Applications of Artificial Intelligence for Precision Agriculture

Real-time citrus detection using YOLO (a real-time AI object detection algorithm) on an NVidia Jetson TX2 board (Graphics Processing Unit, GPU). These results are achieved by using just 150 pictures to train the AI-based system.

Technological advances in computer vision, mechatronics, artificial intelligence, and machine learning have enabled the development and implementation of remote sensing technologies for plant, weed, pest, and disease identification and management. They provide a unique opportunity for the development of intelligent agricultural systems for precision applications. This 5-page document discusses the concepts of artificial intelligence (AI) and machine learning and presents several examples to demonstrate the application of AI in agriculture. Written by Yiannis Ampatzidis, and published by the UF/IFAS Department of Agricultural and Biological Engineering, December 2018.
http://edis.ifas.ufl.edu/ae529

Hurricane Impacts on Florida's Agriculture and Natural Resources

Two oak trees downed due to Hurricane Irma. Photo taken 09-14-17

Hurricanes are capable of affecting almost everything in their paths. Their strong winds and heavy rains can directly impact both inland and coastal areas in short periods that usually last about a day. This new 10-page document reviews basic facts about hurricanes and their effects in Florida and discusses ways they might affect Florida's agriculture and natural resources. Written by Young Gu Her, Ashley Smyth, Pamela Fletcher, Elias Bassil, Ulrich Stingl, Zachary Brym, and Jiangxiao Qiu, and published by the UF/IFAS Department of Agricultural and Biological Engineering, October 2018.
http://edis.ifas.ufl.edu/ae528

Lightning Safety for Florida Agriculture Workers

Lightning streaking across a sky.

Lightning is a common occurrence in Florida. Although lightning kills only about 10% of the people it strikes, it can cause physical and mental complications that victims must face for the rest of their lives. Agriculture workers need to have a good working knowledge of lightning, its effects, and ways to protect others and themselves from this potentially life-threatening hazard. This new 4-page document discusses types of lightning, outdoor safety for farm workers, lightning medical aid, and regulations for employers. Written by Shawn Steed and Alicia Whidden, and published by the UF/IFAS Department of Agricultural and Biological Engineering, October 2018.
http://edis.ifas.ufl.edu/ae526

Instructions on the Use of Unmanned Aerial Vehicles (UAVs)

Franklin Percival, left, and Peter Ifju, professors at the University of Florida, examine a small plane that can photograph and monitor wildlife and their habitats - Oct. 19, 2004. Controlled by its own on-board computer, the plane stores and downlinks high-quality video and flight data to researchers on the ground. The unmanned aerial vehicle, or UAV, is being developed by UF's College of Engineering in cooperation with UF's Institute of Food and Agricultural Sciences. (AP photo/University of Florida/IFAS/Marisol Amador)

All research and commercial activities involving the use of UAVs must be conducted in compliance with applicable federal and state laws, statutes, and regulations. This new 5-page document provides guidance on the appropriate use of unmanned aerial vehicles (UAVs) or unmanned aircraft systems (UAS) in Florida. Written by Sri Charan Kakarla and Yiannis Ampatzidis, and published by the UF/IFAS Department of Agricultural and Biological Engineering, October 2018.
http://edis.ifas.ufl.edu/ae527

Degree-Days: Growing, Heating, and Cooling

Corn stalks growing in a field

How much and when it rains, freezes, and thaws can make the difference between boom and bust for a year's crop. However, temperature can predict more than boom or bust. Atmospheric temperature can predict the growth rates of many plants. For this reason, growers use a concept called growing degree-days (GDD), sometimes called heat units. This 5-page document discusses growing degree-days, use of the AgroClimate website to track and forecast GDD accumulation, heating and cooling degree-days, and methods for calculating HDD, CDD, and GDD. Written by Clyde W. Fraisse and Silvana V. Paula-Moraes, and published by the UF/IFAS Department of Agricultural and Biological Engineering, revised December 2010 and April 2018.
http://edis.ifas.ufl.edu/ae428

AgroClimate Crop Season Planning Tool: Reducing the Risk of Extreme Weather Events During Key Stages of Crop Development

Storm rising over a farm.

This 5-page publication details a new tool available to growers and Extension professionals to manage risks related to climate during seasonal planning stages. The Crop Season Planning tool is a climate-based tool that enables growers to plan planting strategies that will minimize risk to climate extremes based on historical climate data at their location. Written by Caroline G. Staub, Daniel Perondi, Diego Noleto Luz Pequeno, Patrick Troy, Michael J. Mulvaney, Calvin Perry, Brian Hayes, Willingthon Pavan, and Clyde W. Fraisse, and published by the UF/IFAS Department of Agricultural and Biological Engineering, March 2018.
http://edis.ifas.ufl.edu/ae525

How Likely Is a 100-Year Rainfall Event During the Next Ten Years?

Storm rising over a farm.

