Decision support system for the management of key pests and diseases of apple and grapes

RIMpro is a decision support system (DSS) for the sustainable management of pests and diseases in fruit and grape production. Every day, the cloud service together with the weather data system help thousands of growers and consultants worldwide to make the best decisions to protect their crops.

Learn how

Accurate data that saves your crops

RIMpro is based on simulation models that are developed, tested and regularly updated by scientists in production regions around the world. Easily connect your physical weather station or create a virtual weather station and be the next to instantly receive valuable information to control pests and diseases in integrated, low-input, or biological production systems.

Weather data

Connect your weather station in minutes to the RIMpro platform, we can interface with 20 different types of stations.

Remote field monitoring

Monitor the weather and follow the development of pests and diseases through RIMpro’s cloud services.

Real-time information

The models are updated every 30 minutes and use the most recent weather forecast for your location.

Disease models

We offer more than 20 models that have been tested and validated by experts. We constantly update our disease models with new scientific knowledge, practical experiences, and user feedback.

Risk calculations

For each disease and pest, a risk severity indicator is calculated to help you make smart treatment decisions.

Mobile app

All our models in your pocket. Receive notifications and never miss a risk again . available for Android and IOS.

A benchmark model

RIMpro has been helping growers for over 25 years in more than 40 countries worldwide to monitor pests and diseases and reduce their use of pesticides.

Most models are based on analysis of local historical data. They fit well with the local history but failin other regions with a different climate or when local climate changes. RIMpro models are based on the knowledge of how climatic- and geographical factors affect the underlying biological processes. That makes our models robust in explaining pest and disease development in varying climatic situations.