ASHS 2025 Conference

Background: Community Supported Agriculture (CSA) programs have been found to promote numerous positive health and nutrition behaviors, including increased consumption of fruits and vegetables and increased knowledge and self-efficacy in cooking skills. The CSA model can capitalize on this fact by connecting with institutional health and wellness programs. Employers and health insurance companies have funds to support employee wellness and are increasingly interested in programs that focus on the connection between high-quality, nutrient dense foods and health and wellness. The purpose of this study was to assess the impact of a workplace-based local food health and wellness educational curriculum that was tailored to CSA members. Methods: Family and consumer sciences Extension educators enrolled participants (n=41) in the pilot program in two counties in Florida. The educational curriculum had 6 modules that were delivered bi-weekly over 12 weeks. Each module paired a nutritional topic with local food. Nutrition topics included US dietary guidelines, menu planning, healthy cooking, fruits, vegetables, proteins, whole grains, and legumes. Local food topics included the economic importance of buying local food, ways to purchase local food, seasonal cooking, and regional food specialties. The program had both an in-person and online component, and included fact sheets, educational lectures, and on-farm videos of farmers explaining local crops. Researchers used a matched pre- and post-test design which used theory of planned behavior to assess participants’ knowledge, attitudes, beliefs, and intentions to purchase local food. The National Cancer Institute’s Short Fruit and Vegetable Screener was used to assess dietary changes. Wellness was assess using the Centers for Disease Control and Prevention’s Health-Related Quality of Life survey. Results: Participants significantly increased their fruit (p= 0.003) and vegetable (p=0.003) consumption. Participants had significant improvements in wellness indicators, including fewer days that pain limited their activity (p= 0.001), they experienced anxiety (p= 0.015), they felt sad (p=

Background: In the US, roughly one-third of food is wasted, with 37% of that waste occurring in homes. EPA estimates households discard 6.5 pounds weekly. Household food waste is difficult to study because it occurs in the privacy of homes. Citizen science is a research method that enlists community members to collect in real-world conditions in contexts that researchers do not have access. Objectives: The purpose of this study was to collect primary data on households food waste, the primary reasons people generate food waste, the types of packaging households typically discard, and individuals’ knowledge, attitudes, and beliefs about food waste. Methods: A total of 159 citizen scientists (86 Alachua County, 73 Sarasota County) recorded data on their household food waste for 14 days, including recording the total daily weight, types of food discarded, types of food packaging discarded, and reasons for food and packaging waste. Results: A total of 3,823 pounds of compostable food waste was discarded by citizen scientists in two-week period. Households in our study discarded more than 14 pounds of food waste per week, more than double EPA estimates. Fruits and vegetables are the food groups that create the most food waste, with an average of 2.7 servings of fruit and 8.5 servings of vegetables discarded per household over the two-week period. Dinner yielded the most food waste, with household having an average of 36 servings of food wasted at dinner. More than 90% of participants rely on date labels to determine if food is safe to eat, 86% discarded food because it was “old,” and 69% discarded food because of blemishes/damage. Discussion: This multi-county citizen science study provides an initial look at the sources of food and packaging waste in Florida households, and highlights opportunities for future Educational programs focused on how to store and prepare fresh produce could reduce the largest source of household food waste to help address this global problem at the household level.

The state of Oklahoma has a foundation in natural resources and agriculture. To date, despite growth and industry changes, Oklahoma has kept true to its history but operates through the lens of industrial agriculture. The horticultural market is largely untapped and overlooked within the state even with the ample resources, land availability, open market, and a population in need of nutritional supplementation. Connecting with and having conversations with Oklahoma vegetable and fruit producers reveal underlying problems within Oklahoma's local food system and programs which include the fundamentals of production, market accessibility, and distribution problems. These conversations have long-term implications on the future market of the state. The exploration of results found from the conversations will be explored in terms of programming available, and the future of Oklahoma’s food system. The current programming within the state has a variety of approaches to tackling the integration of a local food system or the promotion of specialty crops. The identification and systematic review of programming and policy will expose gaps and shortcomings in the Oklahoma food system. Identifying and understanding barriers in specialty crop producers will create opportunities to improve the methods of production in the state of Oklahoma. Through examining the states’ available resources, programming, and policies for fruit and vegetable producers in the state, a plan for success can be created to increase market access and profitability for producers while also increasing access to local produce for consumers in Oklahoma. The evaluation of Oklahoma’s policies and specialty crop programs or support networks have long term implications on the success of current markets for local vegetable and fruit producers, their challenges they face, and opportunities that lie ahead. The implications of this review will result in a better understanding, connection, and future resources to nurture and support the horticultural market. Keywords: Horticulture, local production, market accessibility

Compost is treated as a waste product by many regulatory agencies, monitored and assessed only for its potential to harm humans or to harm the environment. However, horticulture practitioners are the number one consumer of compost, whether in nursery production, vegetable production, or home landscaping and gardening. In Arkansas, no state regulations require reporting chemical or physical characteristics of compost such as plant nutrient content, pH, bulk density, or organic matter content. Therefore, a statewide survey of participating Arkansas Department of Energy and Environment permitted composting facilities was conducted to characterize the availability of compost throughout the calendar year, the variability in plant nutrient content and physical characteristics. A total of 11 compost sites were sampled from nine compost production operations in Arkansas, including water treatment facilities, commercial depackaging companies, and municipal compost facilities. Yard waste (YW) was a component of all compost feedstocks, but some facilities could further handle food waste (FW) or biosolids (BS). Dry matter analysis found that composts from YW alone contained 1.31% to 1.92% N; composts from YW plus FW contained 2.57% to 3.70% N; and composts from YW BS contained 1.25% to 2.80% N. Major disparities were observed dry matter Na content when FW was included in compost. Composts including FW contained 2,185 to 7,672 mg/kg Na while composts from YW or YW BS contained 167 to 402 mg/kg Na. Present findings indicate that compost feedstocks affect the resulting nutrient content, particularly when introducing FW. Substrate testing beyond the standard testing for pathogens and trace metals will be critical for effective use of composts as a substrate or soil amendment in horticulture systems.

