After providing a proof of concept of the new measurement system of BD and understanding the most affecting factors on the measurement accuracy of θv and
ω and consequently of BD. The plan was to test this new concept in real situation in-situ. In order to do so, a new penetration probe was design and developed. It is
a portable prototype measuring system, consisting of a combination of a NIR spectrophotometer (Avantes spectrometer), a dielectric sensor, a standard penetrometer, a battery and a laptop (Figure 3-13).
The dielectric sensor used in this prototype measuring system has an electronic circuit generating a 100 MHz electromagnetic sine wave, which is propagated into the soil body through a central electrode in the form of a copper ring with a 10, 15 and 1.5 mm height, diameter and wall thickness, respectively. The copper ring is insulated from the probe body, which forms two shielding electrodes as they are connected to the electronic circuits’ negative. Each shielding electrode has a cylinder shape with a 13 and 50 mm diameter and height, respectively. The readout pin of the electronic circuit is connected to the HH2 meter from Delta-T devices, which at the time of reading acts as a power supply and provides data storage.
Although the same electronic circuit of ThetaProbe was used for the prototype sensor, V values of ThetaProbe and the prototype sensor are not comparable, due to the differences in the dimensions and the shapes of the probe’s electrodes, which in turn lead to significant differences in the sinusoidal wave reflection measurements. From the above, it can be concluded that it is necessary to calibrate the prototype sensor in the laboratory using different moisture levels and different types of soils (as explained in more details in point 3.7.1.), to figure out the relationship between these factors and V for the prototype, before carrying out the measurements in the field.
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V is a direct readout of ThetaPobe’s electronic circuit, which was preferred to be used in this study as no need for further transformation formula to be used to record the dielectric constant values, for example.
The probe body also provides protection for the optical fibres, as they run inside its cavity. The optical fibres open in the centre of a high reflection chamber, with a sapphire round window mounted on the top. The sapphire window is located in a small grove made in the probe body to prevent scratches that might form on its surface by the direct contact with the soil (Figures 3-10 and 3-11). The other ends of the optical fibres are connected to the Avantes spectrophotometer and the light source.
Figure 3-11 The combined portable probe of a near infrared (NIR) spectrophotometer and a dielectric sensor, for the measurement of soil volumetric moisture content (θv), gravimetric moisture content (ω) and bulk density (BD).
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Figure 3-12 The reflection chamber of the combined probe.
As the combined probe inserted into the soil vertically, the surrounding soil in contact with probe electrodes will be affected by the fringe fields of the propagated signal, resulting from the two capacitors (Figure 3-12).
Figure 3-13 Shows the electromagnetic fringe fields around the dielectric sensors’ electrodes.
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3.7.1. Laboratory testing of the prototype measuring system
The prototype of the portable soil BD measuring system was first tested in the laboratory using two soil textures, namely, sandy loam and clay loam (Table 3-11). Each soil texture was oven dried for 24 hours at a 105 °C. Stones and large plant residuals were removed and the dry weight of the soil was recorded. Different measured volumes of distilled water were added to the dry soils and mixed properly in order to artificially produce various soil moisture contents. Then, instantly the wet soils were placed in a 1 litre volume plastic packet and the wet weight was recorded. A total of 50 soil samples of each soil texture were prepared to perform the laboratory testing. Three replicates were recorded for vis-NIR spectra and V readings obtained with the NIR spectrophotometer and the dielectric sensor, respectively, from each soil sample with different moisture content and BD. Table 3-11 Information of the soil textures of soils used in the laboratory test of the prototype measurement system.
Soil texture Samples number Clay % Silt % Sand % OM % Sandy loam 50 30 18 52 3.00 Clay loam 50 60 29 11 5.50
The entire spectra data were pre-treated as explained in the point 3.3.4. using the Unscrambler® version 7.8 (Camo Inc.; Oslo, Norway), except for the spectra data noise at the high edge of the frequency, which was made negligible by reducing the spectra data range from 1650 to 2225 nm. Later on, the ANN calibration method was used to analyse the data produced in the laboratory for each soil texture and for both textures. The entire data set (e.g. 50 or 100 samples) were divided into calibration (60%), cross-validation (15%) and test (25%). The ANN analyses included the prediction of θv and ω, using input readings on V and vis- NIR spectra. Finally, BD was estimated using Eqn. 1-9.The prediction accuracy of
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θv, ω and BD of the prototype measuring system was evaluated in terms of R2 and RMSEP values of the independent data sets.
3.7.2. In-situ test of the prototype
In-situ measurement
The prototype portable measurement system was tested for in-situ measurement in five fields with various textures and growing crops. At each point in the field, three V and NIR spectra were measured with the prototype’s dielectric sensor and vis- NIR spectrometer. Average values of the three V and vis-NIR spectra were calculated afterwards. The experiment ran from August, 2013 to December, 2013, at the Silsoe experimental farm of Cranfield University. These fields are the same as those used to study the effect of moisture content of the measurements of output voltage and spectra. However, two more fields were used, namely, Avenue and Onley fields with grass grown. Table 3-12 shows information about the test fields where the prototype was tested.
