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Plant Growth Regulators Affects Texture: study in a Muscat of
Alexandria x Crimson Seedless experimental progeny
Authors: Vicente Salas-Tupper, Javier Gutierrez, Reynaldo Núñez, Nicolás Jiménez, Nallatt Ocarez, Nilo Mejía and Alonso Pérez-Donoso*
Questions
Do plant growth regulators affect firmness?
If they do, how?
Materials and methods
• 640 segregants of Muscat of Alejandria x Crimson Seedless
• Prebloom cytokinin (5ppm) + fruit set gibberellic acid (10ppm)
• 3 seasons:
- 2016-2017
- 2017-2018
- 2018-2019
• Texture measurements with Universal Testing Machine (UTM)
• Double compression test (Texture Profile Analisis)
• Puncture test (2017-2018)
Images extracted from:“Instrumental texture analysis parameters as markers of table-grape and winegrape quality: A review” Rolle et al., 2012
Results2017 2018 2019
Treatment 0.385±0.0035 0.366±0.0034 0.385±0.0036
Control 0.385±0.0033 0.372±0.0033 0.393±0.0037
Significance ns ** **
Treatment 0.702±0.0059 0.841±0.0076 0.878±0.0080
Control 0.708±0.0057 0.848±0.0074 0.890±0.0078
Significance ns ns *
Treatment 0.245±0.0017 0.238±0.0018 0.253±0.0018
Control 0.248±0.0017 0.245±0.0017 0.258±0.0020
Significance * *** **
Treatment 0.040±0.0002 0.038±0.0002 0.039±0.0002
Control 0.041±0.0002 0.039±0.0002 0.039±0.0002
Significance ** *** ns
Treatment 0.021±0.0001 0.022±0.0001 0.022±0.0001
Control 0.021±0.0001 0.022±0.0001 0.022±0.0001
Significance * ns ns
Treatment 0.174±0.0004 0.194±0.0001 0.193±0.0001
Control 0.176±0.0004 0.194±0.0001 0.193±0.0001
Significance *** *** ns
Treatment n/a 0.531±0.0066 n/a
Control n/a 0.543±0.0077 n/a
Significance n/a ns n/a
Treatment n/a 0.037±0.0003 n/a
Control n/a 0.038±0.0003 n/a
Significance n/a * n/a
Table 1. (***) corresponds to p-value<0.0001 , (**) p-value <0.001 between ≥0.0001 , (*) p-value <0.05 between
≥0.001 , p- value above p≥0.05 where considerate non-significative (ns). 2017 sample corresponds to treatment
N=528 control N=533. 2018 sample corresponds to treatment N=517 control N=537. 2019 sample corresponds to
treatment N=496 control N=507. Values represent the RELM proposed mean, and next to them, the standard error.
Cohesiveness/Height (1/mm)
Resiliense/Height (1/mm)
Springiness/Height (mm/mm)
Skin Hardness (N)
Flesh Firmness (N)
Table 1: Texture parameters.
Chewiness/Height (mJ/mm)
Gumminess/Height (N/mm)
Hardness/Height (N/mm)
Results2017 2018 2019
Treatment 0.385±0.0035 0.366±0.0034 0.385±0.0036
Control 0.385±0.0033 0.372±0.0033 0.393±0.0037
Significance ns ** **
Treatment 0.702±0.0059 0.841±0.0076 0.878±0.0080
Control 0.708±0.0057 0.848±0.0074 0.890±0.0078
Significance ns ns *
Treatment 0.245±0.0017 0.238±0.0018 0.253±0.0018
Control 0.248±0.0017 0.245±0.0017 0.258±0.0020
Significance * *** **
Treatment 0.040±0.0002 0.038±0.0002 0.039±0.0002
Control 0.041±0.0002 0.039±0.0002 0.039±0.0002
Significance ** *** ns
Treatment 0.021±0.0001 0.022±0.0001 0.022±0.0001
Control 0.021±0.0001 0.022±0.0001 0.022±0.0001
Significance * ns ns
Treatment 0.174±0.0004 0.194±0.0001 0.193±0.0001
Control 0.176±0.0004 0.194±0.0001 0.193±0.0001
Significance *** *** ns
Treatment n/a 0.531±0.0066 n/a
Control n/a 0.543±0.0077 n/a
Significance n/a ns n/a
Treatment n/a 0.037±0.0003 n/a
Control n/a 0.038±0.0003 n/a
Significance n/a * n/a
Table 1. (***) corresponds to p-value<0.0001 , (**) p-value <0.001 between ≥0.0001 , (*) p-value <0.05 between
≥0.001 , p- value above p≥0.05 where considerate non-significative (ns). 2017 sample corresponds to treatment
N=528 control N=533. 2018 sample corresponds to treatment N=517 control N=537. 2019 sample corresponds to
treatment N=496 control N=507. Values represent the RELM proposed mean, and next to them, the standard error.
Cohesiveness/Height (1/mm)
Resiliense/Height (1/mm)
Springiness/Height (mm/mm)
Skin Hardness (N)
Flesh Firmness (N)
Table 1: Texture parameters.
