Skip to main content
NCBI home page
PLOS One logoLink to PLOS One
. 2020 Sep 28;15(9):e0239263. doi: 10.1371/journal.pone.0239263

Diversity of nutritional content in seeds of Brazilian common bean germplasm

Jessica Delfini 1,2, Vânia Moda-Cirino 2, José dos Santos Neto 2, Juliana Sawada Buratto 2, Paulo Maurício Ruas 3, Leandro Simões Azeredo Gonçalves 1,*
Editor: Roberto Papa4
PMCID: PMC7521705  PMID: 32986739

Abstract

Mineral deficiency is worldwide one of the major problems associated with human health, and biofortification through breeding is considered an important strategy to improve the nutritional content of staple food in countries that face this problem. The assessment of genetic variability for seed nutrient contents is a first step in the development of a biofortified crop. From the germplasm bank IDR–IAPAR–EMATER, a set of 1,512 common bean accessions, consisting of local and commercial varieties and improved lines, was analyzed. High variability among the accessions was observed for all evaluated nutrient contents (P, K, Ca, Mg, Cu, Zn, Mn, Fe and S and protein). In the mean, the contents of the carioca and black market groups (Mesoamerican gene pool), were around 7% higher for the minerals Ca, Cu, Mn and Fe and between 2–4% higher for P, K, Mg and Zn than in the other groups with Mesoamerican and Andean common bean. Few differences were observed among the Mesoamerican accessions that belong to the carioca and black commercial groups. Wide variability was observed among the evaluated genotypes, and the concentrations of the best accessions exceeded the overall mean by 14–28%. Due to the high variability in the evaluated accessions, these results may contribute to the selection of promising parents for the establishment of mating blocks. The nutritional contents of many of the improved lines evaluated in this study were higher than those of the commercial cultivars, indicating the possibility of developing new biofortified cultivars.

Introduction

Minerals are inorganic substances, present in all tissues and fluids of the human body, which play an important role in growth and regulation processes and repair functions of the body [1]. However, more than 2 billion people worldwide have one or more chronic micronutrient deficiencies, particularly of calcium (Ca), iodine (I), iron (Fe), selenium (Se), zinc (Zn) and vitamins [2]. Micronutrient deficiency can delay the growth and cognitive development, impair immune functions and increase the risk of cardiovascular and metabolic diseases [3].

Several strategies, e.g., of supplementation (e.g., in the form of pills), industrial fortification and biofortification, have been applied to combat micronutrient malnutrition. Supplementation and industrial fortification have some practical limitations, since the supplementation pills are not always taken regularly, while industrial food fortification requires a rigorous quality control, with specialized techniques and infrastructures, which are generally restricted in developing countries [4,5]. On the other hand, biofortification is considered a viable and economical means of providing populations who have limited access to dietary diversification and other micronutrient interventions with essential micronutrients [6,7].

Biofortification can be defined as the process of raising the concentration of vitamins and minerals in a crop by plant breeding (conventional methods or genetic engineering) or by agronomic practices (agronomic biofortification). Agronomic biofortification is the process of improving the micronutrient content in edible plant parts by applying fertilizers to the soil or leaves. However in the long term, genetic biofortification is more cost-effective [8].

Several studies have demonstrated the effectiveness of conventional breeding in developing biofortified crops, resulting in an improved micronutrient intake and minimizing deficiency among the target populations. Some examples are higher vitamin A contents in sweet potato [9,10] maize [11] and cassava [12], as well as increased Fe contents in common bean [13,14] and millet [15,16]. Altogether, more than 150 biofortified varieties of 10 different crops have been officially released for production in over 30 countries in Africa, Asia and Latin America and the Caribbean [7].

In conventional breeding, several steps are indispensable to establish biofortified cultivars. The first is to analyze the variability contained in germplasm banks in order to estimate the genetic potential of some accessions for future stages of the breeding program [17]. In an evaluation of the common bean (Phaseolus vulgaris L.) core collection of the International Center for Tropical Agriculture (CIAT), Islam et al. [18] found wide genetic variability for nutritional traits (mean Fe and Zn contents of 54.81 ppm (34.6–91.9 ppm) and 34.40 ppm (20.7–59.4 ppm) respectively). In a collection of 1,150 accessions, wide variability for mineral contents was also reported by Beebe, Gonzalez and Reginfo [19], who concluded that the Fe and Zn grain contents could be increased. The mean Fe and Zn values reported by these authors were 55 ppm (34–89 ppm) and 35 ppm (21 to 54 ppm), respectively. These studies showed evidences that the Mesoamerican gene pool have a tendency to have higher contents of calcium, phosphorus, sulfur and zinc than the Andean gene pool, but in the other hand, Andean accessions showed higher iron contents.

The common bean breeding program of the Rural Development Institute of Paraná –IAPAR–EMATER (IDR–IAPAR–EMATER) currently has a collection of 14,163 accessions deposited by different research institutions and universities, as well as lines developed by the institute itself [20]. These accessions are being characterized in detail and some of them extensively exploited in the breeding program for the development of new cultivars. To date, 39 common bean cultivars have been released, which are being widely cultivated by producers across Brazil. In this sense, the development of new cultivars that combine high yields with resistance or tolerance to biotic and abiotic stresses and high nutritional value becomes increasingly relevant. Therefore, this study evaluated the diversity of the mineral composition and protein content of common bean accessions of the IDR–IAPAR–EMATER germplasm bank, with a view to identifying accessions that can be used as parents in breeding programs to develop cultivars with seeds with higher nutritional value.

Material and methods

Plant material and experimental design

Of the germplasm bank of the IDR–IAPAR–EMATER, 1,512 accessions were evaluated. All information about seed coat color, genetic material and center of origin (1,473 and 39 belonging to Mesoamerican and Andean gene pool, respectively) of the accessions are described in the S1 Table.

The experiments were carried out at different locations in the state of Paraná, Brazil, in two agricultural seasons, resulting in a total of four environments. In the rainy season of 2009, sowing was carried out in September in the counties of Pato Branco (lat. 260° 13`S; long. 520° 40`W 760 m asl,) and Lapa (lat. 250° 46 `S; long. 490° 42`W; 908 m), and in the dry season of 2010 in January, in Ponta Grossa (250° 05`S; long. 500° 09`W; 975 m asl) and Lapa.

Each experimental plot consisted of one 4-m row, at a spacing of 0.50 m between rows and a density of 12 plants per meter. Fertilization at sowing consisted of the application of 300 kg ha-1 of 4-30-10 (N, P2O5, K2O) and in growth stage V4, of 200 kg ha-1 ammonium sulfate. Pests, diseases and weeds were controlled according to the technical recommendations for the crop. At physiological maturity (R9), the plots were harvested and a 100-g sample of disease-free seeds without physical or insect damage was collected and stored in a cold chamber (5.6°C, humidity 33%) until laboratory analysis.

