Exploring the genetic basis of resistance to Neopestalotiopsis species in strawberry.

Aggressive strains of Neopestalotiopsis sp. have recently emerged as devastating pathogens of strawberry (Fragaria × ananassa Duchesne ex Rozier), infecting nearly all plant parts and causing severe outbreaks of leaf spot and fruit rot in Florida and globally. The development of host resistance is imperative due to the absence of fungicides that effectively inhibit Neopestalotiopsis sp. growth on an infected strawberry crop. Here, we analyzed 1578 individuals from the University of Florida's (UF) strawberry breeding program to identify and dissect genetic variation for resistance to Neopestalotiopsis sp. and to explore the feasibility of genomic selection. We found that less than 12% of elite UF germplasm exhibited resistance, with narrow-sense heritability estimates ranging from 0.28 to 0.69. Through genome-wide association studies (GWAS), we identified two loci accounting for 7%-16% of phenotypic variance across four trials and 3 years. Several candidate genes encoding pattern recognition receptors, intra-cellular nucleotide-binding leucine-rich repeats, and downstream components of plant defense pathways co-localized with the Neopestalotiopsis sp. resistance loci. Interestingly, favorable alleles at the largest-effect locus were rare in elite UF material and had previously been unintentionally introduced from an exotic cultivar. The array-based markers and candidate genes described herein provide the foundation for targeting this locus through marker-assisted selection. The predictive abilities of genomic selection models, with and without explicitly modeling peak GWAS markers as fixed effects, ranged between 0.25 and 0.59, suggesting that genomic selection holds promise for enhancing resistance to Neopestalotiopsis sp. in strawberry.

Strawberry soluble solids QTL with inverse effects on yield.

Sugars are the main drivers of strawberry sweetness, and understanding their genetic control is of critical importance for breeding. Large-scale genome-wide association studies were performed in two populations totaling 3399 individuals evaluated for soluble solids content (SSC) and fruit yield. Two stable quantitative trait loci (QTL) on chromosome 3B and 6A for SSC were identified. Favorable haplotypes at both QTL for SSC decreased yield, though optimal allelic combinations were identified with reduced impacts on yield. Metabolites in the starch and sucrose metabolism pathway were characterized and quantified for 23 contrasting genotypes in leaves, white fruit, and red fruit. Variations in sucrose concentrations/efflux indicated genetic variation underlying sucrose accumulation and transportation during fruit ripening. Integration of genome-wide association studies and expression quantitative locus mapping identified starch synthase 4 (FxaC_10g00830) and sugar transporter 2-like candidate genes (FxaC_21g51570) within the respective QTL intervals. These results will enable immediate applications in genomics-assisted breeding for flavor and further study of candidate genes underlying genetic variation of sugar accumulation in strawberry fruit.

Genomic signatures of strawberry domestication and diversification.

Cultivated strawberry (Fragaria × ananassa) has a brief history of less than 300 yr, beginning with the hybridization of octoploids Fragaria chiloensis and Fragaria virginiana. Here we explored the genomic signatures of early domestication and subsequent diversification for different climates using whole-genome sequences of 289 wild, heirloom, and modern varieties from two major breeding programs in the United States. Four nonadmixed wild octoploid populations were identified, with recurrent introgression among the sympatric populations. The proportion of F. virginiana ancestry increased by 20% in modern varieties over initial hybrids, and the proportion of F. chiloensis subsp. pacifica rose from 0% to 3.4%. Effective population size rapidly declined during early breeding. Meanwhile, divergent selection for distinct environments reshaped wild allelic origins in 21 out of 28 chromosomes. Overlapping divergent selective sweeps in natural and domesticated populations revealed 16 convergent genomic signatures that may be important for climatic adaptation. Despite 20 breeding cycles since initial hybridization, more than half of loci underlying yield and fruit size are still not under artificial selection. These insights add clarity to the domestication and breeding history of what is now the most widely cultivated fruit in the world.

Identification of ethyl vanillin in strawberry (Fragaria × ananassa) using a targeted metabolomics strategy: From artificial to natural.