Table 3-12 Information of the fields, where the prototype measuring system was tested.
Fields SN Soil texture Clay% Silt% Sand% OM% Crop
Avenue 20 Sandy loam 16 20 63 3.6 Barley
Beechwood 20 Cay 66 11 23 5.8 Wheat
Clover hill 20 Clay loam 35 24 41 4.8 Barley
Orchard 20 Clay loam 33 26 41 4.15 Wheat
Showground 20 Sandy clay loam
24 17 59 3.34 Barley
Sum 100
Avenue 50 Sandy loam 0.29 0.19 0.51 2.98
Grass
Onley 50 Clay 0.60 0.30 0.10 5.40
Sum 100
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Table 3-13 provides basic statistics of the 200 soil samples, used for the field testing of the portable prototype sensor. Values of θv, ω and BD were obtained with the oven-drying method at 105 °C for 24 h, from soil samples extracted from 5 – 10 cm from the soil top surface, the top of the soil was removed before the readings were recorded and the soil were collected to avoid effect of the high percentage of plants residuals.
Table 3-13 Sample statistics of the soil samples, used for testing the new prototype measuring system. Values were obtained from laboratory measured volumetric moisture content (θv), in cm3 cm-3, gravimetric moisture content (ω) in g g-1 and bulk density (BD) in g cm-3.
Statistic factor
Arable lands Grasslands
θv ω BD θv ω BD Maximum 0.55 0.41 1.60 0.46 0.36 1.78 Minimum 0.12 0.10 1.08 0.24 0.15 1.20 Range 0.43 0.31 0.52 0.22 0.21 0.58 Average 0.34 0.26 1.34 0.35 0.25 1.49 SD 0.14 0.11 0.11 0.09 0.08 0.24
SD is standard deviation, ω is gravimetric moisture content (g g-1), θv is the volumetric moisture content (cm3 cm-3) and BD is soil bulk density (g cm-3).
The light weight and compact size of the prototype in-situ measurement system made it easy to move through the growing crops and carry out the measurements either by assembling the system on a sackbarrow (Figure 3-13) or carrying in a rucksack (Figure3-14).
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Figure 3-14 The prototype of the field measuring system of soil of volumetric moisture content (θv), gravimetric moisture content (ω) and bulk density (BD) assembled on a wheelbarrow.
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Figure 3-15 The prototype of the field measuring system of volumetric moisture content (θv), gravimetric moisture content (ω) and bulk density (BD) carried in a rucksack.
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The ANN technique was deployed to generate calibration models for θv and ω based on 75% of the vis-NIR spectra and V by the prototype sensors (75 soil samples). BD was then estimated using Eqn. 1-9 for the arable, grasslands and individual fields. All estimated BD values obtained by applying the ANN calibration models on the independent validation set (25% = 25 soil samples) were compared with the independent measured BD values (25% = 25 soil samples) using core sampling method. Before running the ANN analyses, the entire spectra data was pre-treated as explained in the Point 3.3.4 using the Unscrambler® version 7.8 (Camo Inc.; Oslo, Norway), except for the noise removing at the higher edge of the operating frequency of the Avantes spectrometer, which has been neglected by limiting the spectra data detection range from 1650 to 2225 nm.
3.7.3. Development of soil maps
Out of the 7 fields sampled with the prototype portable system, two fields were randomly selected for mapping. These were the Avenue arable and grassland fields. Three types of maps for the Avenue fields were developed for each soil property, namely, θv, ω and BD. These three maps are of the measured θv, ω and BD by the oven-drying of the core soil samples as a reference maps, the predicted maps of θv, ω and BD using the prototype combined sensor (for selected points) and predicted maps θv, ω and BD using full-data point maps. The reference and the predicted maps are used for a visual comparison of the prototype measuring system accuracy, the number of the soil samples and the position of the readouts for the reference and the 20 soil samples predicted maps were identical, while the full-data point maps were generated using a double number of the readouts of spectra and V data (A 40 readouts for a 40 different positions per field), as compared to the former two maps. The inverse distance weighing (IDW) interpolation method was used to develop the former two groups of maps using ArcGIS 10.2 (ESRI, USA) software. It was deployed to provide histogram of the prediction errors of the difference between oven-drying measured and the prototype predicted values of soil θv, ω and BD. Based on semivariogram
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parameters and kriging interpolation methods, ArcGIS 10.2 (ESRI, USA) was used to produce the full-data point maps of the field predicted θv and ω from V and vis- NIR spectra, respectively. Then field BD was calculated using Eqn. 1-9, by substituting the predicted values of θv and ω obtained with ANN calibration method and comparison was made between the calculated BD and independent measured BD using core samples method.
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