Analysis of mineral composition and protein content

The following minerals were determined: phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), copper (Cu), zinc (Zn), manganese (Mn), iron (Fe), sulfur (S) and nitrogen (N). Prior to laboratory analyses, the samples were washed in tap water, 0.01M HCl solution and distilled water to prevent contamination by soil particles that could be attached to the seeds. Then the seeds were oven-dried at 60°C for 48h, ground and the flour stored in a glass recipient.

The mineral contents were determined by nitroperchloric digestion with HNO3:HClO4 solution and by atomic emission spectrophotometry (ICP-AES) (Thermo Jarrell Ash ICAP 61E). The protein content was quantified by Kjeldahl’s method and the samples were read on a UV-VIS spectrophotometer. Factor 6.25 was used to convert total seed nitrogen into crude protein [21]. The analysis was developed according to the methodology described by Miyazawa et al. [22].

Statistical analysis

The data were subjected to descriptive analysis (minimum, maximum and mean values; coefficient of variation; asymmetry and kurtosis), using software SAS [23]. Pearson’s correlation analysis using the mean values for each accession was performed using the cor() function in the R package qgraph [24]. The accessions were separated based on two criteria: seed coat color (black, carioca and colored) and genetic material (cultivars, landraces and breeding lines). For these two criteria an analysis of variance (ANOVA) followed by a Tukey test (p < 0.05) were performed for each case to compare significantly differences between the formed groups. To visualize the distribution of the accessions grouped by each criteria a boxplot graph was made. The analyses were done using the R packages agricolae and ggplot2 [25–27].

Subsequently, multivariate analysis using the Ward-Modified Location Model (Ward-MLM) method was performed to group the accessions by the procedures CLUSTER and IML of software SAS [23]. For the Ward clustering method, the distance matrix was calculated by the Gower algorithm [28]. The ideal number of groups was defined according to the criteria pseudo-F and pseudo-T2, together with the likelihood profile associated with the likelihood ratio test. The data distribution in relation to the groups formed was visualized in a boxplot.

The differences between groups and correlation of the variables with the canonical variable were represented in a diagram using the SAS CANDISC procedure [23]. The distance proposed by Matusita [29], used by Krzanowski [30] and later by Franco et al. [31] for the distribution of variables, was applied to determine the dissimilarity between the groups.

Results

Wide variability for mineral and protein contents was detected in the accessions of the IDR–IAPAR–EMATER common bean germplasm bank (Table 1). The coefficients of variation (CV) ranged from 5.66 (protein) to 13.53% (Ca), indicating good experimental precision. The kurtosis values, which indicate the degree of flatness of the data distribution, were close to 3.0 for protein, Zn and P, suggesting a mesokurtic distribution. The other nutrients were classified as leptokurtic, in which the data distribution curve is close to the central value that is greater than the mesokurtic distribution. The asymmetry was positive for Ca, Zn, Mn, Fe and protein, and negative for the other nutrients. Most nutrient distributions were not normal (all except P, Fe and protein) (Table 1).

Table 1. Descriptive statistics for mean mineral and protein contents evaluated in common bean samples of 1,512 accessions of the germplasm bank of the Rural Development Institute of Paraná –IAPAR–EMATER (IDR–IAPAR–EMATER), grown in four environments in the state of Paraná, Brazil.

Nutrient Minimum Mean Maximum CVa Asymmetry Kurtosis Normal Distribution (Yes/No)b
P (g.kg-1) 4.66 6.52 8.38 8.36 -0.11 3.32 Yes
K (g.kg-1) 12.25 17.37 21.75 6.13 -0.28 4.20 No
Ca (g.kg-1) 0.86 1.49 2.40 13.53 0.13 3.58 No
Mg (g.kg-1) 1.71 2.22 2.66 5.88 -0.40 4.07 No
Cu (mg.kg-1) 7.83 12.55 17.63 9.77 -0.13 4.04 No
Zn (mg.kg-1) 26.45 36.15 46.90 7.80 0.27 3.20 No
Mn (mg.kg-1) 11.50 16.59 23.32 10.33 0.49 3.77 No
Fe (mg.kg-1) 51.84 80.48 115.27 9.94 0.16 3.51 Yes
S (g.kg-1) 1.71 2.57 3.09 8.04 -0.85 3.83 No
Protein (g.kg-1) 169.31 202.14 248.43 5.66 0.18 3.06 Yes
Open in a new tab

a CV = Coefficient of variation;

bKolmogorov-Smirnov Normality Test.

Positive correlations were observed among most nutrients. Protein content correlated only with P, while K correlated with P and Zn. In addition, two correlation groups (Fe-Zn-Cu-P and Ca-Mn-Mg) were formed, in which all nutrients involved are correlated with each other (Fig 1).

Fig 1. Graphical representation of Pearson’s correlation among the grain nutrient contents of 1,512 common bean accessions of the germplasm bank of the Rural Development Institute of Paraná –IAPAR–EMATER (IDR–IAPAR–EMATER).

Fig 1

Open in a new tab

Only edges of significant correlations are shown in the graph (p ≤ 0.05).

In the subdivision of accessions by seed coat color (Fig 2), the means of the colored group accessions, were lower than those of the carioca and black groups, except in the case of protein and S contents. The means of the colored group were around 7% lower for the minerals Ca, Cu, Mn and Fe and between 2–4% lower for P, K, Mg and Zn. Significant differences between the mean contents of the black and carioca groups were only observed for K, Mn and S; the black group had highest K and S and the carioca group highest Mn contents. However, some accessions of the black group also had high Fe and some accessions of the carioca group high Zn contents (Fig 2).

Fig 2. Boxplot and Tukey test of grain nutrient content evaluated in 1,512 common bean accessions of the germplasm bank of the Rural Development Institute of Paraná –IAPAR–EMATER (IDR–IAPAR–EMATER), grouped according to the seed coat color and genetic material.

Fig 2

Open in a new tab

Groups labeled by the same lowercase letter did not differ significantly by the Tukey test (p ≤ 0.05).

The variability in the breeding lines was higher than in the cultivars and landraces, aside from the higher mean contents for all nutrients except protein. The mean P, K and Zn concentrations of the breeding lines, cultivars and landraces were similar, while the breeding line means were significantly higher for Ca, Mg, Cu, Mn, Fe and S and lower for protein. For Fe content, the breeding line mean was 5% higher than that of the other groups (Fig 2).

By the logarithmic likelihood function, five groups were formed based on the criteria pseudo-t2 and pseudo-F (S1 Fig and S1 Table). In the boxplot representing the groups, variability was observed between and within them (Fig 3 and Table 2).

Fig 3. Boxplot of the grain nutrient content evaluated in 1,512 common bean accessions of the germplasm bank of the Rural Development Institute of Paraná –IAPAR–EMATER (IDR–IAPAR–EMATER), separated according to the groups formed by the Ward MLM method.

Fig 3

Open in a new tab

Table 2. Means and standard deviation of the nutrient contents in each of the five groups formed by the Ward-MLM method and contribution of the first two canonical variables of each nutrient calculated in the analysis of 1,512 common bean accessions of the germplasm bank of the Rural Development Institute of Paraná –IAPAR–EMATER (IDR–IAPAR–EMATER).

