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Figure 5 in Short-time salinity fluctuations are strong activators of oxidative stress in Mediterranean mussel (Mytilus galloprovincialis)
Figure 5. Activity of the antioxidant enzymes in gills of mussels following exposure to short-time salinity fluctuations. Activity of SOD (a), Activity of CAT (b). Mussels were acclimated to high (24-40‰, HS) and low (6-14 ‰, LS) environmental salinity. The control group was held at 18‰. Each bar represents the mean value from 10 samples with the standard error. Results were considered significant when p<0.05 by Mann-Whitney test (n=10). (p <0.05).
Figure 2 in Short-time salinity fluctuations are strong activators of oxidative stress in Mediterranean mussel (Mytilus galloprovincialis)
Figure 2. Mortality of mussels exposed to short-time salinity fluctuations. The diagram shows the percentage of dead mussels acclimated to high (24-40 ‰, HS) and low (6-14‰, LS) environmental salinity. The control group was held at 18 ‰. Bars indicate mean±SE (n=10).
Fig. 2 in Oxidative stress biomarkers in the African sharptooth catfish, Clarias gariepinus, associated with infections by adult digeneans and water quality
Fig. 2. Monthly variation of physico-chemical parameters during the fish collection period, October 2016–September 2017. A– pH; B– Electrical conductivity; C– Temperature; D– Dissolved oxygen; E– Salinity; F– Turbidity; G– Total dissolved solids.
Fig. 1 in Oxidative stress biomarkers in the African sharptooth catfish, Clarias gariepinus, associated with infections by adult digeneans and water quality
Fig. 1. Various maps of the Incomati River showing the position of the sampling site. A– Mozambique shaded on the African continent; B– shows position of Maputo Province in Mozambique; C– indicates the position of the Incomati River and the sampling site.
Fig. 5 in Oxidative stress biomarkers in the African sharptooth catfish, Clarias gariepinus, associated with infections by adult digeneans and water quality
Fig. 5. Principal Component Analysis (PCA) of physico-chemical variables, biomarkers and parasitism in Clarias gariepinus collected in the Incomati River in Mozambique. Two principal components (PC1 and PC2) explained 45.45% of the total variation between water variables, biomarkers and occurrence of parasites. The EC, TDS and salinity (SAL) are associated with Component 1 while LPX, CAT, SOD, turbidity (TB) and temperature (T) are negatively associated with these variables. CI = co-infection; IM = M. nkomatiensis intensity; IG = G. pedatum intensity, UN = uninfected.
Fig. 4 in Effect of light stress on Crotalaria spectabilis (Fabaceae) and on its herbivore insect, the moth Utetheisa ornatrix (Erebidae: Arctiinae)
Fig. 4. Weight of the pupae of Utetheisa ornatrix (L., 1758) whose larvae were raised with leaves of Crotalaria spectabilis Roth from light stressed plants and non-stressed plants. (A) male pupae; N = 30 for stressed plants and N = 18 for non-stressed plants. (B) female pupae; N = 19 for stressed plants and N = 28 for non-stressed plants. Different letters indicate statistical difference (t = -2.7531; p = 0.009).
Fig. 5 in Effect of light stress on Crotalaria spectabilis (Fabaceae) and on its herbivore insect, the moth Utetheisa ornatrix (Erebidae: Arctiinae)
Fig. 5. FecunditY of Utetheisa ornatrix (L., 1758) females whose larvae were reared on stressed and non-stressed leaves of Crotalaria spectabilis Roth. N = 18 for stressed plants and N = 15 for non-stressed plants.
Fig. 3 in Effect of light stress on Crotalaria spectabilis (Fabaceae) and on its herbivore insect, the moth Utetheisa ornatrix (Erebidae: Arctiinae)
Fig. 3. Development time of the larvae of Utetheisa ornatrix (L., 1758) reared with leaves of Crotalaria spectabilis Roth from light stressed plants and non-stressed plants. N = 49 for stressed plants and N = 46 for non-stressed plants. Different letters indicate statistical difference (t=2.27; p=0.02).
Fig. 1 in Effect of light stress on Crotalaria spectabilis (Fabaceae) and on its herbivore insect, the moth Utetheisa ornatrix (Erebidae: Arctiinae)
Fig. 1. Distribution of stressed plants (with mesh cover) and non-stressed plants of Crotalaria spectabilis Roth in the greenhouse.