Background: Community-supported agriculture (CSA) programs have been found to promote health and nutrition, and consumers frequently cite healthfulness as a motivation for local food purchasing. The CSA model can capitalize on this fact and expand their customer base by partnering with healthcare providers or insurance companies that provide cost-offsets for people to enroll in CSA programs. The purpose of this study was to pilot test the impact of an employer-sponsored cost-offset CSA program. Methods: University of Florida (UF), Institute of Food and Agricultural Sciences Extension developed a collaborative partnership between cooperative Extension, local farms, and the UF Human Resources’ Office of Worklife to fund a cost-offset CSA program. Results: Seventy-seven employees purchased a cost-offset CSA membership. Participants were predominantly female (86%) and in staff positions (72%). Roughly a quarter of participants received food assistance (26%). The most prevalent motivations for joining the program were to support local farms (100%) and the local economy (96%). Ninety-two percent of participants joined the program to improve their diet and to eat food that tastes better. Some participants (36%) joined the program because they had been interested in join a CSA anyway. More than 80% of respondents were satisfied with all aspects of the program. Aspects that participants were not satisfied with was the cost of the CSA membership (18%) and the lack of information about the produce included in the CSA (16%). The overwhelming majority perceived that it improved their diet (92%), increased their fruit and vegetable consumption (88%), and increased their ability to cook seasonal produce (88%). Most participants (78%) indicated they would join a CSA again, with 86% saying they would join with the same farm again. Discussion: Feedback from participants was positive, with participants emphasizing personal benefits like weight loss and discovering new foods. Many indicated that this program was more valuable to them than traditional webinars or programs offered by the office of worklife. The farms appreciated that the program connected them with new customers and the ongoing partnership with UF, which has now entered its third year. Collaborative partnerships take time and effort to develop but can yield ongoing benefits for local farms and community food systems.

Seeding Success - The Louisiana Farm to School (F2S) Program sponsors a four-day intensive training targeting teachers and those that support school gardening and integrating gardens into the curriculum. The training has been offered each summer for the past five years with classroom and hands-on horticulture training in the mornings and in the afternoons, demonstration of classroom lessons linked to state standards, taste tests, and integration of farm to school into the classroom. The horticulture program focuses on the horticulture extension materials developed for the F2S program under the Sustainable School and Home Garden series, including the Louisiana Planting Guide and individual crop guides with all the materials available on the seedstosuccess.com website. Hands-on horticulture activities such as vermicomposting, composting, seeding and “bumping up” and planting transplants are introduced each day that are designed to be used in schools. All of the activities are intended to support the development and maintenance of school gardens and curriculum development. Participants provided feedback on the training and overwhelming benefited from the School Gardening Leadership Certificate Program. Data from the extension program will be presented including data on program, specific topics, and analytics.

Forecasting yield is a timely opportunity to make anticipated harvesting decisions on the grown crop and understand field variability. Such information is a remarkable contribution to the precision agriculture context. However, developing such an approach is challenging for perennial crops such as pecan. These crops present slight canopy changes, which often do not reflect the upcoming yield. Consequently, waiting for the harvest date is the only approach to obtain yield data. Conversely, the advent of image-based data and artificial intelligence techniques has proven their applicability in addressing this issue. Therefore, our objective was to analyze whether UAV multispectral images and AI-based data analysis are suitable for developing forecasting models for yield in pecan trees. Hence, we began collecting multispectral images approximately five months before the harvesting date. Each data collection date had an interval of fifteen days, totaling ten multispectral image sets. Subsequently, we processed the images to generate ten orthomosaics (one for each date). The orthomosaics were used to calculate numerous vegetation indices, texture data, and the canopy area to be used as inputs for the forecasting models. At the harvest date, we measured the yield of 78 individual plants across two pecan fields. Before developing the forecasting models, we performed a correlation analysis to better understand the relationship between the image data and yield. Afterward, we developed the forecasting models using machine learning algorithms, namely, multiple linear regression, decision tree, support vector machine, and random forest. The dataset was split into 70% (n = 55) for training and 30% (n = 23) for testing. The training dataset was used to train the forecasting models, while the testing dataset was used to assess the models’ effectiveness regarding precision (coefficient of determination, R²) and accuracy (mean absolute error, MAE; and root mean squared error, RMSE). All the models produced interesting results and could be implemented to forecast yield in pecan trees. However, random forest outperformed the others (high precision and accuracy) and, therefore, was the remaining model for this study. Forecasting yield in pecan trees presented increased effectiveness, improving the models’ performance early on and establishing higher accuracies closer to the harvesting date. We also performed a feature importance analysis, where predominantly the texture data contributed better to the models’ performance. Certainly, our findings are timely and support pecan growers and stakeholders in making better decisions for harvesting with anticipated and accurate yield data without waiting for the harvesting date.