Nutrient Groups CAN
G1 (80) a G2 (789) G3 (202) G4 (312) G5 (129) CAN1 CAN2
P (g.kg-1) 6.01 (0.51) b 6.57 (0.46) 7.03 (0.48) 6.14 (0.51) 6.61 (0.35) -0.26 0.63
K (g.kg-1) 15.68 (1.27) 17.64 (0.93) 17.8 (0.91) 16.87 (0.88) 17.23 (0.85) -0.13 0.46
Ca (g.kg-1) 1.4 (0.25) 1.5 (0.21) 1.47 (0.18) 1.49 (0.19) 1.51 (0.17) -0.03 0.00
Mg (g.kg-1) 2.01 (0.14) 2.24 (0.12) 2.22 (0.13) 2.24 (0.11) 2.25 (0.10) -0.04 0.11
Cu (mg.kg-1) 10.39 (1.23) 12.31 (0.97) 13.74 (1.00) 12.66 (0.97) 13.25 (1.06) -0.08 0.52
Zn (mg.kg-1) 33.77 (2.86) 35.81 (2.3) 39.72 (2.17) 35.63 (2.81) 35.36 (1.97) 0.05 0.69
Mn (mg.kg-1) 14.74 (1.32) 16.38 (1.43) 16.13 (1.26) 18.26 (1.69) 15.69 (1.09) 0.45 -0.16
Fe (mg.kg-1) 71.43 (7.59) 80.53 (7.61) 83.57 (6.70) 81.77 (7.46) 77.8 (8.94) 0.14 0.28
S (g.kg-1) 2.45 (0.18) 2.55 (0.13) 2.73 (0.12) 2.72 (0.12) 2.12 (0.10) 0.81 0.43
Protein (g.kg-1) 201.99 (2.0) 201.33 (1.79) 202.52 (1.97) 201.45 (1.74) 208.3 (1.64) -0.15 -0.02
Open in a new tab

a Number of accessions;

b Standard deviation.

Group 1 (G1) consisted of only 80 accessions, mostly with colored grain, and included most Andean accessions of this study, which accounted for approximately 31% of all accessions of the group. This group had the lowest contents for 8 of the 10 evaluated nutrients. Group 2 (G2) was the largest, with 52.2% of the studied accessions, with mainly black and carioca grain (71%). In general, the variability in G2 was the highest while the means were not notable for any of the nutrients. However, some accessions had high Ca, Mg and Fe contents. Group 3 (G3) comprised 202 accessions, of which 122 had black, 44 mulatto and the remaining accessions other seed coat colors. Group G3 stood out with the highest P, Cu, Zn and Fe, and some accessions had very high K contents.

Group 4 (G4) comprised mostly accessions of the commercial groups carioca and black, as well as brown, mulatto and others. Mainly the Mn content was very high in G4. Together with G3, the S content was also very high in G4. In the fifth group (G5), only carioca accessions were included, the S content was the lowest and the Mn and Fe contents were rather low, whereas the mean protein contents were the highest.

The first two canonical variables explained 67.64 and 19.44%, respectively, resulting in 87.07% of the total variation (Fig 4). The nutritional contents that contributed most to determine the genetic diversity among the accessions studied in the first canonical variable were S and Mn, while the most important for the second canonical variable were Zn, P and Cu (Table 2). The genotype dispersion based on the first two canonical variables is shown in Fig 4.

Fig 4. Scatter plot of the first two canonical variables for the five groups formed by the Ward-MLM method.

Fig 4

Open in a new tab

The distances between groups by the Ward-MLM strategy based on the distance proposed by Matusita [29] indicated that the shortest distance was between G2 and G3 (estimated value of 7.23). This indicates high similarity between the accessions of these groups. The highest dissimilarity (estimated at 64.28) was observed between G4 and G5 (Table 3).

Table 3. Distance between the groups formed by the Ward-MLM strategy based on the distance proposed by Matusita (1956).

Groups G1 G2 G3 G4
G2 10.73
G3 22.23 7.23
G4 18.27 10.93 17.45
G5 39.77 28.02 42.53 64.28
Open in a new tab

In order to select promising parents to compose crossing panels in the breeding program with the aim of increase grain mineral content, the 20 best genotypes for each of the nine minerals and protein contents were ranked. Of all evaluated accessions, 159 were among these top 20. Of these, 127 had the highest content of only one element, 26 of two elements, three of three elements and three accessions had the highest contents of four elements.

Most accessions selected among the top 20 were breeding lines, and in relation to seed coat color, 61 were of the black, 57 of the carioca, 14 of the mulatto and 6 of the white group. In an individual analysis of each nutrient, the black group accessions had the best contents for most nutrients. Accessions of the white group had the highest Ca and protein and carioca group accessions the highest Mn contents. Two accessions of the white group simultaneously had highest Cu, Zn, S and protein contents, while two other accessions of the black group stood out with high Cu, Zn and P.

For the Fe and Zn contents, which are the main targets of biofortification in common bean, only breeding lines were among the top 20, mostly of the carioca and black groups. One line of the carioca group simultaneously had high Fe as well as Zn contents.

Discussion

Common bean is a primary component of the diet of the population of countries in Latin America as well as in East and Southern Africa, which are regions of the world with high rates of chronic diseases associated with malnutrition [32]. Common bean is not only a crop that plays a key role in feeding populations of underdeveloped countries, but is also highly promising for breeding for biofortification. Previous studies suggest that the Fe content of common bean grain could be increased by 80% and the Zn content by up to 50% [19]. Thus, taking into account the amount of common bean consumed in these countries, the objective of biofortification of common bean for Fe would be to increase the content from 50 to 94 ppm, which would be enough to meet an adult's basic daily Fe requirement [7].

A wide variability for all mineral and protein contents was observed among accessions of the IDR–IAPAR–EMATER germplasm bank. These results indicate that it is possible to identify promising parents for exploitation in breeding programs with a view to increasing the grain nutritional contents. The existence of genetic variability and the possibility of raising the grain mineral content have been confirmed in several common bean germplasm banks in Brazil [33,34], Colombia [18,19], Portugal [35], as well as in the USA [32].

Positive correlations were observed among most nutrients, which may indicate co-segregation of the genetic factors for the different minerals [19]. This correlation is favorable for plant breeding for higher nutritional grain content, since selection for an increase in one nutrient may be favorable for other minerals simultaneously. As observed by Pinheiro et al. [35], two correlation sets (Fe-Zn-Cu-P and Ca-Mn-Mg) were formed. The correlation between Ca and Mn was also mentioned by other authors, who suggested that this correlation is due to the fact that the deposition mechanism in the grain at the uptake or transport level of the two elements is the same [32]. The correlation between P and protein can be explained by the fact that P can be accumulated by an association in the body of proteins, e.g., in the form of phytates [35]. Co-segregation evidences of Fe and Zn due to highly positive correlation was also observed in other crops, suggesting that common mechanisms regulate Fe and Zn accumulation [36].