FIGURE 3. 3.1 von Mises stresses, 3.2 von Mises strains, 3.3 Displacements, 3.4 von Mises stress relationship with reference value, 3.5 von Mises strain relationship with reference value and 3.6 in Insights into the controversy over materials data for the comparison of biomechanical performance in vertebrate
FIGURE 3. 3.1 von Mises stresses, 3.2 von Mises strains, 3.3 Displacements, 3.4 von Mises stress relationship with reference value, 3.5 von Mises strain relationship with reference value and 3.6 Displacement relationship with reference value in front of variation in the elastic modulus (E) in points P and Q.
FIGURE 5. 5.1 von Mises stresses, 5.2 von Mises strains, 5.3 Displacements, 5.4 von Mises stress relationship with reference value, 5.5 von Mises strain relationship with reference value and 5.6 in Insights into the controversy over materials data for the comparison of biomechanical performance in vertebrate
FIGURE 5. 5.1 von Mises stresses, 5.2 von Mises strains, 5.3 Displacements, 5.4 von Mises stress relationship with reference value, 5.5 von Mises strain relationship with reference value and 5.6 Displacement relationship with reference value in front of variation in the elastic modulus (E) in points P and Q.
Figure 4 in The role of silicon in the mitigation of water stress in Eugenia myrcianthes Nied. seedlings
Figure 4. Hierarchical groups based on the Euclidean distance of the characteristics evaluated in Eugenia myrcianthes Nied. seedlings grown under water fluctuations (deficit – 1st P0 and flooding – 2nd P0) and silicon doses (0, 2, and 4 mmol). I: continuous irrigation; S: stress; P0: photosynthesis close to zero; R: recovery.
Figure 3 in The role of silicon in the mitigation of water stress in Eugenia myrcianthes Nied. seedlings
Figure 3. Pearson's linear correlation (r) of the characteristics evaluated in Eugenia myrcianthes Nied. seedlings grown under water regimes (continuous irrigation, deficit – 1st P0, and flooding – 2nd P0) and silicon doses (0, 2, and 4 mmol).
Figure 2 in The role of silicon in the mitigation of water stress in Eugenia myrcianthes Nied. seedlings
Figure 2. Principal component analysis (PCA) of the characteristics evaluated in Eugenia myrcianthes Nied. seedlings grown under water regimes (continuous irrigation, deficit – 1st P0, and flooding – 2nd P0) and silicon doses (0, 2, and 4 mmol). I: continuous irrigation; S: stress; P0: photosynthesis close to zero; R: recovery.
Figure 1 in The role of silicon in the mitigation of water stress in Eugenia myrcianthes Nied. seedlings
Figure 1. Photosynthetic rate (A) of Eugenia myrcianthes Nied. seedlings grown under water regimes (continuous irrigation, deficit – 1st P0, and flooding – 2nd P0), with silicon doses (0, 2, and 4 mmol). I: continuous irrigation; S: stress; P0: photosynthesis close to zero; R: recovery.
Figure 7 in Effects of nanoparticles treatments and salinity stress on the genetic structure and physiological characteristics of Lavandula angustifolia Mill.
Figure 7. UPGMA tree of the evaluated samples based on the molecular ISSR data (treatment's code as in Table 1).
Figure 6 in Effects of nanoparticles treatments and salinity stress on the genetic structure and physiological characteristics of Lavandula angustifolia Mill.
Figure 6. Results of the AMOVA test revealed a significant genetic diversity between the treated samples
Figure 5 in Effects of nanoparticles treatments and salinity stress on the genetic structure and physiological characteristics of Lavandula angustifolia Mill.
Figure 5. UPGMA tree of the studied samples according to essential oil compositions (treatment's code as in Table 1).
Figure 3 in Effects of nanoparticles treatments and salinity stress on the genetic structure and physiological characteristics of Lavandula angustifolia Mill.
Figure 3. Effects of Fe O and ZnO nanoparticles on concentration of the leaves Fe2+ amounts. Whiskers indicate the standard deviation, 2 3 and dissimilar letters showed the significant variation based on Duncan test (P≤ 0.05).
Figure 4 in Effects of nanoparticles treatments and salinity stress on the genetic structure and physiological characteristics of Lavandula angustifolia Mill.
Figure 4. Effects of ZnO and Fe O nanoparticles on intracellular Zn 2+ concentration. Whiskers reveal the standard deviation, and 2 3 dissimilar letters showed the significant variation according to Duncan test (P≤ 0.05).
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