Non-destructive estimation models often require cultivar-specific calibrations due to spectral differences arising from genetic variability. Integrating diverse cultivars into a single model can reduce costs and simplify data collection. However, in persimmons, the abundant and variable proanthocyanidins in the fruit overlap with spectral regions used for sugar estimation, rendering accurate prediction with a single model challenging. In this study, we attempted sugar estimation in diverse persimmon cultivars using near-infrared (NIR) spectroscopy and hyperspectral imaging. A total of 989 spectral measurements were acquired from 34 persimmon cultivars. Regression models employing various pre-processing and modeling techniques achieved a maximum R² of 0.786, indicating the feasibility of modeling sugar content across diverse cultivars with a unified approach. Furthermore, by designing a cover for the NIR sensor and combining it with SNV pre-processing, we demonstrated that stable spectra for sugar estimation can be obtained under outdoor conditions. With further improvements in accuracy, this approach is expected to facilitate rapid fruit quality evaluation and contribute to optimized production.

Combining green roofs with solar modules can protect plants and produce energy in cities. Growing crops in this system is called rooftop agrivoltaics (RAV) and can complement current urban agriculture efforts. We evaluated a group of five leafy green crops (arugula, kale, lettuce, spinach, and Swiss chard) under different solar modules over two years at two locations. Data measurements were taken for fresh and dry weight (FW, DW) stomatal conductance (SC), plant size at harvest (PSH), and microclimate data. Treatments included a polycrystalline opaque silicon module, a cadmium telluride (CdTe) frameless opaque module, a 40% semi-transparent CdTe module, and a full sun control. Four of the five leafy greens produced higher FW and DW under the 40% semi-transparent modules compared to other treatments and the full sun control, except spinach. Most species also produced larger PSH under the PV module treatments compared to the full sun control. Leafy greens under the module treatments resulted in lower SC, however, lettuce and Swiss chard grown under the semi-transparent module treatment produced higher SC compared to all other treatments. This research shows that incorporating photovoltaics on rooftop gardens influences the yield and stomatal conductance of select leafy green crops. While FW and DW mostly decreased under the deep shade treatments (opaque module, frameless module, and bifacial module) SC decreased, possibly due to less solar radiation on the leafy greens, reducing water use. Understanding the growth characteristics and growing environment of high value crops like leafy greens will increase understanding of what food crops are suitable for RAV systems.

Real-time monitoring of crop health is pivotal for advancing precision agriculture, enabling timely interventions to mitigate abiotic stress impacts. This study presents a novel and non-destructive approach for detecting salt stress in hydroponically grown arugula (Eruca sativa L.) using low-cost MQ gas sensors. Arugula seedlings, 11 days post-germination, were transplanted to a deep-water culture (DWC) hydroponic system in the greenhouse facility of The Pennsylvania State University. Salt stress was induced 9 days after planting by supplementing a modified Hoagland nutrient solution with sodium chloride (NaCl) at three concentrations: 0 mM (control), 40 mM, and 80 mM. Electrical conductivity (EC), pH and temperature parameters were regularly monitored during the cultivation period. Three MQ gas sensors—MQ2, MQ135, and MQ137—were integrated into a dome-shaped enclosure positioned over individual net pots, each containing four plants. To achieve a comprehensive volatile organic compound (VOC) profile, sensor units were strategically positioned on multiple plants within each treatment group. A total of 144 plants per treatment were cultivated, and two sets of sensor units recorded VOC emissions for 8 consecutive days. Salt stress significantly influenced plant growth, with fresh weight (FW) and leaf area decreasing as salinity increased. The 80 mM treatment exhibited the lowest FW and leaf area (61.69 ± 2.7 g, p-value = 0.015; 1434.25 ± 58 cm², p-value = 0.003), followed by the 40 mM treatment. All three MQ sensor responses revealed distinct VOC emission patterns correlating with salt stress levels. These sensor outputs were leveraged to train three machine learning models—K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Random Forest—to classify stress-induced VOC signatures. Among these, the cubic KNN model demonstrated superior predictive performance, achieving 98.73% accuracy, 98.74% precision, 98.73% recall, and an F1 score of 0.98 for the test dataset. These findings underscore the potential of cost-effective MQ gas sensors for real-time, non-invasive stress detection in crops, offering a promising tool for precision agriculture and early stress diagnosis. The integration of VOC sensing with machine learning models provides a scalable solution for enhancing crop management strategies in controlled environments.

Land use is a major concern for our society, which impacts governmental regulations, industry and agriculture, and individual property owners. Agrivoltaics (APV) includes the combination of agriculture and photovoltaics energy production on a single plot of land. APV has been proposed as a way to integrate agriculture into large-scale photovoltaic arrays or integrate energy production into established agricultural operations. The objectives of this project were to establish replicated APV research trials with fixed vertical panel photovoltaic arrays and investigate the feasibility of growing various warm- and cool-season crops between them. Warm-season crops included tomato, watermelon, bush bean, and zucchini. Cool-season crops included fall-planted lettuce and beets as well as spring-planted spinach and lettuce. Vertical panels were constructed with four replications that examined systems effects of APV compared to the open-field. A split-plot randomized complete block design was utilized, whereby main plots included system and sub-plots were the crops. For each crop, yield, marketability, quality, and economic data were collected. Crop quality parameters tested included: visual quality, color, firmness, titratable acidity, and total soluble solids. Additionally, PAR sensors were located within crop rows to characterize light availability at the replicated site as well as at another solar array. Sensors were placed approximately 2.5’ above the ground surface to generally mimic mature plant canopy height, transversely across the expected light-treatment area. From the first year of study, similarities among the two systems (APV and open-field) were more numerous than significant differences. Only one statistically-significant treatment effect was found on crop yield, among one of two lettuce varieties grown in the fall (P

