Scoutbox uses image-based insect detection for sticky traps. It is revolutionizing insect monitoring technology by combining image recognition and sophisticated machine learning algorithms. Easy to use, durable, reliable and time saving. See where harmful insects (Whiteflies, Thrips, Leaf miners) and beneficals (nesidiocoris & Macrolophus) are concentrated on an easy-to-read map on your laptop for effective pest control. Scoutbox can read up to 300 trap plates per day for you with the push of a button.
Agrio is an artificial intelligence-based precision agriculture solution that helps you to remotely monitor, identify, and treat plant diseases and pests in your field, farm, and garden. The app leverages and deploys proprietary artificial intelligence and computer vision algorithms. The algorithms contain the knowledge of numerous agronomists and agriculture experts and continuously improve. Available in a number of languages.
The MyIPM smartphone application was originally developed in 2012 by Clemson University for South Carolina peach and strawberry growers, but has since expanded into a tool that serves all fruit growers along the east coast. It has information to aid identification and control. The App includes diagnostics, chemical, biological, and cultural control tactics, search feature to list active ingredients and trade names for each disease/pest together with efficacy and rate per acre.
Cropwise Imagery is a digital farming tool that uses imaging technology to monitor crop health. The user can easily acces all data via their tablet, phone or computer. The data is easy to interpret and can be used to detect anomalities in the field. This farming tool signals the user when something is harming the crops. It indicates problems such as water stress, attacks by defoliating pests, nutritional deficiencies or nematodes.
AkerScout is a directed crop scouting application to help identify and prioritize crop damage to address problem areas needing immediate attention. The application works on standalone mode, however various important features are enabled when you load high resolution aerial vegetation imagery. Features include: Scout task coordination and assignment of multiple fields and scouts; support for various crop types including corn, soy, sugar beet and more added frequently; comprehensive database for identification of pests, diseases and plant limiting stress; GPS enabled crop scouting with identification and capture of disease, pests, weather, plant population, damage severity, photos and notes; field mapping and comprehensive reporting.
Spy Fly is a monitoring system that uses modern technologies to allow the farmer to monitor the phytosanitary conditions of their crops, directly from their smartphone or other device. Equipped with a practical and resistant modular casing, SpyFly is able to attract harmful insects, using the combined action of colour attraction and pheromones, allowing them to be captured on an adhesive surface. At intervals, SpyFly photographs the adhesive paper, transferring the images to a cloud platform, where they are processed and analyzed by algorithms, thus identifying harmful insects. SpyFly also measures meteo-climatic parameters, useful for developing predictive models on the spread of harmful agents.
GoMicro Inspect is a clip-on magnifier that clips onto any smartphone, tablet or iPad producing clear crisp images. It is a great tool for detecting leaf disease and pests early. It can be used with the GoMicro Examine app.
Place traps on the edge of the plantation. The late-season capture of BMSB adults and nymphs (juvenile stages of stink bug) by traps baited with pheromone for two other species - Asian Stink Bug, Plautia stali and Harlequin Bug, Murgantia histrionica, are good indicators for the pest presence (or absence) of BMSB in the orchard. Current lures are not very effective and can’t be used as an alternative control method.
Based on the acclaimed Encyclopaedia of Arable Weeds and developed in association with ADAS, the BASF Weed ID app aims to provide an easy to use reference guide to the major broad-leaved weeds and grass-weeds in the UK supporting weed identification of 140 species.
Multi-sensor data provides a complete view of field conditions and plant health, right on the computer, tablet or smartphone. If there are issues, the grower can take action immediately, avoiding potential damage and loss. AI-powered applications do complex analysis, following the crop water stress index (CWSI). The result is optimal irrigation scheduling and water usage throughout the entire growing cycle. Computer vision algorithms analyze images from various heights and then alerts the grower of risks to crops – long before they’re noticeable to the naked eye.