Plant Foods for Human Nutrition

, Volume 64, Issue 2, pp 174–180

Variability of Nutritional and Cooking Quality in Bean (Phaseolus vulgaris L) as a Function of Genotype

Authors

    • Vivekananda Institute of Hill Agriculture
  • Gyanendra Singh
    • Vivekananda Institute of Hill Agriculture
  • V. Mahajan
    • Vivekananda Institute of Hill Agriculture
  • H. S. Gupta
    • Vivekananda Institute of Hill Agriculture
Original Paper

DOI: 10.1007/s11130-009-0121-4

Cite this article as:
Saha, S., Singh, G., Mahajan, V. et al. Plant Foods Hum Nutr (2009) 64: 174. doi:10.1007/s11130-009-0121-4

Abstract

Screening of natural biodiversity for the better quality traits are of prime importance for quality breeding programs. The objective of this investigation was to select candidate accession of bean having high concentrations of protein as well as macro and micro minerals with good cooking quality for use as parents in breeding programme for these compounds. Thirty-five accessions of bean (Phaseolus vulgaris L) were field grown and their seeds were analyzed for their cooking quality and nutritional composition. Wide variations were observed in most of the measurements e.g. protein (18.7–26.2%), iron (79.4–137.6 ppm) and hardness after cooking (4.65–9.88 Kg) suggesting that there are considerable levels of genetic diversity. Across all accessions the concentration of potassium was negatively correlated with protein (r = −0.43, P < 0.05). Concentrations of protein was significantly greater in accessions VIII, XIII and XIX compared to other accessions analyzed. Iron concentrations were greatest (137 ppm) in XIX and lowest (79 ppm) in XXVII. Lines with less cooking time were line III, X, XXVI, XXX and XXXI. Bean line XIX contains high protein (24.9%) with high zinc (33.3 ppm) and highest iron (137.6 ppm), but it has high hardness after cooking (7.32 kg). Four clusters were computed by cluster analysis that explained quite a good variation in the traits. The great variability for these attributes suggests that these selected accessions may be useful as parents in hybridization programs to produce bean with value-added traits. This information was also potentially useful for pulse breeders working on the development of new varieties.

Keywords

Phaseolus vulgarisVariabilityProteinIronTanninCooking quality

Introduction

Exploring natural biodiversity as a source of novel alleles to improve the productivity, adaptation, quality and nutritional value of crops, is of prime importance in 21st century breeding programs [7]. Efforts are going on to improve the quality of not only grains but also pulses [23].

Among the plant species, grain legumes are considered as the major source of dietary proteins. Protein quality in leguminous seeds does not reach the same level as in animal products. This is due to various factors, among them the well known are the unbalanced amino acid composition, the low true digestibility of protein and the presence of antinutritional factors in the seeds [4, 6, 18]. Other than protein, legumes are a good source of carbohydrates and dietary fibre, being, at the same time, an important source of vitamins (especially B-group) and mineral elements such as K, Zn, Ca and Mg [14, 19]. They are low in fat except a few (soybean and ground nut), sodium and contain no cholesterol. However, legumes contain antinutrients, which hinder the efficient utilization, absorption or digestion of nutrients and thus reduce their bioavailability and their nutritional qualities.

Common bean (Phaseolus vulgaris L) is the most important food legume of the genus Phaseolus. It is a good source of protein and is an excellent source of complex carbohydrates. The common bean is also a good source of vitamins and minerals. In addition to these nutritional components, it contains some antinutritional factors such as protease inhibitors, tannins and phytic acid, among others. Numerous studies have led to the conclusion that phytic acid and tannins may bind proteins and some essential dietary minerals, thus making them unavailable or only partially available for absorption.

Few efforts have been made to improve mineral content in cultivated common bean by breeding programs [23, 24]. As a result, the contribution of genetic factors to mineral accumulation is poorly understood [15]. To our best knowledge, few studies have investigated the mineral content as well as other nutritional and antinutritional components of wild and weedy common beans in order to gain knowledge of their genetic potential for the improvement of cultivated beans. Such information is an essential pre-requisite before heritability and/or environmental studies can be conducted.

