Digital Commons Network^™

Quantifying Tree Height Variation Using Uav And Airborne Lidar, Bowen Li, Jean Fritz Saint Preux

Symposium of Digital Agriculture

Forests are not uniform environments; variations in elevation, sunlight, and edge effects create distinct microhabitats that influence how trees grow and thrive. For example, trees in low-elevation natural forests may exhibit different growth conditions than those at higher elevations, even when other factors remain constant. Uneven sunlight distribution across the canopy further shapes growth patterns. In this pilot study, we compared tree height at forest edges and within the interior of a monoculture stand at the Wright Forestry Center. Tree height was measured from LiDAR and drone-based photogrammetry data. We envision future data collection from additional monocultures and the application …

Dronesar: A Uav Based Synthetic Sperture Radar For Soil Moisture Remote Sensing, Leo Li, Lena Azimi, Melba Crawford, James Garrison

Symposium of Digital Agriculture

Soil Moisture is a critical component of the earth water cycle and very important for plant health and development. DroneSAR is a drone based synthetic aperture radar technology that can provide high resolution field level soil moisture measurement data that can be used for flood/drought monitoring and crop yield prediction. Currently, this technology is under algorithm development for soil moisture retrieval.

Applied Statistical And Deep Learning Methods For Multi-Environment Genomic Prediction In Maize, Christopher Barron, Lorena Benfica, Doug Crabill, Mark Gee, Tom Koch, Seyi Ogunmodede, Chaewon Oh, Hyeong Kyun Park, Nicholas Roberts, Huayu Tang, Mitchell Tuinstra, Jason Vanalstine, Mark Ward

Symposium of Digital Agriculture

Predictive breeding has quickly become a powerful tool for plant breeding because of its ability to apply a high level of genotypic selection in non-target environments. However, much of the work regarding predictive breeding has used training data that is highly replicated and maintains the same genotypes and locations over multiple years, for instance the Genomes2Fields project. In commercial breeding programs, selection from predictive breeding could have the greatest return early on, when there is a great deal of genetic diversity. However, training models on this early pipeline data is difficult because genotypes are generally not replicated, and locations may …

Predicting Soil Health Parameters At Field Scale Using Geospatial Analytics, Lizeng Zhao, Siddhartho S. Paul, Christian H. Krupke, Yichao Rui

Symposium of Digital Agriculture

Resilient agricultural practices are crucial for the sustainability of agroecosystems, crop productivity, and biodiversity conservation. In Fall 2023, research sites were established at Purdue Agricultural Centers across Indiana to compare conventional and resilient agricultural practices (e.g., cover cropping and no-tillage) for long-term changes in soil health, biodiversity, and crop yield. This research conducted baseline soil health assessments at four of these experimental sites using predictive digital soil mapping. In Fall 2024, we collected soil samples using a 25 x 25 m grid from all four sites at depths of 0–7.5 cm and 7.5–15 cm. We also produced a geodatabase that …

Advancing Soil Health Management Through Spatially Optimized Soil Sampling, Nelson O. Otieno, Keith Cherkauer, Shalamar Armstrong, Siddhartho S. Paul

Symposium of Digital Agriculture

Accurately monitoring soil health across farms requires sampling designs that capture spatial heterogeneity without excessive cost. Our systematic review of digital soil mapping approaches screened 181 articles and retained 31 for detailed analysis. Most studies either did not optimize sampling spatially or did not report doing so. Four designs dominated: simple random sampling (SRS), stratified random sampling (StRS), spatial coverage sampling (SCS), and conditioned Latin Hypercube Sampling (cLHS). Only 7% of papers explicitly evaluated spatial representativeness before modeling, typically using Bhattacharyya distance (BD) and Kullback–Leibler divergence (KLD).

