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Patricio R. Munoz
Blueberry Breeding and Genomics Laboratory, Horticultural Sciences Department, University of Florida, Gainesville, FL, USA

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Journal article
Published: 17 August 2021 in Scientia Horticulturae
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Blueberry (Vaccinium spp.) is a specialty crop with expanding production and consumption worldwide. Southern Highbush Blueberries (SHB) require few chilling hours and include early-ripening cultivars which can be harvested in an early market window making the crop more profitable for growers in sub-tropical regions. To expand the marketability of the crop, fruit breeders are seeking to meet the current demand for fruit quality. To this end, this study gathered sensory measurements (firmness, sweetness, sourness, blueberry flavor, green flavor and off-flavors), chemical (pH, titratable acidity and soluble solids concentration), and physical attributes (compression force) on six SHB cultivars, in order to understand how fruit quality traits are affected by environmental conditions such as storage duration, year and harvest date. Differences across environmental conditions for all attributes were observed. Indigocrisp and Keecrisp were the firmest cultivars and maintained firmness over time in storage. Additionally, Indigocrisp was the sweetest and had the most blueberry and green flavors among the cultivars. On the other hand, Arcadia was the softest, as measured by sensory and compression force, but varied with year and harvest. Arcadia and Emerald were the least sweet and most sour of the cultivars, and Endura and Patrecia were intermediate for all sensory attributes. In general, sensory descriptors were well explained by instrumental measurements. Variations across seasons and storage were inconsistent among cultivars, but Indigocrisp was the most stable cultivar for the quality traits evaluated. In the end, all fruit quality traits assayed in this study were influenced by environmental conditions throughout the season.

ACS Style

Haley Sater; Luís Felipe V. Ferrão; James Olmstead; Patricio R. Munoz; Jinhe Bai; Alwin Hopf; Anne Plotto. Exploring environmental and storage factors affecting sensory, physical and chemical attributes of six southern highbush blueberry cultivars. Scientia Horticulturae 2021, 289, 110468 .

AMA Style

Haley Sater, Luís Felipe V. Ferrão, James Olmstead, Patricio R. Munoz, Jinhe Bai, Alwin Hopf, Anne Plotto. Exploring environmental and storage factors affecting sensory, physical and chemical attributes of six southern highbush blueberry cultivars. Scientia Horticulturae. 2021; 289 ():110468.

Chicago/Turabian Style

Haley Sater; Luís Felipe V. Ferrão; James Olmstead; Patricio R. Munoz; Jinhe Bai; Alwin Hopf; Anne Plotto. 2021. "Exploring environmental and storage factors affecting sensory, physical and chemical attributes of six southern highbush blueberry cultivars." Scientia Horticulturae 289, no. : 110468.

Original research article
Published: 14 June 2021 in Frontiers in Plant Science
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Blueberry (Vaccinium corymbosum and hybrids) is a specialty crop with expanding production and consumption worldwide. The blueberry breeding program at the University of Florida (UF) has greatly contributed to expanding production areas by developing low-chilling cultivars better adapted to subtropical and Mediterranean climates of the globe. The breeding program has historically focused on recurrent phenotypic selection. As an autopolyploid, outcrossing, perennial, long juvenile phase crop, blueberry breeding cycles are costly and time consuming, which results in low genetic gains per unit of time. Motivated by applying molecular markers for a more accurate selection in the early stages of breeding, we performed pioneering genomic selection studies and optimization for its implementation in the blueberry breeding program. We have also addressed some complexities of sequence-based genotyping and model parametrization for an autopolyploid crop, providing empirical contributions that can be extended to other polyploid species. We herein revisited some of our previous genomic selection studies and showed for the first time its application in an independent validation set. In this paper, our contribution is three-fold: (i) summarize previous results on the relevance of model parametrizations, such as diploid or polyploid methods, and inclusion of dominance effects; (ii) assess the importance of sequence depth of coverage and genotype dosage calling steps; (iii) demonstrate the real impact of genomic selection on leveraging breeding decisions by using an independent validation set. Altogether, we propose a strategy for using genomic selection in blueberry, with the potential to be applied to other polyploid species of a similar background.

ACS Style

Luís Felipe V. Ferrão; Rodrigo R. Amadeu; Juliana Benevenuto; Ivone De Bem Oliveira; Patricio R. Munoz. Genomic Selection in an Outcrossing Autotetraploid Fruit Crop: Lessons From Blueberry Breeding. Frontiers in Plant Science 2021, 12, 1 .

AMA Style

Luís Felipe V. Ferrão, Rodrigo R. Amadeu, Juliana Benevenuto, Ivone De Bem Oliveira, Patricio R. Munoz. Genomic Selection in an Outcrossing Autotetraploid Fruit Crop: Lessons From Blueberry Breeding. Frontiers in Plant Science. 2021; 12 ():1.

Chicago/Turabian Style

Luís Felipe V. Ferrão; Rodrigo R. Amadeu; Juliana Benevenuto; Ivone De Bem Oliveira; Patricio R. Munoz. 2021. "Genomic Selection in an Outcrossing Autotetraploid Fruit Crop: Lessons From Blueberry Breeding." Frontiers in Plant Science 12, no. : 1.

Journal article
Published: 24 March 2021 in Agronomy
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Wild germplasm can be classified as the raw material essential for crop improvement. Introgression of wild germplasm is normally used in breeding to increase crop quality or resilience to evolving biotic and abiotic threats. Here, we explore the potential of introgressing Vaccinium elliottii into commercial blueberry germplasm. Vaccinium elliottii is a wild diploid blueberry species endemic to the southeastern United States that possesses highly desirable and economically important traits for blueberry breeding such as: short bloom to ripe period, adaptation to upland sandy soils, disease resistance, firmness, and pleasant flavor. To examine the potential of hybridization, we evaluated populations of interspecific hybrids across multiple stages of breeding (i.e., F1, F2, and backcrosses) in two crop seasons. We used our extensive pedigree data to generate breeding values for pre-breeding blueberry hybrid populations. Hybrid performance was evaluated considering fitness (i.e., plant vigor and plant height) in addition to evaluating six fruit-quality and marketable-related traits (i.e., size, firmness, acidity, soluble solids, weight, and yield). Overall, F2 and backcrosses rapidly achieved market thresholds, presenting values not significantly different from commercial blueberry germplasm. Our results confirmed the potential of exploiting the high genetic variability contained in V. elliottii for interspecific hybridization. Additionally, we developed germplasm resources that can be further evaluated and utilized in the breeding process, advancing selections for fruit quality and environmental adaptation.