There is a lack of studies evaluating available genetic variability, especially for quality in given sets of germplasm. Studies related to bean as legume food source of micronutrient are not meager. But, systematic screening studies for the quality evaluation of bean and its use and information for the development of better variety is lacking. Therefore, the present study was undertaken to evaluate bean accessions for breeding better quality varieties.

Materials and Methods

Plant Material and Experimental

Bean accessions (Phaseolus vulgaris L.) (35) were grown in a field experiment in kharif season (June–September), 2007, at experimental farm, Hawalbagh (29°36′ N, 79°40′ E and 1250 m above amsl). The environmental conditions define the area as a sub-temperate, hilly region. Experimental soil was silty clay loam in texture. All accessions were grown in five rows of 3 m length. Mineral fertilizer consisting of 20:40:0 kg ha−1 of N, P, K applied through urea and single super phosphate, and 20 Mg ha−1 FYM was applied to the crop. Beans were harvested manually at mature stage. After harvest and processing, three replicates of 35 bean lines were analyzed for different physicochemical, cooking and nutritional attributes after drawing samples using the quartering procedure [12]. Details of accessions were presented in Table 1.
Table 1

Details of accessions of bean and their seed weight

Sample no.

Accession name

Plant type

Seed weight (g 100 seed−1)

Sample no.

Sample name

Plant type

Seed weight (g 100 seed−1)

I

Local 18

Bush

39.8

XIX

HUR 385

Bush

39.2

II

EC 285576

Bush

42.7

XX

VRJ 132

Bush

51.2

III

HUR 145

Bush

45.4

XXI

VRJ 145

Bush

54.1

IV

Local 27-1

Bush

53.1

XXII

EC 285558

Bush

48.3

V

MJ 7

Bush

42.0

XXIII

IC 17884

Bush

46.2

VI

Local 15

Intermediate

37.2

XXIV

N 380

Bush

53.1

VII

EC 285563

Bush

58.6

XXV

VLR 125

Bush

43.8

VIII

HUR 20

Bush

40.0

XXVI

VL 63

Bush

36.5

IX

Local 37

Bush

38.6

XXVII

VL 64

Bush

46.0

X

HUR 579

Bush

33.8

XXVIII

VRJ 128

Bush

37.4

XI

Local 27-1-1

Bush

41.1

XXIX

VRJ 122

Bush

37.4

XII

VRJ 129

Bush

30.2

XXX

VRJ 147

Bush

38.2

XIII

HUR 146

Bush

39.9

XXXI

VRJ 123

Bush

39.4

XIV

HUR 91

Bush

39.6

XXXII

Dharali 8

Bush

34.8

XV

Local 88

Bush

43.4

XXXIII

VRJ 141

Bush

38.2

XVI

EC 285568

Bush

45.2

XXXIV

Bhimtal 4

Bush

38.7

XVII

IC 16584

Bush

40.5

XXXV

VRJ 138

Bush

38.5

XVIII

EC 285561

Bush

48.1

    

Chemicals and Reagents

All chemicals and reagents were procured from Merck, India, Ltd. Double-distilled water was used throughout the analysis.

Physicochemical Properties

Unprocessed seeds of all the germplasm lines with three replications of bean seed were analyzed for the following physicochemical properties. Seeds (air dried with moisture content 12%; 25 g) were accurately weighed and transferred to a measuring cylinder, where 100 mL distilled water were added. Seed volume was obtained after subtracting 100 mL from the total volume of seeds and water. Density was recorded as gram per cubic cm. One hundred seeds of each line were weighed separately using a digital electronic balance, and total weight was recorded as 100-seed weight.

Seed hardness was measured by a texture analyzer (Stable Micro System, Godalming, UK) using a 36-mm probe with the following program: pre-test speed: 2 mm/s; test speed: 0.5 mm/s; post-test speed: 10 mm/s; trigger force: 5 g; mode: compression; and strain: 60%.

