International Journal of Agronomy
Volume 2018 (2018), Article ID 5468602, 7 pages
https://doi.org/10.1155/2018/5468602

Research Article

Identification of Sources of Resistance for Peanut Aspergillus flavus Colonization and Aflatoxin Contamination

Richard Moise Alansou Dieme,¹ Issa Faye,² Yedomon Ange Bovys Zoclanclounon,³ Daniel Fonceka,³ Ousmane Ndoye,⁴ and Papa Madiallacke Diedhiou¹

¹Université Gaston Berger, BP 211 Saint-Louis, Senegal
²Centre National de Recherches Agronomiques de Bambey, Institut Sénégalais de Recherches Agricoles, BP 211 Bambey, Senegal
³Centre d’Etudes Régional pour l’Amélioration de l’Adaptation à la Sécheresse, Route de Khombole, BP 3320 Thiès, Senegal
⁴Conseil Ouest et centre Africain pour la Recherche et le Développement Agricoles, Avenue Bourguiba, BP 48 Dakar RP, Senegal

Correspondence should be addressed to Richard Moise Alansou Dieme; alansou7dieme@gmail.com

Received 25 May 2018; Revised 7 August 2018; Accepted 13 September 2018; Published 1 October 2018

Academic Editor: Glaciela Kaschuk

Copyright © 2018 Richard Moise Alansou Dieme et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Peanut aflatoxin contamination caused by Aspergillus flavus is a serious constraint for food safety and human health in Senegal. The present study aimed to identify sources of resistance for A. flavus colonization and aflatoxin contamination. Thus, seeds from 67 peanut genotypes were tested under laboratory conditions. Aqueous conidial suspension of an aflatoxinogenic strain of A. flavus was used for inoculation in Petri dishes containing ten seeds of each genotype, and data on incidence and severity were recorded. Total aflatoxin concentration in seeds was determined on 15th day after inoculation using mReader® method. Results showed a significant () variation of aflatoxin, incidence and severity among the tested peanut genotypes. Incidence ranged from 0 to 70% with a mean of 20.36 ± 0.8%. Out of the 67 genotypes, eight showed incidence less than 10%. Severity ranged from 0 to 44% with a mean value of 8.82 ± 0.45%. The genotype 12CS_104 showed aflatoxin concentration level in conformity with the European standard (4 ppb). Out of three clusters revealed by hierarchical classification based on disease incidence and severity, the cluster 1 contained 33 genotypes characterised by low incidence and severity values. These genotypes can be tested under field conditions to confirm their resistance to A flavus.

1. Introduction

Peanut (Arachis hypogaea L.) is an important staple crop in Senegal. The national peanut production was estimated at 1,050,042 tons during the rainy season of 2016 [1]. This crop is mainly produced in Fatick, Kaolack, Kaffrine, Louga, and Thies regions, with more than 60% of the national peanut production [1]. Peanut seeds are widely used for food consumption and play a significant economic role for small-scale farmers and food industries in Senegal [2]. However, pre- and postharvest aflatoxin contamination in peanut is a serious threat for food safety and human health in Senegal [3]. It is one of the major constraints limiting sustainable and good quality seed production in the world [4]. Aflatoxin contamination is due to Aspergillus flavus (Link ex Fries, Teleomorph: Petromyces flavus) [5]. Damages caused by this facultative plant pathogen in maize, peanut, and sesame were reported in Senegal [6]. Considerable economic losses caused by this bacterium are mainly due to crop quality value and international trade restrictions on food stuffs charged in aflatoxin [7].

Aflatoxin is the name of a group of toxin known as G1, G2, B1, B2, M1, and M2 that produced the plant pathogen [8]. These toxins occur naturally and have been found in a wide range of commodities, including peanuts used for animal and human consumption [9]. Aflatoxins are toxic, mutagenic, and carcinogenic compounds [10]. Depending on their levels, toxins can severely affect the liver and induce immune-suppressing effects [9].

To handle this issue, a wide range of preharvest aflatoxin contamination management methods were developed. Application of atoxinogenic isolates of A. flavus [11] and host genetic resistance were tested [12]. In Senegal, previous studies reported that varieties 55-437 and 73-3 were resistant to A. flavus [13]. Identification of new sources of resistance merits to be investigated for efficient peanut breeding program. First step of host genetic resistance is the seed colonization test. Therefore, the present study was undertaken to identify promising peanut genotypes under laboratory conditions.