Blueberries are extremely susceptible to drought due to their shallow root systems and limited water regulation capabilities. Climate change exacerbates drought stress in major blueberry production regions, which affect key physiological traits, such as leaf water content (LWC), photosynthesis (A), stomatal conductance (gs), electron transport rate (ETR), photosystem II efficiency (φPSII) and transpiration rate (E). Current phenotyping methods for measuring these physiological traits are time-consuming and labor-intensive as well as limited by the need for specialized equipment. To address this, a high-throughput phenotyping (HTPP) platform integrated with hyperspectral camera and a novel graph convolutional network (GCN)-based model, Plant-GCN, was developed to predict physiological traits of blueberry plants under drought stress. Spectral reflectance obtained from the hyperspectral images were transformed into a graph representation, with each plant represented as a node, spectral reflectance as node features, and edges defined by spectral similarities. The Plant-GCN model utilizes graph convolutional layers that aggregate information from neighboring nodes, effectively capturing complex interactions in the spectral signature and enhancing the prediction of physiological traits. Plant-GCN achieved a coefficient of determination (R²) of 0.89 for LWC, 0.94 for A, 0.89 for gs, 0.92 for ETR, 0.93 for φPSII and 0.89 for E on the test dataset. The performance of the proposed Plant-GCN model was compared with multilayer perceptron (MLP), partial least squares regression (PLSR), support vector regression (SVR), and random forest (RF), and it consistently outperformed all these models as well as data published in other reports. The high-throughput phenotyping system enabled efficient large-scale data collection, while the Plant-GCN model captured long-range spectral relationships significantly improved the prediction of physiological traits. The high predictability of the models could facilitate the screening of blue-berry cultivars for the specified traits allowing the selection and breeding of new drought tolerant cultivars in the future.

Bacterial leaf scorch is a harmful disease for pecan production, which can cause premature canopy defoliation, reduced kernel weight, and significant yield losses. The disease can cause a 10-13% reduction in shell nut weight and a 14-19% decrease in kernel weight, adversely affecting the quality and quantity of pecan yields. Early detection and precise management are important for minimizing economic losses and sustainable disease management. Current methods, such as manual scouting and conventional imaging, are inadequate for pecan orchards due to the trees' height and their inability to capture temporal changes or disease transmission patterns. Spatio-temporal modeling is a useful technique that enables tracking disease spread across time and location, identifying hotspots and transmission patterns to prioritize areas needing urgent intervention. This study aimed to develop a spatio-temporal model to visualize and evaluate the progression of bacterial leaf scorch disease in pecan orchards. High-resolution multispectral images of pecan trees were collected using a drone- mounted multispectral camera. A 3D point cloud was generated using Pix4D to create a reference NIR point cloud, and other vegetation indices point clouds were then aligned to provide sufficient data for model training. Ten vegetation indices, including the Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Normalized Difference Red Edge Index (NDRE), Modified Red Edge Simple Ratio (MRESR), Enhanced Vegetation Index (EVI), Soil-Adjusted Vegetation Index (SAVI), Optimized Soil-Adjusted Vegetation Index (OSAVI), Atmospherically Resistant Vegetation Index (ARVI), Chlorophyll Index - Red Edge (CI_RE), and Simple Ratio Index (SR), were used to evaluate disease sensitivity. Individual tree canopies were segmented using the 3D DBSCAN algorithm for each index. A point transformer deep learning model was trained with 3D vegetation indices of each tree with the ground truth to develop the prediction ability of the model for classifying individual each tree disease severity level. The early results indicate that the model can classify disease severity in the 3D point clouds, capturing the disease stress in the individual tree. Additionally, integrating a temporal embedding layer into the trained model enables the transformer block to track changes in vegetation indices and quantify disease progression over time. The findings of this study facilitate the monitoring of disease progression and support site-specific management decisions, thereby enhancing the sustainability of pecan production.
Keywords: Artificial intelligence, Spatio-temporal modeling, Multispectral imaging, Spectral analysis, Drone-based Scouting.

Precise and accurate quantification of blackberry flowers are essential for yield forecasting, phenotypic assessment, and enhancing management techniques in precision agriculture. Threshold segmentation of images for blackberry feature quantification could be challenging due to shadows and background variability, while manual flower estimation is subjective and time-consuming. The objective of this research was to apply artificial intelligence and computer vision to identify and quantify blackberry flowers from Unmanned Aerial Vehicle (UAV) remote sensing. A computer vision algorithm You Only Look Once (YOLO) was trained with 1142 image datasets of blackberry flowers to develop an image processing workflow to quantify UAV captured images. A performance analysis was conducted with YOLO variants (YOLOv8s–YOLO12s) for quantifying blackberry flowers. YOLOv10s achieved the best performance with a mAP@0.5 of 58%, precision of 60%, and recall of 58%. Input resolution had a notable impact, performing better at 1024×1024 pixels (mAP@0.5 = 55%) than at 640×640 (mAP@0.5 = 30%). Increasing the training dataset from 250 to 1,142 images progressively improved detection accuracy, highlighting the value of data volume for model generalization. Additionally, flower counts predicted by YOLOv10s showed a strong correlation with flower-to-vegetation ratio (FVR; r = 0.71, p < .001), supporting FVR as a practical proxy for estimating floral density in the field. A contribution to computer assisted agriculture integration in the blackberry industry has been made by investigating the performance of computer vision algorithms on blackberry flower detection. Challenges such as small and uneven sized flowers, overlapping occlusion, and plot-wise analysis must be further investigated. Keywords. UAV, automation, blackberry, phenotyping, artificial intelligence.

