Recurrent Selection Program Research Articles

Accounting for heterogeneous genotypic variance of progenies within populations in autogamous plant breeding: An evaluation in common bean

AbstractIn breeding of autogamous plants, breeders often deal with the evaluation of progenies derived from multiple populations. We hypothesize that selection strategies that account for the heterogeneous genotypic variability of progenies within these populations associated with the population means may improve progeny selection. Thus, the objective of this work was to use two mixed models with progenies nested to population effects to obtain and evaluate indexes for the genotypic values of progenies. We used simulations and a real dataset from a multipopulation recurrent selection program of common bean (Phaseolus vulgaris L.). Progenies from 20 populations were evaluated for grain yield in two different generations. The three studied indexes consider the merit of populations, but differently account for the genotypic variability of progenies within populations: index gM uses a mean estimate, index gH is based on heterogeneous estimates, and the index gW also uses a mean estimate but is weighted by the selection accuracy within populations. The studied populations were highly diverse in both generations, justifying the implementation of the two models to obtain the population means and specific estimates of genotypic variability of progenies for each population. The comparison among indexes suggested that index gW more appropriately explored the information from the genotypic profiles of the common bean studied populations in the genotypic values of progenies. Thus, the index gW has the potential to help breeders of self‐pollinated plant species to improve progeny selection from multiple populations.

Genomic relationship–based genetic parameters and prospects of genomic selection for growth and wood quality traits in Eucalyptus benthamii

The unique adaptation of Eucalyptus benthamii to low temperatures coupled to fast growth and versatile wood quality has made it a valued plantation species in frost-prone areas worldwide, but little is known on its quantitative genetic parameters for key industrial traits. We used GBLUP additive (GA), additive-dominant (GAD), single-step (HBLUP), and pedigree-based predictive models to estimate lignin, extractives, carbohydrates, and wood density at age 4 and tree volume at age 6. By capturing hidden relatedness and correcting pedigree errors, SNP data disentangled non-additive from additive variance providing more realistic estimates of narrow-sense heritability than pedigrees, and more accurate predictions of trait values. Predictive abilities (PAs) ranged from 0.12 for volume (pedigree-based model) to 0.44 for wood density (models H, GA, and GAD). Considerable dominance variance was seen for all traits, growth was the trait most influenced by it, resulting in PAs 48.9% higher when this effect is considered, a result with important consequences both for clonal propagation and overall selection efficiency (Seff). Using a HBLUP model, phenotypes of non-genotyped trees increased PAs by increasing sample size and provided realized relationships with reduced genotyping cost. In a recurrent selection program, the preclusion of progeny testing provides an increase in Seff between 232% and 299%. In a clonal selection program, the elimination of both progeny and initial clonal trial may increase Seff between 134% and 277%. Increasing selection intensity by genomic prediction resulted in an additional impact on Seff. This study provides groundwork to implement genomic selection in E. benthamii breeding.

Genomic Prediction of Yield Traits in Single-Cross Hybrid Rice (Oryza sativa L.).

