Genetic variability and selection of natural populations of Campomanesia adamantium using REML/BLUP mixed modelsAbstract
The Brazilian Cerrado, a biodiversity hotspot, has been significantly impacted by climate change, land use modifications, and unsustainable extractivism, threatening the genetic diversity of many native species. Campomanesia adamantium (Cambess.) O. Berg, known as guavira, is a socioeconomically important fruit species in the Central-West region of Brazil. Given the current and potential value of guavira, alongside climate change, agricultural expansion in the Cerrado and inadequate extractivism, studies are necessary to understand and preserve natural populations and select genotypes for guavira breeding programs. The objectives of this study are to evaluate the morphophysiological traits of the fruits, estimate genetic parameters and genotypic values, and identify superior genotypes in natural guavira populations using mixed models (REML/BLUP). We analyzed 360 genotypes from six natural populations in Jardim and Bonito, MS, Brazil. The fruits were assessed for longitudinal and transversal diameters; fruit, pulp, and seed masses; peel thickness and total soluble solids. Significant genetic variability was detected for transverse diameter, fruit mass, and peel thickness, with heritability estimates ranging from low (0.03 for total soluble solids) to moderate (0.57 for peel thickness). Population structure influenced genetic variance, with populations 3 and 5 contributing the highest number of superior individuals. Genotypes 144, 145, 174, and 176 stood out for the largest number of characters shared traits related to the transverse diameter, fruit mass, and peel thickness, by comparing and identifying relationships between sets of genotypes. The study revealed that environmental factors significantly affect genetic variability, highlighting the importance of targeted selection strategies. Our findings provide valuable insights for conservation and genetic improvement programs for C. adamantium, ensuring the sustainability and economic potential of this native Cerrado species.
Keywords:
guavira; fruit of the Cerrado; phenotypic characteristics; genetic parameters
Resumo
O Cerrado brasileiro, um hotspot de biodiversidade, tem sido significativamente impactado por mudanças climáticas, modificações no uso da terra e extrativismo insustentável, ameaçando a diversidade genética de muitas espécies nativas. Campomanesia adamantium (Cambess.) O. Berg, conhecida como guavira, é uma espécie frutífera socioeconomicamente importante na região Centro-Oeste do Brasil. Dado o valor atual e potencial da guavira, juntamente com as mudanças climáticas, expansão agrícola no Cerrado e extrativismo inadequado, estudos são necessários para entender e preservar populações naturais e selecionar genótipos para programas de melhoramento de guavira. Os objetivos deste estudo são avaliar as características morfofisiológicas dos frutos, estimar parâmetros genéticos e valores genotípicos e identificar genótipos superiores em populações naturais de guavira usando modelos mistos (REML/BLUP). Analisamos 360 genótipos de seis populações naturais em Jardim e Bonito, MS, Brasil. Os frutos foram avaliados quanto aos diâmetros longitudinal e transversal; massas de frutos, polpa e sementes; espessura da casca e sólidos solúveis totais. Foi detectada variabilidade genética significativa para diâmetro transversal, massa do fruto e espessura da casca, com estimativas de herdabilidade variando de baixa (0,03 para sólidos solúveis totais) a moderada (0,57 para espessura da casca). A estrutura populacional influenciou a variância genética, com as populações 3 e 5 contribuindo com o maior número de indivíduos superiores. Os genótipos 144, 145, 174 e 176 se destacaram pelo maior número de caracteres compartilhados relacionados ao diâmetro transversal, massa do fruto e espessura da casca, pela comparação e identificação de relações entre conjuntos de genótipos. O estudo revelou que fatores ambientais afetam significativamente a variabilidade genética, destacando a importância de estratégias de seleção direcionadas. Nossas descobertas fornecem insights valiosos para programas de conservação e melhoramento genético de C. adamantium, garantindo a sustentabilidade e o potencial econômico desta espécie nativa do Cerrado.
Palavras-chave:
guavira; fruto do Cerrado; características fenotípicas; parâmetros genéticos
1. Introduction
Climate change, land use, and soil cover have altered the biodiversity of the Brazilian Cerrado, known for its rich fauna and flora. Changes occur through the expansion of agricultural frontiers, fires, and/or inadequate extractivism, causing losses in native vegetation and natural habitat, compromising the genetic diversity of many species (Françoso et al., 2015; Strassburg et al., 2017; Velazco et al., 2019). Among the compromised plant species is Campomanesia adamantium (Cambess.) O. Berg, popularly known as guavira (Crispim et al., 2021). Guavira is distributed in Argentina, Paraguay, and Brazil, where it occurs in the Cerrado biome. The species is socio-economically important for the indigenous and traditional people living in the Central-West Region and was declared a symbolic fruit of the State of Mato Grosso do Sul in 2017 (Zorgetto-Pinheiro et al., 2023; Crispim et al., 2021).
