scholarly journals Influences of high-reflective mulching membrane coupled with a drip sub-irrigation system on temperature and humidity of the soil

2021 ◽  
Vol 312 ◽  
pp. 12006
Author(s):  
Alessia Di Giuseppe ◽  
Mattia Manni ◽  
Alessandro Petrozzi ◽  
Laura Maria Becchetti ◽  
Beatrice Castellani ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Irrigation System ◽  
Weather Conditions ◽  
Experimental Facility ◽  
Reference Case ◽  
Monitoring Campaign ◽  
Agriculture Sector ◽  
Different Depths ◽  
Original Application ◽  
Set Up

The present study deals with an original application of RR materials to the agriculture sector, evaluating the effectiveness of a high-reflective mulching membrane treated with glass micro-spheres and coupled with a drip sub-irrigation system. An experimental facility, in which this technology is exploited, has been set up in Perugia (Italy). Influences of the mulching membrane on hygrothermal properties of the soil were evaluated through humidity and temperature sensors during the monitoring campaign. Data from unmulched field section was used as a reference case. The effectiveness of this technology was evaluated by focusing on three days that are representative of as much weather conditions. The monitoring campaign conducted from April to May 2021 has demonstrated that the high-reflective mulching membrane can reduce the temperature and relative humidity fluctuations throughout the day. In addition, the mulching membrane can reduce the soil temperature at different depths (i.e. 0.05 m, 0.10 m, and 0.15 m). The highest soil temperature reduction was found equal to 8.95°C at 0.15 m. Basing on such preliminary results, a more detailed and extended monitoring campaign will be performed in summer conditions.

scholarly journals An Automated Plant Irrigation System using μC

2019 ◽  
Vol 9 (2) ◽  
pp. 3558-3562
Keyword(s):  
Water Level ◽  
Irrigation System ◽  
Photovoltaic Cells ◽  
Entire System ◽  
Off Pump ◽  
Agriculture Sector ◽  
Op Amp ◽  
Op Amps ◽  
The Earth ◽  
Set Up

In the agriculture sector Continuous water extraction from the earth decreases water level owing to the slow arrival of a lot of soil in the areas of irrigated land. This is also owing to the unexpected use of water, which leads to a substantial quantity of waste. This automatic irrigation system is used for this purpose. Power comes from photovoltaic cells using solar energy. Therefore it is not necessary to rely on erratic business energy. The circuit consists of sensor components constructed with op-amp IC. Op-amps are set up as a comparator here. In the soil are placed two steep copper cables to see if the soil is moist or dry. The entire system is controlled by a microcontroller. IC which contacts are used to turn the engine ON, the engine is switched OFF when the ground is moist. The above task is carried out by the microcontroller, which receives the signal from the sensors and which functions under software control that can be stored on the microcontroller's Rom. The pump situation is shown on a 16X2 LCD interfacing to the microcontroller. The ON / OFF pump situation is shown. The project can also be strengthened through its interfaces with a GSM modem, which allows control of the engine switching

LYSIMETERS WITH RAINFALL AND SOIL WATER CONTROL

1971 ◽  
Vol 2 (2) ◽  
pp. 79-92 ◽  
Author(s):  
K. J. KRISTENSEN ◽  
H. C. ASLYNG
Keyword(s):  
Soil Moisture Content ◽  
Soil Depth ◽  
Irrigation System ◽  
Drainage System ◽  
Soil Surface ◽  
Trickle Irrigation ◽  
Water Control ◽  
Radiation Equipment ◽  
Different Depths ◽  
Growth Experiments

The lysimeter installation described comprises 36 concrete tanks each with a soil surface of 4 m2. The installation is useful for plant growth experiments under natural conditions involving different treatment combined with various controlled water supplies. The ground installation is at least 20 cm below the soil surface and tillage can be done with field implements. The lysimeter tanks are provided with a drainage system which can drain the soil at the bottom (100 cm depth) to a tension of up to 100 cm. A constant ground-water table at less than 100 cm soil depth can also be maintained. The soil moisture content at different depths is determined from an underground tunnel by use of gamma radiation equipment in metal tubes horizontally installed in the soil. Rainfall is prevented by a movable glass roof automatically operated and controlled by a special rain sensor. Water is applied to the soil surface with a special trickle irrigation system consisting of a set of plastic tubes for each lysimeter tank and controlled from the tunnel. Fertilizers in controlled amount can be applied with the irrigation water.

scholarly journals Prediction of Pest Insect Appearance Using Sensors and Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4846
Author(s):  
Dušan Marković ◽  
Dejan Vujičić ◽  
Snežana Tanasković ◽  
Borislav Đorđević ◽  
Siniša Ranđić ◽  
...  
Keyword(s):  
Machine Learning ◽  
Relative Humidity ◽  
Weather Conditions ◽  
Daily Basis ◽  
Machine Learning Algorithms ◽  
Lower Percentage ◽  
Timely Manner ◽  
Proposed Model ◽  
Set Up ◽  
Accuracy Of Prediction