ACS Style

Diego Cabezas; Ivone De Bem Oliveira; Mia Acker; Paul Lyrene; Patricio Munoz. Evaluating Wild Germplasm Introgression into Autotetraploid Blueberry. Agronomy 2021, 11, 614 .

AMA Style

Diego Cabezas, Ivone De Bem Oliveira, Mia Acker, Paul Lyrene, Patricio Munoz. Evaluating Wild Germplasm Introgression into Autotetraploid Blueberry. Agronomy. 2021; 11 (4):614.

Chicago/Turabian Style

Diego Cabezas; Ivone De Bem Oliveira; Mia Acker; Paul Lyrene; Patricio Munoz. 2021. "Evaluating Wild Germplasm Introgression into Autotetraploid Blueberry." Agronomy 11, no. 4: 614.

Preprint content
Published: 12 March 2021
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Genomic prediction (GP) integrates statistical, genomic and computational tools to improve the estimation of breeding values and increase genetic gain. Due to the broad diversity in biology, breeding scheme, propagation method, and unit of selection, no universal GP approach can be applied in all crops. In a genome-wide family prediction (GWFP) approach, the family bulk is the basic unit of selection. We tested GWFP in two loblolly pine (Pinus taeda L.) datasets: a breeding population composed of 63 full-sib families (5-20 individuals per family), and a simulated population with the same pedigree structure. In both populations, phenotypic and genomic data was pooled at the family level in silico. Marker effects were estimated to compute genomic estimated breeding values at the individual (GEBV) and family (GWFP) levels. Less than six individuals per family produced inaccurate estimates of family phenotypic performance and allele frequency. Tested across different scenarios, GWFP predictive ability was higher than those for GEBV in both populations. Validation sets composed of families with similar phenotypic mean and variance as the training population yielded predictions consistently higher and more accurate than other validation sets. Results revealed potential for applying GWFP in breeding programs whose selection unit are family bulks, and for systems where family can serve as training sets. The GWFP approach is well suited for crops that are routinely genotyped and phenotyped at the plot-level, but it can be extended to other breeding programs. Higher predictive ability obtained with GWFP would motivate the application of GP in these situations.

ACS Style

Esteban F. Rios; Mario H. M. L. Andrade; Marcio F.R. Resende Jr; Matias Kirst; Marcos D.V. de Resende; Janeo E. De Almeida Filho; Salvador A. Gezan; Patricio Munoz. Genomic Prediction in Family Bulks Using Different Traits and Cross-Validations in Pine. 2021, 1 .

AMA Style

Esteban F. Rios, Mario H. M. L. Andrade, Marcio F.R. Resende Jr, Matias Kirst, Marcos D.V. de Resende, Janeo E. De Almeida Filho, Salvador A. Gezan, Patricio Munoz. Genomic Prediction in Family Bulks Using Different Traits and Cross-Validations in Pine. . 2021; ():1.

Chicago/Turabian Style

Esteban F. Rios; Mario H. M. L. Andrade; Marcio F.R. Resende Jr; Matias Kirst; Marcos D.V. de Resende; Janeo E. De Almeida Filho; Salvador A. Gezan; Patricio Munoz. 2021. "Genomic Prediction in Family Bulks Using Different Traits and Cross-Validations in Pine." , no. : 1.

Preprint content
Published: 07 March 2021
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Blueberry (Vaccinium corymbosumand hybrids) is a specialty crop, with expanding production and consumption worldwide. The blueberry breeding program at the University of Florida (UF) has greatly contributed to the expansion of production areas by developing low-chilling cultivars better adapted to subtropical and Mediterranean climates of the globe. The breeding program has historically focused on phenotypic recurrent selection. As an autopolyploid, outcrossing, perennial, long juvenile phase crop, blueberry’s breeding cycles are costly and time-consuming, which results in low genetic gains per unit of time. Motivated by the application of molecular markers for a more accurate selection in early stages of breeding, we performed pioneering genomic prediction studies and optimization for implementation in the blueberry breeding program. We have also addressed some complexities of sequence-based geno- typing and model parametrization for an autopolyploid crop, providing empirical contributions that can be extended to other polyploid species. We herein revisited some of our previous genomic prediction studies and described the current achievements in the crop. In this paper, our contribution for genomic prediction in an autotetraploid crop is three-fold: i) summarize previous results on the relevance of model parametrizations, such as diploid or polyploid methods, and inclusion of dominance effects; ii) assess the importance of sequence depth of coverage and genotype dosage calling steps; iii) demonstrate the real impact of genomic selection on leveraging breeding decisions by using an independent validation set. Altogether, we propose a strategy for the use of genomic selection in blueberry, with potential to be applied to other polyploid species of a similar background.

ACS Style

Luís Felipe V. Ferrão; Rodrigo R. Amadeu; Juliana Benevenuto; Ivone De Bem Oliveira; Patricio R. Munoz. Genomic prediction in an outcrossing and autotetraploid fruit crop: lessons from blueberry breeding. 2021, 1 .

AMA Style

Luís Felipe V. Ferrão, Rodrigo R. Amadeu, Juliana Benevenuto, Ivone De Bem Oliveira, Patricio R. Munoz. Genomic prediction in an outcrossing and autotetraploid fruit crop: lessons from blueberry breeding. . 2021; ():1.