Hybrid rice varieties can outyield the best inbred varieties by 15 – 30% with appropriate management. However, hybrid rice requires more inputs and management than inbred rice to realize a yield advantage in high-yielding environments. The development of stress-tolerant hybrid rice with lowered input requirements could increase hybrid rice yield relative to production costs. We used genomic prediction to evaluate the combining abilities of 564 stress-tolerant lines used to develop Green Super Rice with 13 male sterile lines of the International Rice Research Institute for yield-related traits. We also evaluated the performance of their F1 hybrids. We identified male sterile lines with good combining ability as well as F1 hybrids with potential further use in product development. For yield per plant, accuracies of genomic predictions of hybrid genetic values ranged from 0.490 to 0.822 in cross-validation if neither parent or up to both parents were included in the training set, and both general and specific combining abilities were modeled. The accuracy of phenotypic selection for hybrid yield per plant was 0.682. The accuracy of genomic predictions of male GCA for yield per plant was 0.241, while the accuracy of phenotypic selection was 0.562. At the observed accuracies, genomic prediction of hybrid genetic value could allow improved identification of high-performing single crosses. In a reciprocal recurrent genomic selection program with an accelerated breeding cycle, observed male GCA genomic prediction accuracies would lead to similar rates of genetic gain as phenotypic selection. It is likely that prediction accuracies of male GCA could be improved further by targeted expansion of the training set. Additionally, we tested the correlation of parental genetic distance with mid-parent heterosis in the phenotyped hybrids. We found the average mid-parent heterosis for yield per plant to be consistent with existing literature values at 32.0%. In the overall population of study, parental genetic distance was significantly negatively correlated with mid-parent heterosis for yield per plant (r = −0.131) and potential yield (r = −0.092), but within female families the correlations were non-significant and near zero. As such, positive parental genetic distance was not reliably associated with positive mid-parent heterosis.

How segregating populations of passion fruit react to CABMV infection?

The passion fruit woodiness disease, caused by the cowpea aphid-borne mosaic virus (CABMV), is the most important disease and represents a limiting factor for culture. Cultivars with resistance levels are being developed from backcrosses associated with a recurrent selection program. Studies showing how segregating populations respond to infection over time and describing resistance are necessary and make it possible to characterize the genotypes and select the most promising ones. Therefore, the present study aimed to describe the pathogenesis; evaluate resistance in the Passiflora sp. × CABMV pathosystem; and select the most resistant individuals for generation advance in the recurrent selection program in passion fruit. Five generations of crossbreeding were used, namely, interspecific hybrid, backcrosses BC1.1 and BC1.2 and parents P. edulis and P. setacea. The plants were inoculated in a greenhouse and evaluated for resistance to CABMV. The area under the disease progress curve (AUDPC) was calculated and variance components and genetic values were estimated for the populations under study. High genetic variability was observed between the individuals, ranging from asymptomatic plants to plants exhibiting the most severe symptoms of the disease. Four phenotypic groups were formed, allowing greater differentiation between the generations and their parents. The presence of CABMV was confirmed in plants of the BC1.1 generation and of P. edulis, with characteristic symptoms of the virus. In asymptomatic plants, 75% of the individuals were considered resistant by PTA-ELISA and RT-PCR. The majority of individuals selected for resistance to CABMV belonged to the BC1.2 generation, which might thus be included in the recurrent selection program.

Multiple Small-Effect Alleles of Indica Origin Enhance High Iron-Associated Stress Tolerance in Rice Under Field Conditions in West Africa.

Understanding the genetics of field-based tolerance to high iron-associated (HIA) stress in rice can accelerate the development of new varieties with enhanced yield performance in West African lowland ecosystems. To date, few field-based studies have been undertaken to rigorously evaluate rice yield performance under HIA stress conditions. In this study, two NERICA × O. sativa bi-parental rice populations and one O.sativa diversity panel consisting of 296 rice accessions were evaluated for grain yield and leaf bronzing symptoms over multiple years in four West African HIA stress and control sites. Mapping of these traits identified a large number of QTLs and single nucleotide polymorphisms (SNPs) associated with stress tolerance in the field. Favorable alleles associated with tolerance to high levels of iron in anaerobic rice soils were rare and almost exclusively derived from the indica subpopulation, including the most favorable alleles identified in NERICA varieties. These findings highlight the complex genetic architecture underlying rice response to HIA stress and suggest that a recurrent selection program focusing on an expanded indica genepool could be productively used in combination with genomic selection to increase the efficiency of selection in breeding programs designed to enhance tolerance to this prevalent abiotic stress in West Africa.

