Advances in high technology in agriculture bring new terminology to describe innovations. Here’s a quick reference guide to selected terms in this new vernacular.
Bioinformatics (computational biology)- using biological data to develop mathematical algorithms to study biological systems
Crop Model- Computerized tool using algorithms to predict crop performance based on agronomic and environmental data
Data analytics- examining data to draw conclusions
Digital agriculture- farming activities that depend on the collection, use and analysis of data (includes precision agriculture)
Genome- the full set of genetic instructions of an organism (coded in DNA)
Genome editing- a type of genetic engineering in which DNA is deleted, replaced or inserted, resulting in a genetically modified animal, plant or organism (GMO) with a desired trait such as drought resistance, improved nutritional value or faster rate of gain
Metadata- information that provides details about data (such as method and time of collection, and by whom)
Phenotype- physical characteristics of an organism resulting from its genes an environment
Predictive phenomics- measuring physical and biochemical traits of organisms as they change in response to genetic and environmental influences
Precision agriculture- hardware and software tools that give farmers better control to customize management of specific sites (auto-steer, yield monitors, variable rate machinery)
Remote sensing- the process of gathering data from a distance without making contact with the subject
Ultrasonics- the use of acoustic vibrations to improve materials and industrial processes
Unmanned Aerial Vehicles (UAVs)- lightweight quadcopters (informally known as drones) used for data collection, transmitting remote-sensing data, photos or videos that allow operators to study or make more precise management decisions on large swaths of land