Improving management recommendations for Alternaria leaf blight and head rot of broccoli using fungicide resistance monitoring and population genetics Daniel G. Cerritos Garcia PhD Candidate Plant Science and Landscape Architecture Department Major Advisor: Sydney E. Everhart

Improving management recommendations for Alternaria leaf blight and head rot of broccoli using fungicide resistance monitoring and population genetics   Alternaria leaf blight and head rot (ABHR) is a disease of broccoli that appears in the seedling stage and continues up to harvest. Even minimal black spots on the heads make them unmarketable. In the Eastern US, ABHR is mainly caused by the fungal pathogen Alternaria brassicicola. Other species, including A. japonica, A. alternata, and A. brassicae, can also contribute to disease development. Conventional broccoli growers manage the disease with fungicide applications. They mainly use Quinone-outside inhibitor (QoI) and Succinate dehydrogenase inhibitor (SDHI) fungicides. However, recent reports suggest that resistance may be present in Georgia, New York, and Virginia. Resistance to fungicides occurs when a fungus evolves and acquires a heritable reduction in sensitivity to an anti-fungal agent, such as through mutations. In this study, we sought to investigate if resistance exists in Alternaria populations in the Eastern US, as reports suggest. The standard method used to test Alternaria sensitivity is through spore germination assays. This method is laborious and time-consuming, and measurements can be subjective. The process limits its application to small numbers of isolates. To evaluate many isolates from different regions, a high-throughput method is needed. We developed a microplate assay based on optical density measurements to indirectly estimate inhibition of spore germination by fungicides. Primers to amplify and sequence regions with resistance-conferring mutations for SDHI fungicides were also developed and validated. We used the new high-throughput method to screen more than 600 Alternaria spp. isolates collected in Connecticut, Georgia, Massachusetts, New York, and Virginia between 2019 and 2023. Isolates that showed reduced sensitivity to azoxystrobin (QoI) and boscalid (SDHI) in the microplate assay were further screened for resistance mutations. Results indicated that A. brassicicola, the most abundant species in the Eastern US, was sensitive to azoxystrobin, but multiple resistant isolates to boscalid were detected. Most A. alternata isolates were resistant to both fungicides. The G143A mutation, which confers complete resistance to QoIs, was detected in A. alternata isolates. The H143A mutation, which confers resistance to SDHI, was detected in both species. These results partially explain why fungicides failed to control ABHR. They enable us to make more informed management decisions. Organic growers mainly rely on cultural practices to manage ABHR. Understanding the population biology of the pathogen may help us identify effective cultural practices. We conducted a population genetics study to investigate the structure of A. brassicicola populations in organic farms in Connecticut. High to moderate genetic richness and diversity were observed in most fields in 2022 and 2023. No evidence of recombination was observed, suggesting populations are mainly reproducing asexually. Since we found no evidence of sexual reproduction, we wanted to determine if high genetic diversity was due to multiple introductions of the pathogen. Our data suggests that A. brassicicola has a high dispersal ability. This supports the hypothesis that high diversity results from multiple introductions. These introductions may occur through airborne dispersal of spores or human-mediated dispersal of contaminated seed.

Structural variation mechanisms and their rates in inbred mice

COMMITTEE Dr. Kari Adamsons  Dr. Beth Russell  Dr. Florrie Fei-Yin Ng, Dept of Educational Psychology, The Chinese University of Hong Kong

Xinhao Wang from Nutritional Sciences presents his dissertation on an integrated strategy to reduce strawberry waste using bio-based nanocomposite coatings and a deep learning-powered quality monitoring system. This research addresses the critical challenge of postharvest strawberry loss by developing a comprehensive, dual-domain solution. The findings offer promising sustainable strategies to reduce food waste, enhance food safety, and improve quality management in the perishable food supply chain.

