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West Lafayette, Indiana - West Lafayette, Indiana THEMATIC CATEGORIES’ TOP ABSTRACTS Life Sciences Heterologous Expression of the Anaerobic Fungal Mevalonate Pathway by Elizabeth Frazier (Poster #67) Differences in Lipid Metabolism Gene Expression Between Non-Metastatic and Metastatic Breast Cancer Cells by Josie Asher (Poster #134) Social Sciences/Humanities Big Sister, Big Brother: A Mixed Methods Study on Older Siblings' Role in Infant and Young Child Feeding and Care in Rural Tanzania by Morgan Boncyk (Poster #136) Physical Sciences Chemistry Laboratory Experiment: Molecular Interactions in Liquid Crystals by Carissa Gettelfinger and Kylie Smith (Poster #243) Mathematics/Computational Sciences Using Information Visualization Techniques to Uncover Patterns in Pubescent Lupus Data by Nathan Kanter (Poster #281) Innovative Technology/Entrepreneurship/Design The Impact of Virtual Simulation-based Training on Speech-Language Pathology Students in the Graduate Dysphagia Course: A Pilot Study by Jennine Bryan (Poster #137) Thematic awards are chosen and presented by Purdue University Libraries & School of Information Studies THANK YOU TO THE CONFERENCE SPONSORS College of Agriculture College of Liberal Arts Purdue Archives & College of Education College of Pharmacy Special Collections College of Engineering College of Science Purdue Polytechnic Institute College of Health & Honors College Purdue University Libraries Human Sciences & School of Information Krannert School of Studies Management SPECIAL APPRECIATION TO THE CONFERENCE PLANNING COMMITTEE’S UNIT DELEGATES FOR ORGANIZING THIS EVENT Oral Presentation Abstract Number: 1 :: Life Sciences College of Agriculture Effects of Aging on Genes involved in Photoreceptor Survival Author: Kimaya Bakhle, College of Agriculture Abstract: Abstract Redacted Research Mentor: Dr. Vikki Weake, Biochemistry Juan Jauregui, Biochemistry Oral Presentation Abstract Number: 2 :: Life Sciences College of Agriculture Grinding behavior in mice Author: Haley Davis, Agriculture Abstract: Food grinding is an abnormal behavior where mice grind their food into a fine dust called orts, indicating poor welfare. Supplementing sunflower seeds can lower ort production possibly due to the seed’s nutritional content or manipulating the seed as enrichment. Orts have also been found to have less energetic content than the starting diet. We hypothesized that ort production and content would differ based on nutritional treatment. Twenty-four cages of mice (Crl;CD1; 12 male: 12 female, 4 mice/cage), were randomly allocated to a treatment: control, sunflower seeds (50g), or pelleted seed diet (25g). Baseline orts were determined over 3 weeks (baseline) then treatments were provided for 3 weeks (during). Treatments were removed (after) and cages monitored for another 3 weeks. Orts were weighed each week. The difference from baseline was calculated during and after treatment provision. Bomb calorimetry determined ort cal/g. Data were analyzed as a GLM. Ort production increased in cages supplemented with the pelleted seed diet compared to controls (F2,21=3.72; P=0.04). Ort production increased in seed-like diets after treatments were removed. Sex did not influence ort weight (P>0.05). Ort cal/g was the same across all treatments (F2,18=0.36; P=0.70). In this study, mice ground more when supplemented with pellets similar in nutrition to sunflower seeds, but the orts energy content did not differ between treatments. The mice may be grinding regular diet to gain access to the seed- like pellets. Future research could provide diets in different feeders to determine if grinding occurs when given free access to supplemental feed. Research Mentor: Dr. Brianna Gaskill, Animal Science Lindsey Robbins, Animal Science Oral Presentation Abstract Number: 3 :: Mathematical/Computation Sciences College of Agriculture Digital phenotyping Author: Zhengsen Fu, Engineering Yiming Li, Engineering Xinlue Liu, Engineering Miguel Rodriguez, Engineering Abstract: As machine learning algorithms advancing rapidly throughout the decades, it becomes applicable in many fields. One such utilization is to process image data, which was previously manually processed. The aim of this study was to explore the possibility of implementing such technology to support agricultural researches. With images from Purdue University Controlled Environment Phenotyping Facility, masked RCNN models to detect spikes were trained. The training data were obtained in a standard controlled environment with identical target center position and photo angle to yield similar area of interest for every picture. As the result, the models have good performances recognizing plants from images obtained in the same facility, yielding a mAP (mean average precision) of 85.51% at