This 4-page fact sheet describes proper interpretation of rainfall event probabilities and recurrence intervals, particularly as they are used by engineers and water resources managers in the design and construction of hydraulic structures, such as dams, levees, and canals. This article focuses on rainfall, but its explanations and concepts can be applied to other extreme hydrologic phenomena such as flood and drought. Written by Young Gu Her, William Lusher, and Kati Migliaccio, and published by the UF/IFAS Department of Agricultural and Biological Engineering, March 2018.
http://edis.ifas.ufl.edu/ae523

Plant and Pest Diagnosis and Identification Through DDIS

Rose specimens infected with rose rosette virus. Photo taken on 10-3-15

Pest identification and diagnosis can be difficult and often require consultation with a specialist. Extension county faculty, state specialists, and faculty of the UF/IFAS Office of Information Technology developed the Distance Diagnostic and Identification System (DDIS), which allows users to submit digital images obtained in the field or after delivery to a local Extension office for rapid diagnosis and identification of pest insects, weeds, diseases, and animals. This 4-page document discusses typical DDIS hardware and camera, the DDIS process, sample types, user roles, DDIS for Extension clientele, and DDIS Mobile. Written by J. Xin, L. Buss, C. Harmon, P. Vergot III, M. Frank, and W. Lester, and published by the UF/IFAS Department of Agricultural and Biological Engineering, revised March 2018.
http://edis.ifas.ufl.edu/ae225

What Is a Wireless Sensor Network?

Forage grass and an irrigation sprinkler

A wireless sensor network (WSN) is a system designed to remotely monitor and control a specific phenomenon or event. This new 2-page fact sheet discusses the advantages that the WSN has over traditional stand-alone sensors and controllers, power consumption and conservation, and WSN technologies. Written by Clyde Fraisse, Janise McNair, and Thiago Borba Onofre, and published by the UF/IFAS Department of Agricultural and Biological Engineering, January 2018.
http://edis.ifas.ufl.edu/ae521

Microirrigation for Home Landscapes

Microspray.Microirrigation is a way to water plants using low pressure and low flowrates (usually 15 psi or less and 60 gph or less). Microirrigation systems can be easy to install above, on, or below the soil or mulch in landscape beds and are inexpensive to purchase. This 3-page fact sheet discusses types of microirrigation systems, benefits, design and installation, and maintenance. Written by Anne Yasalonis and Michael Dukes, and published by the UF/IFAS Department of Agricultural and Biological Engineering, October 2017.
http://edis.ifas.ufl.edu/ae524

What Is the ENSO Climatology Tool?

Storm rising over a farm.On a global scale, periodic anomalies in sea surface temperatures coupled with shifts in atmospheric pressure and winds, such as those associated with the El Niño Southern Oscillation (ENSO), can have profound impacts on weather conditions. ENSO affects atmospheric circulation patterns well into the midlatitudes and is the leading driver of seasonal climate variability in the United States. Tremendous advances have been made in predicting the occurrence of ENSO events with confidence three to six months in advance. This 5-page fact sheet discusses the ENSO climatology tool as well as possible challenges. Written by Caroline Staub, Clyde Fraisse, Eduardo Gelcer, and Daniel Dourte, and published by the UF Department of Agricultural and Biological Engineering, March 2017.
http://edis.ifas.ufl.edu/ae522

Yield Mapping Hardware Components for Grains and Cotton Using On-the-Go Monitoring Systems

Cotton field.This 12-page fact sheet discusses yield mapping benefits, grain yield flow sensors, grain moisture sensors, cotton yield flow sensors, differential GNSS receivers, ground speed sensors, header position sensors, computer displays, yield calculation and calibration, and costs of yield mapping hardware components. Written by Rebecca Barocco, Won Suk Lee, and Garret Hortman, and published by the UF Department of Agricultural and Biological Engineering, February 2017.
http://edis.ifas.ufl.edu/ae518

Calibrating Time Domain Reflectometers for Soil Moisture Measurements in Sandy Soils

Campbell Scientific CS616 Water Content Reflectometer.

The UF/IFAS Plant Science Research and Education Unit (PSREU) in Citra, FL developed an in-laboratory calibration protocol for CS616 TDR sensors for sandy soils, which are typical of north central Florida. This new 7-page fact sheet discusses the reflectometer, field site, calibration protocol, and calibration coefficients. Written by Tara Bongiovanni, Pang-Wei Liu, Daniel Preston, Johanna Montanez, Courtnay Cardozo, Steven Feagle, and Jasmeet Judge, and published by the UF Department of Agricultural and Biological Engineering, February 2017.
http://edis.ifas.ufl.edu/ae519

Florida Rainfall Data Sources and Types

Storm rising over a farm.

