scholarly journals Evaluation of Soil Moisture Sensors under Intelligent Irrigation Systems for Economical Crops in Arid Regions

2011 ◽  
Vol 6 (2) ◽  
pp. 287-300 ◽  
Author(s):  
El Marazky
Keyword(s):  
Soil Moisture ◽  
Arid Regions ◽  
Irrigation Systems ◽  
Soil Moisture Sensors ◽  
Intelligent Irrigation

scholarly journals A smart Agriculture Irrigation System using sensor array based IOT

2021 ◽  
Vol 2062 (1) ◽  
pp. 012010
Author(s):  
Kola Murali ◽  
B. Sridhar
Keyword(s):  
Soil Moisture ◽  
Irrigation System ◽  
Sensor Data ◽  
Irrigation Systems ◽  
Soil Moisture Sensors ◽  
Agriculture Irrigation ◽  
Smart Agriculture ◽  
Intelligent Irrigation ◽  
Control Water

Abstract The role of Agriculture is important to build a nation, since more than 58% of the population in our country is dependent on agriculture that means half of the population is investing in agriculture. However, many farmers are unfamiliar with intelligent irrigation systems designed to improve the water used for their crops. The proposed system is to precisely monitor the distribution of the water to crops. This IOT based system has a distributed wireless network of soil moisture sensors to monitor soil moisture. Other sensors such as temperature, humidity, rain, IR, LDR, foot. The gateway device also processes the detector’s information and transmits the data to the farmer. An algorithm was developed using threshold values for soil moisture and nutrients, and these values were programmed into a node com-based gateway to control water for irrigation. Complete sensor data is sent to the free cloud using NODEMCU and displayed on websites and apps. This proposed work presents extensive research on irrigation systems in smart agriculture.

scholarly journals Soil Moisture Sensor-based Systems are Suitable for Monitoring and Controlling Irrigation of Greenhouse Crops

HortScience ◽  
2018 ◽  
Vol 53 (4) ◽  
pp. 552-559 ◽  
Author(s):  
Scott Henderson ◽  
David Gholami ◽  
Youbin Zheng
Keyword(s):  
Soil Moisture ◽  
Crop Production ◽  
Growth Index ◽  
Dry Weight ◽  
Irrigation Systems ◽  
Crop Species ◽  
Moisture Sensor ◽  
Soil Moisture Sensor ◽  
Soil Moisture Sensors ◽  
Microclimate Variation

Sensor-based feedback control irrigation systems have been increasingly explored for greenhouse applications. However, the relationships between microclimate variation, plant water usage, and growth are not well understood. A series of trials were conducted to investigate the microclimate variations in different greenhouses and whether a soil moisture sensor-based system can be used in monitoring and controlling irrigation in greenhouse crop productions. Ocimum basilicum ‘Genovese Gigante’ basil and Campanula portenschlagiana ‘Get Mee’ bellflowers were monitored using soil moisture sensors for an entire crop cycle at two commercial greenhouses. Significant variations in greenhouse microclimates were observed within the two commercial greenhouses and within an older research greenhouse. Evaporation rates were measured and used as an integrated indicator of greenhouse microclimate conditions. Evaporation rates varied within all three greenhouses and were almost double the lowest rates within one of the greenhouses, suggesting microclimates within a range of greenhouses. Although these microclimate variations caused large variations in the growing substrate water contents of containers within the greenhouses, the growth and quality of the plants were unaffected. For example, no significant correlations were observed between the growth of bellflower plants and the average volumetric water content (VWC), minimum VWC, or maximum VWC of the growing substrate. The change in VWC at each irrigation (ΔVWC), however, was positively correlated with the fresh weight, dry weight, and growth index (GI) of the bellflowers. For basil, no significant correlations were observed between plant growth and ΔVWC. This suggests that sensor-based feedback irrigation systems can be used for greenhouse crop production when considerations are given to factors such as the magnitude of microclimate variation, crop species and its sensitivity to water stress, and growing substrate.

scholarly journals Alternatives of IoT Irrigation Systems for the Gardens of Arequipa

2021 ◽  
Vol 15 (22) ◽  
pp. 4
Author(s):  
Jose David Esquicha-Tejada ◽  
Juan Carlos Copa-Pineda
Keyword(s):  
Drinking Water ◽  
Soil Moisture ◽  
Water Consumption ◽  
Potable Water ◽  
Solenoid Valve ◽  
Irrigation Systems ◽  
Advantages And Disadvantages ◽  
Soil Moisture Sensors ◽  
The World ◽  
The Common