Chewiness/Height (mJ/mm)
Gumminess/Height (N/mm)
Hardness/Height (N/mm)
Results2017 2018 2019
Treatment 0.385±0.0035 0.366±0.0034 0.385±0.0036
Control 0.385±0.0033 0.372±0.0033 0.393±0.0037
Significance ns ** **
Treatment 0.702±0.0059 0.841±0.0076 0.878±0.0080
Control 0.708±0.0057 0.848±0.0074 0.890±0.0078
Significance ns ns *
Treatment 0.245±0.0017 0.238±0.0018 0.253±0.0018
Control 0.248±0.0017 0.245±0.0017 0.258±0.0020
Significance * *** **
Treatment 0.040±0.0002 0.038±0.0002 0.039±0.0002
Control 0.041±0.0002 0.039±0.0002 0.039±0.0002
Significance ** *** ns
Treatment 0.021±0.0001 0.022±0.0001 0.022±0.0001
Control 0.021±0.0001 0.022±0.0001 0.022±0.0001
Significance * ns ns
Treatment 0.174±0.0004 0.194±0.0001 0.193±0.0001
Control 0.176±0.0004 0.194±0.0001 0.193±0.0001
Significance *** *** ns
Treatment n/a 0.531±0.0066 n/a
Control n/a 0.543±0.0077 n/a
Significance n/a ns n/a
Treatment n/a 0.037±0.0003 n/a
Control n/a 0.038±0.0003 n/a
Significance n/a * n/a
Table 1. (***) corresponds to p-value<0.0001 , (**) p-value <0.001 between ≥0.0001 , (*) p-value <0.05 between
≥0.001 , p- value above p≥0.05 where considerate non-significative (ns). 2017 sample corresponds to treatment
N=528 control N=533. 2018 sample corresponds to treatment N=517 control N=537. 2019 sample corresponds to
treatment N=496 control N=507. Values represent the RELM proposed mean, and next to them, the standard error.
Cohesiveness/Height (1/mm)
Resiliense/Height (1/mm)
Springiness/Height (mm/mm)
Skin Hardness (N)
Flesh Firmness (N)
Table 1: Texture parameters.
Chewiness/Height (mJ/mm)
Gumminess/Height (N/mm)
Hardness/Height (N/mm)
Materials and methods
• 640 segregants of Moscatel de Alejandría X Crimson Seedless
• 8 sensory analisys sessions (one for each texture parameter)
• Sensory panel composed by 12 non trained judges
• 5 samples x 5 repetitions
Results
Texture Parameters Sensory/Instrumental Firmness
Hardness 0.828
Chewiness 0.747
Gumminess 0.870
Cohesiveness -0.080
Resilience -0.266
Springiness 0.168
Skin Hardness 0.805
Flesh Firmness 0.642
Table 2: Sensorial, instrumental correlation
Table 2. UTM values and sensory values corresponds to
2018 season.
Results
y = 13,018x - 0,823R² = 0,6831
0
1
2
3
4
5
6
7
8
0 0,1 0,2 0,3 0,4 0,5 0,6 0,7
Sensory Firmness vs. Hardness/mm
y = 6,7957x - 1,1105R² = 0,6309
0
1
2
3
4
5
6
7
8
9
10
0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6
Sensory Firmness vs. Chewiness/mm
y = 31,673x - 3,6487R² = 0,754
0
1
2
3
4
5
6
7
8
9
0 0,05 0,1 0,15 0,2 0,25 0,3 0,35 0,4
Sensory Firmness vs. Gumminess/mm
y = 93,023x + 0,4802R² = 0,4127
0
1
2
3
4
5
6
7
8
9
0 0,01 0,02 0,03 0,04 0,05 0,06 0,07 0,08
Sensory Firmness vs Flesh Firmness
y = 5,43x + 0,222R² = 0,6474
0
1
2
3
4
5
6
7
8
0 0,2 0,4 0,6 0,8 1 1,2 1,4
Sensory Firmness vs. Skin Hardness
Results
y = 13,018x - 0,823R² = 0,6831
0
1
2
3
4
5
6
7
8
0 0,1 0,2 0,3 0,4 0,5 0,6 0,7
Sensory Firmness vs. Hardness/mm
y = 6,7957x - 1,1105R² = 0,6309
0
1
2
3
4
5
6
7
8
9
10
0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6
Sensory Firmness vs. Chewiness/mm
y = 31,673x - 3,6487R² = 0,754
0
1
2
3
4
5
6
7
8
9
0 0,05 0,1 0,15 0,2 0,25 0,3 0,35 0,4
Sensory Firmness vs. Gumminess/mm
y = 93,023x + 0,4802R² = 0,4127
0
1
2
3
4
5
6
7
8
9
0 0,01 0,02 0,03 0,04 0,05 0,06 0,07 0,08
Sensory Firmness vs Flesh Firmness
y = 5,43x + 0,222R² = 0,6474
0
1
2
3
4
5
6
7
8
0 0,2 0,4 0,6 0,8 1 1,2 1,4
Sensory Firmness vs. Skin Hardness
Conclusions
• Among all the textural parameters, only gumminess showed a significant and stable decrease due to PGR treatments, other parameters have a varied response, reflecting the season effect.
• Results reveal a strong correlation between sensorial firmness and instrumental gumminess (0.87), hardness (0.83), chewiness (0.75) and skin hardness (0.8).
• Gumminess seems to be an interesting candidate for assessing firmness in grapes at industry and scientific level.
Acknowledgments
• This work was funded by FONDECYT program Nº 1170586
• Agencia Nacional de Investigación y Desarrollo (ANID) / Scholarship Program / DOCTORADO BECAS CHILE/2019 - 21190118
• We thank the economic support of “Dirección de Investigación y Posgrado de la Facultad de Agronomía e Ingeniería Forestal de la Pontificia Universidad Católica de Chile”
Plant Growth Regulators Affects Texture: study in a Muscat of
Alexandria x Crimson Seedless experimental progeny
Authors: Vicente Salas-Tupper, Javier Gutierrez, Reynaldo Núñez, Nicolás Jiménez, Nallatt Ocarez, Nilo Mejía and Alonso Pérez-Donoso*
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