Improving flavor can be an important goal of strawberry through breeding that is enhanced through the accurate identification and quantification of flavor compounds. Herein, a targeted metabolomics strategy was developed using liquid-liquid extraction, an in-house standard database, and GC-MS/MS analysis. The database consisted of key food odorants (KFOs), artificial flavor compounds (AFCs) and volatiles. A total of 131 flavor compounds were accurately identified in Medallion® 'FL 16.30-128' strawberry. Importantly, ethyl vanillin was identified for the first time in natural food. Multiple techniques, including GC-MS, GC-MS/MS and UPLC-MS/MS were applied to ensure the identification. The ethyl vanillin in the Medallion® samples were determined in a range of concentrations from 0.070 ± 0.0006 µg/kg to 0.1372 ± 0.0014 µg/kg by using stable isotope dilution analysis. The identification of ethyl vanillin in strawberry implys the future commercial use a natural flavor compound and the potential to identify genes and proteins associated with its biosynthesis.

Machine learning applications to improve flavor and nutritional content of horticultural crops through breeding and genetics.

Over the last decades, significant strides were made in understanding the biochemical factors influencing the nutritional content and flavor profile of fruits and vegetables. Product differentiation in the produce aisle is the natural consequence of increasing consumer power in the food industry. Cotton-candy grapes, specialty tomatoes, and pineapple-flavored white strawberries provide a few examples. Given the increased demand for flavorful varieties, and pressing need to reduce micronutrient malnutrition, we expect breeding to increase its prioritization toward these traits. Reaching this goal will, in part, necessitate knowledge of the genetic architecture controlling these traits, as well as the development of breeding methods that maximize their genetic gain. Can artificial intelligence (AI) help predict flavor preferences, and can such insights be leveraged by breeding programs? In this Perspective, we outline both the opportunities and challenges for the development of more flavorful and nutritious crops, and how AI can support these breeding initiatives.

Resistance of Strawberry Cultivars and the Effects of Plant Ontogenesis on Phytophthora cactorum and P. nicotianae Causing Crown Rot.

Phytophthora crown rot (PhCR) is an important disease of strawberry worldwide. Phytophthora cactorum is the most common causal agent, however, P. nicotianae was also recently reported causing PhCR in the U.S. Therefore, the goals of this study were to evaluate the resistance of strawberry cultivars from Florida and California, and to study the etiology of the two Phytophthora species causing PhCR. Sixteen strawberry cultivars were evaluated over three Florida seasons for susceptibility to P. cactorum, and P. nicotianae. Inoculations at different days after transplanting (DAT) were also carried out to evaluate the ability of both species to cause PhCR at different phenological stages of the plant. Plant wilting and mortality were assessed weekly, and disease incidence, and the area under the disease progress curve were calculated. Cultivars Sensation 'Florida127', 'Winterstar FL 05-107', and 'Florida Radiance' were susceptible, whereas 'Florida Elyana', 'Camarosa', 'Fronteras', 'Sweet Charlie', and 'Strawberry Festival' were highly resistant to both Phytophthora species. However, some cultivars exhibited stronger resistance to one species over the other. P. cactorum caused more PhCR when plants were inoculated at transplanting, 45, and 60 DAT, whereas P. nicotianae only caused disease when inoculated at transplanting. These results emphasize the importance of screening for disease resistance to guide management recommendations in commercial strawberry production as well as the need for proper pathogen identification since cultivar susceptibility might differ. Varying susceptibility to P. cactorum and P. nicotianae at different growth stages emphasizes the importance of considering both plant and pathogen biology when making management recommendations.

Deep Learning for Strawberry Canopy Delineation and Biomass Prediction from High-Resolution Images.