Efficiency of a recurrent selection method to achieve resistance of common beans to Pseudocercospora griseola in a short period

ABSTRACT The angular leaf spot (ALS), caused by the fungus Pseudocercospora griseola, is one of the most notable diseases of common beans (Phaseolus vulgaris). The most effective strategy to control ALS is quantitative disease resistance provided by major and minor genes. One breeding strategy for obtaining lines with durable resistance to P. griseola is a recurrent selection that aims to gradually assemble favorable alleles. In this study, common beans were artificially inoculated with P. griseola and grown in a greenhouse under a recurrent selection program that aims to accelerate the breeding cycle and assimilate resistant conferring genes per generation. From the initial population, three cycles of evaluation, selection, and intercross were carried out in a greenhouse and the most resistant plants were phenotypically selected. Plants at the V2 stage were inoculated with an isolate of P. griseola, race 63-63. Selected plants were transplanted into pots and intercrossed to reap the next cycle of selection. Progenies obtained from the base population (C0) and subsequent cycles (CI, CII, and CIII) were assessed for the degree of the symptoms for ALS under greenhouse and field conditions. The rate of genetic progress per breeding cycle was - 14.8% and - 5.3% for the plants grown in greenhouse and field, respectively. Artificial inoculation with P. griseola allowed three recurrent selection cycles per year, signifying a promising method to obtain ALS-resistant common bean lines in a short period.

Number of progenies and repetitions for reciprocal full-sib recurrent selection programs in maize

ABSTRACT For a reciprocal recurrent selection (RRS) program to succeed, it is essential to maintain genetic variability throughout the selection cycles and to obtain accurate estimates of genetic parameters, which in turn are directly related to the number of progenies and repetitions evaluated. This study evaluates the potential of maize progenies of the sixth cycle of RRS and proposes, using simulation methods, the ideal combination of the number of progenies and repetitions to employ in reciprocal full-sib recurrent selection. A total of 163 full-sib progenies were evaluated in a randomized block design with six repetitions. Based on the yield data, analysis of variance was carried out, and different scenarios were simulated using the Monte Carlo chain method. These scenarios varied in the number of repetitions (two, four, and six) and progenies (30 to 163). The contrast between progenies and controls was significant, revealing the potential of the progenies of the sixth cycle of RRS. The high magnitude of the selective accuracy (0.77) was reflected in high estimates of heritability, which allowed for efficient phenotypic selection, obtaining selection gains of 14.07%. From the estimates of phenotypic and genotypic variance, heritability, accuracy, and standard error, it was found that a repetition number above two results in drastic changes in the estimates of these parameters; however, with the use of 130 progenies, these estimates tend to stabilize, implying that a high number of progenies does not interfere decisively in the quality of most parameters, except for the limits of maximum and minimum variation.

Germplasm enhancement and cultivar development: The need for sustainable breeding

Abstract: Farmers need sustainable cultivars to increase food supply and value with less production land, animals, and inputs. Next generation plant and animal breeders face climate change adaptation and mitigation challenges. These challenges need to be addressed with opportunities for significant reduction of environmental impact developing cultivars less addicted to fertilizers and soil moisture needs. Sustainable breeding can help balance agriculture with the environment. Sustainable breeders need to integrate long-term pre-breeding activities with cultivar development efforts providing farmers options to comply with environmental regulations. Good choice of germplasm is still the most important decision. The most sophisticated tools will have limited success if poor choices of germplasm are made. Seed companies need capable breeders developing the next generation of sustainable cultivars while public institutions need to mentor sustainable breeders capable to not only broadening and improving unique germplasm but also developing new cultivars carrying desirable traits. Graduates mentored in breeding programs integrating these needs will be selected for industry jobs without need for re-training. Sustainable breeders will need to operate in new breeding centers located in strategic environments for faster genetic improvement ahead of climate changes. Key factors for developing useful and unique sustainable cultivars will be the adaptation of exotic germplasm and the maximization of its genetic improvement before cultivar development through public and private partnerships. Inbreeding, genetic divergence, and reciprocal recurrent selection programs will continue to be essential to purify cultivars and exploit heterosis in economically important species.