Chicago/Turabian Style

Luís Felipe V. Ferrão; Rodrigo R. Amadeu; Juliana Benevenuto; Ivone De Bem Oliveira; Patricio R. Munoz. 2021. "Genomic prediction in an outcrossing and autotetraploid fruit crop: lessons from blueberry breeding." , no. : 1.

Preprint
Published: 26 January 2021
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Wild germplasm can be classified as the raw material essential for crop improvement. Introgression of wild germplasm is normally used in breeding to increase crop quality or resilience to evolving biotic and abiotic threats. Here, we explore the potential of introgressing Vaccinium elliottii into commercial blueberry germplasm. Vaccinium elliottii is a wild diploid blueberry species endemic to the southeastern United States that possesses highly desirable and economically important traits for blueberry breeding such as: short bloom to ripe period, adaptation to upland sandy soils, disease resistance, firmness, and pleasant flavor. To examine the potential of hybridization, we evaluated populations of interspecific hybrids across multiples stages of breeding (i.e., F1, F2, and backcrosses) in two crop seasons. We used our extensive pedigree data to generate breeding values for pre-breeding blueberry hybrid populations. Hybrid performance was evaluated considering fitness (i.e., plant vigor and plant height) in addition to evaluating six fruit-quality and marketable-related traits (i.e., size, firmness, acidity, soluble solids, weight, and yield). Overall, F2 and backcrosses rapidly achieved market thresholds, presenting values not significantly different from commercial blueberry germplasm. Our results confirmed the potential of exploiting the high genetic variability contained in V. elliotii for interspecific hybridization. Additionally, we developed germplasm resources that can be further evaluated and utilized in the breeding process, advancing selections for fruit quality and environmental adaptation.

ACS Style

Diego Cabezas; Ivone De Bem Oliveira; Mia Acker; Paul Lyrene; Patricio R. Munoz. Evaluating the Introgression of Wild Germplasm Into Autotetraploid Blueberry Breeding. 2021, 1 .

AMA Style

Diego Cabezas, Ivone De Bem Oliveira, Mia Acker, Paul Lyrene, Patricio R. Munoz. Evaluating the Introgression of Wild Germplasm Into Autotetraploid Blueberry Breeding. . 2021; ():1.

Chicago/Turabian Style

Diego Cabezas; Ivone De Bem Oliveira; Mia Acker; Paul Lyrene; Patricio R. Munoz. 2021. "Evaluating the Introgression of Wild Germplasm Into Autotetraploid Blueberry Breeding." , no. : 1.

Preprint content
Published: 20 December 2020
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Over the last decade, multiparental populations have become a mainstay of genetics research in diploid species. Our goal was to extend this paradigm to autotetraploids by developing software for quantitative trait locus (QTL) mapping in connected F1 populations derived from a set of shared parents. For QTL discovery, phenotypes are regressed on the dosage of parental haplotypes to estimate additive effects. Statistical properties of the model were explored by simulating half-diallel diploid and tetraploid populations with different population sizes and numbers of parents. Across scenarios, the number of progeny per parental haplotype (pph) largely determined the statistical power for QTL detection and accuracy of the estimated haplotype effects. Multi-allelic QTL with heritability 0.2 were detected with 90% probability at 25 pph and genome-wide significance level 0.05, and the additive haplotype effects were estimated with over 90% accuracy. Following QTL discovery, the software enables a comparison of models with multiple QTL and non-additive effects. To illustrate, we analyzed potato tuber shape in a half-diallel population with 3 tetraploid parents. A well-known QTL on chromosome 10 was detected, for which the inclusion of digenic dominance lowered the Deviance Information Criterion (DIC) by 17 points compared to the additive model. The final model also contained a minor QTL on chromosome 1, but higher order dominance and epistatic effects were excluded based on the DIC. In terms of practical impacts, the software is already being used to select offspring based on the effect and dosage of particular haplotypes in breeding programs.

ACS Style

Rodrigo R. Amadeu; Patricio R. Munoz; Chaozhi Zheng; Jeffrey B. Endelman. QTL Mapping in Outbred Tetraploid (and Diploid) Diallel Populations. 2020, 1 .

AMA Style

Rodrigo R. Amadeu, Patricio R. Munoz, Chaozhi Zheng, Jeffrey B. Endelman. QTL Mapping in Outbred Tetraploid (and Diploid) Diallel Populations. . 2020; ():1.

Chicago/Turabian Style

Rodrigo R. Amadeu; Patricio R. Munoz; Chaozhi Zheng; Jeffrey B. Endelman. 2020. "QTL Mapping in Outbred Tetraploid (and Diploid) Diallel Populations." , no. : 1.

Preprint content
Published: 20 December 2020
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In diploid species, many multi-parental populations have been developed to increase genetic diversity and quantitative trait loci (QTL) mapping resolution. In these populations, haplotype reconstruction has been used as a standard practice to increase QTL detection power in comparison with the marker-based association analysis. To realize similar benefits in tetraploid species (and eventually higher ploidy levels), a statistical framework for haplotype reconstruction has been developed and implemented in the software PolyOrigin for connected tetraploid F1 populations with shared parents. Haplotype reconstruction proceeds in two steps: first, parental genotypes are phased based on multi-locus linkage analysis; second, genotype probabilities for the parental alleles are inferred in the progeny. PolyOrigin can utilize genetic marker data from single nucleotide polymorphism (SNP) arrays or from sequence-based genotyping; in the latter case, bi-allelic read counts can be used (and are preferred) as input data to minimize the influence of genotype call errors at low depth. To account for errors in the input map, PolyOrigin includes functionality for filtering markers, inferring inter-marker distances, and refining local marker ordering. Simulation studies were used to investigate the effect of several variables on the accuracy of haplotype reconstruction, including the mating design, the number of parents, population size, and sequencing depth. PolyOrigin was further evaluated using an autotetraploid potato dataset with a 3×3 half-diallel mating design. In conclusion, PolyOrigin opens up exciting new possibilities for haplotype analysis in tetraploid breeding populations.

