ASHS 2025 Conference

A forum for discussion of potential collaborations with regards to ornamentals – i.e. floriculture, nursery crops, breeding, turf, ornamentals industry, botanic gardens, landscape industry, orchids, etc.

Open to all

Understanding stakeholder priorities helps botanic gardens serve current visitors and develop relevant future programs. A strategic vision planning process investigated stakeholder priorities for university-affiliated Rutgers Gardens in central New Jersey, USA through an online survey conducted February – March 2024. Specific objectives included 1) determining priorities of botanic garden stakeholders to guide vision planning; 2) identifying key learning topic preferences among stakeholders, toward program development; and 3) understanding associations between overall priorities and learning interest to align visioning and programming efforts. Respondents (n=688) included university students (20.6%), faculty/staff (20.1%), and alumni (27.6%); garden visitors, staff, volunteers, members, and donors; and community members at large. The majority identified as white/Caucasian (64.5%), age 50 (50.2%), visit multiple times per year (39.9%), and reside in-state (94.7%). Asked to select their top three priorities, respondents identified Ecology, Conservation, and Biodiversity (41.9%), Display and Demonstration Gardens (34.9%), and Climate Change Resilience (27.3%) as overall leaders. Decreasing in priority were Preservation of Historic Plant Collections (25.0%), Horticultural Research (24.6%), Sustainable Agriculture (20.2%), Public Recreation (17.4%), Horticultural Therapy and Wellness (14.4%), Food Security (11.0%), Culture and Arts (9.2%), and Diversity, Equity, and Inclusion (6.7%). Respondents identified primary learning interest in Home Gardening

Community gardens provide numerous opportunities and benefits to volunteers, visitors, and communities. While there are many benefits to community gardens, there are also many obstacles, including volunteer struggles. Recruiting, organizing, training, and educating volunteers are among the biggest issues with volunteerism. Signage has the potential to alleviate some of these struggles. Signs can advertise the garden’s presence to attract volunteers, promote events and opportunities to keep volunteers engaged, and provide education through interpretive signage. However, many design elements and content choices for signage in community gardens have not been studied. A survey was sent out to a national sample that reflects the USA’s census data (N= 345) for gender, age, region, and household income with a screening question inquiring if participants had an interest with gardening. Photos and questions were prepared to reflect various aesthetic and functional attributes of signage. Questions asked participants their opinion on which design elements were most likely to gain attention, what information is needed to complete a task, and important information to have on a community garden sign. Results showed clear winners for design choices for attention gathering, those being primary colors, wood material, graphically designed, with a non-serif font, and pictures. Educational signage preferences showed that infographics with text and pictures were preferred overall. Signage element survey questions showed that participants preferred pictures over written text. Interactions between findings with demographics and gardening familiarity were also analyzed. Overall, people who had more experience gardening had more positive outlooks on signage compared to those who do not. These findings will allow community gardens to design more purposeful and engaging signage.

Extension Master Gardeners (EMGs) are volunteer educators trained by land-grant universities to teach their local communities about plants and gardening. While EMGs work on a variety of outreach projects, demonstration gardens are a popular project choice for Master Gardener volunteers. In Georgia alone, there are over 250 EMG projects associated with physical garden locations across the state. However, the geographic location of each garden site is not maintained in the state project database. Geographic Information Systems (GIS) have been used to evaluate outreach programs in both public health and environmental sciences, but these techniques have not been applied to EMG programs. This project aimed to determine the location of active EMG demonstration gardens in Georgia using existing project database listings and reported volunteer activity from 2023-2024. Project sites were located using Google Earth keyword searches, and analysis was performed in R Statistical Software. Overall, most EMG garden projects in Georgia could be successfully located, but locatability varied across county programs. Geospatial analysis revealed that multiple garden projects are located outside of their managing program’s county, suggesting actual geographic reach of EMG programs in Georgia may be wider than previously estimated. Collecting and maintaining geographic data associated with EMG projects has many potential applications for program coordinators at local, state, and national levels. These applications include matching new volunteers with conveniently located projects, identifying underserved populations, and visualizing program reach for both public audiences and program stakeholders.

Blueberry (Vaccinium spp.) production has been expanding globally, driven by its unique flavor and numerous health benefits. With increasing demand, it is essential to implement techniques aimed at improving yield in commercial blueberry fields. The distribution of blueberries across the canopy profile is a key factor linked to several management aspects, including the efficiency of mechanical harvesting, pest control strategies, and overall fruit quality. Understanding fruit distribution within the canopy is essential to optimize machine calibration, apply precision agriculture techniques for pest management, and incorporate technologies that enhance fruit quality and maximize production by reducing losses caused by uneven vertical distribution. This study aimed to determine the vertical distribution of blueberry fruits using RGB images and the YOLOv8s model. Data was collected from a commercial Southern Highbush blueberry field in Homerville, GA. Using a cellphone camera, a total of 200 images were collected from 40 plant samples, with each plant photographed from the top to the base at a consistent angle. The images were annotated and classified according to the fruit’s position on the plant (upper, middle, or lower third). The YOLOv8s model was trained on the labeled images and evaluated using standard metrics, including precision, recall, and Intersection over Union (IoU). The dataset was divided into 70% for training, 15% for validation, and 15% for testing, over 200 training epochs. The final outputs consisted of annotated images, performance metrics, and a summary table showing the number of plants analyzed and fruit concentration by canopy zone. Using the YOLOv8s model, we successfully mapped the spatial distribution of blueberry fruits across different canopy zones (upper, middle, and lower thirds). The model achieved moderate to high accuracy metrics, demonstrating good performance in fruit detection and localization. These results indicate the model's potential for practical field applications, although performance could be further enhanced by expanding the dataset and incorporating additional training cycles. Future work aims to test the model across different blueberry varieties and integrate it into a user-friendly web platform. These findings highlight the feasibility of using deep learning tools to support data-driven management decisions in commercial blueberry production systems.