Detection of Non-Additive Gene Action within Elite Maize Populations Evaluated in Contrasting Environments under Rainforest Ecology in Nigeria

Proper understanding of the mode of gene action in open-pollinated varieties (OPVs) maize parents helps breeder in the choice of appropriate breeding method to improve its genetic value. The objectives of the present study were to determine gene action controlling grain yield and other agronomic traits of late maturing elite OPVs and classify the varieties into heterotic groups. Ninety-one hybrids generated from 14 elite OPV parents using diallel mating design were evaluated with their parents plus three commercial checks under marginal rainfall, drought, and optimal environments in Nigeria from 2017 to 2018. The experiment was laid out in a 9 × 12 alpha lattice with three replications in each environment. Results showed that there were significant mean squares for grain yield and most agronomic traits. Significant general combining ability (GCA) and specific combining ability (SCA) mean squares for some of the traits indicated that additive and non-additive genetic gene actions were important in the inheritance of yield and those traits among this set of genotypes. However, non-additive genetic effects were more important than additive for grain yield and other agronomic traits in all research environments. Only TZL Comp-3 C3 DT had significant and positive GCA effects (0.336*) while three hybrids had significant and positive SCA for grain yield across research environments. Because of the preponderance of non-additive gene action over additive gene action, distinct heterotic groups could not be identified but four tester groups were identified by HSGCA (Heterotic grouping based on Specific and General Combining Ability) and three groups by HGCAMT (Heterotic grouping based on the GCA of Multiple Traits). Results of grouping were not related to the endosperm colour but grouping based on HGCAMT was related to the pedigree of the varieties. In conclusion, this study has demonstrated preponderance of non-additive gene action over the additive gene action for all measured traits. The presence of the non-additive gene action present in the studied materials can enhance identification of outstanding varietal hybrids and population testers that can serve as base genetic materials for future maize improvement through reciprocal recurrent selection program in SSA.

Response of Forty (40) High-Producing Cacao Genotypes to Cacao Swollen Shoot Disease

Aims: Cocoa swollen shoot is a dreaded viral disease that is prevalent in the producing areas of West Africa. In Côte d'Ivoire, it undermines the sustainability of cocoa farming. Integrated pest management based on the use of disease-resistant or disease-tolerant plant material remains a sustainable solution.
 Place and Duration of Study: Integrated Pest Management Unit against Cocoa swollen shoot, Experimental greenhouse of Bouaflé, National Centre for Agronomic Research (CNRA).
 Methodology: Forty elite genotypes of cocoa trees selected from different populations in the Reciprocal Recurrent Selection program of Cocoa in Côte d'Ivoire were evaluated against strain D of Cacao Swollen Shoot Virus (CSSV). Five seedlings of each genotype were infected by patch grafting and observed for 5 months.
 Study Design: Plants are placed in a greenhouse in a completely random arrangement, with five repetitions.
 Results: Three cocoa genotypes (C77, C87 and C96) were free of disease symptoms and eight genotypes (C77, C87, C96, C3, C12, C26, C53 and C98) had the lowest infection scores. The disease significantly affected plant development and growth.
 Conclusion: Some genotypes selected within the Reciprocal Recurrent Selection program are promising for breeding against CSSV disease. These eight genotypes will be tested in a field environment to confirm their tolerance.