The mean concentrations found in this study were similar to those reported by Silva et al. [33], who also evaluated mostly Brazilian genotypes of Mesoamerican origin. However, our results exceeded the contents determined in the Mesoamerican Diversity Panel studied by McClean et al. [32]. In an evaluation of common bean accessions of the Mesoamerican and Andean gene pools, Moraghan and Grafton [37] also found lower mean concentrations.

Genotypes of the Andean group as well as colored grains tend to have lower nutrient concentrations. Lower P contents in the Andean than the Mesoamerican group were described in a study published by CIAT [18], and lower mean contents of K, Ca, Zn and Cu were observed by Ribeiro et al. [34] in an assessment of 32 common bean lines with special grain types. In this study, the mean mineral concentration of the colored group, which also includes Andean genotypes, was around 7–2% lower than that of the carioca and black genotypes.

With regard to the mineral composition of accessions of the main commercial groups black and carioca consumed in Brazil, great variability was detected within each one. However, the differences between the groups are few. Most carioca and black genotypes were grouped in G2 and G4, which were the largest groups, with greater variability and amplitude for the studied contents, while G3 was predominantly formed by black accessions and G5 by carioca accessions. In black grain genotypes, Silva et al. [33] identified higher Fe, Zn and protein contents, and higher Mg and Mn contents in carioca grain. These results partly confirm the findings of our study. In the separation of genotypes by color, the black group stood out with high K, Fe and S and the carioca group with high Zn and Mn contents.

Commonly, the main objective of common bean breeding programs is to raise yields, although the improved lines evaluated in this study performed better for all nutrients except protein. Once again, these results refute arguments that claim that modern crop breeding techniques reduce the grain quality [32]. A gradual increase of the Fe and Mg contents over time was observed, i.e., the contents increased in response to conventional breeding, less in landraces and more in cultivars and improved lines.

Only the concentration of grain crude protein was lower in the breeding lines, which can be explained by the negative correlation between grain crude protein content and yield [38]. Despite this reduction, accessions were identified with a balance between the two characteristics, enabling a concomitant improvement of both.

Due to the large number of accessions evaluated, the best 20 with the highest contents for each mineral and protein were selected. The mean of the top 20 accessions in relation to the overall mean was between 22–28% higher for Ca, Mn and Cu and around 14–18% higher for P, K, S, Mg and protein. The mean Zn and Fe contents were, respectively, 18 and 22% higher than the overall mean. Common bean is known as an excellent source of Zn and Fe, since one cup of common bean can currently supply 15 and 25%, respectively, of the recommended daily allowance for these nutrients. Still, cultivars with higher nutritional Fe and Zn contents can potentially be developed [39].

Most of these top 20 accessions were breeding lines, many of which had been improved in the IDR–IAPAR–EMATER breeding program, indicating the potential for the release of new cultivars or even including them in cross panels. In addition, many of these accessions belong to the carioca and black groups, which are the most commonly consumed grain types in Brazil. Thus, new biofortified cultivars could easily be incorporated into the diet of the Brazilian population.

In general, the variability among the evaluated accessions was high, indicating a promising potential for the development of new common bean cultivars with higher grain nutrient contents. Although not addressed as a main target of crop improvement, the nutritional grain quality has been increased indirectly by human selection, evidenced by the fact that breeding lines showed higher contents for some nutrients compared to cultivars and landraces (Fig 2). Thus, if efforts are invested in the development of biofortified cultivars, it will be possible to help combat malnutrition in countries affected by this problem.

Supporting information

S1 Fig. Log-likelihood graph of the ideal number of groups for 1,512 common bean accessions analyzed for grain nutrient and protein content.

(TIF)

Click here for additional data file. (81.7KB, tif)
S1 Table. Information of the 1,512 accessions characterized for seed nutritional content.

1CIAT = International Center for Tropical Agriculture (Centro Internacional de Agricultura Tropical), EMBRAPA = Brazilian Agricultural Research Corporation (Empresa Brasileira de Pesquisa Agropecuária), IAC = Agronomic Institute of Campinas (Instituto Agronômico de Campinas), IDR-Paraná = Rural Development Institute of Paraná –IAPAR–EMATER (Instituto de desenvolvimento Rural do Paraná), USDA = United States Department of Agriculture, ESALQ = Universidade de São Paulo—Escola Superior de Agricultura “Luiz de Queiroz”.

(DOCX)

Click here for additional data file. (156.4KB, docx)
S1 File

(DOCX)

Click here for additional data file. (15.1KB, docx)
S2 File

(PDF)

Click here for additional data file. (237.5KB, pdf)