ACS Style

Chaozhi Zheng; Rodrigo R. Amadeu; Patricio R. Munoz; Jeffrey B. Endelman. Haplotype Reconstruction in Connected Tetraploid F1 Populations. 2020, 1 .

AMA Style

Chaozhi Zheng, Rodrigo R. Amadeu, Patricio R. Munoz, Jeffrey B. Endelman. Haplotype Reconstruction in Connected Tetraploid F1 Populations. . 2020; ():1.

Chicago/Turabian Style

Chaozhi Zheng; Rodrigo R. Amadeu; Patricio R. Munoz; Jeffrey B. Endelman. 2020. "Haplotype Reconstruction in Connected Tetraploid F1 Populations." , no. : 1.

Journal article
Published: 01 December 2020 in G3 Genes|Genomes|Genetics
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A suitable pairwise relatedness estimation is key to genetic studies. Several methods are proposed to compute relatedness in autopolyploids based on molecular data. However, unlike diploids, autopolyploids still need further studies considering scenarios with many linked molecular markers with known dosage. In this study, we provide guidelines for plant geneticists and breeders to access trustworthy pairwise relatedness estimates. To this end, we simulated populations considering different ploidy levels, meiotic pairings patterns, number of loci and alleles, and inbreeding levels. Analysis were performed to access the accuracy of distinct methods and to demonstrate the usefulness of molecular marker in practical situations. Overall, our results suggest that at least 100 effective biallelic molecular markers are required to have good pairwise relatedness estimation if methods based on correlation is used. For this number of loci, current methods based on multiallelic markers show lower performance than biallelic ones. To estimate relatedness in cases of inbreeding or close relationships (as parent-offspring, full-sibs, or half-sibs) is more challenging. Methods to estimate pairwise relatedness based on molecular markers, for different ploidy levels or pedigrees were implemented in the AGHmatrix R package.

ACS Style

Rodrigo R. Amadeu; Leticia A. C. Lara; Patricio Munoz; Antonio A. F. Garcia. Estimation of Molecular Pairwise Relatedness in Autopolyploid Crops. G3 Genes|Genomes|Genetics 2020, 10, 4579 -4589.

AMA Style

Rodrigo R. Amadeu, Leticia A. C. Lara, Patricio Munoz, Antonio A. F. Garcia. Estimation of Molecular Pairwise Relatedness in Autopolyploid Crops. G3 Genes|Genomes|Genetics. 2020; 10 (12):4579-4589.

Chicago/Turabian Style

Rodrigo R. Amadeu; Leticia A. C. Lara; Patricio Munoz; Antonio A. F. Garcia. 2020. "Estimation of Molecular Pairwise Relatedness in Autopolyploid Crops." G3 Genes|Genomes|Genetics 10, no. 12: 4579-4589.

Special issue article
Published: 23 November 2020 in Crop Science
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In breeding programs, superior parental genotypes are used in crosses to generate novel genetic variability for new selection cycles. Genotypes are usually more adapted to environments where the breeding program is located, since selections are performed under specific agroecosystems. Thus, the objective of this study was to evaluate the performance of bermudagrasses (Cynodon Rich. species), St. Augustinegrass [Stenotaphrum secundatum (Walter) Kuntze], seashore paspalum (Paspalum vaginatum Sw.) and zoysiagrasses (Zoysia Willd. species) breeding lines from five different breeding programs (North Carolina State University, Oklahoma State University, Texas A&M University System, University of Florida, and University of Georgia) across the southeastern United States. Three breeding nurseries for each species were evaluated for two years at eight locations: Citra and Hague (FL), College Station and Dallas (TX), Griffin and Tifton (GA), Stillwater (OK), and Jackson Springs (NC). Turfgrass quality (TQ) was evaluated (rated on a 1 to 9 scale) across repeated measurements over time. Data were analyzed using mixed models and principal component analyses were performed using predicted genotypic values. The narrowest range in variation for TQ performance was observed in seashore paspalum breeding lines, whereas greater variation was observed for St. Augustinegrass and zoysiagrasses. St. Augustinegrass presented the lowest genotype by environment interaction in all nurseries. Specific adaptability was not observed for the lines developed by different breeding programs, with the exception of the bermudagrass lines from OSU in nursery 3. This article is protected by copyright. All rights reserved

ACS Style

Beatriz Tomé Gouveia; Esteban Fernando Rios; José Airton Rodrigues Nunes; Salvador A. Gezan; Patricio R. Munoz; Kevin E. Kenworthy; J. Bryan Unruh; Grady L. Miller; Susana R. Milla‐Lewis; Brian M. Schwartz; Paul L. Raymer; Ambika Chandra; Benjamin G. Wherley; Yanqi Wu; Dennis L. Martin; Justin Q. Moss. Multispecies genotype × environment interaction for turfgrass quality in five turfgrass breeding programs in the southeastern United States. Crop Science 2020, 1 .

AMA Style

Beatriz Tomé Gouveia, Esteban Fernando Rios, José Airton Rodrigues Nunes, Salvador A. Gezan, Patricio R. Munoz, Kevin E. Kenworthy, J. Bryan Unruh, Grady L. Miller, Susana R. Milla‐Lewis, Brian M. Schwartz, Paul L. Raymer, Ambika Chandra, Benjamin G. Wherley, Yanqi Wu, Dennis L. Martin, Justin Q. Moss. Multispecies genotype × environment interaction for turfgrass quality in five turfgrass breeding programs in the southeastern United States. Crop Science. 2020; ():1.

