: Ben Sadok et al. 2015
Supplementary Data
Table. S1 Paired sample t-test for texture trait mean values over storage periods in 2011 : decreasing values at S2 are indicated in bold whereas increasing values are underlined.
1

(b)
Table. S2 PCA analysis for Instrumental traits: (a) Eigenvalues and Percentage of Explained Inertia by the first three components (b) Correlations among variables and PCs: significant values are indicated in bold and changes over storage are underlined.
Year PC Eigen value %Variance % Cumulative Variance
(a)
PC 1
S0 S2 S0 S2
7.23 7.23 60.22 60.32
2007 PC 2 2.57 2.86 21.48 23.86
PC 3 1.39 1.15 11.55 9.59
PC 1 6.16 6.63 51.33 55.32
S0
60.22
81.70
93.26
51.33
S2
60.32
84.19
93.79
55.32
2011 PC 2 3.42 3.70 28.51 30.85 79.85 86.17
PC 3
Variables
Penetromety
1.81 1.01 15.13 8.43
PC1
S0
PC2 PC3
94.99
PC1
S2
PC2
94.61
PC3
Fs_07 0.67 0.73 0.06 0.40 0.89 -0 .
05
Dp_07
Stiff_07
Ws_07
0.15
0.59
0.62
0.17
0.69
0.66
0.96
-0.38
0.41
-0.32
0 .
83
0.15
0.83
0.26
0 .
96
0 .
38
-0.43
0.15
FF_07
Compression
H1_07
0.59
0 .
94
0.72
-0.32
-0.29
-0.03
0
0 .
.
54
98
0 .
49
-0.14
-0 .
57
0.14
H2_07 0 .
95 -0.30 0.01 0 .
98 -0.11 0.15
Grad1_07
Grad2_07
WH1_07
0
0
0 .
.
.
91
75
89
-0.14
-0.29
-0.36
-0.15
-0.14
0.07
0
0
0 .
.
.
91
82
93
-0.05
-0.29
-0.14
-0.24
-0.24
0.31
WH2_07
Cohesiv_07
0
0 .
.
93
92
-0.24
-0.31
0.10
0.08
0
0 .
.
91
93
0.02
-0.07
0.34
0.33
Penetromety
Fs_11
Dp_11
Stiff_11
Ws_11
FF_11
Compression
0.35
-0.19
0 .
68
0.14
0.40
0
0 .
.
93
85
0.37
0
0 .
.
96
67
0.07
-0.44 -0.22
0,57
-0.14
0 .
51
0,21
0 .
63
0.03
0.23
0
0 .
.
96
86
0.59
0
0 .
.
96
77
0.09
0.36
-0.40
0.23
-0 .
52
H1_11
H2_11
Grad1_11
Grad2_11
WH1_11
WH2_11
Cohesiv_11
0
0
0
0
0
0
0 .
.
.
.
.
.
.
97
98
85
56
88
91
91
-0.20
-0.13
-0.01
-0.48
-0.19
0.04
-0.09
-0.15
-0.15
0.45
0.54
-0,42
-0.37
-0.41
0
0
0
0
0
0
0 .
.
.
.
.
.
.
99
99
92
79
95
93
95
-0.12
-0.10
0.05
-0.36
-0.15
0.07
-0.05
0.06
0.07
-0.29
-0.26
0.27
0.28
0.28
2

(b)
Table. S3 PCA analysis for sensory traits: (a) Eigenvalues and Percentage of Explained Inertia by the first three components (b) Correlations among variables and PCs: significant values are indicated in bold.
(a)
Year PC Eigen value %Variance % Cumulative Variance
S0 S2 S0 S2 S0 S2
PC 1 4.42 4.37 63.18 62.53 63.18 62.53
2007 PC 2
PC 3
1.16 1.06 16.65 15.21
0.46 0.55 6.59 7.86
79.83
86.43
77.74
85.60
Variables
Sensory
CRUNCH
FIRM
JUIC
PC1
0
0
0 .
.
.
82
87
68
PC2
0.28
-0.08
0
S0
.
59
PC3
0.30
0.22
0.06
PC1
0
0
0 .
.
.
88
84
71
PC2
0.00
-0.26 -0.09
0
S2
.
58
PC3
0.22
0.01
MELT
GRAIN
FIBER
MEALI
-0.52
-0
0
-0
.
.
.
91
82
86
0 .
73
0.09
-0.37 -0.34
-0.24
-0.32
0.31
0.10
-0.58
-0
0
-0
.
.
.
90
88
70
0 .
69 0.32
-0.05 -0.20
-0.15
-0.41
0.28
0.53
3

Table. S4 Correlations between sensory and instrumental traits on the basis of the mean phenotypic values per genotype: significant correlation values are underlined between groups of texture descriptors and indicated in bold within each group of sensory, penetrometry and compression traits
4

Table. S5 Summary of the QTLs detected for the storage index (SI) of texture traits
5