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Gupta UC, Gupta SC. Sources and deficiency diseases of mineral nutrients in human health and nutrition: a review. Pedosphere. 2014;24: 13–38. 10.1016/S1002-0160(13)60077-6 [DOI] [Google Scholar]
  • 2.Kumssa DB, Joy EJM, Ander EL, Watts MJ, Young SD, Walker S, et al. Dietary calcium and zinc deficiency risks are decreasing but remain prevalent. Sci Rep. 2015;5: 1–11. 10.1038/srep10974 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.WHO guideline: Use of multiple micronutrient powders for point-of-use fortification of foods consumed by infants and young children aged 6–23 months and children aged 2–12 years. World Health Organization. Geneva; 2016. doi:Licence: CC BY-NC-SA 3.0 IGO. [PubMed]
  • 4.Díaz-Gómez J, Twyman RM, Zhu C, Farré G, Serrano JC, Portero-Otin M, et al. Biofortification of crops with nutrients: factors affecting utilization and storage. Curr Opin Biotechnol. 2017;44: 1–9. 10.1016/j.copbio.2016.09.005 [DOI] [PubMed] [Google Scholar]
  • 5.Van Der Straeten D, Fitzpatrick TB, De Steur H. Editorial overview: Biofortification of crops: achievements, future challenges, socio-economic, health and ethical aspects. Curr Opin Biotechnol. 2017;44: vii–x. 10.1016/j.copbio.2017.03.007 [DOI] [PubMed] [Google Scholar]
  • 6.Bashir K, Takahashi R, Nakanishi H, Nishizawa NK. The road to micronutrient biofortification of rice: progress and prospects. Front Plant Sci. 2013;4: 1–7. 10.3389/fpls.2013.00001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Bouis HE, Saltzman A. Improving nutrition through biofortification: A review of evidence from HarvestPlus, 2003 through 2016. Glob Food Sec. 2017;12: 49–58. 10.1016/j.gfs.2017.01.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Valença AW, Bake A, Brouwer ID, Giller KE. Agronomic biofortification of crops to fight hidden hunger in sub-Saharan Africa. Glob Food Sec. 2017;12: 8–14. 10.1016/j.gfs.2016.12.001 [DOI] [Google Scholar]
  • 9.van Jaarsveld PJ, Faber M, Tanumihardjo SA, Nestel P, Lombard CJ, Benadé AJS. Beta-carotene-rich orange-fleshed sweet potato improves the vitamin A status of primary school children assessed with the modified-relative-dose-response test. Am J Clin Nutr. 2005;81: 1080–1087. 10.1093/ajcn/81.5.1080 [DOI] [PubMed] [Google Scholar]
  • 10.Low JW, Arimond M, Osman N, Cunguara B, Zano F, Tschirley D. A food-based approach introducing orange-fleshed sweet potatoes increased vitamin A intake and serum retinol concentrations in young children in rural Mozambique. J Nutr. 2007;137: 1320–1327. 10.1093/jn/137.5.1320 [DOI] [PubMed] [Google Scholar]
  • 11.Gannon B, Kaliwile C, Arscott SA, Schmaelzle S, Chileshe J, Kalungwana N, et al. Biofortified orange maize is as efficacious as a vitamin A supplement in Zambian children even in the presence of high liver reserves of vitamin A: A community-based, randomized placebo-controlled trial. Am J Clin Nutr. 2014;100: 1541–1550. 10.3945/ajcn.114.087379 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Talsma EF, Brouwer ID, Verhoef H, Mbera GNK, Mwangi AM, Maziya-dixon B, et al. Biofortified yellow cassava and vitamin A status of Kenyan children: a randomized controlled trial. Am J Clin Nutr. 2016;103: 258–267. 10.3945/ajcn.114.100164 [DOI] [PubMed] [Google Scholar]
  • 13.Haas JD, Luna S V, Lung’aho MG, Wenger MJ, Murray-Kolb LE, Beebe S, et al. Consuming iron biofortified beans increases iron status in Rwandan women after 128 days in a randomized controlled feeding trial. J Nutr. 2016; 1586–92. 10.3945/jn.115.224741 [DOI] [PubMed] [Google Scholar]
  • 14.Glahn R, Tako E, Hart J, Haas J, Lung’aho M, Beebe S. Iron bioavailability studies of the first generation of iron-biofortified beans released in Rwanda. Nutrients. 2017;9 10.3390/nu9070787 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Beer H, Luna S, Pompano L, Przybyszewski E, Udipi S, Ghugre P, et al. Consuming iron-biofortified pearl millet increased hemoglobin concentrations and prevented a decline in energy efficiency in Indian girls. FASEB J. 2014;28: Supplement 6467. [Google Scholar]
  • 16.Finkelstein JL, Mehta S, Udipi SA, Ghugre PS, Luna S V, Wenger MJ, et al. A randomized trial of iron-biofortified pearl millet in school children in India. J Nutr. 2015;145: 1576–1581. 10.3945/jn.114.208009 [DOI] [PubMed] [Google Scholar]
  • 17.Blair MW. Mineral biofortification strategies for food staples: The example of common bean. J Agric Food Chem. 2013;61: 8287–8294. 10.1021/jf400774y [DOI] [PubMed] [Google Scholar]
  • 18.Islam FMA, Basford KE, Jara C, Redden RJ, Beebe S. Seed compositional and disease resistance differences among gene pools in cultivated common bean. Genet Resour Crop Evol. 2002;49: 285–293. 10.1023/A:1015510428026 [DOI] [Google Scholar]
  • 19.Beebe S, Gonzalez AV, Rengifo J. Research on trace minerals in the common bean. Food Nutr Bull. 2000;21: 387–391. [Google Scholar]
  • 20.Moda-Cirino V, Gerage AC, Riede CR, Sera GH, Takahashi M, Abbud NS, et al. Plant breeding at Instituto Agronômico do Paraná –IAPAR. Crop Breed Appl Biotechnol. 2012;S2: 25–30. [Google Scholar]
  • 21.Association of Official Analytical Chemists—International [AOAC]. Official methods of analysis. 18th ed. Gaithersburg: AOAC; 2005.
  • 22.Miyazawa M, Pavan MA, Muraoka T, Carmo CAFS, Mello WJ. Análises químicas de tecido vegetal In: Silva FC, editor. Manual de análises químicas de solos, plantas e fertilizantes. Brasília: Embrapa; 1999. pp. 171–223. [Google Scholar]
  • 23.SAS Institute. JMP IN 4.0.3. Cary, North Carolina; 2000.
  • 24.Epskamp S, Cramer AOJ, Waldorp LJ, Schmittmann VD, Borsboom D. qgraph: Network visualizations of relationships in psychometric data. J Stat Softw. 2012;48: 1–18. Available: http://www.jstatsoft.org/v48/i04/. [Google Scholar]
  • 25.R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2018.
  • 26.Wickham H. ggplot2: Elegant graphics for data analysis [Internet]. New York: Springer-Verlag; 2016. Available: https://ggplot2.tidyverse.org. [Google Scholar]
  • 27.Mendiburu F de. agricolae: Statistical procedures for agricultural research [Internet]. 2019. Available: https://cran.r-project.org/package=agricolae.
  • 28.Gower JC. A general coefficient of similarity and some of its properties. Biometrics. 1971;27: 857–871. Available: https://www.jstor.org/stable/2528823. [Google Scholar]
  • 29.Matusita K. Decision rule, based on the distance, for the classification problem. Ann Inst Stat Math. 1956;8: 67–77. 10.1007/BF02863571 [DOI] [Google Scholar]
  • 30.Krzanowski WJ. Distance between populations using mixed continuous and categorical variables. Biometrika. 1983;70: 235–243. 10.1093/biomet/70.1.235. [DOI] [Google Scholar]
  • 31.Franco J, Crossa J, Villaseñor J, Taba S, Eberhart SA. Classifying genetic resources by categorical and continuous variables. Crop Sci. 1998;38: 1688–1696. 10.2135/cropsci1998.0011183X003800060045x [DOI] [Google Scholar]
  • 32.McClean PE, Moghaddam SM, Lopéz-Millán A-F, Brick MA, Kelly JD, Miklas PN, et al. Phenotypic diversity for seed mineral concentration in North American dry bean germplasm of middle american ancestry. Crop Sci. 2017;57: 3129–3144. 10.2135/cropsci2017.04.0244 [DOI] [Google Scholar]
  • 33.Silva CA, Abreu  de FB, Ramalho MAP, Maia LGS. Chemical composition as related to seed color of common bean. Crop Breed Appl Biotechnol. 2012;12: 132–137. [Google Scholar]
  • 34.Ribeiro ND, Rodrigues J de A, Prigol M, Nogueira CW, Storck L, Gruhn EM. Evaluation of special grains bean lines for grain yield, cooking time and mineral concentrations. Crop Breed Appl Biotechnol. 2014;14: 15–22. 10.1590/s1984-70332014000100003 [DOI] [Google Scholar]
  • 35.Pinheiro C, Baeta JP, Pereira AM, Domingues H, Ricardo CP. Diversity of seed mineral composition of Phaseolus vulgaris L. germplasm. J Food Compos Anal. 2010;23: 319–325. 10.1016/j.jfca.2010.01.005 [DOI] [Google Scholar]
  • 36.Ghandilyan A, Vreugdenhil D, Aarts MGM. Progress in the genetic understanding of plant iron and zinc nutrition. Physiol Plant. 2006;126: 407–417. 10.1111/j.1399-3054.2006.00646.x [DOI] [Google Scholar]
  • 37.Moraghan JT, Grafton K. Genetic diversity and mineral composition of common bean seed. J Sci Food Agric. 2001;81: 404–408. [DOI] [Google Scholar]
  • 38.Leleji OI, Dickson MH, Crowder L V., Bourke JB. Inheritance of crude protein percentage and its correlation with seed yield in beans, Phaseolus vulgaris L. Crop Sci. 1972;12 10.2135/cropsci1972.0011183x001200020004x [DOI] [Google Scholar]
  • 39.Cichy KA, Caldas G V., Snapp SS, Blair MW. QTL analysis of seed iron, zinc, and phosphorus levels in an andean bean population. Crop Sci. 2009;49: 1742–1750. 10.2135/cropsci2008.10.0605 [DOI] [Google Scholar]

