ASHS 2025 Conference

Tomato fruit quality is directly related to marketability and consumer appeal. Unfortunately, consumers are increasingly discontent with the flavor and quality of the product they are purchasing and requesting tomatoes with improved flavor, aroma, texture, and appearance making it a high priority for breeding programs. Traditionally, the selection for fruit quality traits in breeding programs has been done using conventional phenotyping approaches, in which large populations need to be screened. Although this approach has resulted in the release of high quality-high yielding cultivars, it is very time-consuming, delaying cultivar release. An alternative approach to improve breeding efficiency involves the use of modern molecular breeding techniques. In this study, a diverse panel of 305 tomato genotypes, including 284 tomato breeding lines developed by Texas A

Septoria Leaf Spot (SLS), caused by the fungal pathogen Septoria lycopersici, is a highly destructive foliar disease affecting tomatoes. SLS is most severe in the Northeast USA and North Carolina during periods of high humidity and elevated temperatures, which can lead to catastrophic yield loss. No quantitative trait loci (QTL) associated with SLS resistance have been reported. Therefore, the objective of this study was to map the QTL related to SLS resistance in tomatoes. An F2:4 mapping population consisting of 189 individuals derived from NC123S (susceptible) x Wisconsin 55 (moderately resistant) was assessed under both field and greenhouse conditions through artificial inoculation with a spore concentration of 15.3 x 10^4/mL at the Mountain Horticultural Crops Research and Extension Center, Mills River, NC, and Mountain Research Station, Waynesville, NC. The population was genotyped using the SPET (single primer enrichment technology) Allegro targeted genotyping method. SPET-derived SNP (single nucleotide polymorphism) molecular markers were used to construct a linkage map spanning 3810.2 cM. QTL analysis identified 12 QTLs associated with SLS resistance, including two major effects and ten minor effects, typical for at least two environments identified across the genome, explaining phenotypic variation (R² value) ranging from 3.7% to 13.5%. These results demonstrate that the genetic control of SLS resistance is polygenic. This study may provide a foundation for understanding the genetics of SLS resistance and marker-assisted selection (MAS) for transferring SLS resistance genes into elite tomato breeding lines.

Drought is a major abiotic stressor that significantly reduces the growth and yield of tomato (Solanum lycopersicum L.). To mitigate its adverse effects, the development and utilization of drought-tolerant cultivars, combined with advanced breeding strategies, offer sustainable solutions. In this study, a total of 157 USDA tomato accessions were evaluated under controlled greenhouse conditions using a randomized complete block design with four replications, incorporating both a water-deficit treatment and a well-watered control group. The results identified ten accessions, including PI 487624, PI 127828, PI 379018, PI 365903, PI 390515, PI 390663, PI 128657, PI 266376, PI 126444, and PI 298933, as drought tolerant, with leaf wilting and leaf rolling scores of less than four. Broad-sense heritability estimates ranged from 50 percent to approximately 58 percent, indicating a moderate genetic influence on drought tolerance. Correlation analysis revealed strong positive associations ranging from 0.50 to 0.99 among leaf wilting, leaf rolling, plant freshness, leaf thickness, and SPAD chlorophyll content, while negative correlations ranging from -0.40 to -0.81 were observed for plant fresh weight, leaf thickness, Quantum yield of Photosystem II (Phi2), and SPAD chlorophyll content traits. These findings provide valuable insights into tomato breeding programs focused on improving drought resilience in elite cultivars. We plan to expand the evaluation to a broader set of accessions and employ genome-wide association studies and genomic prediction to identify single nucleotide polymorphism markers and candidate genes associated with drought tolerance. The integration of genome-wide association studies and genomic prediction will facilitate marker-assisted selection and genomic selection, improving the efficiency of breeding programs aimed at developing drought-resilient tomato cultivars.