2. Materials and Methods

2.1. Plant Materials

The plant material consisted of 67 genotypes including 58 chromosomal substitutions lines [14] and nine national released varieties. The chromosomal substitution lines belong to a cross between Fleur 11 and a synthetic amphidiploid parent (Table 1).

Table 1: Peanut material used in this study.

No
Genotypes
Description
Country of origin

1
12CS_001
CSL
Senegal

2
12CS_004
CSL
Senegal

3
12CS_006
CSL
Senegal

4
12CS_007
CSL
Senegal

5
12CS_008
CSL
Senegal

6
12CS_009
CSL
Senegal

7
12CS_010
CSL
Senegal

8
12CS_011
CSL
Senegal

9
12CS_012
CSL
Senegal

10
12CS_016
CSL
Senegal

11
12CS_018
CSL
Senegal

12
12CS_020
CSL
Senegal

13
12CS_021
CSL
Senegal

14
12CS_022
CSL
Senegal

15
12CS_023
CSL
Senegal

16
12CS_024
CSL
Senegal

17
12CS_027
CSL
Senegal

18
12CS_028
CSL
Senegal

19
12CS_031
CSL
Senegal

20
12CS_032
CSL
Senegal

21
12CS_033
CSL
Senegal

22
12CS_034
CSL
Senegal

23
12CS_036
CSL
Senegal

24
12CS_037
CSL
Senegal

25
12CS_039
CSL
Senegal

26
12CS_041
CSL
Senegal

27
12CS_042
CSL
Senegal

28
12CS_047
CSL
Senegal

29
12CS_048
CSL
Senegal

30
12CS_050
CSL
Senegal

31
12CS_051
CSL
Senegal

32
12CS_052
CSL
Senegal

33
12CS_053
CSL
Senegal

34
12CS_054
CSL
Senegal

35
12CS_055
CSL
Senegal

36
12CS_059
CSL
Senegal

37
12CS_060
CSL
Senegal

38
12CS_061
CSL
Senegal

39
12CS_062
CSL
Senegal

40
12CS_063
CSL
Senegal

41
12CS_066
CSL
Senegal

42
12CS_070
CSL
Senegal

43
12CS_072
CSL
Senegal

44
12CS_075
CSL
Senegal

45
12CS_076
CSL
Senegal

46
12CS_078
CSL
Senegal

47
12CS_079
CSL
Senegal

48
12CS_084
CSL
Senegal

49
12CS_085
CSL
Senegal

50
12CS_090
CSL
Senegal

51
12CS_091
CSL
Senegal

52
12CS_095
CSL
Senegal

54
12CS_096
CSL
Senegal

55
12CS_100
CSL
Senegal

56
12CS_111
CSL
Senegal

57
12CS_112
CSL
Senegal

58
12CS_118
CSL
Senegal

59
12CS_119
CSL
Senegal

60
55-33
Variety
Senegal

61
55-437
Resistant control
Senegal

62
73-30
CSL
Senegal

63
73-33
Resistant control
Senegal

64
78-936
Variety
Senegal

65
Fleur11
Susceptible control
Senegal

66
GC-8-35
Variety
Senegal

67
L27
Variety
Senegal

Chromosomal substitution lines.

2.2. Isolation of Aspergillus flavus, Sporangial Suspension Preparation, and Inoculation

Aflatoxinogenic strain provided from peanut seeds were purified by successive cultures on 5/2 agar medium. The aflatoxin concentration level was checked using the Reveal® Q⁺ Aflatoxin test kit (accesso peanut enterprise corporation, USA). The spore suspension of A. flavus was obtained by soaking colonized seeds in 50 ml of sterile distilled water. Then, one drop of Tween 20 was added to the solution and thoroughly mixed for 10 minutes. Inoculation was carried out by introducing 100 μl of the supernatant of the spore suspension into each Petri dish.

2.3. Seed Colonization Test

The seed colonization test was conducted following a modified Mehan and McDonald procedure. For each genotype, 50 seeds were sterilized and rinsed properly in sterile distilled water. Then, the seeds were hydrated to about 20% moisture content. The 50 seeds of each genotype were placed in 5 Petri dishes containing 10 seeds, and each Petri dish was considered as a replication. The seeds were inoculated with a conidial suspension (60 µL containing approximately 1 × 10⁸ mL⁻¹ conidia of the aflatoxigenic strain of A. flavus). This preparation was kept at laboratory conditions (25 ± 0.12°C and 82 ± 0.42% relative humidity) for fifteen days.