Decision Letter 0

Roberto Papa

5 Jun 2020

PONE-D-20-08197

Diversity of nutritional content in seeds of Brazilian common bean germplasm

PLOS ONE

Dear Dr. Azeredo Gonçalves,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jul 20 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Roberto Papa, PhD

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Thank you for stating the following financial disclosure:

"The funders had no role in study design, data collection and analysis, decision to

publish, or preparation of the manuscript."

At this time, please address the following queries:

a) Please clarify the sources of funding (financial or material support) for your study. List the grants or organizations that supported your study, including funding received from your institution.

b) State what role the funders took in the study. If the funders had no role in your study, please state: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.”

c) If any authors received a salary from any of your funders, please state which authors and which funders.

d) If you did not receive any funding for this study, please state: “The authors received no specific funding for this work.”

Please include your amended statements within your cover letter; we will change the online submission form on your behalf

3. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

Additional Editor Comments (if provided):

please make changes considering the comments of the reviewers and submit us the final copy of the manuscript

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Diversity of nutritional content in seed of Brazilian common bean germplasm

The authors presented a study on mineral nutrients (P, K, Ca, Mg, Cu, Zn, Mn, Fe and S) and protein content in a collection of 1,512 common bean accessions consisting on local, commercial and improved varieties. A total of 4 environments in 2 crop seasons were evaluated. The aim of the study is to evaluate the diversity regarding to these traits within this germplasm collection in order to identify some parental lines that can be used in future breeding programs.

The study is original and the topic is interesting since the biofortification is one the target for breeding programs nowadays. Nevertheless, some points specially regarding to the material and methods need to be clarify in order to understand better the study.

Abstract:

The abstract is well written and summarizes the information included in the work.

Introduction:

In the introduction, the authors presented the problematic and the objective of the study is clearly established.

Material and Methods:

Line 109: different center of origin…Describe how many of the 1512 accessions are Mesoamerican and how many Andean since this data is later used in the results and it is useful information for the reader.

Line 138: the factor 6.25 is used to convert total seed N to protein content. Reference this conversion factor for common bean.

According to I.E. Ezeagu et al. / Food Chemistry 78 (2002) 105–109. Crude protein analysis conventionally based on multiplying the total nitrogen (N) (Kjeldalh N) by a factor of 6.25 has been suspect. Different conversion factors recommended for cereals and grain products range between 5.70 and 5.83; for dry grain legumes 5.46–5.71 is recommended; while 5.18–5.46 is for nuts and seeds (FAO, 1982).

Considered this reference. François Mariotti, Daniel Tomé, Philippe Mirand. Converting Nitrogen into Protein – Beyond 6.25 and Jones’ Factors. Critical Reviews in Food Science and Nutrition, Taylor & Francis, 2008, 48 (2), pp.177-184. ff10.1080/10408390701279749ff. ffhal-02105858f

Please discuss this and reference the conversion factor used in this study for common bean.

Line 145 -146: the authors said: with these data, a Tukey test and boxplot were performed to show the distribution of the accessions grouped by the criteria using R packages….

Some points are needed to be clarify in this sentence in order to explain better the methods.

Please specify what data is used for the contrast test in order to follow better the methods…. the mean values for each analyzed trait per accession, per seed color group or per genetic material.

Regarding the Tukey test is this multiple means comparison test supporting another global mean test (ANOVA or Krukall wallis etc)?

Specify also in the text the alpha level for the statistical test.

Line 148: Ward-MLM. Specify the complete name of these test. Ward- Modified Location Model.

Lines 159-160: This sentence is a bit confusing; the authors presented a correlation network made with qgraph, but which data is correlated? the dissimilarity coefficients, the distance coefficients, the mean values. Please specify in order to specify this issue.

It would be also interesting to specify what method do you use for correlating the data with qgraph, (cor_auto?)

Results:

Line 182: Positive and median correlations, what do you mean with median correlations?. Are all these correlations significant? Please include in the results the signification level of the correlations to better interpretation the results.

Lines 190-192: This sentence is a bit confusing please rewrite.

Line 197: add (Figure 2)

Line 227-241: In this section of the results the composition of the groups obtained by Ward-MLM method is describe, but the table 2 just reflects the total number of accessions of each group but not the characteristics of the accessions included in each one. It might be interesting to include this information the supplementary material since it is presented as results.

Line 243: It might be Figure 5 instead of Table 2

Line 247: table 2 instead of Fig 5

Lines 258- 263: this paragraph is not easy to follow. Please re-write it.

Discussion:

In general, the discussion is well written and it adresses the main points of the results.

line 336: proper bibliography format [36]

Tables and figures:

Table 1: please review the legend of the table, the superindex a and the cross might be changed.

Figure 1: correlation network, please include the significance level for each correlation or at least for those that are significant.

Figure 2: include significant level considering for the tukey test (plabeled with different letters in the plot indicate differences between group means?

Figure 3. Might be interesting to include the plots for pseudo-t2 and pseudo-F in the supplementary materials as it is the criteria used for the grouping. Suplementary material.

Table 2: in the legend (line 225) delete CV

In general, for all the figures, improve printing quality for seeing details.

The bibliography is well formated

Reviewer #2: In general the study is interesting: the Abstract provide a first insight into the results obtained, giving importance to commercial varieties widely diffused in Brazil as carioca and black beans, arising major interest for partecipatory breeding and breeding strategies in the next future. The Introduction is complete and well structured with references righlty reported. Materials and Method are well organized as the workflow strategy is highly reccomended for these type of experiment and confirmed by previous studies applying the same methodology. Results are clear as they follow the order of the analysis conducted as explained in materials and methods.

In general the study is well conducted and explained but maybe some slight adjustments could be done. I’ve resumed some points below (with reference to manuscript lines).

Line 35 – 39: not clear the distinction among gene pools… I would specify in line 35 that carioca and black market group is characterized by mesoamerican accessions.

Line 91 : maybe some very fast highlights on the conclusions reached by these two authors (very fast because you already explain this in the conclusions, but could be useful to touch the topic in the introduction)… for example: “the mesoamerican gene pool gave higher lectin, clacium,phosphorus,sulfur and zinc than the andean but lower phaseolin and iron” or “The major gene pools differed significantly in almost all grain constituents… (Discussion of Islam, 2002), or see Cominelli et al., 2019.

Line 106: In material and method: will you provide a table with the list of the accessions with the relative gene pool, seed color and genetic material specified? (this is the MAJOR IMPORTANT POINT!!!!)

