Nuru: In-field Pest and Disease Diagnosis

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

Project adoption1

Technology integrated in the ENSURE- East Africa project.

Project	Beneficiaries	Budget	Duration	Key figures
ENSURE- East Africa Enabling Environments for Sustainable Regional Agriculture Extension	3,000,000 farmers.	13.14 million	2024–2027	149,940 farmer leaders & trained farmers. 9,996 trained. 2 → 3.5 t/ha.

See project details ›

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-Field Pest and Disease Diagnosis Tools improve early detection of crop threats, strengthen advisory services, and support timely farmer decision-making through digital diagnostic technologies. The technology can be integrated into food security, digital agriculture, climate resilience, extension services, and crop protection programs. Its adoption contributes to SDG 1 (No Poverty), SDG 2 (Zero Hunger), SDG 9 (Industry, Innovation and Infrastructure), and SDG 13 (Climate Action).

To integrate this technology into your project, plan and budget for the following activities and prerequisites:

Assess major pest and disease challenges, extension service gaps, and digital technology access in target farming communities.
Facilitate access to smartphones, digital diagnostic tools, and internet connectivity where needed to support effective technology use.
Support training for farmers, extension agents, cooperatives, women’s groups, and youth agripreneurs on digital diagnosis tools, pest surveillance, disease identification, and integrated pest management practices.
Invest in digital extension services, awareness campaigns, training programs, and data management systems to increase adoption and effectiveness.
Promote rapid pest and disease detection and response systems to reduce crop losses, improve productivity, and strengthen farming system resilience.
Support the participation of women and youth in digital agriculture services to improve access to information and create employment opportunities.
Establish partnerships with Penn State, research institutes, extension services, technology developers, telecom providers, and private sector actors to support scaling and sustainability.
Track key indicators such as number of farmers using diagnostic tools, crop losses, pest and disease management effectiveness, outbreak response times, and crop yields.

IP

Open source / open access

Scaling Readiness describes how complete a technology\’s development is and its ability to be scaled. It produces a score that measures a technology\’s readiness along two axes: the level of maturity of the idea itself, and the level to which the technology has been used so far.

Each axis goes from 0 to 9 where 9 is the “ready-to-scale” status. For each technology profile in the e-catalogs we have documented the scaling readiness status from evidence given by the technology providers. The e-catalogs only showcase technologies for which the scaling readiness score is at least 8 for maturity of the idea and 7 for the level of use.

The graph below represents visually the scaling readiness status for this technology, you can see the label of each level by hovering your mouse cursor on the number.

Scaling readiness score of this technology

Maturity of the idea 8 out of 9

Uncontrolled environment: tested

Level of use 8 out of 9

Used by some intended users, in the real world

Maturity of the idea										Level of use
9
8
7
6
5
4
3
2
1
	1	2	3	4	5	6	7	8	9

Project	Beneficiaries	Budget	Duration	Key figures
ENSURE- East Africa Enabling Environments for Sustainable Regional Agriculture Extension	3,000,000 farmers.	13.14 million	2024–2027	149,940 farmer leaders & trained farmers. 9,996 trained. 2 → 3.5 t/ha.

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 Jul 2, 2026