We validated insights from the review with two case studies using grid soil …

Multi-Modal Spectral Fusion Foundation Model​, Udaiveer Singh, Rajiv Ranjan, Anjali Aggarwal, Shashank Tamaskar

Symposium of Digital Agriculture

Farms run on data, but our sensors rarely agree: optical is cloud-limited, radar sees structure but not color, UAVs arrive on their own schedule, and resolutions vary by field and season. We introduce a modular multisensor fusion backbone that turns heterogeneous streams (e.g., Sentinel-2, Sentinel-1, Planet/UAV) into a single, field-centric representation designed for agronomic decision-making. The system leverages strong pretrained encoders per modality and a compact cross-modal exchange layer to integrate signals while remaining resilient to gaps (missing sensors, clouds, irregular cadence) and shifts in scale. Training relies on broadly applicable self-supervised objectives and large unlabeled archives, minimizing label demands. …

Site-Specific Mechanical Weed Management For Specialty Crops Through Ai-Driven Robotics, Sandesh Poudel, Sunoj Shajahan

Symposium of Digital Agriculture

Weed management is one of the most urgent and unresolved challenges in specialty crops in most regions in the United States. For crops like horseradish, which are largely cultivated in Illinois and Wisconsin, the weed issue is magnified because of the crop’s long growing season and sensitivity to chemical applications. Farmers in these states are responsible for more than 80% of the US horseradish market. However, for the current weed control practice, they rely on expensive manual labor, which is in short supply, or repeated application of unlabeled herbicides that degrade soil and lead to a herbicide-resistant weed population. Therefore, …

Quantitative Trait Loci (Qtl) Mapping For Protein Content, And Amino Acids In A Cowpea Magic Population, Jean Paul Iyakaremye, Jeneen Fields

Symposium of Digital Agriculture

Cowpeas (Vigna unguiculata (L.) Walp.) are an important food crop and an essential part of traditional cropping systems in tropical and subtropical regions. In addition to their resistance to harsh environmental conditions, cowpeas serve as a significant source of protein for both human and animal consumption. They are also increasingly targeted as a crop due to their potential to contribute to the growing global demand for plant-based protein. Seed protein content ranges from 23% to 32% of seed weight in breeding lines from the International Institute of Tropical Agriculture (IITA) collection. Most breeding programs have focused on drought tolerance, as …

An Ai-Enhanced Soft Robotic System For Selective Strawberry Harvesting, Moeen Ul Islam, Cheng Ouyang, Jiajia Li, Xinda Qi, Qianwen Zhang, Dong Chen

Symposium of Digital Agriculture

Strawberry harvesting is labor-intensive and requires delicate, selective handling. Current robotic solutions rely mostly on rigid arms, which lack flexibility and often cause fruit damage or require complex mechanisms. To address this, we propose an intelligent soft robotic system for efficient and gentle strawberry harvesting. The system combines an AI-powered computer vision module to detect ripe strawberries, a soft silicone-based robotic arm to handle fruit without damage, and a data-driven control method for smooth, adaptive movement. An adjustable ground vehicle supports flexible field navigation. Initial results show a harvest success rate of 66.7% and an average speed of 240 strawberries …

Generalizing Yield Prediction And Evaluating The Common Factors Influencing The Models, Xiaoyu Zhang, Sunoj Shajahan

Symposium of Digital Agriculture

This study combines Sentinel-2 satellite images with yield monitoring data from fields to evaluate yield predictions from spatial, temporal, and modeling dimensions. Combining the Matern-Kriging method, vegetation index and machine learning models, four key aspects were studied: the influence of spatial resolution on ground truth interpolation, the influence of spatial proximity of training fields, single year and multi-year prediction performance, as well as the influence of spatial smoothing for yield map. Random forest is used as the main predictive model. The results show that a smaller Kriging grid size retains more spatial details, while larger grid leads to detail loss. …

Evaluating Cover Crop Performance: A Spatial Approach To Biomass And Nutrient Prediction With Uas Imagery, Sergio Rubiano Sosa, Daniel Quinn, Shalamar Armstrong

Symposium of Digital Agriculture

Farmers and agronomists need accurate, efficient methods for evaluating cover crop (CC) biomass and nutrient content to optimize fertilization strategies and improve soil health. Traditional biomass assessments are labor-intensive and time-consuming, often delaying timely data-driven management decisions. While multispectral cameras, including near-infrared (NIR) and RedEdge sensors, provide high-accuracy data for this purpose, their high cost limits accessibility for many farmers. This study explores the potential of using regular RGB cameras on unmanned aerial vehicles (UAVs) as an affordable alternative to multispectral sensors for estimating CC biomass and key nutrients such as nitrogen (N) and sulfur (S).