Changes in yield determinants and quality traits in wheat after 12 cycles of recurrent selection

The objective of this study was to test the genetic response to 12 cycles of a recurrent selection program for grain yield and related traits. During two seasons the 39 S-derived families (three/C0–C12 populations) were evaluated under conventional (CT) and non-tillage (NT) systems. Grain and biomass yield were determined. The grain number per square meter and harvest index were also estimated. Flour protein content, sodium dodecyl sulphate sedimentation, and lactic acid solvent retention capacity were considered as end-use quality predictive tests. High molecular weight glutenin subunits (HMW-GS) variation was also analyzed. A significant increase in grain yield per selection cycle, estimated in 3.25 g m−2 (1.3%) per year, was found under NT, but there was a not significant genetic progress under CT. The decrease in the percentage of protein in the most advanced selection cycles (11.0% vs. 9.7%) did not negatively affect its quality. HMW-GS variation analysis showed the erosion of extreme subunits related to gluten strength. After 24 years of recurrent selection, the grain yield was improved without affecting its industrial quality.

Phenotypic characterization of recurrent selection S1 Papaya (Carica papaya L.) families by multivariate approach

In the current study, the morphological traits in 222 individuals of the UCP-C0 base population were evaluated to distinguish the phenotypic variability and thus to be used in the papaya recurrent selection program. The studied traits showed considerable differences among the individuals. The fruit weight ranged from 279.7 to 1808.0 g with average of 859.7 g, the number of commercial fruits ranged from 5 to 125 fruits, the fruit and pulp firmness ranged from 76.69 and 59.44 N to 166.70 and 132.93 N respectively, while the soluble solids content was between 5.10 and 14.93° Brix. The principal component analysis showed that five components explained 76% of the total variance. Morphological cluster analysis based on the UPGMA method showed 13 distinct clusters among all the studied accessions, and the fruit weight was that most contributed for the genetic diversity. The results show that the UCP-C0 has wide genetic variability and therefore the choice of genotypes used as parents in the generation of the UCP-C0 was very effective to generate a broad base population for most of the agronomic and fruit quality traits. The strategy to use the highly heterogeneous and heterozygous dioic progenies, and the pollen mix of elite genitors, contributed to the observed results, mainly by the genetic variability present in them. A broad base population is fundamental to establish the recurrent selection program, a classical methodology that may provide superior genotypes at short and long terms.

Increasing the efficiency of recurrent selection for angular leaf spot resistance in common bean

AbstractA common bean (Phaseolus vulgaris L.) breeding program for resistance to Pseudocercospora griseola (Sacc.) Crous & U. Braun (angular leaf spot) using recurrent selection has been conducted since 1998 in Brazil. The selection has been carried out in the field with high natural occurrence of the pathogen. One recurrent selection cycle has been conducted per year. The efficiency of artificial inoculation of P. griseola and early assessment of angular leaf spot severity in common bean progenies of this program were evaluated. For this, 254 and 166 S0:1 progenies from Cycles XVI and XVIII, respectively, were assessed for angular leaf spot severity in field, with natural occurrence of the pathogen and in greenhouse with artificial inoculation of P. griseola. Most progenies showed a high level of resistance to angular leaf spot, indicating the efficiency of recurrent selection. Artificial inoculation of P. griseola in the greenhouse showed promise for the selection of resistant plants in a recurrent selection program allowing breeders to carry out two cycles per year. A scheme was proposed that combined the advantages of early‐generation selection with artificial inoculation of the pathogen in greenhouse with the advantages of selection in field with natural occurrence of P. griseola in the dry season, increasing genetic gain per unit time.

Genetic and phenotypic parameters associated with soybean progenies in a recurrent selection program

Abstract The aim of this study was to estimate genetic and phenotypic parameters associated with progenies from the recurrent selection program for grain yield in soybean. The evaluation of S0:1 progenies was in Lavras in the 2015/2016 crop year. The S0:2 progenies were evaluated in Lavras, Nazareno, and Itutinga. The S0:3 progenies were evaluated in Lavras, Ijaci, and Itutinga in the following crop years. The following traits were evaluated: days to flowering, days to full maturity, bottom pod height, plant height, lodging, and grain yield. The expected gain and gain achieved from selection, genetic correlation, and correlated response were estimated. The variance components show variability among the progenies. It was possible to obtain gains from selection for grain yield for all selection intensities (1, 5, 10, 15, 20, 25, and 30%). The variability and the high performance of the progenies indicate that implementation of the recurrent selection program can be successful.