Due to the problem of drinking water scarcity in different cities around the world, there are innovative proposals to automate garden irrigation in homes, to reduce drinking water consumption. For this research, a sample of 68 inhabitants of the Region of Arequipa - Peru has been surveyed to know the common habits in the irrigation of the gardens. From this data, two systems have been implemented in two average gardens using the Arduino UNO board (integrating with the Ethernet Shield) and the NodeMCU, each proposal integrates soil moisture sensors, water flow sensor, and actuators, such as the solenoid valve and the relay, besides centralizing the information through an IoT System (Home Assistant or Adafruit IO). This has managed to establish a comparison of both, generating a discussion according to the advantages and disadvantages addressed by each proposal and obtaining a saving of potable water in the irrigation of plants.

scholarly journals Minimum Number of Soil Moisture Sensors for Monitoring and Irrigation Purposes

EDIS ◽  
2013 ◽  
Vol 2013 (7) ◽  
Author(s):  
Lincoln Zotarelli ◽  
Michael D. Dukes ◽  
Marcelo Paranhos
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Crop Yield ◽  
Specific Area ◽  
Irrigation Systems ◽  
Fact Sheet ◽  
Soil Moisture Sensors ◽  
Minimum Number ◽  
The Right ◽  
Soil Moisture Variability

Managing soil moisture properly through irrigation is key to increasing crop yield and conserving water. By understanding soil moisture variability, growers can better manage their irrigation systems to apply the right amount of water at the right time. This 4-page fact sheet proposes guidelines for soil moisture sampling that account for spatial variability, which helps to determine the minimum number of soil moisture sensors required to survey and monitor a specific area for irrigation. Written by Lincoln Zotarelli, Michael D. Dukes, and Marcelo Paranhos, and published by the UF Department of Horticultural Sciences, July 2013. http://edis.ifas.ufl.edu/hs1222

scholarly journals An Automated System for Monitoring Soil Moisture and Controlling Irrigation Using Low-cost Open-source Microcontrollers

2015 ◽  
Vol 25 (1) ◽  
pp. 110-118 ◽  
Author(s):  
Rhuanito Soranz Ferrarezi ◽  
Sue K. Dove ◽  
Marc W. van Iersel
Keyword(s):  
Soil Moisture ◽  
Open Source ◽  
Direct Current ◽  
Irrigation System ◽  
Low Cost ◽  
Automated System ◽  
Irrigation Systems ◽  
On Demand ◽  
Soil Moisture Sensors ◽  
Automated Irrigation System

Substrate volumetric water content (VWC) is a useful measurement for automated irrigation systems. We have previously developed automated irrigation controllers that use capacitance sensors and dataloggers to supply plants with on-demand irrigation. However, the dataloggers and accompanying software used to build and program those controllers make these systems expensive. Relatively new, low-cost open-source microcontrollers provide an alternative way to build sensor-based irrigation controllers for both agricultural and domestic applications. We designed and built an automated irrigation system using a microcontroller, capacitance soil moisture sensors, and solenoid valves. This system effectively monitored and controlled VWC over a range of irrigation thresholds (0.2, 0.3, 0.4, and 0.5 m3.m−3) with ‘Panama Red’ hibiscus (Hibiscus acetosella) in a peat:perlite substrate. The microcontroller can be used with both regular 24-V alternating current (AC) solenoid valves and with latching 6- to 18-V direct current (DC) solenoid valves. The technology is relatively inexpensive (microcontroller and accessories cost $107, four capacitance soil moisture sensors cost $440, and four solenoid valves cost $120, totaling $667) and accessible. The irrigation controller required little maintenance over the course of a 41-day trial. The low cost of this irrigation controller makes it useful in many horticultural settings, including both research and production.

scholarly journals Estimating Agricultural Soil Moisture Content through UAV-Based Hyperspectral Images in the Arid Region

2021 ◽  
Vol 13 (8) ◽  
pp. 1562
Author(s):  
Xiangyu Ge ◽  
Jianli Ding ◽  
Xiuliang Jin ◽  
Jingzhe Wang ◽  
Xiangyue Chen ◽  
...  
Keyword(s):  
Data Mining ◽  
Soil Moisture ◽  
Moisture Content ◽  
Hyperspectral Imaging ◽  
Fractional Order ◽  
Arid Regions ◽  
Soil Moisture Content ◽  
Order Derivative ◽  
Imaging Data ◽  
Strategy I

