Data Collection

Data Collection: Poultry Integrations

Gary D. Butcher and Amir H. Nilipour

Using Focus Group Interviews for Planning or Evaluating Extension Programs

Sebastian Galindo-Gonzalez and Glenn D. Israel

Conducting Vegetation Surveys Using Geotagged Photographs from Smartphone and Unmanned Aerial Systems

J. S. Glueckert, A. E. Riner, J. K. Leary, K. L. Gladding, and E. C. Russell

This publication aims to describe a simple method of importing and displaying geotagged images from unmanned aerial systems (UAS) or smartphones as vector symbols that are scaled and oriented to co-register with base layer maps in a geographic information system (GIS) without the need for processing into an orthomosaic. Instructions in this publication are for QGIS, version 3.28 LTR, but can be easily transferable to other GIS software. These methods offer an efficient and effective way to view high-resolution aerial images and photo-point image surveys in a GIS environment, allowing for basic analysis such as annotating features or points of interest. Written by J. S. Glueckert, A. E. Riner, J. K. Leary, K. L. Gladding, and E. C. Russell, and published by the UF/IFAS Department of Agronomy, February 2026.

Determining Sample Size

Glenn D. Israel

Perhaps the most frequently asked question concerning sampling is "What size sample do I need?" The answer to this question is influenced by a number of factors, including the purpose of the study, population size, the risk of selecting a "bad" sample, and the allowable sampling error. This paper reviews criteria for specifying a sample size and presents several strategies for determining the sample size.

How to Identify If Your Time Series Inputs Are Adequate for AI Applications: Assessing Minimum Data Requirements in Environmental Analyses

Eduart Murcia and Sandra M. Guzmán

This publication is intended for scientists, technicians, and decision-makers who want to start using machine learning (ML) in their projects. It provides an overview of the factors that should be considered when employing ML applications with time series (TS) data as input. Written by Eduart Murcia and Sandra M. Guzmán, and published by the UF/IFAS Department of Agricultural and Biological Engineering, January 2024.

Herping Adventures: A Guide to Exploring and Documenting Reptiles and Amphibians with iNaturalist

Brittany M. Mason, Ty Smith, and Corey T. Callaghan

The purpose of this publication is to provide guidance and tips on how to enter the wonderful world of reptiles and amphibians, or "herping," and, further, how to leverage iNaturalist to document herp observations and contribute to science. The intended audience is anyone who is interested in the natural world and wants to learn more about observing herps, identifying herps, and contributing to science by adding their observations to iNaturalist.

Shifting Focus: Collecting Focus Group Data Online

Anissa M. Zagonel, Audrey E. H. King, Lauri M. Baker, Angela B. Lindsey, Sandra Anderson, Ricky W. Telg, and Ashley McLeod-Morin

This new 5-page publication of the UF/IFAS Department of Agricultural Education and Communication presents what focus groups are, the differences between in-person and online focus groups, potential platforms for hosting online focus groups, advantages and disadvantages to online focus groups, and best practices for conducting your own online focus groups. Researchers and practitioners alike can use this document to guide their process of conducting online focus groups. This article only discusses conducting online focus groups through online videoconferencing software.