The mechanism controlling dormancy in buds of woody perennial plants remains largely unknown. However, it is known that exposure to cold temperatures (chilling) promotes the transition from a non-responsive to a responsive status to growth-conducive temperatures (i.e., endo- to ecodormancy transition). In horticulture, hydrogen cyanamide (HC) has been used for decades to overcome chilling accumulation deficiencies for temperate fruit crops grown in subtropical climates. Given the connection between cold hardiness loss and budbreak, we hypothesized that HC would increase the rate of cold hardiness loss (deacclimation rate). To test this, we collected grapevine (Vitis hybrid ‘Petite Pearl’) cuttings from field conditions in Madison, WI in approximately bi-weekly intervals from December to April. Single node cuttings were prepared and randomly separated into two treatments: a control group [0.5% surfactant (Regulaid®, KALO, Inc.)], and an HC group [5% hydrogen cyanamide (Dormex®, Alzchem Group AG) and 0.5% surfactant]. Both groups were treated by submersion for 10s. Cuttings were then placed in cups of water, and under forcing conditions. The forcing conditions used for all collections were 22ºC and 16h light. In later collections, two additional forcing temperatures were used: 8ºC and 16ºC. Cold hardiness was measured using differential thermal analysis on the day of treatment application, from field collected buds (n>10), and in semi-regular intervals from cuttings under forcing conditions, with interval length depending on temperature [e.g., quasi-daily at 22ºC (T0 1d, T0 2d, …); about every two days for 16ºC (T0 2d, T0 4d, …), about every five days for 8ºC]. At each collection time and for each temperature and treatment, 10 cuttings were set apart to observe time to budbreak. As expected, budbreak occurred earlier in HC treated buds compared to control. Using measurements of cold hardiness over time under forcing, we determined deacclimation rates as the slope of linear regressions. The rate of deacclimation in the control group increased progressively with each collection, as chilling accumulated in the field (1.0ºC/d in December to 1.4ºC/d in March). However, the deacclimation rate of the HC-treated group was always greater than the control (1.6ºC/d in December and 1.7ºC/d in March). In March, at 16ºC, there was also a difference between control and HC group in deacclimation rate (1.2ºC/d and 1.4ºC/d), while there were no differences at 8ºC. HC increases the rate of deacclimation in grapevines. We anticipate that understanding the interplay between cold hardiness, deacclimation, and budbreak will be helpful in uncovering the dormancy mechanism.

Dormancy remains a poorly understood process in temperate woody perennial plants. These plants require cumulative exposure to low temperatures (chilling accumulation) during winter to respond to warm temperatures in spring (forcing) and properly break bud. For successful establishment of temperate woody perennial fruit crops, it is important to understand chilling accumulation and dormancy requirements of species and cultivars. Our recent work indicates cold hardiness is an important co-variate in the analyses related to timing of budbreak, and thus chilling accumulation models and dormancy progression studies. Here we set out to understand aspects of chilling accumulation in different conditions by evaluating two measures of dormancy progression, (i) a classic forcing assay, where time to budbreak is evaluated; and (ii) a newer phenotyping of cold hardiness deacclimation rates using grapevine (Vitis spp.). For a comprehensive analysis, we used grapevine canes from V. vinifera cvs. Cabernet Sauvignon and Riesling, and V. hybrid cvs. Concord, Frontenac, Itasca, Marquette, and Petite Pearl. Canes were collected in several states across the continental United States (CO, IA, MN, NY, PA, SD, TX, WI), and in two locations for two states (NY, WI), representing approximately eight different USDA Cold Hardiness Zones (4a-7b), over the course of two winter seasons (2023-2025). Collections occurred in December, January, February, and March of each season. Upon collection or receipt of shipments, initial cold hardiness of buds was measured using differential thermal analysis (DTA). Following, canes were prepared into single node cuttings, and placed in cups of water and in a growth chamber for forcing (22ºC, 16h day/8h night). A subsample of 15 cuttings was used to evaluate time to budbreak, while the remaining cuttings were used for cold hardiness measurements in semi-regular intervals. We used simple linear regression with cold hardiness measurements to determine deacclimation rates (loss of cold hardiness over time; ºC/day). In general, buds from warmer locations (IA, TX, and Long Island, NY) had less initial cold hardiness (field cold hardiness) than colder locations. Dormancy progression was faster in colder locations than warmer locations, observed in both budbreak assays and evaluation of deacclimation rates. Based on our data, time to budbreak is a function of initial cold hardiness and deacclimation rate. Future work will examine the response of deacclimation rates to chilling accumulation models to determine chilling models that best describe dormancy responses across climates, which will then be incorporated into models that predict field cold hardiness and field budbreak.

Freeze-desiccation due to exosmosis to extracellular ice is considered as the major stress during equilibrium freezing. This causes structural / functional perturbations in the plasma membrane which leads to leakage of cellular contents. To gain further insight into the cellular mechanism of freeze-thaw injury, four cations (K , Ca2 , Mg2 , Fe2 ), known for their critical roles in plant growth and development, were measured in the leachate from injured spinach (Spinacia oleracea L. ‘Reflect’) leaves exposed to four freezing-durations (FDs) (0.5, 3.0, 5.5, 10.5 h) at a fixed temperature. In general, leakage of K , Ca2 , Mg2 increased incrementally at longer FDs and leaves sustained greater water-soaking after prolonged freezing. Data indicated a higher abundance of reactive oxygen species (O2− and H2O2) in leaves with greater injury at longer FDs. PSII efficiency was incrementally compromised at longer FDs as determined by chlorophyll fluorescence (Fv/Fm). Total electrolyte leakage from tissues right-after-thaw versus those allowed to recover for 6-d revealed that injury at 0.5 or 3 h FDs was recoverable, but leaves were irreparably injured at 5.5 or 10.5 h FDs. K was the most abundant cation in leachate. Data suggests that K -leakage can be used as proxy for total electrolyte-leakage in determining LT50 and can serve as an ionic marker to delineate moderate (recoverable) versus severe (non-recoverable) freeze-injury. Ca2 - and K -leakage data, together, are compatible with an earlier conjecture that leaked K ions replace membrane-associated Ca2 during post-thaw. It is proposed that thus structurally weakened plasma membrane, together with inhibited active transport functions of plasma membrane (noted in previous studies) lead to enhanced K -leakage from more severely freeze-injured leaves. Unlike other cations, Fe2 -leakage was indeed lower in the injured (0.5 FD) leaves compared to unfrozen control. Moreover, Fe2 was undetectable in the leachate at longer FDs. It is hypothesized that such lack of Fe2 in the leachate could result from Fenton reaction in injured tissues which converts soluble Fe2 into insoluble Fe3 . Enhanced Mg2 -leakage at greater freeze-injury suggests structural/functional impairment of chlorophyll / chloroplast complex, resulting in reduced quantum yield of PSII.

