Analysis of the Accuracy of an FDR Sensor in Soil Moisture Measurement under Laboratory and Field Conditions

Qin, Anzhen; Ning, Dongfeng; Liu, Zhandong; Duan, Aiwang

doi:10.1155/2021/6665829

Cited by 11 publications

(5 citation statements)

References 29 publications

(38 reference statements)

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“…Our previous study indicated that the Insentek sensor was a reliable tool to represent real SWC values in the field with a root mean square error (RMSE) of 0.927% v/v between the Insentek sensor and oven-dry method (Table S1) [36]. Through checking the year-round data, data of Insentek sensors also had good continuity and stability [5]. Crops around the sensors were not missed and uniform, and were representative of the experimental conditions with the similar sizes and vigor.…”

Section: Soil Water Content and Crop Evapotranspirationmentioning

confidence: 97%

“…A center pivot irrigation system (CPIS) is considered adaptable in the mechanized operation for both wheat and maize due to its adaptability to different crops [4]. In addition, due to the over-depletion of aquifers, the NCP has become the severest groundwater depression zone in the world [5]. This especially expedites the development of water-saving techniques, making precision irrigation an inevitable trend for future agriculture in this area.…”

Section: Introductionmentioning

confidence: 99%

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Determining Threshold Values for a Crop Water Stress Index-Based Center Pivot Irrigation with Optimum Grain Yield

et al. 2021

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The temperature-based crop water stress index (CWSI) can accurately reflect the extent of crop water deficit. As an ideal carrier of onboard thermometers to monitor canopy temperature (Tc), center pivot irrigation systems (CPIS) have been widely used in precision irrigation. However, the determination of reliable CWSI thresholds for initiating the CPIS is still a challenge for a winter wheat–summer maize cropping system in the North China Plain (NCP). To address this problem, field experiments were carried out to investigate the effects of CWSI thresholds on grain yield (GY) and water use efficiency (WUE) of winter wheat and summer maize in the NCP. The results show that positive linear functions were fitted to the relationships between CWSI and canopy minus air temperature (Tc − Ta) (r2 > 0.695), and between crop evapotranspiration (ETc) and Tc (r2 > 0.548) for both crops. To make analysis comparable, GY and WUE data were normalized to a range of 0.0 to 1.0, corresponding the range of CWSI. With the increase in CWSI, a positive linear relationship was observed for WUE (r2 = 0.873), while a significant inverse relationship was found for the GY (r2 = 0.915) of winter wheat. Quadratic functions were fitted for both the GY (r2 = 0.856) and WUE (r2 = 0.629) of summer maize. By solving the cross values of the two GY and WUE functions for each crop, CWSI thresholds were proposed as being 0.252 for winter wheat, and 0.229 for summer maize, corresponding to a Tc − Ta threshold value of 0.925 and 0.498 °C, respectively. We conclude that farmers can achieve the dual goals of high GY and high WUE using the optimal thresholds proposed for a winter wheat–summer maize cropping system in the NCP.

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Section: Soil Water Content and Crop Evapotranspirationmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Determining Threshold Values for a Crop Water Stress Index-Based Center Pivot Irrigation with Optimum Grain Yield

et al. 2021

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“…One study found that more accurate estimations for weekly citrus tree irrigation were obtained when soil sensor data was combined with weather information. In this part, we'll take a look at several different types of SMS-enabled smart irrigation systems (Qin, et al, 2021).…”

Section: Soil Moisture-based Irrigation Managementmentioning

confidence: 99%

Ontology-Based Smart Irrigation System: Enhancing Agricultural Water Management

Nisa,

Azam,

Rafiq

et al. 2024

ABBDM

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An Ontology-Based Smart Irrigation System is presented in this research with the goal of improving agricultural water management. The main issue discussed is the inefficiency of conventional irrigation techniques, which results in water waste and lower crop yields. The process used entails creating an ontology, which includes defining concepts, establishing relationships, identifying domains, and populating the ontology. In order to facilitate real-time monitoring and decision-making, the irrigation system also incorporates sensors, actuators, and data processing algorithms. The main conclusions show that the ontology-based approach boosts crop output, encourages sustainable farming practices, and enhances water consumption efficiency. The findings of this study imply that ontology-based smart irrigation systems present a viable way to deal with the problems associated with water scarcity, improve agricultural output, and reduce their negative effects on the environment. The research adds to the expanding corpus of information on intelligent irrigation systems and emphasizes the significance of implementing cutting-edge technologies for agriculture's sustainable water management.

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“…The water balance in the soil and the need for crop irrigation can be estimated by measuring the SMC (Qin et al, 2021). Several studies have reported on irrigation monitoring based on soil moisture sensing (Blessy, 2021; Hamouda et al, 2021; Wang et al, 2021).…”

Section: Smart Strategies For Precision Irrigationmentioning

confidence: 99%

A review on smart irrigation management strategies and their effect on water savings and crop yield

Touil

Richa

Fizir

et al. 2022

Irrigation and Drainage

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Appropriate irrigation water management has attracted a considerable degree of attention because it is crucial to guarantee water and food security worldwide. A smart irrigation system is applied for the rational use of water in agricultural fields and for maximizing crop yield. Thus, the high demand for water resources is decreased, and the adverse environmental impacts of irrigation are reduced. Different irrigation approaches were developed to reduce overirrigation by assessing the soil moisture content or crop water stress index. This paper aims to review conventional and smart irrigation technologies and discuss their effect on water savings, yield, and crop quality. The analysis of prominent studies highlighted that the water use efficiency based on soil moisture sensors depends on the volumetric moisture content threshold value set by farmers. Soil moisture sensor controllers, evapotranspiration controllers, and rain sensors have been shown to save 20%-92%, 20%-71%, and 7%-50% of water, respectively, while maintaining crop growth and quality. The optical sensor-based system showed a better ability to assess crop and soil variability in the field than the on-site measurements. The conventional controlled deficit irrigation technique was found to decrease the crop yield to less than 25% with water savings of up to 13%.

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Analysis of the Accuracy of an FDR Sensor in Soil Moisture Measurement under Laboratory and Field Conditions

Cited by 11 publications

References 29 publications

Determining Threshold Values for a Crop Water Stress Index-Based Center Pivot Irrigation with Optimum Grain Yield

Determining Threshold Values for a Crop Water Stress Index-Based Center Pivot Irrigation with Optimum Grain Yield

Ontology-Based Smart Irrigation System: Enhancing Agricultural Water Management

A review on smart irrigation management strategies and their effect on water savings and crop yield

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