Chicago/Turabian Style

Beatriz Tomé Gouveia; Esteban Fernando Rios; José Airton Rodrigues Nunes; Salvador A. Gezan; Patricio R. Munoz; Kevin E. Kenworthy; J. Bryan Unruh; Grady L. Miller; Susana R. Milla‐Lewis; Brian M. Schwartz; Paul L. Raymer; Ambika Chandra; Benjamin G. Wherley; Yanqi Wu; Dennis L. Martin; Justin Q. Moss. 2020. "Multispecies genotype × environment interaction for turfgrass quality in five turfgrass breeding programs in the southeastern United States." Crop Science , no. : 1.

Journal article
Published: 23 November 2020 in Plants
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The demand for blueberry Vaccinium corymbosum L. (and hybrids) plants has significantly increased in the last 30 years due to its market expansion. In vitro propagation of sterile plants are required for commercial purposes but also for research applications such as plant transformation. Thus far, tissue culture characteristics of the tropical-adapted blueberry have been scarcely studied. In this study we present the following findings: (i) zeatin, a hormone used to promote plant growth, should be used in the 1–2 mg/L range to promote plant architecture optimal for transformation experiments; (ii) red-blue LED lights induce more production of meristems and biomass than white LED or fluorescent lights; (iii) levels as high as 1000 mg/L of decontamination agents (the antibiotics timentin and cefotaxime) can be used to eliminate Agrobacterium overgrowth without inhibiting plant growth during plant transformation experiments; (iv) kanamycin, paromomycin, and geneticin, which are widely used antibiotics to select transgene-carrying transformants, cannot be efficiently used in this system; (v) glufosinate, a widely used herbicide, shows potential to be used as an effective selectable marker for transformed plants.

ACS Style

Francesco Cappai; Alexandria Garcia; Ryan Cullen; Matthew Davis; Patricio R. Munoz. Advancements in Low-Chill Blueberry Vaccinium corymbosum L. Tissue Culture Practices. Plants 2020, 9, 1624 .

AMA Style

Francesco Cappai, Alexandria Garcia, Ryan Cullen, Matthew Davis, Patricio R. Munoz. Advancements in Low-Chill Blueberry Vaccinium corymbosum L. Tissue Culture Practices. Plants. 2020; 9 (11):1624.

Chicago/Turabian Style

Francesco Cappai; Alexandria Garcia; Ryan Cullen; Matthew Davis; Patricio R. Munoz. 2020. "Advancements in Low-Chill Blueberry Vaccinium corymbosum L. Tissue Culture Practices." Plants 9, no. 11: 1624.

Original research article
Published: 16 November 2020 in Frontiers in Plant Science
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Blueberry (Vaccinium corymbosum and hybrids) is an autotetraploid crop whose commercial relevance has been growing steadily during the last 20 years. However, the ever-increasing cost of labor for hand-picking blueberry is one main constraint in competitive marketing of the fruit. Machine harvestability is, therefore, a key trait for the blueberry industry. Understanding the genetic architecture of traits related to machine harvestability through Quantitative Trait Loci (QTL) mapping is the first step toward implementation of molecular breeding for faster genetic gains. Despite recent advances in software development for autotetraploid genetic mapping, a high-resolution map is still not available for blueberry. In this study, we crafted a map for autotetraploid low-chill highbush blueberry containing 11,292 SNP markers and a total size of 1,953.97 cM (average density of 5.78 markers/cM). This map was subsequently used to perform QTL analyses in 2-year field trials for a trait crucial to machine harvesting: fruit firmness. Preliminary insights were also sought for single evaluations of firmness retention after cold storage, and fruit detachment force traits. Significant QTL peaks were identified for all the traits and overlapping QTL intervals were detected for firmness across the years. We found low-to-moderate QTL effects explaining the phenotypic variance, which suggest a quantitative nature of these traits. The QTL intervals were further speculated for putative gene repertoire. Altogether, our findings provide the basis for future fine-mapping and molecular breeding efforts for machine harvesting in blueberry.

ACS Style

Francesco Cappai; Rodrigo R. Amadeu; Juliana Benevenuto; Ryan Cullen; Alexandria Garcia; Adina Grossman; Luís Felipe V. Ferrão; Patricio Munoz. High-Resolution Linkage Map and QTL Analyses of Fruit Firmness in Autotetraploid Blueberry. Frontiers in Plant Science 2020, 11, 1 .

AMA Style

Francesco Cappai, Rodrigo R. Amadeu, Juliana Benevenuto, Ryan Cullen, Alexandria Garcia, Adina Grossman, Luís Felipe V. Ferrão, Patricio Munoz. High-Resolution Linkage Map and QTL Analyses of Fruit Firmness in Autotetraploid Blueberry. Frontiers in Plant Science. 2020; 11 ():1.

Chicago/Turabian Style

Francesco Cappai; Rodrigo R. Amadeu; Juliana Benevenuto; Ryan Cullen; Alexandria Garcia; Adina Grossman; Luís Felipe V. Ferrão; Patricio Munoz. 2020. "High-Resolution Linkage Map and QTL Analyses of Fruit Firmness in Autotetraploid Blueberry." Frontiers in Plant Science 11, no. : 1.

Journal article
Published: 06 November 2020 in Agronomy
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The Cynodon spp. collection maintained by United States Department of Agriculture National Plant Germplasm System (USDA-NPGS) has limited information on nutritive value (NV) traits. In this study, crude protein (CP), phosphorous concentration (P), in vitro digestible organic matter (IVDOM), and neutral detergent fiber (NDF) were determined to (i) estimate genetic parameters for NV, (ii) obtain genetic values for the whole population across two harvests, (iii) estimate genotype by harvest interaction (GHI) for NV traits, and (iv) select accessions exhibiting improved NV traits compared to ‘Tifton 85′. The experiment was setup as a row-column design with two replicates and augmented representation of controls: Tifton 85, ‘Jiggs’, and ‘Coastal’. The whole-population was harvested twice, and data were analyzed using linear mixed models with repeated measures. In addition, a selected population of 15 genotypes were evaluated across 11 harvests to determine the extent of GHI. Genetic parameters revealed the presence of significant genetic variability, indicating potential improvements for NV through breeding. Specifically, P and IVDOM presented large variation, while NDF had lower diversity but some accessions exhibited lower NDF than Tifton 85. Low GHI, except for IVDOM, indicated genotypic stability and potential for selecting improved accessions under fewer harvests. Breeding line 240, PI-316510, and PI-3166536 presented superior NV than Tifton 85.

