Disease Diagnosis: Nuru for in-field Pest

Crop Care in Your Pocket: Nuru App, Your Farming Companion

PlantVillage Nuru is a revolutionary smartphone app powered by artificial intelligence, enabling rapid offline diagnosis of crop damage caused by diseases and pests. This innovation employs machine learning and object recognition, making it accessible on basic smartphones. It offers a vast advantage to farmers, as it provides instant diagnoses and connects users to a community of fellow users. Moreover, it offers valuable guidance on disease and pest control. The app's ability to recognize symptoms and its user-friendly interface empower farmers to swiftly identify and address crop health issues, ultimately contributing to increased agricultural productivity and food security.

This technology is TAAT1 validated.

8•8

Scaling readiness: idea maturity 8/9; level of use 8/9

Adults 18 and over: Positive high

The poor: Positive medium

Under 18: Positive medium

Women: Positive low

Climate adaptability: Highly adaptable

Farmer climate change readiness: Significant improvement

Biodiversity: Positive impact on biodiversity

Carbon footprint: A bit less carbon released

Environmental health: Greatly improves environmental health

Soil quality: Improves soil health and fertility

Water use: A bit less water used

Problem

Farmers face difficulties in quickly identifying major crop damages caused by diseases and pests.
There is a lack of effective means to detect diseases and pests affecting cassava, such as cassava mosaic disease, cassava brown streak disease, and cassava green mite.
Damage caused to maize by fall armyworm is challenging to detect early.
Farmers struggle to access information on diseases and pests affecting their crops.
Access to accurate diagnostic tools is limited, especially in resource-constrained regions.
There is an urgent need for affordable and accessible solutions to help farmers identify and manage crop diseases and pests.
Communication among farmers regarding disease and pest issues is often limited, leading to a lack of information sharing and collaboration.
Farmers require quick and easy access to disease and pest control advice tailored to their specific situation.

Solution

Instant and offline access to accurate diagnoses of major crop damage symptoms caused by diseases and pests.
Detection of diseases and pests, such as cassava mosaic disease, cassava brown streak disease, cassava green mite, and damage to maize by fall armyworm.
Connecting users to other nearby users and providing information on how to control identified diseases and pests.
Utilization of machine learning with object recognition to train software to 'recognize' the characteristics of symptoms caused by diseases and pests.
An Android application available for free on Google PlayStore, usable even on basic specification smartphones.
Translations into multiple languages for increased accessibility, including Swahili.
Post-event analysis of diagnostic reports received from users, enabling the generation of real-time maps.
On-field diagnosis of crop pests and disease types and delivery of relevant control advice to users via their smartphones.

Key points to design your program

In the near future, this section will provide an overview of this technology's success in various contexts, details on partners offering technical support, training, and implementation monitoring, along with other valuable insights for your projects and programs. These details will be added progressively.

In the meantime, use the 'Request information' button if you need to contact us.

IP

Open source / open access

Countries with a green colour: Tested & adopted
Countries with a bright green colour: Adopted
Countries with a yellow colour: Tested
Countries with a blue colour: Testing ongoing

Countries where the technology is being tested or has been tested and adopted
Country	Testing ongoing	Tested	Adopted
Kenya	–No ongoing testing	Tested	Adopted
Tanzania	–No ongoing testing	Tested	Adopted

This technology can be used in the colored agro-ecological zones. Any zones shown in white are not suitable for this technology.

Agro-ecological zones where this technology can be used
AEZ	Subtropic - warm	Subtropic - cool	Tropic - warm	Tropic - cool
Arid
Semiarid
Subhumid
Humid

Source: HarvestChoice/IFPRI 2009

The United Nations Sustainable Development Goals that are applicable to this technology.

Goal 2: zero hunger

Goal 1: no poverty

Goal 3: good health and well-being

Goal 9: industry, innovation and infrastructure

Goal 12: responsible production and consumption

This solution is applied by downloading the PlantVillage Nuru app for free from Google's PlayStore.
Usage can be enhanced by awareness raising and training of farmers and extension officers.

Last updated on 28 April 2025