This new 5-page document introduces the sources, providers, and types of rainfall data available to Florida researchers and residents to promote understanding of the rainfall data and their application in studies and daily life. Written by Meijing Zhang, Young Gu Her, Kati Migliaccio, and Clyde Fraisse, and published by the UF Department of Agricultural and Biological Engineering, January 2017.
http://edis.ifas.ufl.edu/ae517

Smart Strawberry Advisory System for Mobile Devices

Freshly harvested strawberries.Like the web-based SAS, the SAS: Strawberry Advisory System mobile app monitors real-time and forecast weather conditions that increase the risk for Botrytis (gray mold) and anthracnose fruit rots, providing risk level information for each disease. The app provides easy access to the information growers need to make spraying decisions in the field, saving them time, helping improve disease control, and avoiding unnecessary fungicide applications. This 3-page fact sheet provides an overview of the SAS mobile app. Written by Clyde W. Fraisse, Natalia Peres, and José Henrique Andreis, and published by the UF Department of Agricultural and Biological Engineering, August 2015.
http://edis.ifas.ufl.edu/ae516

Estimated Water Savings Potential of Florida-Friendly Landscaping™ Activities

Figure 1. Any homeowner can independently adopt the Florida-Friendly Landscaping practices as long as they are consistent with HOA requirements and other restrictions. Credit: Michael Gutierrez, UF/IFAS
To help homeowners predict the impact of implementing some of the water conservation measures listed on Florida-Friendly Landscaping™ checklist, this 5-page fact sheet offers a table of estimated water savings. Homeowners can select activities which are the best fit for their landscape and can also see which have the most conservation potential. The water savings is compared to a baseline case of typical irrigation behavior. This 5-page fact sheet was written by Mackenzie Boyer and Michael Dukes, and published by the UF Department of Agricultural and Biological Engineering, August 2015. (Photo credit: Michael Gutierrez, UF/IFAS)
http://edis.ifas.ufl.edu/ae515

Field Observations During the Eleventh Microwave Water and Energy Balance Experiment (MicroWEX-11) from April 25 through December 6, 2012

Figure 1. The University of Florida's C-band Microwave Radiometer system (UFCMR) Credit: J. Casanova, University of FloridaThis new report from UF/IFAS researchers provides another set of observation data that can be used to develop better models for accurate prediction of weather and near-term climate. It describes the observations conducted during the MicroWEX-11, a season-long experiment incorporating active and passive microwave observations for bare soil, elephant grass, and sweet corn using a variety of sensors to understand land–atmosphere interactions and their effect on observed microwave signatures. These observations match that of satellite-based passive microwave radiometers and NASA’s recently launched Soil Moisture Active Passive (SMAP) mission. This 96-page report was written by Tara Bongiovanni, Pang-Wei Liu, Karthik Nagarajan, Daniel Preston, Patrick Rush, Tim H.M. van Emmerik, Robert Terwilleger, Alejandro Monsivais-Huertero, Jasmeet Judge, Susan Steele-Dunne, Roger De Roo, Ruzbeh Akbar, Ella Baar, Max Wallace, and Anthony England and published by the UF Department of Agricultural and Biological Engineering, July 2015.
http://edis.ifas.ufl.edu/ae514

SmartIrrigation Avocado App: A Step-by-Step Guide

Figure 1. SmartIrrigation Avocado app iconUF’s SmartIrrigation Avocado for iOS and Android platforms provides a simple ET-based method to schedule irrigation and is expected to provide 20% to 50% water savings based on findings with other schedule tools. This 6-page fact sheet provides configuration instructions and main menu features. Written by D. Mbabazi, K. W. Migliaccio, J. H. Crane, J. H. Debastiani Andreis, C. Fraisse, L. Zotarelli, and K. T. Morgan, and published by the UF Department of Agricultural and Biological Engineering, May 2015.
http://edis.ifas.ufl.edu/ae513

The Role and Impact of Technology on Supply-Chain Management in the Food Industry

Figure 5. Various retail packaging for fresh fruit Credit: Thomas Wright, UFIn competitive markets, innovations such as electronic devices, information technology, and green and sustainable technologies can provide a competitive advantage in managing the supply chain, and determine which operations succeed and which fail. The information in this article is intended to provide insight regarding the potential benefits and limitations of these technologies so that firms in the food industry can make more informed decisions on which technologies should be incorporated into their own systems and to what degree. This 5-page fact sheet was written by Jonathan A. Watson, Allen F. Wysocki, and Ray A. Bucklin, and published by the UF Department of Agricultural and Biological Engineering, April 2015. (UF/IFAS photo: Thomas Wright)
http://edis.ifas.ufl.edu/ae511

Your Farm Weather Station: Installation and Maintenance Guidelines

Figure 1. ET107 model weather station. Credit: Campbell ScientificWeather is a prominent factor in the success or failure of agricultural enterprises, and the technology is improved and less expensive, so many farmers are installing farm-based weather stations for tracking weather conditions, scheduling irrigation, make decisions related to cold protection, and accomplish other tasks. But management decisions must be based on high-quality observations. Sensors must meet accepted minimum accuracy standards, the station must be sited properly and well-maintained.
This 5-page fact sheet provides farmers with basic guidelines for installing and maintaining a weather station. Written by Clyde W. Fraisse, George W. Braun, William R. Lusher, and Lee R. Staudt, and published by the UF Department of Agricultural and Biological Engineering, April 2015.
http://edis.ifas.ufl.edu/ae502