Guavira is a perennial shrub measuring 0.50 to 3.0 m in height, with cultural, food, and medicinal importance (Dresch et al., 2015; Crispim et al., 2018; Castro et al., 2023; Santos et al., 2023). Guavira fruits are juicy, acidic, slightly sweet, and have a low caloric value due to their high water content, dietary fiber, and high mineral content (Vallilo et al., 2006, 2008). The peel and pulp are a source of vitamin C and antioxidant compounds (Pereira et al., 2012; Dresch et al., 2015) with medicinal properties (Cardozo et al., 2018; Crispim et al., 2018). The fruits are appreciated and sold by local communities on the shoulders of highways and at regional fairs, which favors inadequate extractivism. They can be consumed fresh and processed to prepare juices, ice creams, jellies, sweets, and drinks (Cardozo et al., 2018; Crispim et al., 2018).
Guavira cultivation has been recommended to recover deforested or degraded areas and agroforestry systems (Zorgetto-Pinheiro et al., 2023; Crispim et al., 2021; Santos et al., 2019). The genetic variability of natural populations and the relationships with environmental factors regarding biometric traits and fruit quality need to be known to select superior genotypes considering the potential of the species and the strong pressure from environmental changes (Crispim et al., 2018, 2019). Knowing genetic variability is crucial, as it allows the establishment of conservation strategies, genetic improvement programs, and sustainable management of the species.
Our study focuses on natural populations of perennial plants, which present unbalanced data. Therefore, the use of robust statistical tools such as mixed models is necessary. The appropriate procedure is REML/BLUP, which estimates genetic parameters using the restricted maximum likelihood (REML) method and quantifies genetic gains, in addition to selecting superior plants by predicting genotypic values using the best linear unbiased prediction (BLUP) (Resende, 2016; Yamana et al., 2007). This method is widely used in plant breeding and is efficient in several perennial species, including Saccharum officinarum (Carvalho et al., 2020; Moraes et al., 2021; Santos et al., 2023), Coffea arabica (Saavedra et al., 2023) and species of the family Myrtaceae, such as Eucalyptus spp. (Estopa et al., 2023), Psidium spp. (Maitan et al., 2023), and Campomanesia xanthocarpa (Homczinski et al., 2022). However, to the best of our knowledge, there are no studies of this nature on C. adamantium populations in the literature.
In this context, this study aimed to evaluate the morphophysiological traits of fruits, estimate genetic parameters and genotypic values and identify superior genotypes in natural populations of C. adamantium using mixed models.
2. Material and Methods
2.1. Characterization of the study area
The study was conducted in a Cerrado area located in two municipalities: Jardim and Bonito, in the State of Mato Grosso do Sul, Brazil. Three natural populations of guavira were evaluated in each municipality (Figures 1A and 1B).
Geographical location of the Campomanesia adamantium populations sampled in the municipalities of Bonito, MS (A), and Jardim, MS (B), Brazil.
According to Köppen criteria, the climate of the municipality of Jardim is classified as Aw, that is, a tropical climate with a dry winter. It has a rainy season in the summer, from November to April, and a clear dry season in the winter, from May to October, when mean rainfall totals are less than 50 mm. Rainfall exceeds 750 mm annually, reaching 1800 mm (Amaral et al., 2019). The predominant soils in the municipality of Jardim consist of Argissolo Vermelho-Amarelo (Ultisol), Latossolo Vermelho (Oxisol), and Latossolo Vermelho distroférrico (Oxisol). The original vegetation was mainly composed of Cerrado and Cerrado/sub-deciduous tropical forest transition zones (Mato Grosso do Sul, 2016).
The climate in the municipality of Bonito is Aw, with a mean annual temperature of 23.1 °C and a mean annual precipitation of 1,454 mm. The total rainfall in the driest months, July and August, is very low, reaching 33 and 36 mm, respectively. The highest rainfall is concentrated from October to March (Chagas et al., 2014). The predominant soils in the municipality are Chernossolo Rêndzico (Mollisol), Neossolo Regolítico (Entisol), and Latossolo Vermelho distroférrico (Oxisol). The original vegetation was mainly composed of Cerrado and semideciduous tropical forest (Mato Grosso do Sul, 2016).
