Optimizing Deficit Irrigation Management to Improve Water Productivity of Greenhouse Tomato under Plastic Film Mulching Using the RZ-SHAW Model
Abstract
:1. Introduction
2. Materials and Methods
2.1. Experimental Site and Plant Material
2.2. Field Management
2.3. RZ-SHAW Overview, Model Input and Calibration
2.3.1. Model Description
2.3.2. Model Input, Calibration and Validation
2.4. Statistical Analysis
2.5. Quantifying the Effects of Deficit Irrigation Levels using Calibrated RZ-SHAW
3. Results
3.1. Simulations of Tomato Growth Parameters
3.2. Simulations for Soil Water
4. Discussion
4.1. Simulated Plant Water Stress in Experimental Scenarios
4.2. Optimizing Deficit Irrigation Management for Maximizing Yield and Water Productivity
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Depth (cm) | BD (mg m−3) | Pb (cm) | θs (cm3 cm−3) | θr (cm3 cm−3) | Ksat (cm/h) | λ | Soil Root Growth Factors |
---|---|---|---|---|---|---|---|
0–5 | 1.322 | −8.96 | 0.37 | 0.10 | 3.15 | 0.17 | 1.00 |
5–15 | 1.322 | −18.53 | 0.34 | 0.13 | 3.22 | 0.32 | 0.90 |
15–35 | 1.402 | −8.16 | 0.43 | 0.15 | 3.46 | 0.37 | 0.70 |
35–55 | 1.402 | −23.89 | 0.41 | 0.11 | 1.81 | 0.16 | 0.54 |
55–75 | 1.402 | −5.53 | 0.31 | 0.10 | 2.83 | 0.15 | 0.30 |
75–100 | 1.550 | −5.53 | 0.31 | 0.10 | 2.83 | 0.15 | 0.20 |
100–150 | 1.550 | −16.68 | 0.40 | 0.07 | 3.02 | 0.30 | 0.05 |
Parameter | Description | Value |
---|---|---|
CSDL | Critical Short-Day Length below which reproductive development progresses with no daylength effect (for short day plants) (hour) | 12.0 |
PPSEN | Slope of the relative response of development to photoperiod with time (positive for short day plants) (1/h) | 0.0 |
EM-FL | Time between plant emergence and flower appearance (R1) (photothermal days) | 20.0 |
FL-SH | Time between first flower and first pod (R3) (photothermal days) | 9.5 |
FL-SD | Time between first flower and first seed (R5) (photothermal days) | 19.8 |
SD-PM | Time between first seed (R5) and physiological maturity (R7) (photothermal days) | 49.0 |
FL-LF | Time between first flower (R1) and end of leaf expansion (photothermal days) | 50.3 |
LFMAX | Maximum leaf photosynthesis rate at 30 C, 350 vpm CO2, and high light (mg CO2/m2-s) | 1.1 |
SLAVR | Specific leaf area of cultivar under standard growth conditions (cm2/g) | 357.7 |
SIZLF | Maximum size of full leaf (three leaflets) (cm2) | 333.1 |
XFRT | Maximum fraction of daily growth that is partitioned to seed and shell | 0.69 |
WTPSD | Maximum weight per seed (g) | 0.004 |
SFDUR | Seed filling duration for pod cohort at standard growth conditions (photothermal days) | 30.0 |
SDPDV | Average seed per pod under standard growing conditions (#/pod) | 300.0 |
PODUR | Time required for cultivar to reach final pod load under optimal conditions (photothermal days) | 67.9 |
Scenarios | LAI | Plant Height | Biomass | Yield | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ObLAI | SimLAI | RRMSE | PBIAS | IoA | R2 | ObPH | SimPH | RRMSE | PBIAS | IoA | R2 | RE | RE | |
ET50 | 6.9 | 6.8 | 18.1% | 1.0% | 0.73 | 0.70 | 89.0 | 74.1 | 23.5% | 16.7% | 0.95 | 1.00 | 8.7% | 12.1% |