Modeling plant canopy biophysical parameters at the individual plant level remains a major challenge. This study presents a workflow for automatic strawberry canopy delineation and biomass prediction from high-resolution images using deep neural networks. High-resolution (5 mm) RGB orthoimages, near-infrared (NIR) orthoimages, and Digital Surface Models (DSM), which were generated by Structure from Motion (SfM), were utilized in this study. Mask R-CNN was applied to the orthoimages of two band combinations (RGB and RGB-NIR) to identify and delineate strawberry plant canopies. The average detection precision rate and recall rate were 97.28% and 99.71% for RGB images and 99.13% and 99.54% for RGB-NIR images, and the mean intersection over union (mIoU) rates for instance segmentation were 98.32% and 98.45% for RGB and RGB-NIR images, respectively. Based on the center of the canopy mask, we imported the cropped RGB, NIR, DSM, and mask images of individual plants to vanilla deep regression models to model canopy leaf area and dry biomass. Two networks (VGG-16 and ResNet-50) were used as the backbone architecture for feature map extraction. The R 2 values of dry biomass models were about 0.76 and 0.79 for the VGG-16 and ResNet-50 networks, respectively. Similarly, the R 2 values of leaf area were 0.82 and 0.84, respectively. The RMSE values were approximately 8.31 and 8.73 g for dry biomass analyzed using the VGG-16 and ResNet-50 networks, respectively. Leaf area RMSE was 0.05 m2 for both networks. This work demonstrates the feasibility of deep learning networks in individual strawberry plant extraction and biomass estimation.

A multi-omics framework reveals strawberry flavor genes and their regulatory elements.

Flavor is essential to consumer preference of foods and is an increasing focus of plant breeding programs. In fruit crops, identifying genes underlying volatile organic compounds has great promise to accelerate flavor improvement, but polyploidy and heterozygosity in many species have slowed progress. Here we use octoploid cultivated strawberry to demonstrate how genomic heterozygosity, transcriptomic intricacy and fruit metabolomic diversity can be treated as strengths and leveraged to uncover fruit flavor genes and their regulatory elements. Multi-omics datasets were generated including an expression quantitative trait loci map with 196 diverse breeding lines, haplotype-phased genomes of a highly-flavored breeding selection, a genome-wide structural variant map using five haplotypes, and volatile genome-wide association study (GWAS) with > 300 individuals. Overlaying regulatory elements, structural variants and GWAS-linked allele-specific expression of numerous genes to variation in volatile compounds important to flavor. In one example, the functional role of anthranilate synthase alpha subunit 1 in methyl anthranilate biosynthesis was supported via fruit transient gene expression assays. These results demonstrate a framework for flavor gene discovery in fruit crops and a pathway to molecular breeding of cultivars with complex and desirable flavor.

Combining canopy reflectance spectrometry and genome-wide prediction to increase response to selection for powdery mildew resistance in cultivated strawberry.

High-throughput phenotyping is an emerging approach in plant science, but thus far only a few applications have been made in horticultural crop breeding. Remote sensing of leaf or canopy spectral reflectance can help breeders rapidly measure traits, increase selection accuracy, and thereby improve response to selection. In the present study, we evaluated the integration of spectral analysis of canopy reflectance and genomic information for the prediction of strawberry (Fragaria × ananassa) powdery mildew disease. Two multi-parental breeding populations of strawberry comprising a total of 340 and 464 pedigree-connected seedlings were evaluated in two separate seasons. A single-trait Bayesian prediction method using 1001 spectral wavebands in the ultraviolet-visible-near infrared region (350-1350 nm wavelength) combined with 8552 single nucleotide polymorphism markers showed up to 2-fold increase in predictive ability over models using markers alone. The integration of high-throughput phenotyping was further validated independently across years/trials with improved response to selection of up to 90%. We also conducted Bayesian multi-trait analysis using the estimated vegetative indices as secondary traits. Three vegetative indices (Datt3, REP_Li, and Vogelmann2) had high genetic correlations (rA) with powdery mildew visual ratings with average rA values of 0.76, 0.71, and 0.71, respectively. Increasing training population sizes by incorporating individuals with only vegetative index information yielded substantial increases in predictive ability. These results strongly indicate the use of vegetative indices as secondary traits for indirect selection. Overall, combining spectrometry and genome-wide prediction improved selection accuracy and response to selection for powdery mildew resistance, demonstrating the power of an integrated phenomics-genomics approach in strawberry breeding.