Procedures for identification of superior progenies in successive generations of evaluation in common bean

When breeding the common bean in Brazil, the best progenies are chosen, normally, from solely the generation under analysis at the conclusion of the evaluation, without considering what occurred in the past. However, a number of recently published studies show that if an evaluation were to consider all relevant generations, the gain from selection could be higher, especially when an index that involves information from the population that gave rise to the progenies is used. Thus, the aim of this study was to compare three selection procedures in the evaluation of successive generations and to discuss the implications of the progeny × environment interaction in terms of success of selection. Cycle XV progenies from a bean recurrent selection program were used. The traits evaluated were grain yield, plant architecture and grain type. Analysis of variance was carried out and the variance components and heritabilities were estimated. The same analyses were made using mixed models. A selection index weighted by the effect of populations and progenies within populations (WSI) was also obtained. We estimated the correlations between the classification of the progenies using the three procedures and the coincidence of the best progenies evaluated in S0:4 with the progenies in the previous generations. We found that the classification of the progenies by the BLUP’s and WSI did not expressively differ from that obtained when using only the mean, even when a number of generations were considered in the selection. None of the procedures used effectively mitigated the effect of the progeny × environment interaction.

Responses of sour passion fruit (<i>Passiflora edulis</i> Sims) seeds from the third recurrent selection cycle during storage

Conflicting responses have been found for the period of conservation of passion fruit seeds. Therefore, this study aimed to evaluate the response of the seeds of passion fruit progenies to a 24-month storage period. The sour passion fruit progenies from the third cycle of Universidade Estadual do Norte Fluminense Darcy Ribeiro - UENF intrapopulation recurrent selection program were grown in Itaocara- RJ and the progenies seeds were evaluated for: germination potential, germination first count, accelerated aging, first count of accelerated aging test, seedling and radicle size and germination speed index. The germination and vigor of the seeds of the full-sib progenies were assessed by analysis of variance and factorial arrangement with 3 progenies and 7 periods of storage and the averages were compared by Tukey test at 5% probability. Progenies 1 and 2 responded better to germination (92% for both progeny) and vigor test of accelerated aging (92% for both progeny), rootlet size (6.4 and 5.8 cm, respectively) and germination speed index (2.91 and 2.85, respectively) during storage. Variations were observed during the storage period in mean of progenies for germination (81-93%) and vigor for all traits, except accelerated aging (84-91%). At eight months of storage, the seeds presented increased vigor; at 16 months, they showed reduced vigor. The passion fruit seeds of the progenies under analysis can be stored for up to 24 months with high and uniform germination rate and no loss in vigor. The seeds from the passion fruit breeding program showed increases in the variables of germination and vigor during the selection process for fruit production variables, proving the efficiency of the breeding program.

CP-Hilda 2, new yellow grain synthetic maize (Zea mays) variety resistant to horse´s tooth (Claviceps gigantea) for the Mexican highlands

En producción de maíz, la semilla de variedades de polinización libre ofrecen al agricultor obtener un precio más bajo que la semilla de híbridos comerciales, no es necesario comprar semilla nueva cada año, por su estabilidad genética puede sembrarse varios años, ofrecen más estabilidad en rendimiento de grano y tipo de planta, es más fácil de conseguir, puede competir en rendimiento con un híbrido y puede propagarse entre agricultores. El presente trabajo es resultado de actividades desarrolladas para la obtención de la variedad sintética de maíz de endosperma amarillo CP-Hilda 2, con buen comportamiento agronómico y resistencia genética a la enfermedad “diente de caballo”, siguiendo un programa de selección recurrente con líneas S1.