10
8
6
4
2
0
16
14
12
2007
2011
1 2 3 4 5 6 7 8 9 10 11 12
Months
30
25
20
15
10
5
2007
2011
0
1 2 3 4 5 6 7 8 9 10 11 12
Months
Figure S1. Temperature records during the two studied harvest years 2007 and 2011: (a) minimal temperature (b) Maximal temperature.
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GLOBAL MODEL RESULTS
Instrumental traits
Regarding traits related to flesh and skin firmness (i.e. FF, Fs and Ws), three QTLs were detected on LG5, LG6 and LG12 for FF in 2007 (FF_07; Table 5, Figure 4). A global model was built for these QTLs and showed no significant interaction between cofactors. Together, these QTLs explained 15.9% of the trait variability (Table 5). Two other QTLs were detected for FF at S0 on
LG6 and LG12 (FF_07_S0; Table 5, Figure 4). The global model did not include any interaction between QTLs and explained 13.4% of the variability (Table 5). Similarly, two QTLs were detected on LG6 and LG12 for Fs at S0 and explained together 13.8% of the variability
(Fs_07_S0; Table 5). Two other QTLs were detected for Fs at S2 on LG4 and LG6 (Fs_07_S2;
Table 5). The global model did not include any interaction between QTLs and explained 25.9% of the variability (Table 5). Three QTLs were detected for S2-specific BLUPs of Ws on LG2 ,
LG6 and LG16 (Ws_07_S2; Table 5, Figure 4). Together, these QTLs explained 30.69% of the variability (Table 5).
In 2011, two QTLs were mapped on LG1 and LG15 for FF (FF_11; Table 5, Figure 4). Together, the two QTLs explained 22.9% of the variability (Table 5). Moreover, three QTLs were mapped for Fs at S2 on LG1, LG5 and LG11 (Fs_11_S2; Table 5). The global model did not include any interaction between QTLs and explained 37.5% of the variability (Table 5).
Considering traits describing tissue elasticity (i.e. Dp and Stif), three QTLs were detected on
LG2, LG12 and LG16 for Dp in 2007 (Dp_07; Table 5, Figure 4). A global model built for these
QTLs showed significant interaction between the QTLs on LG2 and LG16 and explained 31.14% of the trait variability (Table 5). Moreover, two QTLs were detected on LG2 and LG16 for Dp at
S2 (Dp_07_S2; Table 5, Figure 4). Together, the two QTLs showed significant interaction effect and explained 35.75% of the variability (Table 5). Regarding the fruit stiffness, co-localizing
QTLs were detected for Stif_07 and Stif_07_S0 on LG6 and LG12 (Figure 4). The global model did not include any interaction between QTLs and explained 11.7% and 13.8% of the variability, respectively (Table 5). In 2011, two QTLs were detected for Dp at S2 on LG5 and LG11
(Dp_07_S2, Figure 4). Together, the two QTLs explained 13.4% of the variability (Table 5).
For traits describing global fruit hardness and elasticity (i.e. H1&2, WH1&2, Cohesiv and
Grad1&2), three QTLs were detected on LG2, LG4 and LG12 for H2 in 2007 (H2_07; Figure 4).
The global model did not include any interaction between QTLs and explained 28.73% of the
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variability (Table 5). Considering the positive compression force area, two QTLs were mapped for WH1 in 2007 on LG1 and LG12 (WH1_07, Figure 4). The global model did not include any interaction between QTLs and explained 16.21% of the variability (Table 5).
In 2011, five QTLs were detected for H1 on LG1 , LG2 , LG3 , LG5 and LG8 (H1_11, Figure 4).
Together, these QTLs explained 39.7% of the variability and showed significant interaction effect
(P<0.05). Moreover, two QTLs were mapped for H1 at S0 on LG5 and LG15 (H1_11_S0, Table
5, Figure 4). The global model did not include any interaction between QTLs and explained
18.9% of the variability (Table 5). Likewise, three QTLs were detected for H2 at S0 on LG5,
LG8 and LG15 (H2_11_S0; Table 5, Figure 4). Together, these QTLs explained 28.52% of the variability (Table 5). Again, three QTLs were mapped for WH1 in 2011 on LG1, LG5 and LG8
(WH1_11; Table 5, Figure 4). The global model did not include any interaction between QTLs and explained 37.68% of the variability (Table 5). Similarly, four QTLs were detected for
WH2_11 on LG1, LG5, LG8 and LG15 (Figure 4). Together, these QTLs explained 40.31% of the variability and showed significant interaction effect (P<0.05), (Table 5). In addition, two
QTLs were detected for the coefficient of elasticity Grad 1 on LG1 and LG8 (Grad1_11; Table 5,
Figure 4). The global model did not include any interaction between QTLs and explained 27.53% of the variability (Table 5). Two other QTLs were mapped for Grad1 at S0 on LG3 and LG5
(Grad1_11_S0; Table 5, Figure 4). Together, these QTLs explained 11.11% of the variability and showed significant interaction effect (P<0.05), (Table 5).
Sensory traits
Two QTLs were detected for fruit meltiness in 2007 on LG5 and LG7 (Melt_07, Figure 4). The global model did not include any interaction between QTLs and explained 9.93% of the variability (Table 5). In 2011, four QTLs were mapped for Meali at S2 on LG2, LG5, LG7 and
LG12. The global model did not include any interaction between QTLs and explained 20.69% of the variability (Table 5). Finally, two QTLs were detected for Melt at S2 on LG6 and LG7
(Melt_11_S2, Figure 4). Together, these QTLs explained 20.69% of the variability (Table 5).
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