Comparative Transcriptome Analysis to Identify Candidate Genes for FaRCg1 Conferring Resistance Against Colletotrichum gloeosporioides in Cultivated Strawberry (Fragaria × ananassa).

Colletotrichum crown rot (CCR) caused by Colletotrichum gloeosporioides is a serious threat to the cultivated strawberry (Fragaria × ananassa). Our previous study reported that a major locus, FaRCg1, increases resistance. However, the genomic structure of FaRCg1 and potential candidate genes associated with the resistance remained unknown. Here, we performed comparative transcriptome analyses of resistant 'Florida Elyana' and susceptible 'Strawberry Festival' after infection and identified candidate genes potentially involved in resistance. In 'Florida Elyana', 6,099 genes were differentially expressed in response to C. gloeosporioides. Gene ontology analysis showed that the most upregulated genes were functionally associated with signaling pathways of plant defense responses. Three genes in the genomic region of FaRCg1 were highly upregulated: a von Willebrand Factor A domain-containing protein, a subtilisin-like protease, and a TIFY 11A-like protein. Subgenome-specific markers developed for the candidate genes were tested with a diverse panel of 219 accessions from University of Florida and North Carolina State University breeding programs. Significant and positive associations were found between the high-resolution melting (HRM) marker genotypes and CCR phenotypes. These newly developed subgenome-specific functional markers for FaRCg1 can facilitate development of resistant varieties through marker-assisted selection.

Evolution of the MLO gene families in octoploid strawberry (Fragaria ×ananassa) and progenitor diploid species identified potential genes for strawberry powdery mildew resistance.

Powdery mildew (PM) caused by Podosphaera aphanis is a major fungal disease of cultivated strawberry. Mildew Resistance Locus O (MLO) is a gene family described for having conserved seven-transmembrane domains. Induced loss-of-function in specific MLO genes can confer durable and broad resistance against PM pathogens. However, the genomic structure and potential role of MLO genes for PM resistance have not been characterized yet in the octoploid cultivated strawberry. In the present study, MLO gene families were characterized in four diploid progenitor species (Fragaria vesca, F. iinumae, F. viridis, and F. nipponica) and octoploid cultivated (Fragaria ×ananassa) strawberry, and potential sources of MLO-mediated susceptibility were identified. Twenty MLO sequences were identified in F. vesca and 68 identified in F. ×ananassa. Phylogenetic analysis divided diploid and octoploid strawberry MLO genes into eight different clades, in which three FveMLO (MLO10, MLO17, and MLO20) and their twelve orthologs of FaMLO were grouped together with functionally characterized MLO genes conferring PM susceptibility. Copy number variations revealed differences in MLO composition among homoeologous chromosomes, supporting the distinct origin of each subgenome during the evolution of octoploid strawberry. Dissecting genomic sequence and structural variations in candidate FaMLO genes revealed their potential role associated with genetic controls and functionality in strawberry against PM pathogen. Furthermore, the gene expression profiling and RNAi silencing of putative FaMLO genes in response to the pathogen indicate the function in PM resistance. These results are a critical first step in understanding the function of strawberry MLO genes and will facilitate further genetic studies of PM resistance in cultivated strawberry.

Genetic Analysis of Methyl Anthranilate, Mesifurane, Linalool, and Other Flavor Compounds in Cultivated Strawberry (Fragaria × ananassa).