2.4. Data Collection

The seeds’ colonization was observed during two weeks, and aflatoxin concentration was measured using the Reveal® Q⁺ Aflatoxin test kit (accesso peanut enterprise corporation, USA). The incidence was calculated using the following formula:

The severity scale of aflatoxin on seeds was estimated using a modified Tonapi et al. [15] scale. It was defined as follows: 0, noninfected seeds; 1, seeds whose surface covered by the fungus is less than 20%; 2, 20%–40% seed surface covered by the fungus; 3, 40%–60% seed surface covered by the fungus; 4, 60%–80% seed surface covered by the fungus; and 5, 80%–100% seed surface covered by the fungus. The severity calculation based on Tonapi et al. [15] formula was as follows:

where i is severity scale from 0 to 5 and is the number of seed corresponding to scale of severity.

2.5. Data Analysis

Data analysis was performed with the open-source statistical software R version 3.4.5 [16]. Descriptive statistics of recorded data were generated with pastecs package [17]. In order to find out variability of incidence and severity according to tested genotypes, data were subjected to Poisson regression analysis using glm (generalized linear model) function of package stats implemented in the R. Spearman’s rank correlation test was performed to highlight relationship between incidence, severity, and aflatoxin concentration levels using correlation test function of package stats. Identification of different groups of genotypes based on incidence and severity was performed based on a principal component analysis and a hierarchical clustering with the functions PCA and HCPC of package FactoMineR [18], respectively. The Euclidean distance and Ward classification method were used to classify tested genotypes. The function fviz_pca_biplot [19] was used to plot the principal components analysis biplot in different clusters based on hierarchical classification.

3. Results

3.1. Reaction of Peanut Genotypes to Aspergillus flavus

Analysis of variance revealed highly significant () variation of aflatoxin incidence and severity among the tested peanut genotypes (Table 2).

Table 2: Deviance values from the Poisson regression model on incidence and severity.

Source of variation
Degree of freedom
Incidence
Severity

Replication
4
33.9 (ns)
2.04 (ns)

Genotype
66
7242.2
190.08

Significant chi-squared test at 0.001 level of probability; ns = not significant.

The severity ranged between 0 and 44%, respectively, with a mean of 8.82 ± 0.45%. The recorded incidence ranged from 0 to 70% with an average value of 20.36 ± 0.80% (Table 3).

Table 3: Means of incidence and severity of the tested lines.