Understanding the Cooling Properties of Forested Wetlands and their Role as Climate Moderators   Heat has been a major issue in the United States being the deadliest weather-related event in the past 30-years. There have been several heat mitigation strategies cities have implemented such as street trees and stormwater infrastructure, but despite these implementations they have not dealt with the main symptoms of heat islands. Land cover change from natural land to dense concentrations of pavement, building and other surfaces that absorb heat contribute to the phenomenon. In contrast, wetlands are cooling islands that can regulate their local microclimate. We aimed to (1) investigate the phenomenon with a systematic review to view current research, (2) conduct our measurement campaign to understand wetland buffer-width and wetland characteristics that influence cooling, and (3) view local climate policy in Connecticut towns and how wetlands fit into their framework. Findings have found that wetlands act as a climate moderator keeping cool in summer and warm in winter. Hydrology plays a huge influence on wetland cooling. Connecticut towns could benefit greatly if they were to implement wetlands into their towns to mitigate heat and improve air quality.

Microbial communities profoundly impact host biology by influencing immune development, metabolic processes, and therapeutic outcomes. However, accurately profiling these communities at sufficient resolution to capture subtle, biologically meaningful differences remains challenging. Variability in microbiome composition—even among genetically identical laboratory animals under controlled conditions—can confound experimental results and hinder reproducibility. Addressing this challenge requires methods capable of experimentally standardizing microbiomes and computationally profiling them with strain-level resolution. First, I will present a bioinformatics workflow capable of handling large-scale microbiome datasets with high resolution. This workflow was used to demonstrate that a single antibiotic-free cecal microbiome transplantation (CMT) effectively standardizes gut microbiomes across genetically diverse mouse populations, reducing unwanted variability without promoting antibiotic-resistant pathogens. I will then introduce AmpliconHunter, a tool developed to facilitate precise identification and tracking of these microbiomes. AmpliconHunter is a highly scalable computational tool for accurate PCR amplicon sequence prediction using degenerate primers. Its performance enables efficient strain-level profiling and evaluation of primer pairs with similar accuracy and significantly improved speed when compared to existing methods. I will also detail my work creating AmpliconHunter2: a SIMD-accelerated update to the original that completes analysis for V1V9 primers on the ~2.4M genomes from the AllTheBacteria project in 38.73 minutes, compared to 419.45 minutes for AmpliconHunter (~10.8x speedup). Finally, I will introduce another tool: Microbiome HiFi Amplicon Sequence Simulator (MHASS) creates realistic synthetic PacBio HiFi amplicon sequencing datasets for microbiome studies, by integrating genome-aware abundance modeling, realistic dual-barcoding strategies, and empirically derived pass-number distributions from actual sequencing runs. MHASS generates datasets tailored for rigorous benchmarking and validation of long-read microbiome analysis workflows, including ASV clustering and taxonomic assignment. Together, these innovations will provide practical, robust and scalable methods to address microbiome variability, improving reproducibility and translational potential in microbiome-focused biomedical research. All tools are made available on GitHub under an MIT license. AmpliconHunter and AmpliconHunter2 are also made available as freely accessible web servers at https://ah1.engr.uconn.edu and https://ah2.engr.uconn.edu/.

Title: Walking Through the Sacred: How Sacredness Transforms Embodied Perceptual Experiences Program: Ecological Psychology

This is a doctoral dissertation defense in Kinesiology

Major Advisor: Grégory Pierrot Associate Advisors: Katharine Capshaw, Erika Williams Departmental Readers: Eleni Coundouriotis and Najnin Islam

Event will be held in the Library Class of 1947 Room. Virtual attendance details can be found at swapecoevo.weebly.com/phd-defense.

This dissertation focused on deep learning methods for large-scale dish classification and nutrient estimation through ingredient-guided RGB-D imaging supported by vision-text contrastive learning and Swift UI iOS application development.

Efficiency-Aware Computational Intelligence for Resource-Constrained Manufacturing Toward Edge-Ready Deployment

Examining practitioners views of Sport for Development (SfD) Learning, Leadership, and Education Policy (Concentration in Sport Management)

COMMITTEE Dr. Eva Lefkowitz  Dr. Keith Bellizzi  Dr. Amanda Denes

This dissertation focused on the design and development for fluorescent sensor array for the foodborne pathogenic bacterial and biofilm identification with machine learning techniques. it also includes the investigation of interfacial biofilm monitoring and quantification for better pathogenic biofilm control and food safety.