Blossom-end rot (BER) is a physiological disorder in tomatoes that renders the fruit to be unmarketable. In tomato, BER initiates around 7-10 days post anthesis (DPA) at the distal end of the fruit as a water-soaked symptom that can progress into a necrotic lesion covering the entire fruit during development. Calcium deficiency in the distal end of the fruit is thought to trigger BER initiation. In this study, we have used near isogenic lines (NILs) that segregate for BER and harbors quantitative trait loci (QTLs) BER11.1 and BER11.2. Physiological characterization indicated lower calcium concentration and reduced number of vascular bundles in the distal inner and distal pericarp tissue in the susceptible fruit in comparison to the with resistant fruit. To further delineate the molecular mechanisms underlying BER development and to identify the potential candidate gene(s) underlying QTL BER11.1

Fresh market tomato (Solanum lycopersicum) is one of the most important vegetable crops in the US, but this labor-intensive industry faces severe labor shortages and rising production costs amid heavy competition from lower-cost imports. With labor accounting for over 30% of total production expenses, much of which is due to harvesting, the industry's long-term sustainability depends on developing more labor-efficient systems. Mechanical harvesting presents a promising solution, but tomato fruit are highly susceptible to bruising, a challenge that could be amplified by mechanized handling. Fruit firmness plays a crucial role in resistance to internal bruising, making it a key breeding target for improving harvest efficiency and post-harvest quality. The UF/IFAS tomato breeding program has developed tomato lines with traits beneficial for mechanical harvesting, including compact growth habit (CGH) and increased fruit firmness. To investigate the genetic basis of fruit firmness in CGH lines, bi-parental populations were developed from firm and soft inbred parents. Genome-wide association analysis identified multiple minor-effect QTLs, confirming the quantitative nature of this trait in the population. Variance component analysis revealed that fruit firmness is primarily controlled by additive genetic variance, suggesting a strong potential for improvement through selection with appropriate strategies such as genomic selection (GS), which has been successfully used to improve quantitative traits in many crop species. GS models were successfully trained to predict fruit firmness, demonstrating the feasibility of integrating GS into the UF/IFAS tomato breeding program. Model optimization, including adjustments to training population size, marker density, and the incorporation of significant QTLs as fixed effects, improved prediction accuracy and computational efficiency. This study confirms the presence of significant fruit firmness variability in UF/IFAS germplasm, supporting its use in breeding firmer CGH tomatoes suited for mechanical harvest. Future research will refine GS models by incorporating multi-trait and multi-environment analyses, leveraging variance-covariance relationships to enhance prediction accuracy and accelerate genetic gains.

Speed breeding is a technique that utilizes controlled environments and optimal lighting (photoperiod) conditions to accelerate germination, development, and maturity of plants. One of the major constraints for its adoption and implementation in vegetable breeding programs is the high cost associated with growth chambers. The objective of this study is to develop a Speed Breeding protocol for chile peppers using an improvised, low-cost growth chamber constructed using polyvinyl chloride (PVC) plastic, greenhouse film, mylar reflective film, full-spectrum and far-red light-emitting diode (LED) growth lights. Four C. annuum L. genotypes, namely, NuMex Lotalutein (a serrano type), NuMex Odyssey (New Mexican), NuMex Las Cruces (cayenne), and Early Jalapeno (jalapeno) were planted in two randomized flat trays, using SunGro propagation soil, and watered twice daily. After reaching the 2-3 leaf stage, the treatments (control and Speed Breeding, SB) were transplanted into 8” pots, incorporating sterilized and LM-AP soil mixtures. The control group was cultivated in standard greenhouse conditions for growing chile peppers, exposed to normal daylight intensity and duration, and an average temperature of 21°C and humidity of 40%. The chamber was also constructed in the same greenhouse. From weeks 1 to 5 after planting, the SB-treatment was subjected to 20h/4h light/dark conditions daily, and 9h/15h light/dark after week 5. Light intensity was increased by ~100 photosynthetic active radiation (PAR) weekly after week 5, from ~150 PAR to ~800 PAR. Data was recorded weekly to examine the effects of treatment on germination rate, plant size, leaf number and color, number of flowers, buds, and fruits, and days to flower and fruit. There were significant differences (Tukey HSD, P < 0.05) between treatments for germination rates, number of buds, fruits, leaves, and days to flowering. The SB-treated pepper plants exhibited faster and higher germination, darker green leaves, and a higher number of buds and fruits compared to the control. For instance, SB plants started flowering, on average, about 20 ± 5 days earlier, germinated 5 ± 1 days earlier, and had, on average, 15 ± 2 more buds than the control. Notably, all genotypes under the SB-treatment had at least one fully mature fruit ~106 days after sowing. These results suggest that, at minimal costs, there is a potential to achieve increased generation times to accelerate cultivar development and genetic improvement in chile peppers.

