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Water management practices involve complex decisions and daily operations that are affected by water and nutrient requirements of the crop, temporal distribution of rainfall, and weather conditions. The Citrus Irrigation Management System (CIMS) was developed to assist citrus microirrigation, cold protection, and fertigation management. The system integrates an expert system, conventional control, a crop water requirement simulation model, databases, and irrigation management tools into a single system to assist the decision-making by irrigation managers. The system can be used as an irrigation management tool to automate an irrigation system. Soil moisture sensors and an automated weather station were installed in the field to collect real-time field data for inputs to the system. Both laboratory and field tests showed that the integrated system worked as a management tool for irrigation, fertigation, and cold protection. The system is highly automated and has the potential to improve microirrigation management, to achieve water and energy savings, and to prevent water pollution due to improper fertigation management.

Agricultural scientists currently use desk- or lap-top computers to perform genomic research with on-line databases provided by data acquisition centers such as NCBI or plant-specific databases such as TAIR. However, these researchers are often located at remote sites, distant from any computers. In this case, the databases can not be accessed and the research is postponed until computers and internet service become available. Recently, the emergence of wireless and mobile networks has made possible the extension of web-enabled databases to wider applications and locations. The research proposed here provides a method to facilitate on-line searching of biological databases used in agriculture through the use of mobile, handheld devices such as personal digital assistants (PDAs) and smart phones. The technologies involved include: Web services, WAP, WML, and handheld computing. We demonstrate the application of this technology to a plant-based query and compare the computer and handheld device user-interfaces. These mobile applications not only substantially improve agriculture genome research by simplifying user interfaces, but also provide a convenient, searchable resource in remote locations.

The water surface temperature of Lake Okeechobee under clear sky conditions was investigated in this study through the use of Automatic Picture Transmission (APT) thermal infrared data from the National Oceanic and Atmospheric Administration (NOAA) satellite Advanced Very High Resolution Radiometers (AVHRR). Cloud-free data were acquired during the months of May and December 1989. An image processing approach and regression model were used to convert the grey-level digital numbers of the APT imagery into temperature values. A third-order polynomial equation was successfully used to convert the digital numbers into temperature values with a high coefficient of determination (r2=0·98). The satellite-derived temperatures for Lake Okeechobee were correlated with ground-truth temperature measurements (r2 = 0·74). The results of this study indicate that APT data are capable of being converted into lake surface temperatures with acceptable accuracy. Results of paired Mest and variogram analyses indicate...

Plant pests and diseases cause significant economic losses in agriculture throughout the world. To enable accurate monitoring pest activities, pest detection data are collected, stored, manipulated and analyzed. The ability to track pests and plant diseases through space and time allows us to manage pests wisely and effectively. The use of GIS and GPS technologies has had a considerable impact on pest management. Unlike a traditional GIS application, this work focuses on geo-tagged non-map photographic media. Digital photos are widely used as pest samples for diagnosis. With advances in digital imaging technology, one distinct feature of current digital cameras is that images provide not only pictures of pests, but also the GPS coordinates where the photo is taken, and metadata named Exchangeable Image File Format (EXIF) embedded in the image. Such geo-tagged images provide us with information of what, when and where. Thus images with GPS coordinates can be seamlessly transferred to an information management system to assist with pest tracking and management. This paper describes a web-based system to dynamically extract the EXIF metadata from photos. The system provides an environment to track and map pest information based on the geo-tagged digital pest samples. Geo-based digital imaging is an effective means to collect data and track pests and pathogens.

Pest distribution information for a region is particularly important for specialists and decision makers. Dynamic map is an effective way for pest data visualization and analysis. Traditionally, GIS software is applied to create a visual and dynamic pest distribution map, in which different regions; county, state, or nation, are colored according to the number of pest occurrences. The use of GIS in many cases is only for data visualization. Adobe Flash provides a cost effective alternative in creating dynamic interactive maps based on database, XML representation and ActionScript. This paper presents a dynamic pest mapping mechanism using Adobe Flash instead of expensive GIS software. Flash map retrieves pest data from remote databases and presents the data on a regional demarcated map with proper color legends. Based on Flash map, a generalized map service is developed. This service enables users to create their own customized map which can be embedded in their applications. This solution serves as a useful tool for pest distribution analysis, diagnosing, and plant management. The Flash-based approach can also be applied to other mapping applications.

Water surface temperatures of Lake Okeechobee are measured using automatic picture transmission (APT) thermal infrared data from the National Oceanic and Atmospheric Administration (NOAA) polar‐orbit satellite advanced very high resolution radiometers (AVHRR). The cloud‐free APT thermal infrared data are acquired during the months of May and December, 1989. The spatial temperature variation of Lake Okeechobee is investigated. The correlation of pan evaporation with water surface temperature and solar radiation is studied. A regression model of evaporation based on satellite‐derived water temperature, ground‐measured water temperature, and solar radiation is developed. The results indicate that pan evaporation is highly correlated with the temperature and solar radiation, and that the satellite‐derived lake temperatures have a better correlation (r2=0.84) to the pan evaporation than did the ground‐point measurements (r2=0.68), especially for afternoon situations. This implies that the NOAA polar‐orbit sate...

The main focus of this work is software engineering (SE) and applications development for extension audiences that are users of handheld computers. A SE procedure implemented at the University of Florida to develop applications for use in extension is described. The SE and adoption outlined here focuses on the software life cycle with special emphasis on the assessment of needs of the extension audience and the technical aspects of software development for the Pocket PC.

Agriculture is under constant threat of natural disasters, exotic animal diseases, pests, and potential bioterrorism. In the case of agricultural emergency, county, state, federal, and volunteer organizations need to work together to prevent outbreaks and conduct emergency management. One of the challenges in agricultural emergency management is to provide the right information at the right time. Information technology provides a means to assist decision makers, first responders, and emergency response teams in the event of emergency. To effectively cope in an agricultural emergency, a joint effort based on a new concept, the State Agricultural Response Team (SART), has been made in Florida. This paper describes a newly developed web application that provides a communication bridge and much needed resources for agricultural response teams.

A distance diagnostic and identification system (DDIS) was developed at the University of Florida. The system allows users to submit digital samples obtained in the field for rapid diagnosis and identification of plants, diseases, insects, and animals. DDIS provides an environment for agricultural extension agents and specialists to share information on plants, insects and diseases. Through interactions on the Internet between extension agents and specialists, problems can be quickly communicated and assessed. Specialists around the state can perform diagnosis and identification and provide best management practice recommendations to the users. Turnaround time is reduced from days, or sometimes weeks to hours compared to traditional, manual techniques for submitting biological samples. DDIS is a Java–based three–tier application using Java Remote Method Invocation (RMI) and object database technologies. The preliminary results showed that 27% of samples were positively identified and another 27% of samples were tentatively identified. The system creates a digital image library with associated site, crop, and pest or disorder data that could be used in educational programs, assisted diagnosis, and data mining.