Seeds weighing 25 g were counted and transferred to a measuring cylinder with 100 mL water. The cylinders were covered with aluminum foil and left overnight at room temperature. The next day, the seeds were drained, superfluous water removed with filter paper and swollen seeds reweighed. Hydration capacity was determined by using the formula: \( {\text{hydration}}\;{\text{capacity}}\;{\text{per}}\;{\text{seed}}\left( {{{\text{mg}} \mathord{\left/ {\vphantom {{\text{mg}} {\text{seed}}}} \right. } {\text{seed}}}} \right) = {{\left[ {{\text{weight}}\;{\text{of}}\;{\text{soaked}}\;{\text{seed}}\left( {\text{g}} \right) - {\text{weight}}\;{\text{of}}\;{\text{seeds}}\;{\text{before}}\;{\text{soaking}}\;\left( {\text{g}} \right)} \right]} \mathord{\left/ {\vphantom {{\left[ {{\text{weight}}\;{\text{of}}\;{\text{soaked}}\;{\text{seed}}\left( {\text{g}} \right) - {\text{weight}}\;{\text{of}}\;{\text{seeds}}\;{\text{before}}\;{\text{soaking}}\;\left( {\text{g}} \right)} \right]} {{\text{number}}\;{\text{of}}\;{\text{seeds}}}}} \right. } {{\text{number}}\;{\text{of}}\;{\text{seeds}}}} \). Hydration index was calculated using the formula: \( {\text{hydration}}\;{\text{index}} = {{{\text{hydration}}\;{\text{capacity}}\;{\text{per}}\;{\text{seed}}} \mathord{\left/ {\vphantom {{{\text{hydration}}\;{\text{capacity}}\;{\text{per}}\;{\text{seed}}} {\text{weight}}}} \right. } {\text{weight}}}\;{\text{per}}\;{\text{seed}} \).

Seeds weighing 25 g were counted, their volume noted and soaked overnight. The volume of the soaked seeds was noted in a graduated cylinder. Swelling capacity was calculated as: \( {\text{swelling}}\;{\text{capacity}}\;{\text{per}}\;{\text{seed}}\left( {{{\text{mL}} \mathord{\left/ {\vphantom {{\text{mL}} {\text{seed}}}} \right. } {\text{seed}}}} \right) = {{\left[ {{\text{volume}}\;{\text{after}}\;{\text{soaking}}\;\left( {\text{mL}} \right) - {\text{volume}}\;{\text{before}}\;{\text{soaking}}\;\left( {\text{mL}} \right)} \right]} \mathord{\left/ {\vphantom {{\left[ {{\text{volume}}\;{\text{after}}\;{\text{soaking}}\;\left( {\text{mL}} \right) - {\text{volume}}\;{\text{before}}\;{\text{soaking}}\;\left( {\text{mL}} \right)} \right]} {{\text{number}}\;{\text{of}}\;{\text{seeds}}}}} \right. } {{\text{number}}\;{\text{of}}\;{\text{seeds}}}} \). The swelling index was calculated using the formula: \( {\text{swelling}}\,{\text{index}} = \,{{{\text{swelling}}\,{\text{capacity}}\,{\text{per}}\,{\text{seed}}} \mathord{\left/ {\vphantom {{{\text{swelling}}\,{\text{capacity}}\,{\text{per}}\,{\text{seed}}} {\text{volume}}}} \right. } {\text{volume}}}\,{\text{per}}\,{\text{seed}}\left( {\text{mL}} \right) \).

Cooking Quality

Relative cooking time was measured following the method by Saha et al. [20]. Seeds (10 g) were taken in beakers; distilled water was added in the ratio of 1:4 (w/v) and placed inside a pressure cooker (pressure 1 kg cm−2 and temperature 121 °C). Irrespective of the hardness of the seed, it was boiled for 30 min. “Degree of cooking” was tested individually by estimating the hardness of cooked seed after fixed time. A hardness range of 4–5 kg was standardized for cooked seed by comparing the test by pressing between the index finger and thumb. The exact hardness was measured because the desired hardness for cooked seed cannot be measured exactly with hand pressed/feel method. The hardness was measured using a texture analyzer as per the program: pre-test speed: 2 mm/s; test speed: 0.5 mm/s; post-test speed: 10 mm/s; trigger force: 5 g; mode: compression; and strain: 50% using a 36-mm probe.

Cooking loss was measured after cooking seeds (50 g) with 100 mL water. After cooking, seeds were removed and the residual water was evaporated after boiling. The dry residue was measured and quantified as cooking loss and represented as per cent dry matter.