Data was collected from …

A Simple Approach To Delineating Field Boundaries Using Satellite Imagery, Seth T. Van Hoveln

Symposium of Digital Agriculture

Accurate delineation of agricultural field boundaries is crucial for farm management, research, and policy development. However, publicly available boundary datasets are often limited in accuracy, very expensive, or use deep learning architectures that require extensive annotated data that are not available, limiting access. This project presents a simple, image-processing-based method for delineating field boundaries using openly available satellite images. Our method manipulates the images using a variety of image processing techniques and is able to generate an accurate boundary for a selected field. By providing a simple and accessible solution, this approach has the potential to transform boundary delineation practices, …

High Throughput Phenotyping For Improved Sorghum Protein Digestibility, Erin C. Widener, Mitchell R. Tuinstra

Symposium of Digital Agriculture

Protein digestibility (PD) is a quantitative trait that is generally lower in sorghum than other cereals such as corn & rice. This affects the ability for humans and animals to obtain vital nutrients from sorghum food products and feedstuffs. Previous efforts helped create and identify sorghum lines with highly digestible protein (HDP) phenotypes using mutagenesis. This creates variation for the trait that can be exploited by breeding programs. However, phenotyping large populations is highly time consuming using wet-chemistry techniques and can exhaust resources quickly, leading to bottlenecks in development of breeding objectives. Near-Infrared Spectroscopy (NIRS) offers a fast, non-destructive alternative …

Geospatial Modeling Of Spatiotemporal Variability In Farm-Scale Soil Organic Matter Dynamics, Amiya Kalra, Rachel Stevens, Shams R Rahmani, Daniel J. Quinn, Shaun Casteel, Siddhartho S. Paul

Symposium of Digital Agriculture

Soil organic matter (SOM) is a key indicator of soil health, which is vital for maintaining future crops and income. Furthering our understanding of long-term variability in SOM and digital soil mapping methods of SOM will help farmers make management decisions supporting stable yields. While SOM dynamics have been studied in some regional-scale and plot-level studies, their spatiotemporal variability at farm scale is largely unstudied. In this research, we used geospatial models to identify and interpret long-term trends (2015-2024) in SOM at farm scale using the Purdue University research farm in West Lafayette, Indiana as a case study. Our SOM …

Spatial Modeling Improves Field Assessment Of Integrated Scn Management, Vinicius Garnica, Horacio D. Lopez-Nicora

Symposium of Digital Agriculture

Field spatial heterogeneity often obscures treatment effects in soybean cyst nematode (SCN) management trials. We compared tensor-product penalized spline (TPS) models to a traditional split-plot ANOVA model to evaluate two genetic resistance sources (PI 88788 and Peking) and fluopyram seed treatment against HG Type 1.2.5.7 SCN populations in Ohio. By definition, HG Type 1.2.5.7 reproduces >10% of the level on a susceptible soybean line when tested on Peking and PI 88788 resistance sources. TPS models substantially improved model fit (62.2 AIC units for yield, 27.5 for reproduction factor) and precision (lower standard errors; for example 67 to 55 kg ha⁻¹) …

Methodology For Evaluating Precision Spraying Using Drones., Tulisha Malichi, Victor Hugo Morales Peña, Pablo Ignacio Gonzalez Pastor, Helberth Manuel Natareno Alvarado, Cecilia Alejandra Osorio Fuentes, Jan Carlos Sáenz Mendoza, Elvia Jimena López Cordon, María Nadishdade Jesús Quiej Espinoza, Wilder Desaily Montufar Alvarado, Gerardo Daniel Quiñonez Lllescas

Symposium of Digital Agriculture

This study presents a comprehensive methodology for evaluating precision spraying in agriculture using drone technology. Precision spraying has become a key innovation in sustainable farming, offering increased accuracy, reduced waste, and minimized environmental contamination. However, to ensure these benefits are realized, drones must be properly tested, calibrated, and validated under real field conditions. The proposed methodology integrates drone flight calibration, field-based spraying trials, and post-field analysis using hydrosensitive cards processed through specialized software tools, such as ImageJ and StainMaster. By systematically varying flight parameters such as altitude, speed, and nozzle type, the study assesses how these factors influence droplet size, …