peak, which later becomes a convenient tool for researchers to analyze the image data. However, for other spike images from the internet or from the field, the performance would be unsatisfying. Large number of objects cannot be detected or recognized as expected. The mAP was less than ten per cent. The main reason leading to this result is that the classifier was fully trained over the lab images. Despite the poor performance on internet images, for our current purposes of only implementing masked RCNN within the facility, it would be enough. The team is considering expanding the training data sets by including more images from the field, so that the functionality of the model would not be limited to only the facility Research Mentor: Augusto Cesar Magalhaes de Souza, Digital phenotyping Yang Yang, Oral Presentation Abstract Number: 4 :: Life Sciences College of Agriculture The Role of a Putative Amino Acid Transporter in Nitrogen Response in Arabidopsis thaliana Author: Wenyi Ran, Agriculture Abstract: Abstract Redacted Research Mentor: Ying Li, Horticulture & Landscape Architecture Russell Julian, Horticulture & Landscape Architecture Oral Presentation Abstract Number: 5 :: Social Sciences/Humanities College of Agriculture Measuring Interest and Engagement in Extension Programming Author: Ashley Rosenkrans, College of Agriculture Danielle Marks, College of Agriculture Abstract: In extension programming, it is crucial to use evidence-based methods to optimize participant learning. However, there is limited implementable strategies to review and quantify programming impact on participants. The objective of our study was to evaluate and describe participant interest and engagement in the inaugural offering of the Shell Egg Academy. We randomly selected eight sessions (25-40 participants/session) across 16 total offerings and evaluated participant engagement, interest, and motivation. Instructor (n = 8) teaching type was recorded during each of the sessions and each instructor taught only one session. A questionnaire was administered immediately following each session and contained Likert-style questions to evaluate interest, motivation, and self-reported engagement. Sessions were recorded and reviewed using the Behavioral Engagement Related to Instruction protocol. Overall, instructors selected lecture as the primary instructional tool, providing little variation in teaching strategies. Participant situational interest, including exploration intention, instant enjoyment, and attention demand was moderate to high during each session. Intrinsic motivation and identified regulation were also moderate to high during the sessions, indicating that participants felt a personal importance and natural enjoyment in participation. Participant engagement did not differ between sessions. This study is one of the first to describe participant interest and motivation on engagement in extension programming. Additional work is needed to better understand the impact of adopting different instructional strategies to programming in order to maximize participant experience and build evidence-based program evaluation practices. Research Mentor: Elizabeth Karcher, Animal Sciences Darrin Karcher, Animal Sciences Oral Presentation Abstract Number: 6 :: Life Sciences College of Agriculture Coupling Metabolic Source Isotopic Pair Labeling and Genome Wide Association for Metabolite and Gene Annotation in Plants Author: Abigail Sipes, Agriculture Abstract: To deepen our understanding of the plant gene function, it is important that we advance our knowledge of plant genomes and metabolic activity. It is important to have a solid understanding of the genes that are responsible for the synthesis of certain metabolites. With this information in hand, we will have the capability to unlock higher plant productivity, develop new strategies to protect plants from stressors, and develop new plant-based products. This project applies isotopic labeling and mutant strategies to identify amino acid-derived metabolites in Arabidopsis and then apply Genome-Wide Association (GWA) to characterize the genes responsible for their synthesis. We will isotopically identify amino acid-derived specialized metabolites in Arabidopsis by feeding wild type Arabidopsis tissues with 13C and 12C labeled amino acids. A computational pipeline will then be used to identify metabolic features that are derived from the labeled amino acids. This project aims to classify metabolites based on the precursor-of-origin to provide the function of annotated genes that are associated with plant metabolism. Research Mentor: Clint Chapple, Biochemistry Oral Presentation Abstract Number: 7 :: Life Sciences College of Agriculture Effect of Dry Aging on Pork Quality Attributes Author: Anna Wagner, Agriculture
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