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Morphological and physiochemical changes of jojoba under water pollution stress condition

M. S. Aboryia
M. S. Aboryia
, 
Mohamed Saleh M. Ali
Mohamed Saleh M. Ali
, 
Ahmed F. Elshiekh
Ahmed F. Elshiekh
, 
Basmah M. Alharbi
Basmah M. Alharbi
, 
Ibrahim Eid Elesawi
Ibrahim Eid Elesawi
, 
Ahmed M. Fikryi
Ahmed M. Fikryi
, 
Ahmed A. Helaly
Ahmed A. Helaly
, 
Fatma R. Ibrahim
Fatma R. Ibrahim
, 
Eman A. swedan
Eman A. swedan
, 
Hany G. Abd El-Gawad
Hany G. Abd El-Gawad
, 
Samy F. Mahmoud
Samy F. Mahmoud
 and 
El-Sayed A. EL-Boraie
El-Sayed A. EL-Boraie
   | Aug 01, 2024
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Article Category: ORIGINAL ARTICLE
Published Online: Aug 01, 2024
Page range: -
Received: Feb 29, 2024
Accepted: Jun 19, 2024
DOI: https://doi.org/10.2478/fhort-2024-0016
Keywords
© 2024 M. S. Aboryia et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Figure 1.

The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100%, on the NSI% (A), JHI% (B) and JSDI% (C). The results are the average of two subsequent seasons (2022 and 2023), with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. JHI%, jojoba height increase percentage; JSDI, jojoba stem diameter increase percentage; NSI%, number of shoots increase percentage; RADW, raw agricultural drainage water; TSDW, treated sewage drainage water.
The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100%, on the NSI% (A), JHI% (B) and JSDI% (C). The results are the average of two subsequent seasons (2022 and 2023), with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. JHI%, jojoba height increase percentage; JSDI, jojoba stem diameter increase percentage; NSI%, number of shoots increase percentage; RADW, raw agricultural drainage water; TSDW, treated sewage drainage water.

Figure 2.

The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100%, on the NLI% (A), LT (mm) (B), LA (cm2) (C) and VQ (D). The results are the average of two subsequent seasons (2022 and 2023), with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. LA, leaf area; LT, leaf thickness; NLI%, Number of leaves increase percentage; RADW, raw agricultural drainage water; TSDW, treated sewage drainage water; VQ, Visual quality.
The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100%, on the NLI% (A), LT (mm) (B), LA (cm2) (C) and VQ (D). The results are the average of two subsequent seasons (2022 and 2023), with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. LA, leaf area; LT, leaf thickness; NLI%, Number of leaves increase percentage; RADW, raw agricultural drainage water; TSDW, treated sewage drainage water; VQ, Visual quality.

Figure 3.

The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100%, on LFW (g) (A), LDW (g) (B) and SCC (mg · g−1 DW) (C). The results are the average of two subsequent seasons (2022 and 2023), with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. LDW, leaf dry weight; LFW, leaf fresh weight; RADW, raw agricultural drainage water; SCC, soluble carbohydrate content; TSDW, treated sewage drainage water.
The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100%, on LFW (g) (A), LDW (g) (B) and SCC (mg · g−1 DW) (C). The results are the average of two subsequent seasons (2022 and 2023), with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. LDW, leaf dry weight; LFW, leaf fresh weight; RADW, raw agricultural drainage water; SCC, soluble carbohydrate content; TSDW, treated sewage drainage water.

Figure 4.

The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100%, on HM concentrations as Ni ppm (A), Al ppm (B), Cr ppm (C) and Cd ppm (D). The results are the average of two subsequent seasons (2022 and 2023), with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. HM, Heavy metal; RADW, raw agricultural drainage water; TSDW, treated sewage drainage water.
The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100%, on HM concentrations as Ni ppm (A), Al ppm (B), Cr ppm (C) and Cd ppm (D). The results are the average of two subsequent seasons (2022 and 2023), with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. HM, Heavy metal; RADW, raw agricultural drainage water; TSDW, treated sewage drainage water.

Figure 5.

The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100%, on nitrogen content (mg · 100 g−1 DW) (A), phosphorus content (mg · 100 g−1 DW) (B) and potassium content (mg · 100 g−1 DW) (C). The results are the average of two subsequent seasons (2022 and 2023), with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. RADW, raw agricultural drainage water; TSDW, treated sewage drainage water.
The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100%, on nitrogen content (mg · 100 g−1 DW) (A), phosphorus content (mg · 100 g−1 DW) (B) and potassium content (mg · 100 g−1 DW) (C). The results are the average of two subsequent seasons (2022 and 2023), with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. RADW, raw agricultural drainage water; TSDW, treated sewage drainage water.

Figure 6.