Lines
Incidence
Severity

Mean
Std deviation
Mean
Std deviation

12CS_001
44
13.42
1.02
0.44

12CS_004
30
12.25
0.74
0.23

12CS_006
30
15.81
0.46
0.29

12CS_007
18
8.37
0.34
0.21

12CS_008
12
16.43
0.22
0.27

12CS_009
24
8.94
0.58
0.33

12CS_010
18
8.37
0.4
0.27

12CS_011
18
14.83
0.42
0.48

12CS_012
32
13.04
0.82
0.43

12CS_016
34
8.94
0.82
0.54

12CS_018
38
13.04
0.66
0.33

12CS_020
22
10.95
0.5
0.34

12CS_021
52
10.95
1.64
0.49

12CS_022
16
15.17
0.36
0.43

12CS_023
18
13.04
0.28
0.24

12CS_024
28
10.95
0.5
0.21

12CS_027
18
8.37
0.26
0.19

12CS_028
18
8.37
0.3
0.20

12CS_031
16
5.48
0.4
0.28

12CS_032
14
11.40
0.16
0.11

12CS_033
10
12.25
0.2
0.23

12CS_034
14
15.17
0.28
0.34

12CS_036
14
5.48
0.26
0.15

12CS_037
16
5.48
0.32
0.19

12CS_039
14
8.94
0.22
0.23

12CS_041
24
15.17
0.64
0.38

12CS_042
24
18.17
0.42
0.42

12CS_047
18
13.04
0.4
0.22

12CS_048
6
8.94
0.08
0.13

12CS_050
34
11.40
0.76
0.29

12CS_051
34
20.74
0.72
0.36

12CS_052
30
15.81
0.76
0.67

12CS_053
36
15.17
0.98
0.59

12CS_054
26
11.40
0.68
0.44

12CS_055
18
8.37
0.48
0.54

12CS_059
24
16.73
0.48
0.48

12CS_060
12
13.04
0.4
0.39

12CS_061
14
11.40
0.24
0.19

12CS_062
18
8.37
0.26
0.15

12CS_063
18
14.83
0.42
0.53

12CS_066
32
22.80
0.8
0.76

12CS_070
22
19.24
0.56
0.53

12CS_072
14
13.42
0.26
0.28

12CS_075
28
13.04
0.66
0.36

12CS_076
12
4.47
0.18
0.08

12CS_078
10
12.25
0.16
0.18

12CS_079
18
16.43
0.34
0.34

12CS_084
14
5.48
0.3
0.21

12CS_085
22
8.37
0.5
0.32

12CS_090
14
13.42
0.34
0.50

12CS_091
26
11.40
0.64
0.48

12CS_095
12
8.37
0.26
0.27

12CS_096
16
8.94
0.48
0.58

12CS_100
40
12.25
0.96
0.34

12CS_104
6
8.94
0.14
0.26

12CS_111
6
8.94
0.1
0.14

12CS_112
18
16.43
0.26
0.32

12CS_118
20
10.00
0.3
0.20

12CS_119
20
7.07
0.42
0.28

55-33
4
5.48
0.04
0.05

55-437
12
10.95
0.18
0.19

73-30
6
5.48
0.06
0.05

73-33
16
11.40
0.28
0.19

78-936
12
4.47
0.24
0.31

Fleur_11
28
16.43
0.5
0.17

GC-8-35
22
10.95
0.6
0.24

L27
10
0.00
0.16
0.13

Mean
20.36
8.82

Standard error
0.80
0.45

One genotype (12CS_104) showed aflatoxin concentration level less than 4 ppb. A total of 34 genotypes presented aflatoxin concentration level up to 2000 ppb (Figure 1).

Figure 1: Number of peanut genotypes according to aflatoxin concentration level interval values.

Out of the 67 genotypes, eight showed incidence less than 10% while 33 showed incidences between 10 and 20% and 16 with incidences ranged from 20 to 30% (Figure 2).

Figure 2: Number of peanut genotypes showing aflatoxin presence according to incidence intervals.

3.2. Correlation between Incidence, Severity, and Aflatoxin Concentration Level

Spearman’s rank correlation test revealed a strong relationship (, ) between incidence and severity of peanut genotypes. Positive and significant correlations were detected between aflatoxin concentration levels and disease incidence (, ) and aflatoxin concentration levels and disease severity (, ) (Table 4).

Table 4: Spearman’s rank matrix correlation performed on incidence, severity, and aflatoxin concentration levels data.

Incidence
Severity
Aflatoxin concentration levels

Incidence
1.00

Severity
0.93
1.00

Aflatoxin concentration levels
0.28
0.35
1.00

Significant Spearman’s rank correlation test at 0.05 level of probability. Significant Spearman’s rank correlation test at 0.01 level of probability. Significant Spearman’s rank correlation test at 0.001 level of probability.

3.3. Classification of the Tested Genotypes according to Sensibility and Aflatoxin Concentration Level

The factorial axes 1 and 2 explained 60.5 and 39.5% of overall variability, respectively (Figure 3). Hierarchical classification performed on principal component analysis revealed three clusters of genotypes based on disease incidence and aflatoxin concentration levels (Figure 3). The clusters 1, 2, and 3 grouped 33, 20, and 14 genotypes, respectively. The incidence and aflatoxin concentration are significantly () associated to cluster 1 (Table 4).

Figure 3: Principal component analysis biplot showing peanut genotypes clustering based on their severity and incidence.

Mean values of these two variables in this cluster are less than the overall mean. Therefore, cluster 1 is characterized by desirable genotypes which combine low incidence values and aflatoxin concentration levels. Cluster 2 is significantly () related to the aflatoxin concentration level (Table 5).

Table 5: Description of each cluster based on incidence, aflatoxin concentration levels, and paragon and singular genotype per cluster.