Line 142: maybe would be nice to make a simple PCA to see how accessions behave considering variables that you use to create your preliminary groups. I would add also the belonging to a gene pool that at the end gives also a correlation with the dimensions of the seeds

Line 146: Tukey test and boxplot could be done also separating by gene pools?

Line 220: In Table 2, you show the different groups with the relative contribution of the first two canonical variables of each nutrient and means/st.dev of the nutrient contents in each group. However, while describing the groups (just below the table) you specify the descriptors of each group but without a rational order. Eventually, would be nice to have descriptors cited always in the same order for all the groups and I would give a world to each category you considered at the beginning, thus: seed color, genetic material and I would add also the belonging to the gene pool. (Eventually a pCoA for each group would be useful to see how accessions in each group distribute in relation to the categories mentioned above?)

Line 304: maybe a fast citations of the co-segregation evidences of Fe and Zn too?

Line 311: rightly you talk about gene pools but in your experiment seems that you skip the belonging to a gene pool as an important factor. Maybe it has a sense considering your experiment but it is not clear to the reader… this should be specified somewhere as I’ve showed in the comments above.

Line 356: a reference when you say “increased indirectly by human selection”.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Ester Murube Torcida

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2020 Sep 28;15(9):e0239263. doi: 10.1371/journal.pone.0239263.r002

Author response to Decision Letter 0

27 Jul 2020

Dear editor,

On behalf of my collaborators, I am submitting the manuscript titled “Diversity of nutritional content in seeds of Brazilian common bean germplasm”, after reviewing as requested by referees.

We believe that we addressed all questions and concerns and we are grateful for the opportunity to improve our manuscript. All changes are marked in the text as requested and specific answers are presented as follows:

Response to reviewers

Reviewer #1:

1. Line 109: different center of origin…Describe how many of the 1512 accessions are Mesoamerican and how many Andean since this data is later used in the results and it is useful information for the reader.

Response: The information was added to the main text.

2. Line 138: the factor 6.25 is used to convert total seed N to protein content. Reference this conversion factor for common bean.

According to I.E. Ezeagu et al. / Food Chemistry 78 (2002) 105–109. Crude protein analysis conventionally based on multiplying the total nitrogen (N) (Kjeldalh N) by a factor of 6.25 has been suspect. Different conversion factors recommended for cereals and grain products range between 5.70 and 5.83; for dry grain legumes 5.46–5.71 is recommended; while 5.18–5.46 is for nuts and seeds (FAO, 1982).

Considered this reference. François Mariotti, Daniel Tomé, Philippe Mirand. Converting Nitrogen into Protein – Beyond 6.25 and Jones’ Factors. Critical Reviews in Food Science and Nutrition, Taylor & Francis, 2008, 48 (2), pp.177-184. ff10.1080/10408390701279749ff. Please discuss this and reference the conversion factor used in this study for common bean.

Response:

We understand and appreciate your concern about that. This is a controversy question and some crossed opinions can be found about this matter over all types of food. Usually for common beans the 6.25 factor, recommended by the Association of Official Analytical Chemists (AOAC) (now referenced in the text) is used. Therefore, as the purpose of this article is to characterize the germplasm bank and also to compare the values obtained with previous works, we chose to use the 6.25 factor. We understand that the proportion of protein among the accessions will not be affected by the multiplying factor, which would not affect the diversity study.

Reference added to the text:

Association of Official Analytical Chemists - International [AOAC]. Official methods of analysis. 18th ed. Gaithersburg: AOAC; 2005.

Some references with articles about the bean crop:

Silva CA, Abreu  de FB, Ramalho MAP, Maia LGS. Chemical composition as related to seed color of common bean. Crop Breed Appl Biotechnol. 2012;12: 132–137.

Wiesinger JA, Cichy KA, Glahn RP, Grusak MA, Brick MA, Thompson HJ, et al. Demonstrating a Nutritional Advantage to the Fast-Cooking Dry Bean (Phaseolus vulgaris L.). J Agric Food Chem. 2016;64: 8592–8603. doi:10.1021/acs.jafc.6b03100

Celmeli T, Sari H, Canci H, Sari D, Adak A, Eker T, et al. The nutritional content of common bean (phaseolus vulgaris l.) landraces in comparison to modern varieties. Agronomy. 2018;8. doi:10.3390/agronomy8090166

Coelho CMM, Bellato C de M, Santos JCP, Ortega EMM, Tsai SM. Effect of phytate and storage conditions on the development of the ‘ hard-to-cook .’ J Sci Food Agric. 2007;1243: 1237–1243. doi:10.1002/jsfa

Jannat S, Shah AH, Shah KN, Kabir S, Ghafoor A. Genetic and nutritional profiling of common bean (Phaseolus vulgaris l) germplasm from Azad Jammu and Kashmir and exotic accessions. J Anim Plant Sci. 2019;29: 205–214.

3. Line 145 -146: the authors said: with these data, a Tukey test and boxplot were performed to show the distribution of the accessions grouped by the criteria using R packages….

Some points are needed to be clarify in this sentence in order to explain better the methods. Please specify what data is used for the contrast test in order to follow better the methods…. the mean values for each analyzed trait per accession, per seed color group or per genetic material. Regarding the Tukey test is this multiple means comparison test supporting another global mean test (ANOVA or Krukall wallis etc)? Specify also in the text the alpha level for the statistical test.

Response: The complete description of the analytic analyses was added to the text.

“The accessions were separated based on two criteria: seed coat color (black, carioca and colored) and genetic material (cultivars, landraces and breeding lines). For these two criteria an analysis of variance (ANOVA) followed by a Tukey test (p < 0.05) were performed for each case to compare significantly differences between the formed groups. To visualize the distribution of the accessions grouped by each criteria a boxplot graph was made.”

4. Line 148: Ward-MLM. Specify the complete name of these test. Ward- Modified Location Model.

Response: Done

5. Lines 159-160: This sentence is a bit confusing; the authors presented a correlation network made with qgraph, but which data is correlated? the dissimilarity coefficients, the distance coefficients, the mean values. Please specify in order to specify this issue.

It would be also interesting to specify what method do you use for correlating the data with qgraph, (cor_auto?)

Response: The sentence was moved to a better place that makes more sense in relation to the order of the analyzes shown in the results and in the MeM, and more details was added.

6. Line 182: Positive and median correlations, what do you mean with median correlations? Are all these correlations significant? Please include in the results the signification level of the correlations to better interpretation the results.

Response: Only edges of significant correlations are shown in the graph (p ≤ 0.05). Added this information to the figure legend.

7. Lines 190-192: This sentence is a bit confusing please rewrite.

Response: Done

8. Line 197: add (Figure 2)

Response: Done

9. Line 227-241: In this section of the results the composition of the groups obtained by Ward-MLM method is describe, but the table 2 just reflects the total number of accessions of each group but not the characteristics of the accessions included in each one. It might be interesting to include this information the supplementary material since it is presented as results.