Watermelon is a preferred fruit in the Caribbean and all over the world and is the second most consumed cucurbit by harvest weight in the Virgin Islands after cucumber. While quality of water of watermelon is commonly judged by sweetness, the ratios of types of sugars are hardly considered. Watermelon is classified as one of the fruits with very high glycemic index, GI – the measure by which a dietary intake increases the blood sugar compared to pure glucose whose GI is 100. Watermelon is normally promoted as a highly nutritious as it is one of the best sources of potassium, but can be both a blessing and curse, especially for consumers with high blood sugar-related ailments. Here we report on preliminary efforts we are making to produce watermelons that have reduced GI. We are using hybridization as well as exploiting genotype-by-environment interactions to influence sugar composition in fleshy fruit tissues. We have obtained three hybrids that have at least 22% reduced glucose and at per brix compared to the parents. We are also testing a series of shadehouse systems, two of which show the potential to lower glucose ratio in the fruits. We hope to refine these methods and evaluate the watermelon lines for yield and sugar trait stability before recommending plant materials and production systems to interested farmers. Key words: Hybrids, sugar, glycemic index, genotype by environment, production system, sucrose, watermelon.

The need to improve crops has never been critical with the rising population and climate change resulting in high abiotic stress and disease pressures in production areas. In recent years, artificial intelligence (AI)-based approaches have been implemented in the context of plant breeding and crop improvement. Modern AI tools hold the promise of accelerating the development of resilient, higher-yielding, and more sustainable horticultural crops, by rendering a deeper understanding of complex genetic systems and phenotypes, and how these interact with their environment to express desirable traits. As an approach, AI is an important component of the plant breeding toolbox which may now currently be an indispensable addition to modern vegetable breeding programs. For example, AI allows for the prediction of phenotypic values through genetic markers, and this allows plant breeders to perform selection even before the trials are conducted in the field. The ASHS Vegetable Breeding and Interest Group seeks to provide research updates from experts who have worked on the applications of AI in crop breeding and genetic improvement. The workshop will provide a summary of various AI methodologies, recent advances, and render opportunities for future collaboration and research directions in the implementation of AI in vegetable breeding programs. Objectives 1. Summarize the different AI approaches used in breeding and genetic improvement of various traits in vegetables 2. Provide the attendees with recent advances in AI for plant breeding 3. Discuss future research directions and applications of AI in plant breeding programs The workshop will be conducted during the annual ASHS meeting (July 28- August 1, 2025) in New Orleans, Louisiana. The workshop will be in-person. Audience: The workshop will be open to all ASHS attendees (both public and private sectors) and will be interactive.

Moderators: Dennis Lozada, New Mexico State University
Devi Kandel, Langston University

Speakers:

• Cheryl Dalid, University of Florida - Leveraging Phenomics and Genomics Data in Strawberry Breeding
• Stephen Ficklin, Washington State University - Towards Identification of Biomarkers for Environmentally-controlled Traits
• Madhi Haghshenas-Jaryani, New Mexico State University - AI-enabled Agricultural Robots and Intelligent Machines for Precision Farming of Chile Pepper Cultivation in New Mexico
• Tanzeel Rehman, Auburn University - AI-Driven High-Throughput Phenotyping for Assessing Physiological Stress in Blueberry
• Kevin Wang, University of Florida - AI-Powered Phenomics: Accelerating Breeding Across Horticultural Crops