The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100% on: chlorophyll a (μg · cm−2) (A), chlorophyll b (μg · cm−2) (B), total chlorophyll (μg · cm−2) (C) and carotenoids (μg · cm−2) (D). The results are the average of two subsequent seasons (2022 and 2023) with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. RADW, raw agricultural drainage water; TSDW, treated sewage drainage water.
The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100% on: chlorophyll a (μg · cm−2) (A), chlorophyll b (μg · cm−2) (B), total chlorophyll (μg · cm−2) (C) and carotenoids (μg · cm−2) (D). The results are the average of two subsequent seasons (2022 and 2023) with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. RADW, raw agricultural drainage water; TSDW, treated sewage drainage water.

Figure 7.

The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100% on proline (mg · g−1 FW) (A), IL (%) (B) and MDA (μM · g−1 FW) (C). The results are the average of two subsequent seasons (2022 and 2023) with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. IL%, ion leakage; MDA, malondialdehyde; RADW, raw agricultural drainage water; TSDW, treated sewage drainage water.
The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100% on proline (mg · g−1 FW) (A), IL (%) (B) and MDA (μM · g−1 FW) (C). The results are the average of two subsequent seasons (2022 and 2023) with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. IL%, ion leakage; MDA, malondialdehyde; RADW, raw agricultural drainage water; TSDW, treated sewage drainage water.

Figure 8.

The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100% on O2•− (mM · min−1 · g−1 FW) (A), H2O2 (mM · min−1 · g−1 FW) (B) and DPPH% (C). The results are the average of two subsequent seasons (2022 and 2023) with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. DPPH, 2,2-diphenyl-1-picrylhydrazyl; RADW, raw agricultural drainage water; TSDW, treated sewage drainage water.
The effect of different concentrations of RADW and TSDW at four levels, 25%, 50%, 75% and 100% on O2•− (mM · min−1 · g−1 FW) (A), H2O2 (mM · min−1 · g−1 FW) (B) and DPPH% (C). The results are the average of two subsequent seasons (2022 and 2023) with n = 3 for each season. According to Duncan’s multiple range test, each parameter’s mean values and standard error (±SE) are significantly different when each is followed by a different alphabetical letter at p ≤ 0.05. DPPH, 2,2-diphenyl-1-picrylhydrazyl; RADW, raw agricultural drainage water; TSDW, treated sewage drainage water.

Figure 9.

Person’s correlation matrix among the resistant-related parameters on jojoba. Values express the average values of the wastewater treatments on jojoba plant. The correlations are calculated by the Row-wise method. DPPH, 2,2-diphenyl-1-picrylhydrazyl; IL%, ion leakage; JHI%, jojoba height increase percentage; JSDI, jojoba stem diameter increase percentage; LA, leaf area; LDW, leaf dry weight; LT, leaf thickness; MDA, malondialdehyde; NLI, Number of leaves increase percentage; NSI%, number of shoots increase percentage; SCC, soluble carbohydrate content; VQ, Visual quality.
Person’s correlation matrix among the resistant-related parameters on jojoba. Values express the average values of the wastewater treatments on jojoba plant. The correlations are calculated by the Row-wise method. DPPH, 2,2-diphenyl-1-picrylhydrazyl; IL%, ion leakage; JHI%, jojoba height increase percentage; JSDI, jojoba stem diameter increase percentage; LA, leaf area; LDW, leaf dry weight; LT, leaf thickness; MDA, malondialdehyde; NLI, Number of leaves increase percentage; NSI%, number of shoots increase percentage; SCC, soluble carbohydrate content; VQ, Visual quality.

Figure 10.

First and second PCA scores plot of different waste water treatments (A). First. and second PCA scores plot of the correlation in analysed parameters (B). DPPH, 2,2-diphenyl-1-picrylhydrazyl; IL%, ion leakage; JHI%, jojoba height increase percentage; JSDI, jojoba stem diameter increase percentage; LA, leaf area; LDW, leaf dry weight; LT, leaf thickness; MDA, malondialdehyde; NLI, Number of leaves increase percentage; NSI%, number of shoots increase percentage; PCA, principal component analysis; RADW, raw agricultural drainage water; SCC, soluble carbohydrate content;TSDW, treated sewage drainage water; VQ, Visual quality.
First and second PCA scores plot of different waste water treatments (A). First. and second PCA scores plot of the correlation in analysed parameters (B). DPPH, 2,2-diphenyl-1-picrylhydrazyl; IL%, ion leakage; JHI%, jojoba height increase percentage; JSDI, jojoba stem diameter increase percentage; LA, leaf area; LDW, leaf dry weight; LT, leaf thickness; MDA, malondialdehyde; NLI, Number of leaves increase percentage; NSI%, number of shoots increase percentage; PCA, principal component analysis; RADW, raw agricultural drainage water; SCC, soluble carbohydrate content;TSDW, treated sewage drainage water; VQ, Visual quality.
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