An Academia-Community Partnership Aiming To Benefit The Well-Being Of Shelter Cats And Promote The Learning Outcomes Of College Students, Shlomit Flaisher-Grinberg

People and Animals: The International Journal of Research and Practice

More than three million cats enter U.S. animal care and control facilities annually. Although many are adopted, others spend a prolonged amount of time at the animal shelter while facing a variety of stressors. The current project explored the possibility of creating an academia–community partnership aiming to establish a college-based foster program that will allow undergraduate students to socialize and train shelter cats as a part of an academic course. It was hypothesized that the program will positively impact the well-being of shelter cats, improve their adoption outcomes, and support students’ learning outcomes. Students enrolled in the Learning course at …

Indiana At A Glance: County Trends, 2025 Edition, Roberto Gallardo

Purdue University Press Books

Indiana at a Glance: County Trends, 2025 Edition provides an overview of macro socioeconomic and demographic trends based on county-level data in ten-year periods in Indiana, the upper Midwest region, and the nation. Analyzing data primarily from 2013 through 2023, this book presents information that contextualizes the design and implementation of specific policies enacted by elected officials and community leaders, and reveals the impact these initiatives have on the public.

Inspired, in part, by the United States Department of Agriculture’s Rural America at a Glance reports, as well as the author’s more than twenty years of work in the field, …

Birck Nanotechnology Center Technical Overview, Purdue University Office Of Research, Ron Reger

University General Facility Boilerplate Descriptions

Overview of the Birck Nanotechnology Center infrastructure including the Scifres Nanofabrication Laboratory and a suite of specialized laboratory facilities.

Tacscope: A Miniaturized Vision-Based Tactile Sensor For Surgical Applications, Md Rakibul Islam Prince, Sheeraz Athar, Pokuang Zhou, Yu She

School of Industrial Engineering Faculty Publications

The lack of tactile feedback in robot-assisted minimally invasive surgery (RMIS) limits surgeons’ ability to palpate tissues, a critical technique for locating abnormalities such as tumors. To address this challenge, we introduce TacScope, a novel, vision-based tactile sensor leveraging the magnification properties of a spherical-surface elastomer to provide tactile feedback for advanced clinical applications. TacScope features a robust, low-cost, and easyly fabricate design, enabling seamless integration into surgical robotic setups. It reconstructs high-resolution 3D geometry from variations in particle-density distribution across its elastomer surface, requiring only a single image for calibration. The curved elastomer membrane alters particle-density distribution under …

Mortal Writing: Toward Braver Concepts Of “Better Writers,” Peerness, And Nationality, Enrique Paz, Annalee Roustio

The Writing Center Journal

Reflecting on experiences with two Afghan students writing in response to events following the U.S. withdrawal from Afghanistan in 2021, this essay challenges traditional writing center practices in response to the evolving and urgent writing needs of diverse (international) student populations. Focusing on the intersectional identities of student writers and the geopolitical realities they face, we develop further the call to transform writing centers into “brave spaces.” Deploying this framework of bravery, we call for a reevaluation of the concept of “better writers,” of empathy constructed primarily through peerness, and of the current conceptualization of nationality in writing center scholarship. …

“It Would Literally Take The World To End For Us To Do This”: Writing Center Consultants’ Affective Responses To Consulting Modalities, Anita Long, Destiny R. Brugman

The Writing Center Journal

This article discusses findings from semi-structured interviews with writing consultants about their affective experiences working across three different consulting modalities: in person, asynchronous, and synchronous. This study offers affect as a lens for understanding consultants’ responses to and strategies for consulting in multiple modalities and argues that by attending to affect, emotion, and disposition in consulting we can better support our consultants when they’re consulting in different modalities.