Chemical Analysis

Determination of Total Phenolics Content

Total phenolics content of the methanol extracts was determined by the Folin-Ciocalteu assay and tannic acid was used as standard [21]. Sample (500 mg) was weighed into 50 mL plastic extraction tubes and vortexed with 25 mL extraction solvent (80% ethanol). Then, the sample with the extraction solvent was heated at 60 °C (water bath) for 1 h, allowed to cool at room temperature, and homogenized for 30 s with a sonicator. Two hundred fifty microlitres (three replicates) were introduced into screw cap test tubes; 1.0 mL Folin-Ciocalteu’s reagent and 1.0 mL sodium carbonate (7.5%) were added. The tubes were vortexed and heated for 15 min at 45 °C. The absorption at 765 nm was measured (Model U 2001, Hitachi UV/Vis spectrophotometer) and the total phenolic content was expressed as tannic acid equivalents in mg per 100 g dry material.

Determination of Nutritional Attributes

Protein content was determined according to the AOAC [2] methods. Bean seeds were analyzed for nutrient parameters after di-acid digestion (HNO3: HClO4; 10:4 v/v). The K content was determined by flame photometry, while Fe, Zn, Cu and Mn contents were analyzed by using an atomic absorption spectrophotometer. Phosphorus (P) was estimated photometrically via development of the phospho-molybdate complex [22].

Statistical Analysis

Data represent the mean of three replicate samples for each bean line. The genotypic mean value of each parameter was used for statistical analysis using SPSS programme (SPSS Inc., Version 10, Chicago, Illinois, IL, USA). Correlation analysis and cluster analysis were performed using SPSS.

Results and Discussion

Variations in Bean Seed Properties

Wide variation was observed in most of the evaluated attributes (Table 2). This is due to wide genetic basis of the tested bean genotypes. Wide variation (1.09 (XXXV)−1.41 (I) g ml−1) was observed in density of evaluated bean accessions, suggesting that there are considerable levels of genetic diversity. Considerable variations were observed in seed hydration and swelling capacity. Hydration and swelling capacity ranged between 0.31 (I)–0.59 (XXIV) and 0.30 (XXXV)–0.56 (XXIV) g per seed. Seed hardness also varied between 34.1–57.6 kg.
Table 2

Basic statistics for physicochemical and cooking qualities of 35 tested bean accessions

 

Trait

Unit

Mean

SD

Min.

Max.

Mode

CV (%)

Group attribute 1 (Physicochemical properties)

Density

g ml−1

1.24

0.07

1.09

1.41

1.24

5.76

Hydration capacity per seed

g

0.43

0.07

0.31

0.59

0.39

16.58

Hydration index

1.03

0.09

0.78

1.25

1.05

8.31

Swelling capacity

g

0.40

0.07

0.30

0.56

0.43

16.80

Swelling index

1.19

0.10

0.91

1.39

1.18

8.63

Hardness

kg

45.76

5.46

34.14

57.56

45.00

11.94

Group attribute 2 (Cooking quality)

Hardness after cooking

kg

6.52

1.09

4.65

9.88

5.50

16.71

Cooking losses

%

8.38

2.29

5.28

14.98

7.30

27.32

Table 3

Basic statistics for nutritional properties of 35 tested bean accessions

 

Trait

Unit

Mean

SD

Min

Max

Mode

CV (%)

Group attribute 3 (Nutritional properties)

Proximate composition

Protein

%

22.37

2.05

18.66

26.17

24.0

9.16

Ash

4.29

0.25

3.75

4.75

4.2

5.92

Macrominerals

Phosphorous (P)

%

0.44

0.04

0.36

0.49

0.43

7.94

Potassium (K)

1.09

0.08

0.98

1.29

1.07

7.38

Microminerals

Zinc (Zn)

ppm

33.55

4.36

25.07

44.77

29.1

13.00

Copper (Cu)

5.21

1.39

1.83

7.54

5.60

26.68

Iron (Fe)

103.92

14.99

79.35

137.56

97.3

14.43

Manganese (Mn)

20.87

4.88

11.05

39.39

18.70

23.40

Antinutritional factor

Tannin (Tannic acid eq.)

g T.A.Eq. 100 g−1

0.90

0.24

0.51

1.56

0.88

27.23

In terms of cooking quality, hardness after cooking ranged between 4.7 (XXVI)–9.9 (XXII) kg after fixed time of pressure cooking. Cooking loss was ranged between 5.3 (VII)–15.0 (XXXI) %. Kigel [10] reported hard-to-cook problem of bean seeds. The need for prolonged cooking can be related to either hardshell, which do not allow to adsorb enough water or adsorbed water failed to soften during soaking and cooking [9]. Low water absorption by hardshell can be due to low permeability of the seed coat to water. Agbo et al. [1] showed differences in micropyle size and in other microstructural differences that were related to seed coat permeability and water uptake by the seed.