ACS Style

Cleber De Souza; Yolanda Lopez; Patricio Munoz; William Anderson; Miguel Dall’Agnol; Marcelo Wallau; Esteban Rios. Natural Genetic Diversity of Nutritive Value Traits in the Genus Cynodon. Agronomy 2020, 10, 1729 .

AMA Style

Cleber De Souza, Yolanda Lopez, Patricio Munoz, William Anderson, Miguel Dall’Agnol, Marcelo Wallau, Esteban Rios. Natural Genetic Diversity of Nutritive Value Traits in the Genus Cynodon. Agronomy. 2020; 10 (11):1729.

Chicago/Turabian Style

Cleber De Souza; Yolanda Lopez; Patricio Munoz; William Anderson; Miguel Dall’Agnol; Marcelo Wallau; Esteban Rios. 2020. "Natural Genetic Diversity of Nutritive Value Traits in the Genus Cynodon." Agronomy 10, no. 11: 1729.

Registration
Published: 05 November 2020 in Journal of Plant Registrations
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‘Mislevy’ (Reg. no. CV‐46, PI 693070) bermudagrass [Cynodon dactylon (L.) Pers.] was selected at the University of Florida, and a series of research projects was conducted to evaluate the merit of Mislevy to be released as a new bermudagrass cultivar in Florida. A grazing experiment was conducted in South Florida and clipping trials conducted in South Florida, north‐central Florida, and North Florida. In the grazing trial, Mislevy was compared with Jiggs, World Feeder, and ‘Tifton 85’ bermudagrass, and four stargrass (Cynodon nlemfuensis Vanderyst) cultivars/entries at four grazing frequencies. Mislevy, Jiggs, and Florona had the greatest overall herbage accumulation (HA), but Mislevy had greater HA at late maturity (7 wk). In the clipping trials, Mislevy was compared with Jiggs, Tifton 85, ‘Tifton 44’, ‘Coastal’, Alicia (North Florida only), and ‘Russell’ (North Florida only) bermudagrass. Mislevy and Jiggs had greater spring HA and total HA than the other cultivars/entries in South Florida and North Florida. In South Florida, all cultivars/entries had the presence of Bipolaris spp. in the aboveground forage at the 9‐wk regrowth interval; however, Mislevy and Tifton 44 had greater proportion of green tissue. In north‐central Florida, there was no difference in spring HA among cultivars, and Tifton 85 had greater total annual HA than Mislevy. Mislevy may be a viable option to increase bermudagrass genetic diversity and provide superior spring and annual HA in South Florida.

ACS Style

J. M. B. Vendramini; E. Rios; J. C. B. Dubeux Jr.; K. Quesenberry; P. Munoz. Registration of ‘Mislevy’ bermudagrass. Journal of Plant Registrations 2020, 15, 7 -15.

AMA Style

J. M. B. Vendramini, E. Rios, J. C. B. Dubeux Jr., K. Quesenberry, P. Munoz. Registration of ‘Mislevy’ bermudagrass. Journal of Plant Registrations. 2020; 15 (1):7-15.

Chicago/Turabian Style

J. M. B. Vendramini; E. Rios; J. C. B. Dubeux Jr.; K. Quesenberry; P. Munoz. 2020. "Registration of ‘Mislevy’ bermudagrass." Journal of Plant Registrations 15, no. 1: 7-15.

Journal article
Published: 19 October 2020 in Heredity
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Blueberry (Vaccinium spp.) is an important autopolyploid crop with significant benefits for human health. Apart from its genetic complexity, the feasibility of genomic prediction has been proven for blueberry, enabling a reduction in the breeding cycle time and increasing genetic gain. However, as for other polyploid crops, sequencing costs still hinder the implementation of genome-based breeding methods for blueberry. This motivated us to evaluate the effect of training population sizes and composition, as well as the impact of marker density and sequencing depth on phenotype prediction for the species. For this, data from a large real breeding population of 1804 individuals were used. Genotypic data from 86,930 markers and three traits with different genetic architecture (fruit firmness, fruit weight, and total yield) were evaluated. Herein, we suggested that marker density, sequencing depth, and training population size can be substantially reduced with no significant impact on model accuracy. Our results can help guide decisions toward resource allocation (e.g., genotyping and phenotyping) in order to maximize prediction accuracy. These findings have the potential to allow for a faster and more accurate release of varieties with a substantial reduction of resources for the application of genomic prediction in blueberry. We anticipate that the benefits and pipeline described in our study can be applied to optimize genomic prediction for other diploid and polyploid species.

ACS Style

Ivone De Bem Oliveira; Rodrigo Rampazo Amadeu; Luis Felipe Ventorim Ferrão; Patricio R. Muñoz. Optimizing whole-genomic prediction for autotetraploid blueberry breeding. Heredity 2020, 125, 437 -448.

AMA Style

Ivone De Bem Oliveira, Rodrigo Rampazo Amadeu, Luis Felipe Ventorim Ferrão, Patricio R. Muñoz. Optimizing whole-genomic prediction for autotetraploid blueberry breeding. Heredity. 2020; 125 (6):437-448.

Chicago/Turabian Style

Ivone De Bem Oliveira; Rodrigo Rampazo Amadeu; Luis Felipe Ventorim Ferrão; Patricio R. Muñoz. 2020. "Optimizing whole-genomic prediction for autotetraploid blueberry breeding." Heredity 125, no. 6: 437-448.

