Cassava diseases threaten success of proposed ethanol plant

Reduction in cassava production due to cassava mosaic disease (CMD) and cassava brown streak disease (CBSD) threatens food security. 

As Uganda takes steps to make cassava an eco-friendly feedstock for ethanol production, agricultural experts say the crop still faces disastrous diseases that have perennially caused severe yield losses and threatened food security.

Dr Titus Alitai, 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 cause havoc to government plans of supporting a project that seeks to utilize cassava pulp for ethanol production.

At the tail end of last year, President Yoweri Museveni 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 ethanol derived from cassava a sustainable alternative cooking fuel.

Taking a long view, Museveni noted that if the project obtained a firm footing, Uganda would be able to export fuel made from cassava to other countries in the region.

But that depends on a consistent supply of cassava, which has struggled to overcome disease issues. CMD and CBSD still remain a threat and that status quo has been helped by poor farming 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,” Alitai said.

It is not clear, however, if some of the resistant cassava varieties that will likely be supplied by the National Crops Resources Research Institute, which is one of the six National Agricultural Research Institutes mandated to conduct, carry out research and knowledge generation on how to deal with crop diseases such as CMD, will be genetically modified (GM) cassava.

Research findings from the National Agricultural Research Organization have shown that GM cassava is resistant to CMD and CBSD.

Many scientists across the East African region have advocated for the adoption of GM cassava as a means of sustainably enhancing Uganda’s food security. But the country’s environment policy regarding the adoption of biotechnology has in recent years been erratic, if not checkered.

In 2017, a biotechnology and biosafety bill was passed, but it was referred back by the President for adjustments. It was passed yet again in 2018, but with stern liability sections that analysts say impede biotechnology development in the country.

In Uganda, CMD accounts for an estimated annual yield loss of more than 60 million US dollars 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, revealed that the application has already provided an accurate 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 said.

“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 at Namulonge who will, in turn, develop effective disease contingencies and supply CMD resistant varieties to affected regions across the country,” she added.

“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.”

Alitai 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.”

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

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.

Original Post: New Vision