A University of Rwanda (UR)-led project has developed innovative devices to monitor the cassava value chain aiming to boost productivity and quality, reduce post-harvest losses, cut greenhouse gas (GHG) emissions, and improve cassava export potential.

The research findings, conducted under the project titled "Internet of Things (IoT) and Artificial Intelligence (AI)-Based Climate Inequality Monitoring System for the Agricultural Value Chain: A Case Study of the Cassava Value Chain", were presented on August 27, 2025 at UR’s Huye campus.

Funded by the National Council for Science and Technology (NCST), the project was implemented in partnership with the Rwanda Agriculture and Animal Resources Development Board (RAB), Kinazi Cassava Processing Plant (KCP), local farmers, and the Swedish University of Agricultural Sciences (SLU).

The research team included Dr Omar Gatera (Principal Investigator), Dr Florence Uwamahoro, Prof. Damien Hanyurwimfura, Dr Athanase Nduwamungu, Dr Claire d'André Hirwa, Dr. Anna Berlin and Mr. Felix Niyigena.

One of the project’s core objectives was to enhance cassava productivity and quality while reducing GHG emissions from traditional farming practices.

"To achieve this, we developed a device that monitors soil nutrients (i.e.; N, P, K, Ph, MC) and environmental conditions (i.e.; T, H, CO2). It guides farmers on when and how to fertilise and cultivate, and how farming can reduce emissions. We also published 4 papers to validate our methods,” explained Dr. Omar Gatera, a Senior Lecturer at UR’s College of Science and Technology, who also serves as the Head of PhD Studies and Research in the African Centre of Excellence in the Internet of Things (ACEIoT).

The project’s broader objectives were to explore the current state of the cassava value chain including its challenges, strengths, opportunities, weaknesses, threats, and market conditions to improve the quality and safety of the cassava value chain, and enhance its competitiveness in the global market using low-cost and efficient technologies such as Artificial Intelligence/Machine Learning (AI/ML) and the Internet of Things (IoT).

It also aimed to mitigate GHG emissions associated with the cassava value chain, establish a system for the remote monitoring of the value chain, and enhance knowledge and skills related to the cassava value chain and emerging agricultural technologies among students, entrepreneurs, and policymakers.

"We conducted surveys and published research papers for validation purposes. The establishment of a system for remote monitoring of the cassava value chain involved developing both the physical device and an AI/ML algorithm.

"We also designed a dashboard for data monitoring and created a website to share project findings and results. We introduced new tools that can help farmers enhance productivity, improve product quality, and reduce environmental impact from agricultural practices,” Gatera said.

The main achievements were the analysis of current situation of cassava value chain in Rwanda, development of two device, one for soil and environmental monitoring and quality flour for cassava, ML algorithm for environmental and yield prediction for cassava farming, created QR code for labelling, created dashboard and website (https://cassava.gosur.org/) for findings dissemination, built the capacity of junior researchers and postgraduate students in grant development and research paper writing, one Master student "Mr. Gabriel Karerangabo" and two PhD students "Mr. Egas J. Armando" and "Mr. Nyakuri Jean Pierre" students in the ACEIoT who completed their research under the project support and project members&039; supervision. In this project, 10 research papers were developed, among them, 4 were published, 2 were accepted for publication and 4 were submitted to international conferences.

Post-harvest monitoring

He said there are two devices developed to monitor cassava value chain; environmental conditions and post-harvest handling.

One device is used on farmers with nine sensors, covering over 500 square metres and another is used during transportation, storage at the market and the industry levels.

"So, the devices can control the environment, the temperature, humidity, the Ph of the product stored there, but also the moisture content of the product there. So, what we want to achieve is to maintain the quality of the processed cassava throughout the supply chain until it reaches consumers,” he explained.

"By using this device, we aim to safeguard consumer health and safety and enhance the economy of the country through agricultural produce. We also emphasise that the device is affordable, making it accessible and usable by a wide range of users across different stages of the value chain,” he noted.

Critical control points (CCP) along the cassava value chain

The cassava value chain, from cultivation to market, has several critical stages, each with parameters that must be monitored to ensure quality and sustainability.

Production stage focuses on soil quality, pest control, plant health, and nutrient levels.

Key control points include soil moisture, temperature, humidity, acidity, and the presence of greenhouse gases.

Processing stage emphasises on hygiene and the quality of the final product.

Key control points include water quality, cassava colour changes, mould presence, Ph, moisture content, and storage conditions.

Transportation stage seeks to preserve quality during transit by monitoring ambient conditions like temperature, humidity, and harmful gases.

This ensures cassava doesn’t spoil or degrade before reaching consumers.

Marketing stage focuses on storage and environmental conditions to ensure cassava remains nutritious and safe.

Factors like moisture content, temperature and humidity are key control points to maintaining market-readiness.

Florence Uwamahoro, Deputy Director General for Agriculture Development at RAB noted that AI and IoT technologies will transform the cassava value chain by providing real-time monitoring and data-driven insights.

This , she said, help farmers make better decisions and improve productivity—directly contributing to food security.

"By integrating AI and IoT into cassava farming, we can detect diseases early, track crop performance, and optimize processing. This not only reduces post-harvest losses but also empowers smallholder farmers with the tools they need to thrive," she said.

Farmers embrace new tools

Local cassava farmers welcomed the technology, noting its potential to modernise farming and boost income.

Seraphine Nyirahabimana, Seraphine Nyirahabimana, a farmer who grows cassava on two hectares in Kayonza District, said that farmers were in need of such high-level skills and precision to modernise cassava farming.

"This technology could help detect threats like crop diseases and guide us on improving productivity. Previously, our cassava was often rejected due to poor quality, leading to losses. Now, we’ll have better market access," she said.

Sylvain Harerimana, a farmer from Bugesera District, reiterated that the technology will provide vital information to improve cassava farming.

"The devices help determine fertiliser needs and monitor soil moisture. We hope they will be affordable.”

Athanase Nduwumuremyi, Senior Research Fellow at RAB and coordinator of the Roots and Tubers Programme, stated the project's results are significant for Rwanda’s food security.

"Cassava is ranked second in terms of production after banana, and third in terms of land coverage. The crop contributes significantly—18 per cent—but farming systems and poor agricultural practices remain major challenges. However, challenges like poor farming practices and short shelf life remain.”

He emphasised that cassava tubers must be processed or consumed within 24 hours after harvest to avoid deterioration from fungal and bacterial infections.

"Data from this project will help improve decision-making for both farmers, processors and policy makers” he noted.