Unmanned aerial vehicle (UAV)-based hyperspectral remote sensing is an important monitoring technology for the soil moisture content (SMC) of agroecological systems in arid regions. This technology develops precision farming and agricultural informatization. However, hyperspectral data are generally used in data mining. In this study, UAV-based hyperspectral imaging data with a resolution o 4 cm and totaling 70 soil samples (0–10 cm) were collected from farmland (2.5 × 104 m2) near Fukang City, Xinjiang Uygur Autonomous Region, China. Four estimation strategies were tested: the original image (strategy I), first- and second-order derivative methods (strategy II), the fractional-order derivative (FOD) technique (strategy III), and the optimal fractional order combined with the optimal multiband indices (strategy IV). These strategies were based on the eXtreme Gradient Boost (XGBoost) algorithm, with the aim of building the best estimation model for agricultural SMC in arid regions. The results demonstrated that FOD technology could effectively mine information (with an absolute maximum correlation coefficient of 0.768). By comparison, strategy IV yielded the best estimates out of the methods tested (R2val = 0.921, RMSEP = 1.943, and RPD = 2.736) for the SMC. The model derived from the order of 0.4 within strategy IV worked relatively well among the different derivative methods (strategy I, II, and III). In conclusion, the combination of FOD technology and the optimal multiband indices generated a highly accurate model within the XGBoost algorithm for SMC estimation. This research provided a promising data mining approach for UAV-based hyperspectral imaging data.

scholarly journals Suitability Evaluation of Typical Drought Index in Soil Moisture Retrieval and Monitoring Based on Optical Images

2020 ◽  
Vol 12 (16) ◽  
pp. 2587
Author(s):  
Yan Nie ◽  
Ying Tan ◽  
Yuqin Deng ◽  
Jing Yu
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Arid Regions ◽  
Drought Index ◽  
Dynamic Monitoring ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Rapid Acquisition ◽  
Semi Arid ◽  
Soil Moisture Inversion

As a basic agricultural parameter in the formation, transformation, and consumption of surface water resources, soil moisture has a very important influence on the vegetation growth, agricultural production, and healthy operation of regional ecosystems. The Aksu river basin is a typical semi-arid agricultural area which seasonally suffers from water shortage. Due to the lack of knowledge on soil moisture change, the water management and decision-making processes have been a difficult issue for local government. Therefore, soil moisture monitoring by remote sensing became a reasonable way to schedule crop irrigation and evaluate the irrigation efficiency. Compared to in situ measurements, the use of remote sensing for the monitoring of soil water content is convenient and can be repetitively applied over a large area. To verify the applicability of the typical drought index to the rapid acquisition of soil moisture in arid and semi-arid regions, this study simulated, compared, and validated the effectiveness of soil moisture inversion. GF-1 WFV images, Landsat 8 OLI images, and the measured soil moisture data were used to determine the Perpendicular Drought Index (PDI), the Modified Perpendicular Drought Index (MPDI), and the Vegetation Adjusted Perpendicular Drought Index (VAPDI). First, the determination coefficients of the correlation analyses on the PDI, MPDI, VAPDI, and measured soil moisture in the 0–10, 10–20, and 20–30 cm depth layers based on the GF-1 WFV and Landsat 8 OLI images were good. Notably, in the 0–10 cm depth layers, the average determination coefficient was 0.68; all models met the accuracy requirements of soil moisture inversion. Both indicated that the drought indices based on the Near Infrared (NIR)-Red spectral space derived from the optical remote sensing images are more sensitive to soil moisture near the surface layer; however, the accuracy of retrieving the soil moisture in deep layers was slightly lower in the study area. Second, in areas of vegetation coverage, MPDI and VAPDI had a higher inversion accuracy than PDI. To a certain extent, they overcame the influence of mixed pixels on the soil moisture spectral information. VAPDI modified by Perpendicular Vegetation Index (PVI) was not susceptible to vegetation saturation and, thus, had a higher inversion accuracy, which makes it performs better than MPDI’s in vegetated areas. Third, the spatial heterogeneity of the soil moisture retrieved by the GF-1 WFV and Landsat 8 OLI image were similar. However, the GF-1 WFV images were more sensitive to changes in the soil moisture, which reflected the actual soil moisture level covered by different vegetation. These results provide a practical reference for the dynamic monitoring of surface soil moisture, obtaining agricultural information and agricultural condition parameters in arid and semi-arid regions.

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