Drought stress poses significant environmental challenges to agricultural plants, especially tomatoes, by hindering their growth and reducing yields. Biostimulants like fulvic acids (FA) have emerged promising strategies for mitigating drought effects and enhancing water-use efficiency. However, the regulatory mechanisms of FA-induced drought tolerance are not yet fully understood. This study aimed to characterize FA-induced drought tolerance mechanism in tomatoes. Four-week-old plants were treated with FA at 240 mg per plant, and drought conditions were imposed by withholding 75% of the water supplied to well-watered plants. The plant growth performance and the physiological responses were evaluated. Leaf samples were collected at two stages: the early drought stage (3 days after treatment) and the later stage (7 days after treatment), for untargeted hormonomics and metabolomics analysis using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS). Under drought conditions, control plants exhibited significant stress symptoms, including reduced height and leaf wilting during the later phase. In contrast, FA-treated plants developed less drought symptoms and improved stomatal conductance. The hormonomics and metabolomics analysis identified 114 hormones and 243 metabolites in ESI . Using orthogonal partial least-squares discriminant analysis (OPLS-DA), we determined that 39 hormones and 162 metabolites (with a VIP score > 1.0) were significant discriminants among the different treatments. Under drought conditions, 2-hydroxy melatonin and abscisic acid (ABA) levels were significantly increased in FA-treated plants, along with higher concentrations of amino acids such as glycine and threonine. These findings suggest that fulvic acids modulate the phytohormones ABA and melatonin to induce drought tolerances, orchestrating a response that enhances drought tolerance by sustaining elevated levels of osmoprotective amino acids.

The irrigation of grasses dominates domestic water use across the globe, and a better understanding of water use and drought resistance in grasses is of undeniable importance for water conservation. Drought resistance is a complex trait composed of three distinct, but complementary, strategies: escape, avoidance, and tolerance. In grasses, drought escape is commonly displayed via summer dormancy, and drought avoidance and tolerance are displayed by grasses experiencing dehydration. Breeding programs have released cultivars with improved drought resistance, but the underlying mechanisms remain unknown. In this study, we used a number of plant physiology methods to characterize the mechanisms driving drought resistance in four zoysiagrass cultivars reported to exhibit contrasting levels of drought resistance. They were Lobo, Zeon, Empire, and Meyer. A dry-down was performed through deficit irrigation until 70% decline in evapotranspiration. No drought escape mechanism was identified in this project. Drought avoidance was characterized by the rate of dehydration over time, and drought tolerance was characterized by the decline in functional traits with increasing dehydration. Through this approach, we were able to separate avoidance from tolerance and demonstrate that drought tolerance governs drought resistance in commercial cultivars of zoysiagrass. Interestingly, we also demonstrated that canopy mortality during drought can only be reliably assessed using image analyses shortly after rehydration. This is because severe leaf rolling occurs during drought, confounding leaf rolling with actual leaf mortality. This study advances our understanding of i) drought resistance across commercial cultivars of zoysiagrass and ii) potential methods to select drought-resistant cultivars in turfgrass breeding programs.

Salinity stress is a growing concern in agriculture, particularly as climate change accelerates soil salinization and limits freshwater availability. Here, we evaluated the effectiveness of classic (low-throughput) versus high-throughput physiological phenotyping methods in detecting early salinity tolerance in Brassica juncea cultivars (‘Carolina Broadleaf’ and ‘Southern Giant Curl’). Traditional phenotyping relies on point measurements such as shoot biomass and leaf gas exchange, which, while valuable, are time-intensive, offer limited temporal resolution, and can be destructive. In contrast, high-throughput phenotyping enables continuous, real-time monitoring of plant physiological responses, providing a dynamic and detailed understanding of stress adaptation mechanisms. We conducted a 42-day experiment in a controlled greenhouse environment, exposing mustard green cultivars to three salinity treatments: control (0.397 dS/m), moderate salinity (10.81 dS/m, ~20% of seawater), and high salinity (24.93 dS/m, ~50% of seawater). The high-throughput PlantArray system was used to measure key physiological parameters, transpiration rates, and net plant weight gain, while traditional phenotyping involved weekly surveys of including stomatal conductance, chlorophyll fluorescence, and biomass accumulation. We found that high-throughput phenotyping allows for earlier and more precise detection of salinity tolerance. Classic methods confirmed significant reductions in biomass, with shoot fresh weight decreasing by up to 80% in high-salinity treatments, but these differences were only detectable at harvest and not before. In contrast, high-throughput phenotyping revealed early signs of osmotic adjustment within the first 20 days, as plants initially maintained transpiration before exhibiting a decline due to ion accumulation. ‘Carolina Broadleaf’ resist moderate salinity, maintaining growth comparable to the control for the first 20 days, suggesting that early harvesting could mitigate yield losses. Overall, this study underscores the advantages of high-throughput phenotyping in improving the precision and efficiency of breeding programs. By integrating continuous physiological measurements, this approach enables earlier and more informed selection of salt-tolerant cultivars, reducing time needed for tolerance screening. Future research should focus on expanding these methods to operational conditions and integrating genomic data to enhance genotype-environment modeling for stress adaptation.