Cluster 1
Cluster 2
Cluster 3

Mean
Overall mean
value†
Mean
Overall mean
value
Mean
Overall mean
value

Description of clusters by variables

Incidence
15.09
20.35
<10⁻³
18.8
20.35
>0.05
35.00
20.35
<10⁻³

Aflatoxin
915.65
2143.89
<10⁻³
4075.50
2143.89
<10⁻³
2279.57
2143.89
>0.05

Description of clusters by distances

Top 3 representative genotypes††
12CS_039 (0.11)
12CS_090 (0.16)
73-33 (0.29)
12CS_010 (0.12)
12CS_079 (0.22)
12CS_027 (0.24)
12CS_050 (0.15)
12CS_066 (0.41)
12CS_016 (0.42)

Top 3 characteristic genotypes†††
12CS_104 (2.82)
55-33 (2.75)
12CS_111 (2.74)
78-936 (3.68)
12CS_028 (2.39)
12CS_031 (2.28)
12CS_021 (3.45)
12CS_001 (3.00)
12CS_100 (2.59)

†Correlation signification of variables with a cluster. †† Based on the closest distance between each genotype and the respective cluster centres. ††† Based on the farthest distance from a genotype projected point in a cluster to the centres of the two others.

The mean value of aflatoxin concentration in cluster 2 (4075.5 ppb) is 190% which is higher than the overall mean (2143.8 ppb). Thus, this second cluster is characterized by genotypes with high level of aflatoxin. Incidence is linked to cluster 3 (Table 5). Mean value of this variable (35%) in cluster 3 is superior to overall mean (20.35%). Thus, the cluster 3 encompasses the most susceptible genotypes to A. flavus.

Based on the closest distance between each genotype and the respective cluster centres, 12CS_039, 12CS_010, and 12CS_050 were the first representative genotypes (paragon) of cluster 1, 2, and 3, respectively (Table 4). Based on the farthest distance from a genotype projected point in a cluster to the centres of the two others, clustering revealed that cluster 1, 2, and 3 were characterised by the genotypes 12CS_104, 78-936, and 12CS_021, respectively (Figure 3, Table 5). Based on results, out of 67 genotypes, 33 promising genotypes (cluster 1) were noted (Figure 3).

4. Discussion

In the present study, a wide phenotypic variation was observed among the tested genotypes for incidence, severity, and aflatoxin concentrations. This variation can be explained by the variability of seed coat structure of the tested genotypes. In fact, the seed coat can constitute a barrier to A. flavus seed invasion depending on its thickness and/or permeability [20], and Zhou and Liang [21] studies showed that genotypes seed coat with smaller hilum, more compact arrangement and thicker testa showed more resistance to A. flavus. In addition, implication of wax and cutin layers of seed coat was demonstrated to be related to genotypes resistance [22]. Another explanation of this wide variation in incidence, severity, and aflatoxin rate can be biochemical compounds’ differential variability in the tested seeds. Lindsey and Turner [23] demonstrated that the presence of polyphenol compounds, specifically, tannins in seed can have inhibitor effect against A. flavus. Amaya et al. [24] and Liang et al. [25] showed the difference among seed coat biochemical compounds to determine sensibility to A. flavus. Liang [22] demonstrated that the presence of trypsin in seeds can also be related to resistance to A. flavus. Turner et al. [26] isolated and identified the 5,7-dimethoxyisoflavone as an inhibitor for A. flavus invasion in peanut seed.

12CS_104 was the most resistant genotype to aflatoxin contamination with an aflatoxin level lower than the European Union standards (4 ppb). However, except 12CS_104, all the genotypes have their aflatoxin concentration level higher than the Chinese (20 ppb) standards. Indeed, the highest aflatoxin concentration level was observed with genotype 78-936. The contrasting genotypes observed in this study can be used as positive and negative checks, respectively, for accurate field experiment. Furthermore, these contrasted genotypes can be used to develop mapping population for genetic study such as inheritance of aflatoxin and identification of quantitative trait loci (QTL). The varieties 55-437 and 73-30 showed incidence less than 15% as reported by the previous study realized 30 years ago by Zambettakis et al. [13], but their aflatoxin concentration levels were largely up to the European Union standards.

The correlation test showed a positive relationship between A. flavus colonization and aflatoxin contamination. This confirmed that the presence of A. flavus induced aflatoxin production in seeds. Hierarchical classification highlighted three clusters according to incidence, severity, and aflatoxin concentration levels. The relatively low values of incidence observed on the 33 genotypes belonged to cluster 1 should be confirmed under field conditions. These genotypes can be evaluated in different locations on infested fields.

5. Conclusion

This study uncovered that the lines 12CS_104 exhibited low values of incidence and severity. Furthermore, its aflatoxin concentration level was smaller than standards. This genotype represents a relevant tool for the breeding program for resistance to A. flavus as a potentially resistant gene donor.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

Acknowledgments

The authors sincerely thank the West Africa Agricultural Productivity Program (WAAPP) for financial support and facilities help.

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