27 Figure 3.2 The relationship between the volumetric water content (θv), measured using the gravimetric method, and the average sensor output (mV) for three different EC-5 soil water content sensors in a 4 liter container filled with coconut/perlite (CP). 32 Figure 3.4 The relationship between the sensor output (mV) and the volumetric water content (θv), determined by the gravimetric method for (a) coir/perlite (CP) and (b) coir/pine bark/vermiculite (CPBV).
INTRODUCTION
Motivation for the study
It is also limiting as it does not allow unsupervised measurements of soil water content (Annandale et al., 2011). After the sensors are calibrated, the soil water content limits should be determined (upper and lower drained limits) in the laboratory.
Aims and objectives
Thesis structure
LITERATURE REVIEW
- Eucalyptus spp. planting stock quality
- Forestry nursery growing media
- Efficient irrigation scheduling in a nursery greenhouse
- Theoretical aspects of irrigation scheduling
- Soil water content
- Soil water potential
- Drained upper limit
- Plant available water
- Refill point
- Lower limit
- Air-filled porosity
- Practical aspects of soil water monitoring
- Measuring soil water content
- Methods for measuring soil water potential
- Choosing the right sensor for automated irrigation system
- Influence of soil properties on soil water measurements
- Summary
The change in soil heat capacity is highly dependent on soil water content. The soil water content is then related to the soil water potential of the ceramic cup through a water retention relationship curve.
LABORATORY CALIBRATION OF EC-5 SOIL WATER SENSOR IN DIFFERENT
- Introduction…
- Materials and methods
- Instrumentation
- Calibration procedure
- Soil water potential
- Statistical tools
- Results and discussion
- Sensor response to soil water content
- Manufacturer calibration evaluation
- Soil water retention curves
- Conclusions
The soil retention properties define the relationship between soil water content and soil matrix potential. The relationship between sensor output and θv is represented in Figure 3.2 as the mean and standard error of data sets from three EC-5 soil water content sensors. The variations at high soil water content were probably due to the spatial variation in soil mass density caused by packing differences of the growing media in the container.
EC-5 soil water content sensors are affected by the volume of soil surrounding them, and small soil volumes reduce measurement accuracy (Cobos and Chambers, 2010). The factory calibration determined by equation 3.1 was compared to the laboratory calibration for the EC-5 soil water content sensor for CP, CPBV, PB, and sandy soil in Figures 3.6 to 3.9, respectively. The manufacturer specified a 5% error in groundwater content measurements if soil-specific calibration is not performed (Decagon Devices, 2014).
On average, the factory calibration underestimated θv by 0.092 m3 m-3 compared to the laboratory calibration of 0.003 m3 m-3 at low soil water content. Commercially available Decagon EC-5 soil water content sensors were calibrated in the laboratory against the standard gravimetric method using four different nursery growth environments. Containers with large sizes over and underestimated the water content of growing media in low and high water content, respectively.
IRRIGATION SCHEDULING FOR EUCALYPTUS PLANTING STOCK UNDER
Introduction
Materials and methods
- Site description
- Description of planting stock
- Experiment 1 (E. grandis x E. urophylla cuttings)
- Experiment 2 (E. dunnii seedlings)
- Microclimate
- Sensor description
- EC-5 soil water content
- Datalogger
- Experimental design and treatments
- Seedling measurements
- Web-based data communication
The charge stored by the soil and measured by a capacitor is directly related to the dielectric permittivity of the soil or substrate. For this study, 12 Decagon EC-5 soil water content sensors (Decagon Devices, Inc., Pullman, WA, USA) were connected to channels with one end of the CR1000 data logger to measure the water content in the growth media in Unigro seedlings from 0.062 liter to measure. plugs and 0.05 liter polystyrene plugs for experiments 1 and 2, respectively. Sensors were placed in cavities in the center of the tray to avoid edge effects.
Sensors were placed in the center of the tray to avoid seedling edge effect for trials 1 and 2 (Figure 4.5). Measured seedlings were selected in the center of the tray to minimize the seedling edge. Seedling stomatal conductance was measured using an SC1 leaf porometer (Decagon Devices, Inc., Pullman, WA, USA) by randomly selecting 30 seedlings from the center of the tray.
Measurements were made every third week on the third fully expanded leaf of the selected seedling. The ICFR greenhouse datalogger was wired to the UKZN AIM system using a serial link cable and a port on one of the loggers (Figure 4.6). The data table shown at the bottom left of the screen (Figure 4.7) can be downloaded and the data exported to Microsoft Excel for further analysis.
Results and discussion
- Greenhouse microclimate
- Sensor performance in controlling irrigation
- Experiment 1 (E. grandis x E. urophylla cuttings)
- Experiment 2 (E. dunnii)
- Seedling growth response to different irrigation regimes
- Root collar diameter and height
- Stomatal conductance
- Seedling morphology
- Electrical conductivity
With medium and heavy watering, an average of 5 mm per day is used throughout the growing cycle. Average daily drainage per treatment in the low irrigation treatment was 0.4 mm per 3 mm irrigation applied. In general, a large SE was observed between sensor measurements in the low irrigation treatment compared to the other treatments.
