Crops Resources Research Institute (NaCRRI) at Namulonge.  NaCRRI will, in turn, develop effective disease contingencies and supply CMD resistant varieties to affected regions across the country,” Aduwo adds.

“The process of capturing the cassava leaf image from the cassava garden and sending to a computer server for CMD detection/classification takes less than a minute, provided there is an internet connection.”

Alicai said Aduwo’s app will improve on the efficiency and scale at which the CMD disease’s data is collected. 

“With her app, we shall be able to know which areas around the country need speedy interventions. Previously, we did surveys, but the processing of data took months. But with this digital platform, data on CMD will be availed within a short time,” Aduwo said.

In the past 10 years, several research papers on the CMD by Aduwo have been published and have received golden opinions, for good measure.

Her research publication journey on automating CMD set forth in 2010 when Google gave Aduwo and her two research colleagues a $10,000 grant. At length, they produced the paper entitled “Automated learning-based diagnosis of CMD”.  Several other papers followed in subsequent years.

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