The appearance of pest insects can lead to a loss in yield if farmers do not respond in a timely manner to suppress their spread. Occurrences and numbers of insects can be monitored through insect traps, which include their permanent touring and checking of their condition. Another more efficient way is to set up sensor devices with a camera at the traps that will photograph the traps and forward the images to the Internet, where the pest insect’s appearance will be predicted by image analysis. Weather conditions, temperature and relative humidity are the parameters that affect the appearance of some pests, such as Helicoverpa armigera. This paper presents a model of machine learning that can predict the appearance of insects during a season on a daily basis, taking into account the air temperature and relative humidity. Several machine learning algorithms for classification were applied and their accuracy for the prediction of insect occurrence was presented (up to 76.5%). Since the data used for testing were given in chronological order according to the days when the measurement was performed, the existing model was expanded to take into account the periods of three and five days. The extended method showed better accuracy of prediction and a lower percentage of false detections. In the case of a period of five days, the accuracy of the affected detections was 86.3%, while the percentage of false detections was 11%. The proposed model of machine learning can help farmers to detect the occurrence of pests and save the time and resources needed to check the fields.

scholarly journals 3GPP Channel Model Emulation with Analysis of MIMO-LTE Performances in Reverberation Chamber

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Nabil Arsalane ◽  
Moctar Mouhamadou ◽  
Cyril Decroze ◽  
David Carsenat ◽  
Miguel Angel Garcia-Fernandez ◽  
...  
Keyword(s):  
Channel Model ◽  
Reference Case ◽  
Reverberation Chamber ◽  
Single Input Single Output ◽  
Single Output ◽  
Received Power ◽  
Communication Devices ◽  
Set Up ◽  
Multiple Clusters ◽  
Active Link

Emulation methodology of multiple clusters channels for evaluating wireless communication devices over-the-air (OTA) performance is investigated. This methodology has been used along with the implementation of the SIMO LTE standard. It consists of evaluating effective diversity gain (EDG) level of SIMO LTE-OFDM system for different channel models according to the received power by establishing an active link between the transmitter and the receiver. The measurement process is set up in a Reverberation Chamber (RC). The obtained results are compared to the reference case of single input-single output (SISO) in order to evaluate the real improvement attained by the implemented system.

scholarly journals Quality control of 10-min soil temperatures data at RMI

2015 ◽  
Vol 12 (1) ◽  
pp. 23-30 ◽  
Author(s):  
C. Bertrand ◽  
L. González Sotelino ◽  
M. Journée
Keyword(s):  
Quality Control ◽  
Soil Temperature ◽  
Bare Soil ◽  
Climate Conditions ◽  
Air Temperatures ◽  
Temperature Observation ◽  
Soil Temperatures ◽  
Different Depths ◽  
Temperature Records ◽  
Energy Processes

Abstract. Soil temperatures at various depths are unique parameters useful to describe both the surface energy processes and regional environmental and climate conditions. To provide soil temperature observation in different regions across Belgium for agricultural management as well as for climate research, soil temperatures are recorded in 13 of the 20 automated weather stations operated by the Royal Meteorological Institute (RMI) of Belgium. At each station, soil temperature can be measured at up to 5 different depths (from 5 to 100 cm) in addition to the bare soil and grass temperature records. Although many methods have been developed to identify erroneous air temperatures, little attention has been paid to quality control of soil temperature data. This contribution describes the newly developed semi-automatic quality control of 10-min soil temperatures data at RMI.

Wavelet neural networks and gene expression programming models to predict short-term soil temperature at different depths

2018 ◽  
Vol 175 ◽  
pp. 37-50 ◽  
Author(s):  
Saeed Samadianfard ◽  
Esmaeil Asadi ◽  
Salar Jarhan ◽  
Honeyeh Kazemi ◽  
Salar Kheshtgar ◽  
...  
Keyword(s):  
Gene Expression ◽  
Neural Networks ◽  
Soil Temperature ◽  
Gene Expression Programming ◽  
Programming Models ◽  
Wavelet Neural Networks ◽  
Short Term ◽  
Different Depths

scholarly journals Exploring the relation between aerosol optical depth and PM<sub>2.5</sub> at Cabauw, the Netherlands

