Virtual Agronomy
'Virtual agronomist (eng. virtual agronomist, abbreviation virtual reality and the profession of agronomist) - the use of digital technologies in agriculture, as a substitute for human manual and mental labor. A virtual agronomist is built through programming, based on computer technology and programming the specialist’s skills into a digital format. Refers to Internet of Things technologies.
Virtual agronomist' (Template:Lang-en) - software agent, assistant, assistant, online specialist substitute for a person, which can perform tasks (or services) for the user based on information entered by the user, data on technologies of high professional skills in cultural and ornamental and industrial cultivation of agricultural crops, as well as information obtained from various Internet resources (weather, soil composition, agricultural characteristics, region and agricultural technology, automation complex and agronomy needs).
This could include field management and monitoring, running data collection automation, machine vision for yield analysis, and automating growth in a vertical farm. Examples of this kind are the programs Trimble, [[1]] ([[2]]), [[3]], [[4]].
Description
In the context of the use of professional abbreviation by a virtual agronomist in the cultivation of grains, vegetables and fruits, herbs and forage crops, three key ones are defined: -A drone equipped with computer vision that regularly monitors fields -Agricultural machinery controlled by unmanned vehicles -Urban farming management platforms Key areas of application of the virtual agronomist: - field monitoring - detection, location, recognition, identification, classification and analysis of weeds, plant diseases, insects and pests. - analysis and forecasting of the harvest, harvest dates - resource management, soil analysis, calculation of water resources, fertilizers, weather conditions - automation of control and management on a vertical farm by creating artificial conditions similar to natural ones. - big data analysis, machine learning, artificial intelligence The professional format of intelligent personal digital farming services - "automated" and "smart" farms - are formed on the basis of mobile devices and application programming interfaces (API), and are distributed through mobile applications. At the same time, intelligent automated virtual agronomists are designed to perform specific tasks specified in the user instructions and embedded technical solutions.
Known implementations of virtual agronomist
Template:Section importance Field monitoring
- Taranis Israel program.
Taranis Field Monitoring The Taranis system receives information from data analysis obtained from surveillance sensors, weather data, high-resolution aerial photographs and is capable of identifying sectors of the field with slow plant growth, identifying plants damaged by insects that are not receiving enough nutrients, and identifying diseased plants. As a result, Taranis will offer solution options, calculate deadlines and options for action.
- Watson Decision Platform for Agriculture USA
The platform processes information obtained from remote sensing of land in the fields. The farmer receives real-time data on the damage to cereal crops by diseases or pests. Assesses the condition of plants, calculates the required amount of pesticides, optimal timing for treating problem areas and suggests preventive measures. The system independently collects data on weather conditions in a specific area, humidity, and meteorological situation, provides a graph of changes in soil moisture, creates a forecast for yield and growth dynamics based on data from previous seasons. Recognition_application_interface
- There are a number of other platforms in the world that can analyze information and provide recommendations for housekeeping:
· Health Change Maps and Notifications platform from Farmers Edge; · Field Manager application from Bayer; · Hummingbird Technologies platform. Recognition application interface. These platforms use data from satellites, ground monitoring, and meteorological information using algorithms to analyze them. Monitoring of plant diseases
- Plantix app from Peat.
Plant disease diagnostic services allow you to diagnose about 60 diseases. Contains a library of images, which has a convenient service for sorting images. As the number of downloaded images increases, disease diagnostic algorithms also improve.
