"Precision agriculture (PA) is a farming management strategy based on observing, measuring and responding to temporal and spatial variability to improve agricultural production sustainability."
The use of technology, such as GPS and sensors, to optimize crop production and reduce input costs.
Remote sensing: This topic involves the use of aerial imagery and satellite data to analyze plant health, crop growth, and yield potential.
GIS (Geographic Information System): This is a software tool used to visualize and analyze spatial and temporal data related to crop management. It can be used to create maps, conduct spatial analyses, and make informed decisions.
Soil Analysis: This is used to measure soil fertility, nutrient levels, and other characteristics that are important to agriculture. Soil analysis helps to optimize irrigation and fertilization practices.
Precision Irrigation: This topic involves the use of sensors, weather data, and other tools to optimize irrigation practices. It helps to maximize crop yield while conserving water.
Crop Modeling: This is the use of computer models to forecast crop growth, development, and yield potential. It helps to optimize planting and harvesting schedules and improve decision-making.
Weather Forecasting: This topic involves the use of tools and techniques to predict weather patterns and trends. It helps farmers make informed decisions about crop management, such as when to plant or harvest.
Pest and Disease management: This is the use of data and analytical tools to detect and manage pests and diseases that can impact crop health and yield potential.
Sensor Technology: This involves the use of sensors to measure environmental factors like temperature, humidity, moisture, and light. The data collected is used to make informed decisions about irrigation, fertilization and crop management practices.
Precision Livestock Farming: An application of precision agriculture to livestock production that relies on sensors and data analysis to manage animals and their environment.
Machinery and Equipment: This topic involves the use of specialized machinery and equipment like drones, tractors, and sprayers to optimize crop management practices.
Data Analytics: This topic involves the use of software and algorithms to process and analyze large and complex datasets. It helps to generate insights and identify patterns to make informed decisions about crop management.
Crop Phenotyping: This involves the use of sensors and imaging technology to measure various crop traits such as crop health, size, growth rate and productivity.
Nutrient Management: This is the process of managing the supply of nutrients required by crops during growth for optimal yield potential.
Farm Management Information Systems (FMIS): These are software applications used to manage and analyze farm data, such as yield data, planting dates, pesticide and herbicide use, soil fertility data, and weather data.
Variable Rate Technology (VRT): VRT involves adjusting inputs such as seed, fertilizer, and pesticides according to the specific needs of each area of a field. By analyzing data such as soil and moisture levels, VRT can optimize crop yields while reducing overall costs.
Automated Steering Systems: These systems use GPS technology to guide farm equipment along precise paths through fields. By doing so, they can reduce overlap and error while also saving on fuel consumption.
Remote Sensing: Remote sensing uses drones or satellites to collect data on a range of variables such as temperature, soil moisture, and plant health. This information can be useful for guiding decisions around irrigation and fertilization.
Precision Irrigation: Precision irrigation involves applying water only where and when it is needed. Using soil moisture sensors and real-time weather data, it aims to optimize irrigation schedules and reduce water waste.
Prescription Farming: Prescription farming employs data analytics to create customized crop management plans for each area of a field, based on factors such as soil type, past yields, and weather forecasts. This can improve yields while minimizing waste.
Yield Monitoring: Yield monitoring gives farmers real-time data on crop yields, allowing them to make adjustments and optimize their harvest. Data can be collected using sensors or manually by field technicians.
Crop Scouting: Crop scouting involves inspecting fields for signs of disease, insect infestations, or other problems early on, allowing farmers to address issues before they spread and reduce crop yields. This can be done either through manual scouting or by using automated sensors and image analysis technology.
"The goal of precision agriculture research is to define a decision support system (DSS) for whole farm management with the goal of optimizing returns on inputs while preserving resources."
"First conceptual work on PA and practical applications go back to the late 1980s."
"Among these many approaches is a phytogeomorphological approach which ties multi-year crop growth stability/characteristics to topological terrain attributes."
"The interest in the phytogeomorphological approach stems from the fact that the geomorphology component typically dictates the hydrology of the farm field."
"The practice of precision agriculture has been enabled by the advent of GPS and GNSS."
"The farmer's and/or researcher's ability to locate their precise position in a field allows for the creation of maps of the spatial variability of as many variables as can be measured."
"These arrays consist of real-time sensors that measure everything from chlorophyll levels to plant water status, along with multispectral imagery."
"This data is used in conjunction with satellite imagery by variable rate technology (VRT) including seeders, sprayers, etc. to optimally distribute resources."
"Recent technological advances have enabled the use of real-time sensors directly in the soil, which can wirelessly transmit data without the need for human presence."
"Precision agriculture has also been enabled by unmanned aerial vehicles that are relatively inexpensive and can be operated by novice pilots."
"These agricultural drones can be equipped with multispectral or RGB cameras."
"These multispectral images contain multiple values per pixel in addition to the traditional red, green, blue values such as near-infrared and red-edge spectrum values used to process and analyze vegetative indexes such as NDVI maps."
"These drones are capable of capturing imagery and providing additional geographical references such as elevation, which allows software to perform map algebra functions to build precise topography maps."
"These topographic maps can be used to correlate crop health with topography, the results of which can be used to optimize crop inputs such as water, fertilizer, or chemicals such as herbicides and growth regulators through variable rate applications."
"Precision agriculture (PA) is a farming management strategy based on observing, measuring, and responding to temporal and spatial variability to improve agricultural production sustainability."
"The goal of precision agriculture research is to define a decision support system (DSS) for whole farm management with the goal of optimizing returns on inputs while preserving resources."
"The practice of precision agriculture has been enabled by the advent of GPS and GNSS."
"These arrays consist of real-time sensors that measure everything from chlorophyll levels to plant water status, along with multispectral imagery."
"Recent technological advances have enabled the use of real-time sensors directly in the soil, which can wirelessly transmit data without the need for human presence."