Response: The table 2 shows the number of accessions, means and standard deviation of the nutrients contents in each group. Also, a supplementary table are now included showing the access belonging to each Ward-MLM group.

10. Line 243: It might be Figure 5 instead of Table 2

Response: Done

11. Line 247: table 2 instead of Fig 5

Response: Done

12. Lines 258- 263: this paragraph is not easy to follow. Please re-write it.

Response: Done

13. line 336: proper bibliography format [36]

Response: Done

14. Table 1: please review the legend of the table, the superindex a and the cross might be changed.

Response: Done

15. Figure 1: correlation network, please include the significance level for each correlation or at least for those that are significant.

Response: Done

16. Figure 2: include significant level considering for the tukey test (plabeled with different letters in the plot indicate differences between group means?

Response: Done

17. Figure 3. Might be interesting to include the plots for pseudo-t2 and pseudo-F in the supplementary materials as it is the criteria used for the grouping. Suplementary material.

Response: Done

18. Table 2: in the legend (line 225) delete CV

Response: Done

19. In general, for all the figures, improve printing quality for seeing details.

Response: All figures were submitted to PACE and fulfilled the required quality parameters.

Reviewer #2:

1. Line 35 – 39: not clear the distinction among gene pools… I would specify in line 35 that carioca and black market group is characterized by Mesoamerican accessions.

Response: Done

2. Line 91 : maybe some very fast highlights on the conclusions reached by these two authors (very fast because you already explain this in the conclusions, but could be useful to touch the topic in the introduction)… for example: “the mesoamerican gene pool gave higher lectin, clacium,phosphorus,sulfur and zinc than the andean but lower phaseolin and iron” or “The major gene pools differed significantly in almost all grain constituents… (Discussion of Islam, 2002), or see Cominelli et al., 2019.

Response: The information was added to the introduction.

3. Line 106: In material and method: will you provide a table with the list of the accessions with the relative gene pool, seed color and genetic material specified? (this is the MAJOR IMPORTANT POINT!!!!)

Response: A supplementary table with the list of accession with center of origin, seed coat color and genetic material is being provided now.

4. Line 142: maybe would be nice to make a simple PCA to see how accessions behave considering variables that you use to create your preliminary groups. I would add also the belonging to a gene pool that at the end gives also a correlation with the dimensions of the seeds

Response: A PCA was performed as suggested, however there was no different behavior for each group considering the preliminary groups. Regarding the gene pool, it would not be possible to do this due to the low number of accessions of Andean origin.

5. Line 146: Tukey test and boxplot could be done also separating by gene pools?

Response: The number of accessions of Andean gene pool is very low compared to the Mesoamerican, and since all of the Andean accessions have colored grains and showed similar results to the colored Mesoamerican accessions they were grouped together in the analyses.

6. Line 220: In Table 2, you show the different groups with the relative contribution of the first two canonical variables of each nutrient and means/st.dev of the nutrient contents in each group. However, while describing the groups (just below the table) you specify the descriptors of each group but without a rational order. Eventually, would be nice to have descriptors cited always in the same order for all the groups and I would give a world to each category you considered at the beginning, thus: seed color, genetic material and I would add also the belonging to the gene pool. (Eventually a pCoA for each group would be useful to see how accessions in each group distribute in relation to the categories mentioned above?)

Response: Looking at the characteristics of the accessions that formed each group, the color of the coat was the one that most contributed to the formation of the groups, so this characteristic being the most discussed. In the case of origin, only G1 comprised a significant number of Andean accessions, so origin was only mentioned for this group. Genetic material was not mentioned in the discussion of the groups because, as the dataset is formed mostly by breeding lines, in all groups the breeding lines were the majority and in none of the cases this characteristic becomes relevant in the formation of the groups.

We appreciate your suggestion to do a PCoA for each of the two categories (seed color and genetic material) but it would generate too much graphs and would difficult the correct interpretation of the graphs. Knowing that genetic material didn’t contributed to the formation of the groups we opted for a more general view of the groups. Now a supplementary table was provided with the information of access belonging to each Ward-MLM group, and also, the distribution of each group related to the nutrients composition are shown in the boxplots (Fig 3).

7. Line 304: maybe a fast citations of the co-segregation evidences of Fe and Zn too?

Response: Done

8. Line 311: rightly you talk about gene pools but in your experiment seems that you skip the belonging to a gene pool as an important factor. Maybe it has a sense considering your experiment but it is not clear to the reader… this should be specified somewhere as I’ve showed in the comments above.

Response: As cited before, the number of accessions Andean gene pool is very low compared to the Mesoamerican, that’s why studies were not performed exclusively for origin. The number of Andean accessions was added to MeM to evidence the low number of those in the study

9. Line 356: a reference when you say “increased indirectly by human selection”.

Response: Done

Decision Letter 1

Roberto Papa

3 Sep 2020

Diversity of nutritional content in seeds of Brazilian common bean germplasm

PONE-D-20-08197R1

Dear Dr. Azeredo Gonçalves,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Roberto Papa, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: After considering all the changes suggested by the reviewers, I think the manuscript improves in terms of clarity and ease of understanding the study. As I already included in my first review, I consider that the printing quality of the images is not very good and I urge the journal editing team to check this issue in the final publication.

It seems to be a very interesting study that highlight the importance of studying nutritional characteristics in a crop as important as the common bean.

Reviewer #2: Authors have efficiently addressed the doubts arose by the reviewers in an exhaustive way. Tables and figures have been updated as suggested. The new submitted document is more legible and understandable by readers, in particular for the part relative to matherials and methods. Authors gave complete explanations to reviewers on decisions and modifications made after the first review. The article is now complete and ready for submission.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Ester M. Murube Torcida

Reviewer #2: No

Acceptance letter

Roberto Papa

15 Sep 2020

PONE-D-20-08197R1

Diversity of nutritional content in seeds of Brazilian common bean germplasm

Dear Dr. Azeredo Gonçalves:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Prof. Roberto Papa

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Log-likelihood graph of the ideal number of groups for 1,512 common bean accessions analyzed for grain nutrient and protein content.

    (TIF)

    Click here for additional data file. (81.7KB, tif)
    S1 Table. Information of the 1,512 accessions characterized for seed nutritional content.

    1CIAT = International Center for Tropical Agriculture (Centro Internacional de Agricultura Tropical), EMBRAPA = Brazilian Agricultural Research Corporation (Empresa Brasileira de Pesquisa Agropecuária), IAC = Agronomic Institute of Campinas (Instituto Agronômico de Campinas), IDR-Paraná = Rural Development Institute of Paraná –IAPAR–EMATER (Instituto de desenvolvimento Rural do Paraná), USDA = United States Department of Agriculture, ESALQ = Universidade de São Paulo—Escola Superior de Agricultura “Luiz de Queiroz”.

    (DOCX)

    Click here for additional data file. (156.4KB, docx)
    S1 File

    (DOCX)

    Click here for additional data file. (15.1KB, docx)
    S2 File

    (PDF)

    Click here for additional data file. (237.5KB, pdf)

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.

    Articles from PLoS ONE are provided here courtesy of PLOS

    RESOURCES