This App detects crop fungal diseases at a primary stage and proposes adequate treatment.This app can be used to identify plant diseases from a photograph. Agrix Tech's AI can be embedded in 3rd parties apps.
This is a Plant Disease Identifier. Upload an image of (tomato, potato) plants and identify the disease that affects it. Learn about remedies and there is a practical video explanation to prevent further loss of plants.
Farmwave equipment uses vision-based artificial intelligence to add value. Farmwave hardware can be mounted on the header and back of farm machinery to capture, and geo-tag, an image every 5 seconds. For example, the hardware can be mounted on a sprayer and used to take images that assist with: pest and disease identification; plant counts; growth stage (crop height); weed detection (see and spray); % application coverage; nozzle performance.
The device collects particles from the air, such as fungal spores. At the end of the user-defined sampling period, the sample is moved through a series of different processes, which enables the instrument to detect the amount of spores of a target species that were in the air during the sampling period. To do this, the spores are broken open in order to release the DNA inside. Once broken open, a subsample of the disrupted spores is transferred to a tube of dried reagents within the device, in order to detect the DNA of a specific crop pathogen using a DNA-specific assay.
Pocket Diagnostic in-field tests are designed to give growers, consultants and inspectors information about plant health where and when it is needed. Disease presence can be confirmed in just a few minutes anywhere in the glasshouse, field or supply chain. Everything needed for testing plants in the field is included in the pack. The unique ‘bottle and ball’ sample preparation method means that only 20-30 seconds of shaking are needed before the test can be run. Lateral flow devices are used to detect disease in plants.
Model and Decision Support for the risk of Peronospora infection in onion. German platform hosted by ISIP.
This Plant Health app includes a set of tools to optimize the management of crops with regard to diseases, pests and phytosanitary treatments/spraying. One of the tools available is for disease and pest prediction models. There are a number of models, developed for different types of crops (vineyards, apples, pears, olive trees, etc). These models are based on academic studies and scientific papers and were developed to be available in any country. They mostly rely on weather conditions, after setting up the base parameters of the crop, to indicate the current and future risk of certain diseases/pests and trigger alerts if the risk is High. This is one tool in a larger crop management system.
Dino-Lite digital microscopes provide a powerful, portable and feature-rich solution for microscopic inspection at up to 900x magnification and 5-megapixel resolution. With these products, farmers and experts are able to identify insects quickly and efficiently in order to take the right measures.
Pats design drones that eradicate flying pest insects. Their bio-inspired solution proactively controls harmful insect populations. The bat-like drones work autonomously and keep infestations in check. By selectively eliminating harmful insects the ecological balance in a greenhouse ecosystem is sustained. With this approach they enable sustainable insect control in horticulture, to facilitate the market’s needs to become more sustainable.
This analytical tool based DNA array technology can provide quantitative identification for more than 150 different fungal and bacterial pathogen species, selected upon relevance for horticultural crops. Every microarray allows 8 determinations. Easy-to-use sampling kit for sample collection by non-specialist technicians is provided. Producers will take the samples themselves. Samples are shipped to a laboratory where pathogens are detected by using DNA microarray technology. Provided online tool to support the end-users (farmers, agronomists at cooperatives, consultants) in making decisions on pest management, establishing not only the sampling collection but also interpretation of the VegAlert data, permitting to the farmers to improve knowledge about phytopathogen prevalence and epidemiology.