2008 ◽  
Vol 8 (5) ◽  
pp. 17939-17986 ◽  
Author(s):  
M. Schaap ◽  
A. Apituley ◽  
R. M. A. Timmermans ◽  
R. B. A. Koelemeijer ◽  
G. de Leeuw
Keyword(s):  
The Netherlands ◽  
Ground Level ◽  
Weather Conditions ◽  
Fair Weather ◽  
Modis Aod ◽  
Data Points ◽  
Set Up ◽  
The Relationship ◽  
Lidar Observations ◽  
Pm2.5 Concentration

Abstract. To acquire daily estimates of PM2.5 distributions based on satellite data one depends critically on an established relation between AOD and ground level PM2.5. In this study we aimed to experimentally establish the AOD-PM2.5 relationship for the Netherlands. For that purpose an experiment was set-up at the AERONET site Cabauw. The average PM2.5 concentration during this ten month study was 18 μg/m3, which confirms that the Netherlands are characterised by a high PM burden. A first inspection of the AERONET level 1.5 (L1.5) AOD and PM2.5 data at Cabauw showed a low correlation between the two properties. However, after screening for cloud contamination in the AERONET L1.5 data, the correlation improved substantially. When also constraining the dataset to data points acquired around noon, the correlation between AOD and PM2.5 amounted to R2=0.6 for situations with fair weather. This indicates that AOD data contain information about the temporal evolution of PM2.5. We had used LIDAR observations to detect residual cloud contamination in the AERONET L1.5 data. Comparison of our cloud-screed L1.5 with AERONET L2 data that became available near the end of the study showed favorable agreement. The final relation found for Cabauw is PM2.5=124.5*AOD–0.34 (with PM2.5 in μg/m3) and is valid for fair weather conditions. The relationship determined between MODIS AOD and ground level PM2.5 at Cabauw is very similar to that based on the much larger dataset from the sun photometer data, after correcting for a systematic overestimation of the MODIS data of 0.05. We applied the relationship to a MODIS composite map to assess the PM2.5 distribution over the Netherlands. Spatial dependent systematic errors in the MODIS AOD, probably related to variability in surface reflectance, hamper a meaningful analysis of the spatial distribution of PM2.5 using AOD data at the scale of the Netherlands.

scholarly journals Irrigating Wastewater using RWIS for Treating in Soil-Plant System

2019 ◽  
pp. 31-33
Author(s):  
Dahn Rosenqvist
Keyword(s):  
Municipal Wastewater ◽  
Irrigation System ◽  
Specific Area ◽  
Waste Products ◽  
Plant System ◽  
Set Up ◽  
Controlled Flooding ◽  
Computer Operation ◽  
Natural Purification ◽  
Pilot Tests

In Sweden, large areas of willow plantations designated for energy purposes have been established. Pilot tests, using various waste products from society for fertilisation and/or irrigating purposes, have been carried out at Kagerods wastewater plant since 1992. These tests have clearly shown that recycling of municipal wastewater in Salix plantations, can replace a large part of the conventional wastewater treatment, due to natural purification processes in the soil/plant system. During the last few years, several full-scale treatment plants based on the soil/plant system have been set up. Rosenqvist Mek.Verkstad has developed the irrigation system "RWIS" for distribution of wastewater into the plantation. The system uses a controlled flooding technique, combined with computer operation controlled electric valves placed in the fields. By measuring the flow and having knowledge about the contents of the wastewater, it is possible to have total control over the wastewater that is distributed in a specific area. The irrigation system has to be able to withstand trying conditions, without major maintenance in between harvests.

Effect of the weather conditions during solution preparation on lysozyme crystallization

2017 ◽  
Vol 50 (5) ◽  
pp. 1341-1351 ◽  
Author(s):  
Qing-Di Cheng ◽  
Rui-Qing Chen ◽  
Jin He ◽  
Da-Wei Li ◽  
Fan Yang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Environmental Factors ◽  
Protein Crystallization ◽  
Weather Conditions ◽  
Crystallization Experiment ◽  
Solution Preparation ◽  
Crystallization Solution ◽  
Potential Factor ◽  
Weather Parameters ◽  
Set Up

Protein crystallization is a delicate process that is always sensitive to environmental factors. When the environmental factors are not well controlled or not controlled at all, identical crystallization droplets from the same mother liquid may yield different crystallization results. One environmental factor, the weather conditions during crystallization solution preparation, is not usually considered as a parameter for protein crystallization. In this paper, it is shown that the weather parameters during preparation of the crystallization experiment, including the ambient temperature, humidity, pressure and particulate matter in the air, can all affect the reproducibility of lysozyme crystallization. An identical lysozyme crystallization experiment was repeated for an entire year, and the weather conditions when each crystallization experiment was set up were recorded along with the crystallization results. Among the parameters recorded, the humidity during the experiment setup showed the strongest effect on lysozyme crystallization. On the basis of these results, it is suggested that the weather conditions during crystallization solution preparation should be considered as a potential factor that can influence protein crystallization.

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