The authors followed all Brazilian legal frameworks (Law 13,123/15 and Decree 8,772/16) regarding the Genetic Heritage for scientific research purposes (SISGEN No. A9CDAAE) when accessing plant material in this study. The fruits were harvested in November 2015 from 60 plants of each population, totaling 360 genotypes. Subsequently, they were stored in identified plastic bags, placed in a thermal box with ice, and transported to the Laboratory of Genetics and Plant Breeding at the Federal University of Grande Dourados, Dourados, MS, Brazil, where they were stored for up to five days in a refrigerator at a temperature of 5 °C.
Ten fruits from each plant were selected to evaluate the following traits: i) longitudinal diameter (LD, mm); ii) transverse diameter (TD, mm) – measured with a digital caliper, with a degree of precision of ±0.01 mm; iii) fruit mass (FM, g) – measured individually on an electronic scale; iv) pulp mass (PM, g) – the epicarp of the fruits was removed using a spatula and the pulp mass with seeds of 10 fruits was estimated; v) seed mass (SM, g) – the seeds were washed in running water for 5 minutes to remove the pulp and weighed individually on an electronic scale; vi) peel thickness (PT, mm) – measured with a digital caliper with an accuracy of ±0.01 mm; and vii) and total soluble solids (TSS, °Brix) – determined with a digital refractometer.
2.2. Genetic-statistical analyses
Genetic-statistical analyses were conducted using mixed REML/BLUP models, in which REML (restricted maximum likelihood) allowed the estimation of genetic parameters and BLUP (best linear unbiased prediction) allowed the estimation of predicted genotypic means. A deviance analysis (ANADEV) was conducted to test the significance of the model effects. The authors also used the likelihood ratio test (LRT), in which significance was assessed by the Chi-square test with one degree of freedom. The LRT is the scientifically recommended test in the analysis of mixed models with unbalanced data, replacing ANOVA and the F-test in cases of models with balanced data (Resende and Duarte 2007). The full model and the reduced model were adjusted to apply the test, considering and disregarding the effect to be tested, and then the values corresponding to −2 times the log-likelihood (D = −2 Log L) were subtracted.
The following statistical model was adopted (Equation 1):
where y is the data vector, l is the vector of location effects (assumed to be fixed) added to the overall mean, g is the vector of genotypic effects (assumed to be random), i is the vector of population effects (random), and e is the vector of (random) errors or residuals. The uppercase letters X, Z, and W represent the incidence matrices for the mentioned effects.
The following variance components were obtained: Vg – genotypic variance; Ve – environmental variance; Vp – phenotypic variance; h2mg – heritability of the genotype mean, assuming complete survival; Ac – accuracy of genotype selection, assuming complete survival; CVg – genotypic coefficient of variation; and CVr – relative coefficient of variation.
The individual ranking was performed based on the predicted genotypic mean (µ + g). Thus, the superior individuals were ranked for each evaluated trait, considering the effective size according to Resende et al. (2001) Statistical analyses were performed in the R software (R Development Core Team, 2020), using the lme4 package (Bates et al., 2024).
3. Results
Statistically significant differences between genotypes were identified for the traits transversal diameter, fruit mass, and peel thickness using the chi-square test (Table 1). These results indicate the existence of genetic variability, suggesting possible genetic gains when selecting these traits. No statistically significant differences were observed for longitudinal diameter, pulp mass, seed mass, and total soluble solids when testing the effect of genotype, indicating similar performance between genotypes for these traits. However, significant differences were found for all evaluated traits when testing the effect of different populations.
Deviance analysis for the different traits of the fruits of three natural populations of guavira from Jardim and Bonito, MS, Brazil.
We identified genetic variability between individuals for all analyzed traits, with the percentages of variances relative to the total variance ranging from 1% (TSS) to 29.77% (PT) (Table 2). The magnitude of the estimated mean heritability ranged from low to moderate (Resende and Duarte, 2007) for the traits of total soluble solids (0.03) and peel thickness (0.57), respectively.