ET75 | 9.5 | 9.8 | 16.7% | −3.4% | 0.84 | 0.83 | 91.5 | 90.1 | 9.1% | 1.6% | 0.99 | 0.99 | 8.3% | 14.0% |
ET100 | 11.1 | 11.2 | 9.2% | −0.8% | 0.95 | 0.92 | 92.1 | 92.6 | 13.4% | −0.5% | 0.99 | 0.98 | 3.5% | 11.3% |
ET125 | 11.8 | 12.4 | 13.4% | −4.8% | 0.90 | 0.91 | 90.7 | 101.3 | 22.7% | −11.7% | 0.97 | 0.99 | 5.2% | 10.8% |
ET150 | 11.3 | 12.4 | 14.5% | −9.6% | 0.88 | 0.91 | 90.4 | 101.3 | 22.6% | −12.1% | 0.97 | 0.99 | 6.9% | 7.0% |
Depth (cm) | ET50 (Validation) | ET75 (Validation) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
ObVWC | SimVWC | RRMSE | PBIAS | IoA | R2 | ObVWC | SimVWC | RRMSE | PBIAS | IoA | R2 | |
0–5 | 0.166 | 0.171 | 12.4% | −3.2% | 0.79 | 0.70 | 0.185 | 0.187 | 11.0% | −0.8% | 0.76 | 0.64 |
5–15 | 0.161 | 0.156 | 11.9% | 3.1% | 0.74 | 0.65 | 0.176 | 0.179 | 8.5% | 2.9% | 0.76 | 0.64 |
15–35 | 0.160 | 0.159 | 11.7% | 0.3% | 0.77 | 0.61 | 0.174 | 0.175 | 8.9% | −0.3% | 0.82 | 0.68 |
35–55 | 0.157 | 0.162 | 9.5% | −3.2% | 0.81 | 0.75 | 0.177 | 0.175 | 10.0% | 1.3% | 0.76 | 0.64 |
Mean (0–55) | 0.161 | 0.162 | 8.7% | −0.7% | 0.86 | 0.75 | 0.178 | 0.177 | 7.7% | 0.8% | 0.85 | 0.72 |
Depth (cm) | ET100 (Calibration) | ET125 (Validation) | ||||||||||
0–5 | 0.195 | 0.198 | 8.5% | −1.6% | 0.74 | 0.56 | 0.215 | 0.221 | 9.4% | −2.9% | 0.79 | 0.72 |
5–15 | 0.177 | 0.179 | 5.9% | −0.7% | 0.81 | 0.69 | 0.191 | 0.191 | 5.7% | −0.3% | 0.86 | 0.74 |
15–35 | 0.187 | 0.184 | 7.1% | 1.4% | 0.80 | 0.67 | 0.193 | 0.198 | 7.1% | −2.3% | 0.77 | 0.69 |
35–55 | 0.181 | 0.183 | 7.1% | −0.6% | 0.82 | 0.70 | 0.200 | 0.194 | 5.7% | 2.8% | 0.82 | 0.76 |
Mean (0–55) | 0.185 | 0.186 | 5.5% | −0.4% | 0.86 | 0.76 | 0.200 | 0.201 | 5.6% | −0.7% | 0.86 | 0.83 |
Depth (cm) | ET150 (Validation) | |||||||||||
0–5 | 0.230 | 0.230 | 5.9% | 0.3% | 0.86 | 0.73 | ||||||
5–15 | 0.200 | 0.196 | 5.6% | 1.9% | 0.74 | 0.59 | ||||||
15–35 | 0.207 | 0.203 | 4.1% | 1.7% | 0.85 | 0.79 | ||||||
35–55 | 0.202 | 0.199 | 5.7% | 1.5% | 0.72 | 0.57 | ||||||
Mean (0–55) | 0.210 | 0.207 | 4.3% | 1.3% | 0.86 | 0.76 |
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Cheng, H.; Ji, S.; Ge, H.; Abdalhi, M.A.M.; Zhu, T.; Chen, X.; Ding, W.; Feng, S. Optimizing Deficit Irrigation Management to Improve Water Productivity of Greenhouse Tomato under Plastic Film Mulching Using the RZ-SHAW Model. Agriculture 2022, 12, 1253. https://doi.org/10.3390/agriculture12081253
Cheng H, Ji S, Ge H, Abdalhi MAM, Zhu T, Chen X, Ding W, Feng S. Optimizing Deficit Irrigation Management to Improve Water Productivity of Greenhouse Tomato under Plastic Film Mulching Using the RZ-SHAW Model. Agriculture. 2022; 12(8):1253. https://doi.org/10.3390/agriculture12081253
Chicago/Turabian StyleCheng, Haomiao, Shu Ji, Hengjun Ge, Mohmed A. M. Abdalhi, Tengyi Zhu, Xiaoping Chen, Wei Ding, and Shaoyuan Feng. 2022. "Optimizing Deficit Irrigation Management to Improve Water Productivity of Greenhouse Tomato under Plastic Film Mulching Using the RZ-SHAW Model" Agriculture 12, no. 8: 1253. https://doi.org/10.3390/agriculture12081253