Mobile Technology and Apps

Clyde Fraisse, Natalia A. Peres, andJ. H. Debastiani Andreis

Haimanote K. Bayabil, Kati W. Migliaccio, J. H. Debastiani Andreis, Clyde Fraisse, Kelly T. Morgan, andG. Vellidis

As freshwater resources become increasingly scarce, efficient irrigation scheduling methods that allow efficient irrigation water uses are required. Migliaccio et al. (2016) have developed an app called Smartirrigation Turf, an easy-to-use mobile tool that delivers information to improve irrigation scheduling for urban turf. The app was only available for Florida and Georgia, but recently, we have made improvements to the app and made it available to any location throughout the contiguous United States. 

Arnold Schumann, Laura Waldo, Perseveranca Mungofa, and Chris Oswalt

A UF/IFAS numbered peer reviewed Fact Sheet. in support of UF/IFAS Extension program: Plant Systems

Lakesh K. Sharma, Rishabh Khanna, and Hardeep Singh

This publication discusses the general concept of web and mobile application development and provides knowledge and stepwise instructions to develop an application in agricultural systems. The primary audience is researchers, extension personnel, consultants, and students who are interested in developing and using web and mobile applications for decision-making.

Chris Oswalt, Jamie D. Burrow, Chris Oswalt, Mongi Zekri, Matthew T. Smith, andAlissa Hevesh

2025–2026 Florida Citrus Production Guide

Mary G. Lusk

The purpose of this publication is to provide step-by-step guidance on how to find soil data about a given parcel of land in the Web Soil Survey. This publication can be used by residents, growers, gardeners, construction personnel, landscape managers, septic system installers and inspectors, and many others. Written by Mary G. Lusk, and published by the UF/IFAS Department of Soil, Water, and Ecosystem Sciences, February 2025.

Santhi Daggubati, Xu Wang, Xue Zhou, Shubham Singh, andJessica Chitwood-Brown

Manual quantification of specialty crop traits, such as flowers and fruits, is often labor-intensive, time-consuming, and inconsistent, limiting scalability and precision. We present PhenoSnap, an artificial intelligence (AI)-powered web application that provides an intuitive and efficient interface for automated specialty crop trait extraction from images. PhenoSnap bridges the gap between advanced computer vision technologies and practical agricultural applications by eliminating the need for programming expertise. This ready-to-use solution can enable growers, breeders, and Extension faculty to accelerate field work and enhance decision-making related to strawberry and tomato yield estimation for breeding selections and strawberry runner management. Written by Santhi Daggubati, Xu Wang, Xue Zhou, Shubham Singh, and Jessica Chitwood-Brown, and published by the UF/IFAS Department of Agricultural and Biological Engineering, June 2026.

Clyde W. Fraisse, Mauricio A. Z. Karrei, and Margaret Walsh

This guide introduces users to a recently developed web-based tool on AgroClimate.org that was designed to systematically monitor climate indicators and detect anomalies with the potential to affect the agricultural industry in Florida and elsewhere in the continental United States. Written by Clyde W. Fraisse, Mauricio A. Z. Karrei, and Margaret Walsh, and published by the UF/IFAS Department of Agricultural and Biological Engineering, January 2024.