The role of nature in improving health is being explored in a growing number of healthcare fields. At the University of Florida, programs using nature-based interventions include physical medicine and rehabilitation, oncology, addiction recovery, Parkinson’s Disease, mental health, and autism, among others. These expanding program opportunities are slowly but steadily moving nature into the domain of public health. Some of the more recognizable examples of this trend are therapeutic gardens and nature prescriptions but there are many other ways to use nature to boost health in cities around the world. Spending time in green spaces (plant-dominated) and blue spaces (water-dominated) is linked to improved life satisfaction, reduced anxiety, and increased happiness. Nature exists on a spectrum and whether experiencing ‘big’ nature or ‘micro’ nature, high quality contact generates an increase in positive emotions and feelings of vitality, a decrease in negative emotions, relief from mental fatigue, and an improvement in our attention span. This presentation will explore research that highlights the health benefits of nature interaction, the primary components of high-quality nature experiences, and the key factors in connecting people and nature.

The dissemination of agrivoltaic technology within Indigenous communities remains insufficiently understood, posing significant challenges to its successful implementation. As agrivoltaic systems continue to expand across the United States, it is imperative to examine how different social groups perceive and accept this technology. The Navajo Nation, the largest Indigenous tribe in the U.S., spans the Four Corners region, with the San Juan River Valley serving as a critical agricultural hub. To evaluate the feasibility of agrivoltaic adoption within this context, a sub-study was conducted as part of a broader Indigenous farmers’ needs assessment, focusing specifically on Navajo farmers in the San Juan River Valley. This study employed a qualitative survey consisting of eight binary-response questions to assess participants' knowledge of and interest in agrivoltaics. Results indicate that only 6% (n=126) of respondents were previously familiar with agrivoltaics, yet 88% expressed interest in learning more about the technology upon receiving an explanation. Furthermore, 73% of respondents were interested in exploring the use of photovoltaic systems to support their farms’ energy needs, although only 12% had prior experience with solar energy systems, underscoring key barriers to adoption. These findings suggest that agrivoltaic systems hold promise as a strategy for enhancing both local support for renewable energy development and food security within the Navajo Nation. However, significant knowledge gaps and limited technical expertise present obstacles to widespread implementation. The results emphasize the necessity of targeted educational and training programs to facilitate the successful integration of agrivoltaic systems. Without such efforts, adoption may remain limited due to a lack of familiarity and technical proficiency. Ultimately, this research underscores the potential for agrivoltaics to contribute to sustainable agricultural practices and renewable energy expansion within the Navajo Nation, highlighting the critical role of knowledge transfer and capacity-building initiatives in ensuring long-term success.

Climate anxiety among children is on the rise and research shows that discussing the issues and empowering youth are some ways to approach the issue. Historically, school gardens were used to teach children many subjects while addressing environmental issues and while fostering a love of plants and ecosystems. The objective of this study was to examine the influence of a 10-week outdoor, after-school youth gardening education program for first through third-grade students, specifically evaluating the effects on horticulture interest, environmental locus of control, and climate anxiety before and after participation in the program. The treatment group participated in an outdoor gardening program that involved hands-on learning related to growing plants and providing sustainable habitats while working through measures to create a National Wildlife Schoolyard Habitat as well as a recognized San Marcos Certified Habitat Stewardship Program landscape. The control group participated in the pre- and post-survey only and was not a part of the outdoor gardening or wildlife certification program, but was involved in other after-school activities offered at the elementary school. The survey questions were adopted from pre-determined, reliable, and valid instruments as well as adjusted for reading levels. Surveys utilized 5-point Likert scale questions with answer options employing emoticons that ranged from happy to sad. Pre- and post-survey data was analyzed through The Wilcoxon Signed-Rank tests and descriptive statistics. Data from this study determined the potential for school programs to increase horticultural interest in schools while empowering youth to make positive environmental action.

Foot health in the workplace, particularly among farmers and agricultural professionals, is often neglected, despite its significant impact on overall health and well-being. In Florida, environmental conditions frequently lead to hot, damp feet, exacerbated by improper footwear, which contributes to poor foot health. Due to a reluctance to seek medical intervention, foot issues often progress to more severe complications. This commercial horticulture extension program aimed to improve foot health awareness, increase learning gains, and promote healthy behavior changes in agriculture and horticulture workers. Objectives: The primary objectives were: (1) to improve knowledge and skills related to foot health, and (2) to encourage the adoption of healthy foot care behaviors. Methods: A total of 238 clients were pre-surveyed from 2020 - 2024 to assess their foot health and identify areas of need. Participants were then invited to attend an extension program in-person or via webinar. Four classes were presented over the four-year span, focusing on foot health and safety, addressing issues like foot or leg pain, diseases, and deformities. Practical solutions were provided, including individual diagnostic assessments by a podiatrist/surgeon who demonstrated exercises and discussed the use of orthotics for improving foot health. Participants were encouraged to rate their foot health and report discomfort. A post-intervention survey was conducted three months later to evaluate changes in knowledge, behavior, and foot health status. Outcomes and Results: The pre-survey revealed that 69% of participants reported foot issues, with an average self-assessed foot health grade of 6.85 out of 10. After attending the educational session and implementing recommended practices, 98% of participants (n=25) reported significant relief from foot discomfort. Moreover, 95% committed to behavior changes, such as performing leg exercises, using orthotics, and changing footwear. The average foot health grade improved to 8.0 out of 10, representing an 11.5% improvement. Additionally, 96% (n=9) of participants shared their knowledge with 35 others, expanding the intervention's impact. Conclusion: This study shows that educational interventions focused on foot health can lead to significant improvements in knowledge and foot health outcomes among agricultural workers. The adoption of behaviors like using orthotics, performing exercises or consulting with a podiatrist resulted in measurable improvements. The widespread sharing of information indicates that the intervention had a positive ripple effect. Continued efforts to promote foot health in high-risk occupations are essential to prevent long-term complications and improve quality of life.

