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)
This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.
Orejuela-Romero et al. Rev. Fac. Agron. (LUZ). 2023 40(2): e234012
5-6 |
Generating the best utilization of water content by plants exposed
to water stress under the R-70 treatment. Although the values fall in
the fourth sampling (R-70), they return to be the highest at the end of
the experiment. WUE for C-100 from the second data collection is
reported below the two decit irrigation treatments, which may have
been inuenced by external factors such as the location of the plants
in the growth chamber. Both WUE and biomass of the R-70 treatment
were the highest recorded, which relates to the research of Killi et
al. (2017), where he points out that WUE is associated with biomass
production in sunowers and can be seen to inuence it directly.
Once the experiment was concluded, the dry mass in grams
of stems and leaves of the three treatments was obtained. In the
statistical analysis, there were no signicant dierences (p=0.971)
in the root biomass of the dierent irrigations applied. It is possible
that the number of individuals per treatment may have caused non-
determinant results. The above is presented in gure 4.
0
2
4
6
8
10
12
14
16
18
1 2 3 4 5 6
DRY MASS IN GRAMS
MEASUREMENT PERIOD PER DAY
C-100 R-70 R-50
Figure 4. Dry mass in grams of stems and leaves of the three
treatments. C-100: full irrigation (100%), R-70: 70 %
Irrigation was carried out every three days. The sampling
days were in February 1:06, 2:12, 3:14, 4:18 and 5:27.
Of the values obtained in the treatments, C-100 presented higher
root dry mass values than R-70 but lower than R-50. According to
Killi et al. (2017), sunowers under water stress present an increased
investment in root systems, propitiating a greater use of available soil
water. What could have generated the increase of the root system in
R-50 due to the high decit irrigation to which it had been subjected.
A more extensive root network can cause plants to make better use of
the available water. The above is presented in gure 5.
Therefore, periods of drought will have a negative impact on the
growth of sunower crops, being that García-Tejero et al. (2017),
reported relationships between thermal indicators and physiological
parameters in plants. What would be correlated in our experiment
by manifesting elevated temperatures in sunower plants and
physiological parameters reported in plants. While R-70 had the
highest values in stem biomass, followed by C-100 and nally R-50.
Dierences in stem biomass were not signicant (p=0.745) for the
three treatments.
Conclusions
The temperatures obtained by thermography; no signicant
dierences (p=0.054) were found between the dierent treatments by
means of the analysis of variance. However, there was a tendency to
increase the temperature from the rst measurement in the treatments
subjected to decit irrigation. The R-70 treatment, despite not being
the most restrictive irrigation, leads to a greater increase in leaf
temperature on all days sampled. This could indicate the tendency of
sunowers to regulate water loss by closing the stomata for a decit
irrigation of 70 % and resist water stress.
Generating the best use of water content by plants exposed to
water stress under the R-70 treatment, sunowers under water stress
show an increased investment in root systems, leading to a greater
use of available soil water. This may have led to an increase in the
root system in R-50 due to the high decit irrigation to which it had
been subjected. A more extensive root network may cause the plants
to make better use of the available water.
Having an eect that R-70 had the highest values in stem biomass,
followed by C-100 and nally R-50. The dierences in stem biomass
were not signicant (p=0.745) for the three treatments.
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s13007-021-00721-w
10
30
50
70
90
1 2 3 4 5 6
DRY HIGHER ROOT DRY MASS
VALUES MASS IN GRAMS
MEASUREMENT PERIOD PER DAY
C-100 R-70 R-50
Figure 5. The treatments, C-100 presented higher root dry mass
values than R-70 but lower than R-50. C-100: full
irrigation (100%), R-70: 70 % Irrigation was carried out
every three days. The sampling days were in February
1:06, 2:12, 3:14, 4:18 and 5:27.