Seedlings of the low watering treatment were visually observed to have reduced growth compared to the medium and high watering treatments. After irrigation treatments were applied (day 279), gs for the low irrigation treatment was lowest at 55 mmol m-2 s-1 (Figure 4.16). On the other hand, seedlings in the high-irrigation treatment had greater shoot mass, balanced by sufficient root growth.
The leaf area of seedlings with medium watering was 20% less than with heavy watering, and with low watering the leaf area was the lowest (30% less than with heavy watering). The low irrigation treatment had the highest EC of 175.6 μS/cm8 at day 299 compared to the medium and high irrigation treatments at 117 μS/cm and 76.7 μS/cm, respectively. The high watering treatment had the lowest EC of all treatments, almost equivalent to irrigation water.
Analysis of economics
- Fully automated irrigation systems
- Costs of a datalogger controlled irrigation system
- Benefits of a datalogger automated irrigation system
The cost of implementing an automated irrigation system using a datalogger controller was realized for a forestry research nursery in twelve months. A mobile phone modem can be added to the system to activate early warning via SMS or email or TCP/IP protocols. This system is also capable of sending an SMS and/or email notification to alert the nursery manager if there is a problem with the irrigation system.
However, the benefits such as saving water, time and pumping costs can be achieved. A total water saving of 53.5% was achieved by completely switching from a timer-based system to an automatic irrigation system. 2013) estimate the time required to run a fixed timer-based system at 5 hours per week. In a study by Nzokou et al. 2010) on automatic irrigation system using drip irrigation, a significant reduction in labor requirements for operating the automatic irrigation system improved the overall profitability of the farm.
For this study, management of the irrigation system was significantly reduced as monitoring was mostly done online. The data logger is able to send an alert to a nursery manager if there is a problem with an irrigation system. Such a system could be a useful tool to provide a nursery manager with the ability to observe changes in nursery conditions in near real-time online to allow for early intervention.
Conclusion…
In contrast, the low water treatment had a low nutrient runoff due to low water application. 2010) reported other benefits of an automated system such as reduced pollution of rivers, dams and groundwater. Seedlings in the high irrigation treatment showed the highest root collar diameter, height and stomatal conductance, followed by the medium and low irrigation treatments. However, seedlings in the low water treatment were stronger and more resistant to water stress.
No significant differences were observed between the root-to-shoot ratio for the different treatments, but the high-watering treatment had the greatest seedling mass and total leaf area. The high amount of irrigation in the medium and high irrigation treatments washed nutrients into the growth medium, as indicated by the low EC for these treatments. Analysis of economics showed that the initial costs of switching from a fixed timer-based to an automated irrigation system are high.
This system further provides an early warning to the user if there is a problem with the irrigation system. In summary, the results of this study showed that the low-cost Decagon EC-5 soil water content sensors can be used for container irrigation scheduling for plantations with small cavity volumes. In addition, such a system can be useful for conducting studies where more detailed information is needed on the state of water in the media at different times, or it can be useful for more precise control of irrigation where treatment with different irrigation rates is required. (such as in drought stress studies).
CONCLUSIONS AND RECOMMENDATIONS FOR FURTHER RESEARCH
Overall conclusions
For example, in winter, when the seedlings were younger, the low water treatment was watered every second day, while the medium and high water treatments were watered daily. In summer, due to the increase in air temperature and the increase in seedling size, the low watering treatment was watered daily, while the medium and high watering treatments were watered twice a day. Low watering treatment had the lowest mean RCD and height, followed by medium and high watering treatments.
The low growth in the low water treatment was most likely due to the low soil water content. Seedlings in the low water treatment are more likely to survive better under field conditions. The gs for the high water treatment was consistently greater throughout the study, followed by medium and low water treatments.
This showed that transpiration rates in the high water treatment were the highest for all treatments. The high water treatment had the highest daily average drainage, followed by medium and low water treatments. Seedlings with low water treatment were more robust, hardier and resistant to water stress compared to those in the medium and high water treatments.
Recommendations for future research
In this study, commercially available Decagon EC-5 soil water content sensors were successfully used to control irrigation for E. Measurement of groundwater tension in single aggregates using the filter paper method. Available at http://www.decagon.com/education/calibration-and-evaluation-of-an-improved-low-cost-soil- moisture-sensor-13492-01-an/ (Accessed: 13 October 2014).
Available at http://www.decagon.com/education/measurement- volume-of-decagon-volumetric-water-content-sensors/ (Accessed: 22 December 2014). Precision and accuracy of three alternative instruments for measuring soil water content in two Pacific Northwest forest soils. Determining the timing and amount of irrigation of winter cover crops using dielectric constant and capacitance soil water content profile methods.
Using hourly soil water content measured with a frequency domain reflectometer to schedule irrigation of cabbage. Using the Dual Probe Heat Pulse Technique to Monitor Soil Water Content in the Vadose Zone. Available at http://www.decagon.com/education/using-soil-water-sensors-for-efficient-irrigation-in-greenhouses/ (Accessed: 16 August 2014).