Protein content varied between 18.7 (XXXIV)–26.2 (VIII) % (Table 3). Our report was consistent with the report by Baudoin and Maquet [5], where it was reported that protein content in 14 genotypes of P. vulgaris ranged between 19.1–29.7%. Guzman-Maldonado [8] reported that protein content of wild bean was more, which was ranged between 18.0–33.0% than cultivated one (mean 20.6%). Ash content varied between 3.8 (X)–4.8 (XXII) %. Martinez et al. [13] reported that ash content varied between 6.8–8.2% in green bean.

Phosphorous (P) and potassium (K) content in bean seed ranged between 0.36 (XXXII)–0.49 (XXI) and 0.98 (XIX)–1.29 (XI) % (dry matter basis). Our result related to P content is within the range reported by Moraghan and Grafton [15], whereas, K content was in lower range. It was reported that seed P and K content ranged between 0.41–0.47% and 1.42–1.69% under green house condition. In another study, Moraghan and Grafton [15] reported that P and K ranged between 0.45–0.54% and 1.54–1.69%, respectively.

Mean Fe and Zn content in thirty-five bean seed lines were 33.6 and 103.9 μg g−1, respectively, which was consistent with Koehler et al. [11]. Our result was consistent with the report by [16] in terms of Zn content, whereas, it was in higher range in Fe concentration. Mean Fe and Zn concentration in eight bean seeds ranged between 53–69 and 24–32 μg g−1 [16]. Whereas, higher Fe content was reported in bean seed by Guzmán-Maldonado et al. [8]. Mean Fe content was 100 μg g−1 in cultivated bean, whereas, it reached up to 280 μg g−1 in wild cultivars. According to the results of Barampama and Simard [3], mineral contents of common bean are significantly influenced by locality.

Tannin content in bean seed ranged between 0.51 (XXVIII)–1.56 (III) g tannic acid equivalent per 100 g seed (Table 3). In earlier study tannin content was reported to be 21.3–39.7 g eq. catechin per kg seed in wild and cultivated bean [8].

Bean line XIX contains high protein (24.9%) with high zinc (33.3 ppm) and highest iron (137.6 ppm), but it has high hardness after cooking (7.32 kg). Low seed hardness and hardness after cooking i.e. least cooking time was recorded in line XXXV. Lines with less cooking time were line III, X, XXVI, XXX and XXXI. Lines XI, XXXII, XXXIII, XXXIV were richer in iron and protein contents and among these lines, line XI contains highest K content. Line III and IX were higher in tannin content among 35 lines.

Correlation between Different Attributes

Few significant correlation coefficients among traits ranged from −0.434** (eg. protein versus potassium) to 0.757** (seed weight versus hydration and swelling capacity) (Table 4). Significant correlation between physico-chemical properties were obvious. However, among nutritional attributes, protein was positively correlated with swelling capacity and index, hydration capacity. Dry matter loss during cooking was negatively correlated (−0.38; P < 0.05) with protein content. Among microminerals, zinc content was negatively correlated with swelling and hydration capacity and seed weight. Further, it also positively correlated with ash content. Manganese was negatively correlated (−0.36; P < 0.05) with copper content. Whereas, potassium content was negatively correlated with protein content and positively correlated with ash and zinc content. Cooking time showed a positive correlation with seed size in 27 bean accessions grown in Tanzania, suggesting that small to medium seed size should be selected for shorter cooking time [17]. Our result is in consistent with the report. Positive correlation (0.367*, P < 0.05) between seed weight and hardness after cooking depicting same trend.
Table 4

Association (correlation coefficient) among physicochemical, nutritional attributes and anti-nutrients in bean accessions