The cultivated strawberry (Fragaria × ananassa) is an economically important fruit crop that is intensively bred for improved sensory qualities. The diversity of fruit flavors and aromas in strawberry results mainly from the interactions of sugars, acids, and volatile organic compounds (VOCs) that are derived from diverse biochemical pathways influenced by the expression of many genes. This study integrates multiomic analyses to identify QTL and candidate genes for multiple aroma compounds in a complex strawberry breeding population. Novel fruit volatile QTL was discovered for methyl anthranilate, methyl 2-hexenoate, methyl 2-methylbutyrate, mesifurane, and a shared QTL on Chr 3 was found for nine monoterpene and sesquiterpene compounds, including linalool, 3-carene, ß-phellandrene, α-limonene, linalool oxide, nerolidol, α-caryophellene, α-farnesene, and ß-farnesene. Fruit transcriptomes from a subset of 64 individuals were used to support candidate gene identification. For methyl esters including the grape-like methyl anthranilate, a novel ANTHANILIC ACID METHYL TRANSFERASE-like gene was identified. Two mesifurane QTL correspond with the known biosynthesis gene O-METHYL TRANSFERASE 1 and a novel FURANEOL GLUCOSYLTRANSFERASE. The shared terpene QTL contains multiple fruit-expressed terpenoid pathway-related genes including NEROLIDOL SYNTHASE 1 (FanNES1). The abundance of linalool and other monoterpenes is partially governed by a co-segregating expression-QTL (eQTL) for FanNES1 transcript variation, and there is additional evidence for quantitative effects from other terpenoid-pathway genes in this narrow genomic region. These QTLs present new opportunities in breeding for improved flavor in commercial strawberry.

Genomic Characterization of the Fruity Aroma Gene, FaFAD1, Reveals a Gene Dosage Effect on γ-Decalactone Production in Strawberry (Fragaria × ananassa).

Strawberries produce numerous volatile compounds that contribute to the unique flavors of fruits. Among the many volatiles, γ-decalactone (γ-D) has the greatest contribution to the characteristic fruity aroma in strawberry fruit. The presence or absence of γ-D is controlled by a single locus, FaFAD1. However, this locus has not yet been systematically characterized in the octoploid strawberry genome. It has also been reported that the volatile content greatly varies among the strawberry varieties possessing FaFAD1, suggesting that another genetic factor could be responsible for the different levels of γ-D in fruit. In this study, we explored the genomic structure of FaFAD1 and determined the allele dosage of FaFAD1 that regulates variations of γ-D production in cultivated octoploid strawberry. The genome-wide association studies confirmed the major locus FaFAD1 that regulates the γ-D production in cultivated strawberry. With the hybrid capture-based next-generation sequencing analysis, a major presence-absence variation of FaFAD1 was discovered among γ-D producers and non-producers. To explore the genomic structure of FaFAD1 in the octoploid strawberry, three bacterial artificial chromosome (BAC) libraries were developed. A deletion of 8,262 bp was consistently found in the FaFAD1 region of γ-D non-producing varieties. With the newly developed InDel-based codominant marker genotyping, along with γ-D metabolite profiling data, we revealed the impact of gene dosage effect for the production of γ-D in the octoploid strawberry varieties. Altogether, this study provides systematic information of the prominent role of FaFAD1 presence and absence polymorphism in producing γ-D and proposes that both alleles of FaFAD1 are required to produce the highest content of fruity aroma in strawberry fruit.

Volatiles Influencing Sensory Attributes and Bayesian Modeling of the Soluble Solids-Sweetness Relationship in Strawberry.

Descriptive analysis via trained sensory panels has great power to facilitate flavor improvement in fresh fruits and vegetables. When paired with an understanding of fruit volatile organic compounds, descriptive analysis can help uncover the chemical drivers of sensory attributes. In the present study, 213 strawberry samples representing 56 cultivars and advanced selections were sampled over seven seasons and subjected to both sensory descriptive and chemical analyses. Principal component analysis and K-cluster analyses of sensory data highlighted three groups of strawberry samples, with one classified as superior with high sweetness and strawberry flavor and low sourness and green flavor. Partial least square models revealed 20 sweetness-enhancing volatile organic compounds and two sweetness-reducing volatiles, many of which overlap with previous consumer sensory studies. Volatiles modulating green, sour, astringent, overripe, woody, and strawberry flavors were also identified. The relationship between soluble solids content (SSC) and sweetness was modeled with Bayesian regression, generating probabilities for sweetness levels from varying levels of soluble solids. A hierarchical Bayesian model with month effects indicated that SSC is most correlated to sweetness toward the end of the fruiting season, making this the best period to make phenotypic selections for soluble solids. Comparing effects from genotypes, harvest months, and their interactions on sensory attributes revealed that sweetness, sourness, and firmness were largely controlled by genetics. These findings help formulate a paradigm for improvement of eating quality in which sensory analyses drive the targeting of chemicals important to consumer-desired attributes, which further drive the development of genetic tools for improvement of flavor.