Review
Published: 09 October 2020 in Agronomy
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Southern highbush blueberry cultivation has expanded into non-traditional growing areas worldwide due to elite cultivars and improved horticultural practices. This article presents a comprehensive review of current production systems—alternatives to traditional open field production—such as production in protected environments, high-density plantings, evergreen production, and container-based production. We discuss the advantages and disadvantages of each system and compare their differences to open field production. In addition, we provide potential solutions for some of the disadvantages. We also highlight some of the gaps existing between academic studies and production in industry, providing a guide for future academic research. All these alternative systems have shown the potential to produce high yields with high-quality berries. Alternative systems, compared to field production, require higher establishment investments and thus create an entry barrier for new producers. Nevertheless, with their advantages, alternative productions have the potential to be profitable.

ACS Style

Yang Fang; Gerardo H. Nunez; Mariana Neves Da Silva; Douglas A. Phillips; Patricio R. Munoz. A Review for Southern Highbush Blueberry Alternative Production Systems. Agronomy 2020, 10, 1531 .

AMA Style

Yang Fang, Gerardo H. Nunez, Mariana Neves Da Silva, Douglas A. Phillips, Patricio R. Munoz. A Review for Southern Highbush Blueberry Alternative Production Systems. Agronomy. 2020; 10 (10):1531.

Chicago/Turabian Style

Yang Fang; Gerardo H. Nunez; Mariana Neves Da Silva; Douglas A. Phillips; Patricio R. Munoz. 2020. "A Review for Southern Highbush Blueberry Alternative Production Systems." Agronomy 10, no. 10: 1531.

Review
Published: 24 August 2020
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Southern highbush blueberry plantations have been expanded into worldwide non-traditional growing areas with elite cultivars and improved horticultural practices. This article presents a comprehensive review of current production systems – alternatives to traditional open field production – such as production in protected environments, high-density plantings, evergreen production, and container-based production. We discuss the advantages and disadvantages of each system and compare their differences to the open field production. In addition, potential solutions have been provided for some of the disadvantages. We also highlight some of the gaps existing between academic studies and production in industry, providing a guide for future academic research. All these alternative systems have shown the potential to produce high yields with high quality berries. Alternative systems, compared to the field production, require higher establishment investments and thus create an entry barrier for new producers. Nevertheless, with their advantages, alternative productions have potential to be profitable.

ACS Style

Yang Fang; Gerardo H. Nunez; Mariana Neves Da Silva; Douglas A. Phillips; Patricio R. Munoz. A Review for Southern Highbush Blueberry Alternative Production Systems. 2020, 1 .

AMA Style

Yang Fang, Gerardo H. Nunez, Mariana Neves Da Silva, Douglas A. Phillips, Patricio R. Munoz. A Review for Southern Highbush Blueberry Alternative Production Systems. . 2020; ():1.

Chicago/Turabian Style

Yang Fang; Gerardo H. Nunez; Mariana Neves Da Silva; Douglas A. Phillips; Patricio R. Munoz. 2020. "A Review for Southern Highbush Blueberry Alternative Production Systems." , no. : 1.

Original research article
Published: 16 July 2020 in Crop Science
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Estimation of genotype‐by‐environment interaction (GEI) is important in breeding programs because it provides critical information to guide selection decisions. In general, multi‐environment trials exhibit heterogeneity of variances and covariances at several levels. Thus, the objectives of this study were to: (i) find the best genetic covariance matrix to model GEI and compare changes in genotypic rankings between the best covariance structure against a compound symmetry structure, (ii) define mega‐environments for turfgrass performance across the southeastern United States, and (iii) estimate genetic correlations between drought/non‐drought and growing/non‐growing conditions to determine the extent of GEI under specific environments. Three nurseries with 165, 164 and 154 genotypes were evaluated in 2011–2012, 2012–2013 and 2013–2014, respectively. These nurseries were conducted at eight locations [Citra (FL), Hague (FL), College Station (TX), Dallas (TX), Griffin (GA), Tifton (GA), Stillwater (OK), and Jackson Springs (NC)]. The response variables were averaged turfgrass quality (TQ), TQ under drought (TQD); non‐drought TQ (TQND); TQ under actively growing months (TQG); and TQ under non‐growing months (TQNG). This study demonstrated that: (i) the best variance structure varied among traits and seasons, and changes in genotype rankings were dependent on GEI; (ii) considering TQ and TQND, mega‐environments formed between Jackson Springs, NC and College Station, TX, and between Citra, FL, Dallas, TX and Griffin, GA, while Stillwater, OK, Hague, FL and Tifton, GA represented unique environments across the southeastern United States; and (iii) genetic correlations between drought/non‐drought and growing/non‐growing conditions suggested that indirect selection can be efficient in multi‐environment trials for contrasting environmental conditions. Bermudagrass nurseries were screened for TQ in eight locations across the southeastern United States. Changes in genotype rankings by modeling covariance structures depend on the extent of GEI. The magnitude of the genetic variance was similar under drought or non‐drought conditions across locations. Five locations from three mega‐environments can discriminate bermudagrass genotypes for TQ. Indirect selection for TQ in bermudagrass can be achieved under drought/non‐drought and growing/non‐growing conditions for MET. This article is protected by copyright. All rights reserved

ACS Style

Beatriz Tomé Gouveia; Esteban Fernando Rios; José Airton Rodrigues Nunes; Salvador A. Gezan; Patricio R. Munoz; Kevin E. Kenworthy; J. Bryan Unruh; Grady L. Miller; Susana R. Milla‐Lewis; Brian M. Schwartz; Paul L. Raymer; Ambika Chandra; Benjamin G. Wherley; Yanqi Wu; Dennis Martin; Justin Q. Moss. Genotype‐by‐environment interaction for turfgrass quality in bermudagrass across the southeastern United States. Crop Science 2020, 60, 3328 -3343.