CP-Vero 1, white maize (Zea mays) synthetic variety resistant to head smut (Sporisorium reilianum f. sp. zeae) for Mexican highlands

En la producción de maíz, el agricultor se encuentra ante la alternativa de sembrar semilla comercial de maíz híbrido o semilla de polinización libre incluyendo variedades mejoradas o poblaciones nativas. La semilla de maíz híbrido tiene un alto costo, es necesario comprar semilla nueva para cada siembra mientras que la semilla de una variedad mejorada puede sembrarse por varios años, puede competir en rendimiento con un híbrido, es de bajo costo y puede compartirse entre agricultores. Una variedad sintética ofrece ventajas adicionales sobre una variedad mejorada común, con buen rendimiento de grano y uniformidad en floración y fenotipo. Este trabajo presenta actividades involucradas en la obtención de la variedad sintética de maíz de endospermo blanco CP-Vero 1 siguiendo un programa de selección recurrente de líneas S1 para obtener buenas características agronómicas y resistencia al carbón de la espiga.

Intrapopulation recurrent selection in sweet sorghum for improving sugar yield

Sweet sorghum [Sorghum bicolor (L.) Moench] accumulates fermentable sugars in the stalk making this crop an important bioenergy feedstock. The objectives of this study were to implement an intrapopulation recurrent selection program to increase the sugar yield in sweet sorghum [Sorghum bicolor (L.) Moench] and to estimate the genetic progress after a recurrent selection cycle for the main agro-industrial traits of interest. The base population for cycle 0 (C0) was developed from 15 fertility restorer lines using a genetic male-sterile source to promote recombination. A total of 196 half-sib progeny from C0 were evaluated in experiments with a 14 × 14 lattice design in the 2016–2017 season. The following traits were evaluated: days to flowering (DF), plant height (PH), fresh biomass yield (FBY), total soluble solids content (TSS) and tons of Brix per hectare (TBH). Data were analyzed using the mixed model approach. Genetic variation was observed among the C0 half-sib progeny for all of the agro-industrial traits studied. The 40 best progeny were selected based on the best linear unbiased predictions (BLUPs) for TBH, which were then recombined to form the base population for cycle 1 (C1). Subsequently, 40 half-sib progeny from each cycle (C0 and C1) were randomly selected and evaluated in experiments with a 9 × 9 lattice design to estimate the genetic progress for DF, PH, FBY, TSS and TBH traits. The genetic progress was significant, with increases of 3.73% for PH, 8.04% for FBY, and 8.65% for TBH, demonstrating the efficiency of the intrapopulation recurrent selection program used.

Genomic Selection with Allele Dosage in Panicum maximum Jacq.

Genomic selection is an efficient approach to get shorter breeding cycles in recurrent selection programs and greater genetic gains with selection of superior individuals. Despite advances in genotyping techniques, genetic studies for polyploid species have been limited to a rough approximation of studies in diploid species. The major challenge is to distinguish the different types of heterozygotes present in polyploid populations. In this work, we evaluated different genomic prediction models applied to a recurrent selection population of 530 genotypes of Panicum maximum, an autotetraploid forage grass. We also investigated the effect of the allele dosage in the prediction, i.e., considering tetraploid (GS-TD) or diploid (GS-DD) allele dosage. A longitudinal linear mixed model was fitted for each one of the six phenotypic traits, considering different covariance matrices for genetic and residual effects. A total of 41,424 genotyping-by-sequencing markers were obtained using 96-plex and Pst1 restriction enzyme, and quantitative genotype calling was performed. Six predictive models were generalized to tetraploid species and predictive ability was estimated by a replicated fivefold cross-validation process. GS-TD and GS-DD models were performed considering 1,223 informative markers. Overall, GS-TD data yielded higher predictive abilities than with GS-DD data. However, different predictive models had similar predictive ability performance. In this work, we provide bioinformatic and modeling guidelines to consider tetraploid dosage and observed that genomic selection may lead to additional gains in recurrent selection program of P. maximum.