 

HRD

HRDC

DEN

HC

HI

SC

SI

DM

PR

ASH

ZN

FE

CU

MN

P

K

TAN

SW

0.426*

0.367*

0.119

0.757**

−0.25

0.757**

0.072

−0.23

0.29

−0.10

−0.42*

−0.41*

−0.14

0.04

0.445*

−0.23

−0.14

HRD

 

0.335*

0.321

0.497**

−0.032

0.489**

0.185

−0.122

0.080

−0.197

−0.193

−0.317

−0.37*

0.292

0.023

−0.219

−0.12

HRDC

  

−0.001

0.408*

0.094

0.419*

0.142

−0.084

0.332

0.115

−0.169

−0.144

−0.21

0.277

0.081

−0.174

−0.23

DEN

   

0.127

−0.42*

0.265

0.533**

−0.47**

0.248

−0.335*

−0.116

−0.146

−0.29

0.416*

0.027

0.155

0.051

HC

    

0.378*

0.970**

0.420*

−0.288

0.390*

0.033

−0.384*

−0.247

−0.14

0.203

0.365*

−0.226

−0.17

HI

     

0.260

0.452**

0.242

0.084

0.425*

0.226

0.353*

0.070

−0.098

0.154

0.034

−0.156

SC

      

0.518**

−0.388*

0.449**

−0.023

−0.389*

−0.228

−0.12

0.254

0.318

−0.209

−0.21

SI

       

−0.296

0.382*

0.074

0.109

0.279

−0.105

0.293

0.056

.148

−0.22

DM

        

−0.377*

0.454**

0.511**

0.307

0.098

−0.45**

−0.026

0.332

−0.08

PR

         

−0.045

−0.191

−0.027

−0.06

0.090

0.255

−0.43**

0.167

ASH

          

0.540**

0.172

0.162

−0.295

0.485**

0.423*

−0.24

ZN

           

0.596**

0.279

−0.215

0.086

0.473**

−0.14

FE

            

0.004

0.008

−0.188

0.168

−0.06

CU

             

−0.359*

−0.007

−0.072

−0.21

MN

              

−0.185

−0.028

0.082

P

               

0.093

0.010

K

                

−0.06

SW seed weight, HRD seed hardness, HRDC hardness after cooking, DEN density, HC hydration capacity, HI hydration index, SC swelling capacity, SI swelling index, DM dry matter lost after cooking, PR protein, ASH ash, ZN zinc, FE iron, CU copper, MN manganese, P phosphorous, K potassium, TAN tannin

*P < 0.05; **P < 0.01

Statistical Procedure for Classification

In order to see patterns of clustering between the bean accessions studied hierarchical cluster analysis was used. The data matrix included as objects, attributes were analyzed for the thirty-five accessions. The variables were the attributes described in the experimental section. Pearson correlation was used as similarity criterion and furthest neighbour as a clustering method (Fig. 1). Using a similarity level 35 bean accessions were classified into mainly four groups (Fig. 1). An important conclusion is obtained from this: based on composition, the differences between the accessions studied are still great enough to classify them correctly, on the basis of the variables introduced in the present analysis.
https://static-content.springer.com/image/art%3A10.1007%2Fs11130-009-0121-4/MediaObjects/11130_2009_121_Fig1_HTML.gif
Fig. 1

Cluster analysis: Dendogram of 35 bean accessions

The dendrogram of 35 bean accessions showed 4 clusters. (Fig. 1). Cluster 1 consisted of ten genotypes, (starting from top XIII to IX). Cluster 2 comprised of a mixture of 12 accessions collected from different parts of Uttarakhand, India. Five accessions formed cluster 3. Cluster 4 consisted of 8 genotypes. All these important traits may be used in the cross breeding programmes to increase variability for different cooking/nutritional characteristics and to make suitable selections that are acceptable to consumers. From a breeding standpoint, the high variability suggests that it should be possible to obtain appreciable responses to selection for these traits. These results are also potentially useful in the efficient conservation of an important part of the agricultural biodiversity of India.

Acknowledgements

The author thanks Mr. Sanjay Kumar for assisting in chemical analysis.

Copyright information

© Springer Science+Business Media, LLC 2009