As environmental sustainability becomes increasingly important to consumers of fresh cut flowers, the educators of floral design should consider adding topics covering sustainability within the floral industry into their curriculums. Perceptions of sustainability can vary depending on the US region in which a person lives and works. The main purpose of this study was to compare the perceptions of environmentalism and the use of sustainable floral design practices currently being implemented by professional florists based on the geographical area in which they live within the US. By investigating florists' attitudes toward sustainability and their current practices based on the US region in which they live, this study sought to shed light on the current sustainable practices being implemented within the floral design industry so that educators can make informed decisions when modifying their curriculums depending on where they are located within the US. A majority of respondents from each region in the study indicated they were personally aware of sustainable products (75.4% overall) and mechanics (80.5% overall) in floral design. Differences were found in the sustainable practices being implemented by professional florists based on the US region in which they live. Overall respondents from the West indicated they used fair-trade products, sustainable and/or compostable containers, sustainable and/or compostable floral foams, recycled carboard, composted flower waste, and is attempting to eliminate plastic at a higher rate than other US regions. Based on what professional florists are currently implementing into their own business models and what consumers have indicated as being important sustainable considerations to them when making floral purchases in past research studies, topics that focus on sourcing locally grown fresh cut flowers, post-harvest care for specialty cut flowers, growing specialty cut flowers within limited space, methods for composting fresh cut flower waste, sustainable design techniques that can be incorporated into multiple design styles an occasions, and current sustainable floral products on the market for use in floral design are all example of sustainable topics that could be incorporated into a floral design curriculum.

ASHS Annual Meetings (now conferences) have evolved over the 60 years of my attendance. From the 1965 Annual Meeting in Urbana Illinois where I stayed in a tent on the University quadrangle, to the most recent conference in Honolulu, they have been professionally stimulating, exciting and memorable. The dogwood pin given to attendees of the 1966 meeting with ISHS in Maryland, the long drive from St. Paul to College Station, Texas in 1967 and the ISHS/ASHS meeting in Davis stimulated my involvement and commitment to attending these important conferences. Involvement with the ASHS infrastructure began when I became a Board member representing the Great Plains Section when attending the meeting in Manhattan Kansas. I was immersed into the ASHS system further as the Chair of Local Arrangements for the 1972 meeting in St Paul (remember the chicken fiasco?) The Guelph meeting in 1974 was memorable because I attended "on the way" to sabbatical at the University of Nottingham and was "on the way back" to the 1975 meeting in Honolulu (September meeting). It was an easier drive from St. Paul to Ames in 1982 where I took my grad students in a van to save them money (I have always encouraged my students to become ASHS members by paying for their first year's memberships). Past President Dermot Coyne sponsored me for ASHS Fellow, awarded at the meeting in East Lansing in 1988. My second meeting in Honolulu was of note because following inducements of pineapples, luau and more, I purchased a timeshare to make sure that I'd take a "real" vacation in addition to my usual tacking on a few days to ASHS conferences. Among the important changes with which I had the privilege to assist was the creation of the ASHS Endowment Fund, and now the "$125 for Five" campaign that will continue to help deserving students. Of course I am humbled to say that one of my greatest honors was election as President of ASHS. Following the devastation wrought by Hurricane Katrina, I was inundated with "where can we meet", "when can we meet" emails and calls. I was proud to respond that we will help New Orleans by following through with our commitment to meet there. I will mention many more important ASHS changes and insights as part of my presentation this year as we return to the site of my Presidential Address in the "Big Easy".

The United States during the national crises of the First and Second World Wars developed gardening and food production programs in order to support the war effort and to supply food for the troops and those at home. The National War Garden Commission, a private organization, was created in 1917 one month before the US entry in World War 1. The role of the commission was to encourage US citizens to cultivate in all available space, offering free seeds and plants and to “Sow the Seeds of Victory!” President Woodrow Wilson in 1917 indicated “everyone who creates or cultivates a garden helps,” and tasked government agencies with aiding the effort to conserve food and other supplies for soldiers. The civilian garden program was supported by the commission who gave away free booklets on gardening, canning, and food preservation. These gardens, termed “war gardens” were grown throughout the country on vacant land, parks, backyards, and schools; there was call for schools to join the United States School Garden Army. There were many war gardens in the USA and around the world. There were more than 5.2 million war gardens in the USA by 1918. Towards the end of World War 1 the effort shifted to victory gardens with the goal of feeding the hungry, and prevention of starvation. With the advent of World War 2 the victory gardens were mobilized to provide resources to fight the war and support the US allies. Almost 20 million Americans planted gardens – in backyards, vacant lots, athletic fields, schools, roof tops. Produce from their gardens would help to lower the price of vegetables needed by the US War Department to feed the troops, thus saving money that could be spent elsewhere on the military. An estimated 40 % of the nation’s fresh vegetables were produced in victory gardens. The federal government, via the USDA provided resources such as seeds, production guides, and guidance in order to support victory gardens. The guides were intended to provide information to novice gardeners on growing food as well as proper canning and preservation techniques. The current farm to school movement and the People’s Garden program have their roots in the previous wartime efforts in order to support a more diverse resilient food system and address issues such as food access and climate change.