AMA Style

Beatriz Tomé Gouveia, Esteban Fernando Rios, José Airton Rodrigues Nunes, Salvador A. Gezan, Patricio R. Munoz, Kevin E. Kenworthy, J. Bryan Unruh, Grady L. Miller, Susana R. Milla‐Lewis, Brian M. Schwartz, Paul L. Raymer, Ambika Chandra, Benjamin G. Wherley, Yanqi Wu, Dennis Martin, Justin Q. Moss. Genotype‐by‐environment interaction for turfgrass quality in bermudagrass across the southeastern United States. Crop Science. 2020; 60 (6):3328-3343.

Chicago/Turabian Style

Beatriz Tomé Gouveia; Esteban Fernando Rios; José Airton Rodrigues Nunes; Salvador A. Gezan; Patricio R. Munoz; Kevin E. Kenworthy; J. Bryan Unruh; Grady L. Miller; Susana R. Milla‐Lewis; Brian M. Schwartz; Paul L. Raymer; Ambika Chandra; Benjamin G. Wherley; Yanqi Wu; Dennis Martin; Justin Q. Moss. 2020. "Genotype‐by‐environment interaction for turfgrass quality in bermudagrass across the southeastern United States." Crop Science 60, no. 6: 3328-3343.

Journal article
Published: 21 May 2020 in Agronomy
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Alfalfa is planted in more than 30 million hectares worldwide, but despite its popularity in temperate regions, it is not widely grown in subtropical agroecosystems. It is critical to improve alfalfa for such regions, considering current predictions of global warming and the increasing demands for animal-based products. In this study, we examined the diversity present in subtropical alfalfa germplasm and reported genetic parameters for forage production. An initial screening was performed from 2014 to 2016, evaluating 121 populations from different subtropical origins. Then, a breeding population was created by crossing selected plants, resulting in 145 full-sib and 36 half-sib families, which were planted in a row-column design with augmented representation of three controls (‘Bulldog805′, ‘FL99′ and ‘UF2015′). Dry matter yield (DMY), canopy height (AH), and percentage blooming (BLOOM) were measured across several harvests. Moderate narrow-sense heritability and high genetic correlations between consecutive harvests were estimated for all traits. The breeding line UF2015 produced higher DMY than FL99 and Bulldog805, and it could be a candidate cultivar release. Several families produced higher DMY than all checks, and they can be utilized to develop high yielding and adapted alfalfa cultivars for subtropical agroecosystems.

ACS Style

Janam P. Acharya; Yolanda Lopez; Beatriz Tome Gouveia; Ivone De Bem Oliveira; Jr. Marcio F. R. Resende; Patricio R. Muñoz; Esteban F. Rios. Breeding Alfalfa (Medicago sativa L.) Adapted to Subtropical Agroecosystems. Agronomy 2020, 10, 742 .

AMA Style

Janam P. Acharya, Yolanda Lopez, Beatriz Tome Gouveia, Ivone De Bem Oliveira, Jr. Marcio F. R. Resende, Patricio R. Muñoz, Esteban F. Rios. Breeding Alfalfa (Medicago sativa L.) Adapted to Subtropical Agroecosystems. Agronomy. 2020; 10 (5):742.

Chicago/Turabian Style

Janam P. Acharya; Yolanda Lopez; Beatriz Tome Gouveia; Ivone De Bem Oliveira; Jr. Marcio F. R. Resende; Patricio R. Muñoz; Esteban F. Rios. 2020. "Breeding Alfalfa (Medicago sativa L.) Adapted to Subtropical Agroecosystems." Agronomy 10, no. 5: 742.

Preprint content
Published: 15 May 2020
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Blueberry (Vaccinium corymbosumand hybrids) is an autotetraploid crop whose commercial relevance has been growing steadily during the last twenty years. However, the ever-increasing cost of labor for hand-picking blueberry is one main constraint in competitive marketing of the fruit. Machine harvestability is, therefore, a key trait for the blueberry industry. Understanding the genetic architecture of traits through quantitative trait locus (QTL) mapping is the first step towards implementation of molecular breeding for faster genetic gains. Despite recent advances in software development for autotetraploid genetic mapping, a high-resolution map is still not available for blueberry. In this study, we crafted a map for autotetraploid low-chill highbush blueberry containing 11,292 SNP markers and a total size of 1,953.97 cM (average density of 5.78 markers/cM). This map was subsequently used to perform QTL analyses for traits relevant to machine harvesting: firmness, firmness retention, and fruit detachment force. Significant QTL peaks were identified for all the traits. The QTL intervals were further explored for putative candidate genes. Genes related to cell wall remodeling were highlighted in the firmness and firmness retention intervals. For fruit detachment force, transcription factors involved in fruit abscission were detected. Altogether, our findings provide the basis for future fine-mapping and molecular breeding efforts for machine harvesting in blueberry.

ACS Style

Francesco Cappai; Rodrigo R. Amadeu; Juliana Benevenuto; Ryan Cullen; Alexandria Garcia; Adina Grossman; Luis Felipe V. Ferrao; Patricio R Munoz. High-Resolution Linkage Map and QTL Analyses for Machine Harvest Traits in Autotetraploid Blueberry. 2020, 1 .

AMA Style

Francesco Cappai, Rodrigo R. Amadeu, Juliana Benevenuto, Ryan Cullen, Alexandria Garcia, Adina Grossman, Luis Felipe V. Ferrao, Patricio R Munoz. High-Resolution Linkage Map and QTL Analyses for Machine Harvest Traits in Autotetraploid Blueberry. . 2020; ():1.

Chicago/Turabian Style

Francesco Cappai; Rodrigo R. Amadeu; Juliana Benevenuto; Ryan Cullen; Alexandria Garcia; Adina Grossman; Luis Felipe V. Ferrao; Patricio R Munoz. 2020. "High-Resolution Linkage Map and QTL Analyses for Machine Harvest Traits in Autotetraploid Blueberry." , no. : 1.