Strawberry sweetness and consumer preference are enhanced by specific volatile compounds.

Breeding crops for improved flavor is challenging due to the high cost of sensory evaluation and the difficulty of connecting sensory experience to chemical composition. The main goal of this study was to identify the chemical drivers of sweetness and consumer liking for fresh strawberries (Fragaria × ananassa). Fruit of 148 strawberry samples from cultivars and breeding selections were grown and harvested over seven years and were subjected to both sensory and chemical analyses. Each panel consisted of at least 100 consumers, resulting in more than 15,000 sensory data points per descriptor. Three sugars, two acids and 113 volatile compounds were quantified. Consumer liking was highly associated with sweetness intensity, texture liking, and flavor intensity, but not sourness intensity. Partial least square analyses revealed 20 volatile compounds that increased sweetness perception independently of sugars; 18 volatiles that increased liking independently of sugars; and 15 volatile compounds that had positive effects on both. Machine learning-based predictive models including sugars, acids, and volatiles explained at least 25% more variation in sweetness and liking than models accounting for sugars and acids only. Volatile compounds such as γ-dodecalactone; 5-hepten-2-one, 6-methyl; and multiple medium-chain fatty acid esters may serve as targets for breeding or quality control attributes for strawberry products. A genetic association study identified two loci controlling ester production, both on linkage group 6 A. Co-segregating makers in these regions can be used for increasing multiple esters simultaneously. This study demonstrates a paradigm for improvement of fruit sweetness and flavor in which consumers drive the identification of the most important chemical targets, which in turn drives the discovery of genetic targets for marker-assisted breeding.

Discovery of three loci increasing resistance to charcoal rot caused by Macrophomina phaseolina in octoploid strawberry.

Charcoal rot caused by Macrophomina phaseolinais an increasing economic problem in annualized strawberry production systems around the world. Currently there are no effective postfumigation chemical controls for managing charcoal rot, and no information is available on the genetic architecture of resistance to M. phaseolina in strawberry (Fragaria ×ananassa). In this study, three multiparental discovery populations and two validation populations were inoculated at planting and evaluated for mortality in three consecutive growing seasons. Genome-wide SNP genotyping and pedigree-based analysis with FlexQTL™ software were performed. Two large-effect quantitative trait loci (QTL) increasing charcoal rot resistance were discovered and validated in cultivated germplasm. FaRMp1 was located on linkage group 2A in the interval 20.4to 24.9 cM, while FaRMp2 was located on linkage group 4B in the interval 41.1to 61.2 cM. Together these QTLs explained 27% and 17% of the phenotypic variance in two discovery populations consisting of elite breeding germplasm. For both QTLs, the resistant allele showed some evidence of partial dominance, but no significant interaction was detected between the two loci. As the dosage of resistant alleles increased from 0 to 4 across the two QTLs, mortality decreased regardless of the combination of alleles.A third locus, FaRMp3 on 4D, was discovered in FVC 11-58, a reconstituted F.×ananassa originating from diverse F. virginiana and F. chiloensis accessions. This locus accounted for 44% of phenotypic variation in four segregating crosses. These findings will form the basis for DNA-informed breeding for resistance to charcoal rot in cultivated strawberry.

Unraveling the Complex Hybrid Ancestry and Domestication History of Cultivated Strawberry.