Estimates of genetic parameters for the traits longitudinal diameter (LD), transverse diameter (TD), fruit mass (FM), pulp mass (PM), seed mass (SM), peel thickness (PT), and total soluble solids (TSS) in three natural populations of guavira from Jardim and Bonito, MS, Brazil.
The genetic coefficients of variation (CVg) were high for fruit mass, pulp mass, seed mass, and peel thickness, indicating effective selection for these traits. On the other hand, the relative coefficients of variation (CVr), which represent the ratio between the genetic coefficient of variation and the environmental coefficient of variation, were low, ranging from 0.11 for total soluble solids to 0.67 for peel thickness. Ideally, these estimates should approach 1.0. However, the interpretation of this parameter must also consider the number of replications, as experimental precision and high accuracy can be obtained even with values below one. Selective accuracy (Ac) was considered moderate to high for most traits, except for the total soluble solids, which was low (0.18).
We applied a selection intensity of 10% aiming to select among the 360 genotypes those with superior performance for the traits evaluated in this study. We performed individual ranking based on the predicted genotypic mean (µ + g) (Table 3). Importantly, we considered the traits that showed significant differences between populations.
Selection of superior individuals in six natural populations (POP) of guavira for the traits transverse diameter (TD), fruit mass (FM), pulp mass (PM), seed mass (SM), peel thickness (PT), and total soluble solids (TSS), from fruits harvested at two locations, Bonito (L1) and Jardim (L2), MS, Brazil.
In this study, we detected genetic variability between different populations for all analyzed traits. Therefore, selection between populations increases the probability of identifying superior individuals, as this approach considers both populations and superior individuals. In general, populations 3 and 5 contributed the majority of genotypes selected for the evaluated traits, suggesting their high potential to originate productive genotypes (Table 3).
Population 3, located in Bonito, presented high percentages of superior individuals in terms of transverse diameter (88.8%), fruit mass (61.1%), pulp mass (75%), and seed mass (100%). All selected individuals for the trait total soluble solids belonged to population 5, located in Jardim.
Quantitative trait breeding rarely manages to bring together several high-performance traits in a single genotype. The Venn diagram is a valuable visual tool for comparing and identifying relationships between sets of genotypes. Genotypes 144, 145, 174, and 176 stood out for the largest number of characters, sharing traits related to the transverse diameter, fruit mass, and peel thickness (Figure 2).
Venn diagram showing the number of overlapping genotypes among the top 10% identified in the natural populations of guavira for the traits transverse diameter (TD), fruit mass (FM), peel thickness (PT), and total soluble solids (TSS).
Another relevant intersection occurs between transverse diameter and fruit mass, with a high number of shared genotypes (22). It suggests a possible correlation or association between both traits in the listed genotypes. On the other hand, the intersection between total soluble solids and peel thickness included only one genotype (279).
4. Discussion
The observed significant differences indicate the existence of genetic variability, showing possible genetic gains and higher success in selection between populations to the detriment of individual selection, as they explain part of the total genetic variance (Table 1). We observed no significant differences between genotypes for soluble solids content. However, this trait should be investigated, as it is an indication of the ripening point of fruits for seed harvesting, which must be at least 15.75 °Brix to obtain 95% seed germination (Melchior et al., 2006).
The means of selected individuals in terms of fruit diameter and mass (Table 2) were higher than the values reported by Vieira et al. (2019), who obtained 15.57 ± 0.50 mm and 3.7 ± 0.44 g, respectively, in ten populations collected at Fazenda Santa Madalena (22°08’05” S and 55°08’17” W), in Dourados, MS, Brazil.
The soluble solids content is an important quality factor for several fruits and is related to flavor, as it has a high positive correlation with sugar contents (Vieira et al., 2019). The mean value of the individuals selected in the present study (13.74 °Brix) was lower than that found by Vieira et al. (2019), who found around 17.13 ± 1.45 °Brix. Importantly, the soluble solids content can be influenced by several factors, including ripening, climate and environment, variety, management, and postharvest storage (Campos et al., 2012). Therefore, we can infer that the fruits may have been influenced, as we observed a low mean value of total soluble solids compared to the mean value reported by Silva et al. (2021) which was 19.24 °Brix. Thus, individuals may not have expressed their potential for this trait, which is a factor that can be evaluated in future studies.