“I (Still) Need Help On Many Things”: A Writing Center Replication Study Of First-Generation College Students’ Writing Challenges And Cultural Capital, Red Douglas, Ashley Cerku, Isabelle Lundin, Mary Gallagher, Xavier Iriarte, Sophia E. Williams, Kaylie Williams

The Writing Center Journal

Research has increasingly addressed first-generation (FG) students both in and outside the center (Baelemian & Feng, 2013; Bond, 2019; Denny et al., 2018; Ward et al., 2012), but there remains a need to address this unique student population from the perspective of critical theory. In a replication study of Bond’s 2019 “‘I Need Help on Many Things, Please’: A Case Study Analysis of First-Generation College Students’ Use of the Writing Center,” we examined the needs and perceptions of self-reported FG students in a writing center at a large, regional, public R2 university in the Midwest. We gathered preexisting digital data …

“I Just Need Another Set Of Eyes”: Understanding Students’ Idea Of The Writing Center, Isabelle M. Lundin, Neal Lerner

The Writing Center Journal

In this article, we describe writing center clients’ “idea” of the writing center based on interviews with 26 writing center users and qualitative coding of interview transcripts. Participants’ constructs of the writing center provide a lens to better understand how they perceive writing as an activity, the “writing culture” of the institution, the role of the writing center in their writing processes, and, ultimately, if they see writing centers in the way we would expect them to. The tensions we derived from our data are (1) between who and what tutors are and offer: discipline-specific expertise (including the disciplines of …

Exploring The Efficacy Of A Source-Based Writing Tutoring Intervention For Multilingual Students In The Writing Center, Dana Lynn Driscoll, Osman Ozdemir

The Writing Center Journal

Source-based writing skills, which include evaluating, synthesizing, and citing sources, are skills that students are expected to acquire as part of college-level writing. Unfortunately, many multilingual writers (MLWs), especially those in advanced degree programs, lack programmatic support and instruction. Thus, writing centers represent a critical site to offer MLWs tutorial-based support. Our study examined whether or not writing centers can help MLWs develop—and transfer—source-based writing skills in a sequence of three tutorials. We recruited five advanced student MLW participants from different cultural backgrounds who were uncomfortable with source use. Through pre-and postwriting samples, interviews, writing process recording videos, and a …

Front Matter, Georganne Nordstrom, Isaac K. Wang, Sherry Wynn Perdue

The Writing Center Journal

Front matter and introduction for Writing Center Journal 43.2.

The Rhetorical Function Of Writing Center Employee Handbooks, Talisha Haltiwanger Morrison

The Writing Center Journal

In his award-winning book, Around the Texts of Writing Centers, R. Mark Hall (2017) asserts the importance of everyday writing center texts, claiming that these documents “both enact and forward writing center scholarship” (p. 3). It is Hall’s position that such “everyday” documents are essential to understanding the work of writing centers, but that their very ubiquity leads writing center scholars and administrators to ignore them or take their functions for granted. In this study, I take up Hall’s call for more scholarly attention to everyday writing center texts through a thematic rhetorical analysis of nine writing center employee …

Back Matter, Georganne Nordstrom, Isaac K. Wang, Sherry Wynn Perdue

The Writing Center Journal

Back matter for Writing Center Journal 43.2.

Insights From A Simple Mathematical Model Of Autism Spectrum Disorders, Charles F. Babbs

Weldon School of Biomedical Engineering Faculty Working Papers

This preliminary report explores insights about mechanisms of autism spectrum disorders (ASDs) gained from a mathematical model of interconnected clusters of excitatory neurons. This local, integrate-and-fire, spiking neural network is subjected to random noise from other populations of excitatory and inhibitory neurons outside the network. Its emergent behavior in response to different ratios of inhibitory to excitatory noise mimics several aspects of ASDs. The spiking neural network functions according to rules of classical neurophysiology, involving resting membrane potential, threshold potential, excitatory or inhibitory post-synaptic potentials, action potential, and refractory period. Key parameters include the incremental change in membrane potential, p …

Quantifying Interest In And Sentiment Of Online Media About Greenhouse Gas Emissions From Cattle Production In The United States, Michael L. Smith, Jinho Jung, Nicole Olynk Widmar, Danielle J. Ufer, Maria Berikou, Jayson Lusk

Department of Agricultural Economics Faculty Publications

The public is paying increased attention to the environmental impacts associated with cattle production systems in the US. Thus, cattle producers are increasingly exploring ways to communicate their efforts to reduce those environmental and climate impacts. This study uses online and social media data from 2018 to 2022 to examine public interest in and sentiment about beef and dairy cattle production when discussed within the context of greenhouse gas (GHG) emissions. Variation in mentions and net sentiment over the reporting period is quantified and analyzed. Over the period of data collection, which was interrupted by the COVID-19 pandemic, we find …