Cultivated strawberry (Fragaria × ananassa) is one of our youngest domesticates, originating in early eighteenth-century Europe from spontaneous hybrids between wild allo-octoploid species (Fragaria chiloensis and Fragaria virginiana). The improvement of horticultural traits by 300 years of breeding has enabled the global expansion of strawberry production. Here, we describe the genomic history of strawberry domestication from the earliest hybrids to modern cultivars. We observed a significant increase in heterozygosity among interspecific hybrids and a decrease in heterozygosity among domesticated descendants of those hybrids. Selective sweeps were found across the genome in early and modern phases of domestication-59-76% of the selectively swept genes originated in the three less dominant ancestral subgenomes. Contrary to the tenet that genetic diversity is limited in cultivated strawberry, we found that the octoploid species harbor massive allelic diversity and that F. × ananassa harbors as much allelic diversity as either wild founder. We identified 41.8 M subgenome-specific DNA variants among resequenced wild and domesticated individuals. Strikingly, 98% of common alleles and 73% of total alleles were shared between wild and domesticated populations. Moreover, genome-wide estimates of nucleotide diversity were virtually identical in F. chiloensis,F. virginiana, and F. × ananassa (π = 0.0059-0.0060). We found, however, that nucleotide diversity and heterozygosity were significantly lower in modern F. × ananassa populations that have experienced significant genetic gains and have produced numerous agriculturally important cultivars.

Cultivar Selection Is an Effective and Economic Strategy for Managing Charcoal Rot of Strawberry in Florida.

Macrophomina phaseolina, the causal agent of charcoal rot, is a soilborne pathogen that affects strawberry crowns leading to plant wilt and collapse. Disease management involves a combination of physical, cultural, and chemical methods. Field trials were conducted for 10 consecutive Florida seasons (2010-11 to 2019-20) to determine the susceptibility of strawberry cultivars to charcoal rot and the effect of cultivar selection on disease and to estimate the economic impact of cultivar selection on disease management. Six cultivars grown commercially in Florida were chosen and grouped as highly susceptible (HS) ('Strawberry Festival' and 'Treasure'), susceptible (S) ('Florida Radiance' and 'Florida Beauty'), and moderately resistant (MR) (Sensation 'Florida127' and Winterstar 'FL05-107') according to their susceptibility levels. After a primary analysis of the individual trials, a network meta-analysis was conducted to estimate and compare the final disease incidence and the disease progress rate of each susceptibility group. The economic impact of charcoal rot on strawberry production and gross revenue was estimated based on plant production functions, weekly fruit prices, and disease progress over time with parameters obtained via the meta-analytical models. Disease incidence was reduced by 91.5 and 77.3%, respectively, when the MR and S cultivar groups were adopted instead of the HS group. There was a 62.5% reduction in the disease incidence when the MR group was used instead of the S group. Significant differences in disease progress rates were also observed when the MR and S groups were adopted instead of the HS group. Therefore, the adoption of more resistant cultivars is an effective strategy when incorporated into a charcoal rot integrated management program and can significantly impact growers' revenue by reducing disease incidence, preventing yield loss, and, consequently, minimizing economic losses.

RosBREED: bridging the chasm between discovery and application to enable DNA-informed breeding in rosaceous crops.

The Rosaceae crop family (including almond, apple, apricot, blackberry, peach, pear, plum, raspberry, rose, strawberry, sweet cherry, and sour cherry) provides vital contributions to human well-being and is economically significant across the U.S. In 2003, industry stakeholder initiatives prioritized the utilization of genomics, genetics, and breeding to develop new cultivars exhibiting both disease resistance and superior horticultural quality. However, rosaceous crop breeders lacked certain knowledge and tools to fully implement DNA-informed breeding-a "chasm" existed between existing genomics and genetic information and the application of this knowledge in breeding. The RosBREED project ("Ros" signifying a Rosaceae genomics, genetics, and breeding community initiative, and "BREED", indicating the core focus on breeding programs), addressed this challenge through a comprehensive and coordinated 10-year effort funded by the USDA-NIFA Specialty Crop Research Initiative. RosBREED was designed to enable the routine application of modern genomics and genetics technologies in U.S. rosaceous crop breeding programs, thereby enhancing their efficiency and effectiveness in delivering cultivars with producer-required disease resistances and market-essential horticultural quality. This review presents a synopsis of the approach, deliverables, and impacts of RosBREED, highlighting synergistic global collaborations and future needs. Enabling technologies and tools developed are described, including genome-wide scanning platforms and DNA diagnostic tests. Examples of DNA-informed breeding use by project participants are presented for all breeding stages, including pre-breeding for disease resistance, parental and seedling selection, and elite selection advancement. The chasm is now bridged, accelerating rosaceous crop genetic improvement.