Estimates of genetic parameters allow us to guide selection strategies and obtain gains (Ramalho et al., 2012). Furthermore, they provide valuable insights for implementing effective selection strategies in natural guavira populations. These parameters, related to traits, show the complexity of the genetic and environmental variability present in these populations. Genotypic variance (Vg) shows the presence of genetic diversity in the studied populations, allowing the selection of superior genotypes. However, environmental variance (Ve) exceeds genotypic variance for all traits, indicating that environmental factors play a significant role in the observed variations (Table 2).
The parameter h2mg is crucial, as it highlights the proportion of genetic variability relative to the total variability. Moderate h2mg values in traits such as longitudinal diameter, transverse diameter, fruit mass, pulp mass, and peel thickness suggest that selection based on these attributes can be effective, contributing to genetic improvement over generations. On the other hand, the higher proportion of environmental variance affected the heritability estimates for total soluble solids (0.03), considered low (Resende and Duarte, 2007). The higher the heritability estimates, the greater the chances of successful selection. However, the data were collected on fruits from natural guavira populations, which implies higher environmental variance and, consequently, lower heritability than in controlled environments and/or annual species.
The genotypic coefficient of variation (CVg) provides additional insights into the variability relative to the genotypic mean. Notably, peel thickness has higher CVg, indicating proportionally greater genotypic variation relative to the genotypic mean. Similarly, this trait may be of particular interest for selection programs, as the expressed genetic variability can be explored in breeding, thus obtaining fruits with smaller or greater peel thicknesses, depending on the objective of the breeding program. We selected individuals with smaller peel thicknesses in this study.
Importantly, estimates of genetic parameters vary depending on the genetic structure of the population and the environmental conditions to which the population was subjected and evaluated (Ramalho et al., 2012). Thus, recognizing that selection must consider environmental variations, as evidenced by Ve and CVr values, is crucial despite efforts to select based on genetic variability (Table 2). Local adaptability, reflected in the genotypes selected in different locations, highlights the influence of the environment on the expression of traits.
Selection strategies must be complemented by practices that minimize environmental variability, such as controlling growing conditions. In summary, the implementation of selection programs in natural guavira populations must be carefully designed, considering the dynamic interaction between genetic and environmental factors. The search for superior genotypes, supported by an in-depth understanding of heritability and selection accuracy, can enhance genetic improvement efforts toward the production of more adapted and productive varieties.
Studies using other species have highlighted the variability in the response to selection in natural populations, resulting from the complex interaction between genetic and environmental factors (Silveira et al., 2020; Silva et al., 2021; Gil et al., 2022). Incorporating these experiences can provide valuable information about the potential effectiveness of selection strategies for guavira. Given the significant genetic variability in different populations and locations, the need for genetic improvement strategies that maximize the expression of their genetic potential becomes evident (Table 3). An effective breeding method can be outlined considering the existing genetic variability, prominent traits, and environmental peculiarities.
Initially, direct selection of superior genotypes within populations based on key traits such as transverse diameter, fruit mass, pulp mass, seed mass, peel thickness, and soluble solids proves to be a promising approach. However, this selection must be carefully guided by genetic parameters, especially h2mg, which indicates the proportion of phenotypic variation explained by genetic variation.
In the context of plant breeding, the graphic representation of the Venn diagram (Figure 2) is useful for analyzing and contrasting different sets of genetic and phenotypic traits or plant populations. It allows us to visualize and understand the intersections and differences between plants with different traits, helping breeders identify traits that are shared or exclusive to certain populations. This intersection is important for plant breeding, as it indicates the presence of individuals that can exhibit desirable characteristics for more than one trait, which can be explored for selection and targeted crossings.
5. Conclusions
There is genetic variability in the morphophysiological traits of fruits in natural populations of Campomanesia adamantium, indicating potential for selection and genetic improvement of the species. Heritability estimates ranged from low to moderate, highlighting the influence of the environment on the phenotypic expression of the evaluated traits.
Populations 3 and 5 exhibited a higher number of superior individuals, suggesting that these regions may be strategic for the conservation and sustainable exploitation of the species. The application of the REML/BLUP method enabled the identification of promising genotypes, particularly genotypes 144, 145, 174, and 176, which displayed larger transverse fruit diameters, higher fruit mass, and thinner pericarp thickness.
This study provides valuable insights for conservation and breeding programs of C. adamantium, aiming at the preservation of Cerrado biodiversity and the socio-economic valorization of this native species.
Data Availability Statement
Data will be available upon request.
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Editor:
Jairo Lizandro Schmitt
