Thresholds for Irrigation Management of Processing Tomatoes Using Soil Moisture Sensors in Southwestern Ontario

2013 ◽  
Vol 56 (1) ◽  
pp. 155-166 ◽  
Author(s):  
F. Jaria ◽  
C. A. Madramootoo
Keyword(s):  
Soil Moisture ◽  
Irrigation Management ◽  
Soil Moisture Sensors ◽  
Processing Tomatoes

scholarly journals Smart & Green: An Internet-of-Things Framework for Smart Irrigation

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 190 ◽  
Author(s):  
Nidia G. S. Campos ◽  
Atslands R. Rocha ◽  
Rubens Gondim ◽  
Ticiana L. Coelho da Silva ◽  
Danielo G. Gomes
Keyword(s):  
Soil Moisture ◽  
Irrigation Management ◽  
Management Plan ◽  
Matric Potential ◽  
Outlier Removal ◽  
Temporal Window ◽  
Soil Moisture Sensors ◽  
Management Scheme ◽  
Smart Agriculture ◽  
Different Sources

Irrigation is one of the most water-intensive agricultural activities in the world, which has been increasing over time. Choosing an optimal irrigation management plan depends on having available data in the monitoring field. A smart agriculture system gathers data from several sources; however, the data are not guaranteed to be free of discrepant values (i.e., outliers), which can damage the precision of irrigation management. Furthermore, data from different sources must fit into the same temporal window required for irrigation management and the data preprocessing must be dynamic and automatic to benefit users of the irrigation management plan. In this paper, we propose the Smart&Green framework to offer services for smart irrigation, such as data monitoring, preprocessing, fusion, synchronization, storage, and irrigation management enriched by the prediction of soil moisture. Outlier removal techniques allow for more precise irrigation management. For fields without soil moisture sensors, the prediction model estimates the matric potential using weather, crop, and irrigation information. We apply the predicted matric potential approach to the Van Genutchen model to determine the moisture used in an irrigation management scheme. We can save, on average, between 56.4% and 90% of the irrigation water needed by applying the Zscore, MZscore and Chauvenet outlier removal techniques to the predicted data.

scholarly journals Performance Assessment of Five Different Soil Moisture Sensors under Irrigated Field Conditions in Oklahoma

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3786 ◽  
Author(s):  
Sumon Datta ◽  
Saleh Taghvaeian ◽  
Tyson Ochsner ◽  
Daniel Moriasi ◽  
Prasanna Gowda ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Cropping Systems ◽  
Irrigation Management ◽  
Clay Content ◽  
Field Capacity ◽  
Irrigation Scheduling ◽  
Irrigated Agriculture ◽  
Undisturbed Soil ◽  
Soil Moisture Sensors ◽  
Rosetta Model

Meeting the ever-increasing global food, feed, and fiber demands while conserving the quantity and quality of limited agricultural water resources and maintaining the sustainability of irrigated agriculture requires optimizing irrigation management using advanced technologies such as soil moisture sensors. In this study, the performance of five different soil moisture sensors was evaluated for their accuracy in two irrigated cropping systems, one each in central and southwest Oklahoma, with variable levels of soil salinity and clay content. With factory calibrations, three of the sensors had sufficient accuracies at the site with lower levels of salinity and clay, while none of them performed satisfactorily at the site with higher levels of salinity and clay. The study also investigated the performance of different approaches (laboratory, sensor-based, and the Rosetta model) to determine soil moisture thresholds required for irrigation scheduling, i.e., field capacity (FC) and wilting point (WP). The estimated FC and WP by the Rosetta model were closest to the laboratory-measured data using undisturbed soil cores, regardless of the type and number of input parameters used in the Rosetta model. The sensor-based method of ranking the readings resulted in overestimation of FC and WP. Finally, soil moisture depletion, a critical parameter in effective irrigation scheduling, was calculated by combining sensor readings and FC estimates. Ranking-based FC resulted in overestimation of soil moisture depletion, even for accurate sensors at the site with lower levels of salinity and clay.

scholarly journals Common Questions When Using Soil Moisture Sensors for Citrus and Other Fruit Trees

EDIS ◽  
2021 ◽  
Vol 2021 (2) ◽  
pp. 4
Author(s):  
Eric Herrera ◽  
Sandra M. Guzmán ◽  
Eduart Murcia
Keyword(s):  
Soil Moisture ◽  
Transmission Line ◽  
Time Domain ◽  
Irrigation Management ◽  
Fruit Trees ◽  
Fruit Tree ◽  
Biological Engineering ◽  
Soil Moisture Sensors ◽  
Tree Production ◽  
Extension Personnel

This guide is for Extension personnel who may encounter questions from growers about the functioning and accuracy of soil moisture sensors (SMSs) for fruit tree production. The 4-page publication focuses on two types of handheld sensors currently used in Florida for irrigation management of citrus and other trees: the transmission line oscillator (TLO) and time-domain transmissometer (TDT). Written by Eric Herrera, Sandra M. Guzmán, and Eduart Murcia, and published by the UF/IFAS Department of Agricultural and Biological Engineering, February 2021.

scholarly journals The value of satellite remote sensing soil moisture data and the DISPATCH algorithm in irrigation fields

2018 ◽  
Author(s):  
Mireia Fontanet ◽  
Daniel Fernández-Garcia ◽  
Francesc Ferrer
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Spatial Scales ◽  
Irrigation Management ◽  
Irrigation Scheduling ◽  
Rainfall Events ◽  
Soil Moisture Sensors ◽  
Gravimetric Measurements ◽  
Agricultural Applications ◽  
Remote Sensing Techniques

Abstract. Soil moisture measurements are needed in a large number of applications such as climate change, watershed water balance and irrigation management. One of the main characteristics of this property is that soil moisture is highly variable with both space and time, hindering the estimation of a representative value. Deciding how to measure soil moisture before undertaking any type of study is therefore an important issue that needs to be addressed correctly. Nowadays, different kinds of methodologies exist for measuring soil moisture; Remote Sensing, soil moisture sensors or gravimetric measurements. This work is focused on how to measure soil moisture for irrigation scheduling, where soil moisture sensors are the main methodology for monitoring soil moisture. One of its disadvantages, however, is that soil moisture sensors measure a small volume of soil, and do not take into account the existing variability in the field. In contrast, Remote Sensing techniques are able to estimate soil moisture with a low spatial resolution, and thus it is not possible to apply these estimations to agricultural applications. In order to solve this problem, different kinds of algorithms have been developed for downscaling these estimations from low to high resolution. The DISPATCH algorithm downscales soil moisture estimations from 40 km to 1 km resolution using SMOS satellite soil moisture, NDVI and LST from MODIS sensor estimations. In this work, DISPATCH estimations are compared with soil moisture sensors and gravimetric measurements to validate the DISPATCH algorithm in two different hydrologic scenarios; (1) when wet conditions are maintained around the field for rainfall events, and (2) when it is local irrigation that maintains wet conditions. Results show that the DISPATCH algorithm is sensitive when soil moisture is homogenized during general rainfall events, but not when local irrigation generates occasional heterogeneity. In order to explain these different behaviours, we have examined the spatial variability scales of NDVI and LST data, which are the variables involved in the downscaling process provided by the MODIS sensor. Sample variograms show that the spatial scales associated with the NDVI and LST properties are too large to represent the variations of the average water content at the site, and this could be a reason for why the DISPATCH algorithm is unable to detect soil moisture increments caused by local irrigation.

scholarly journals Designing Low-Cost Capacitive-Based Soil Moisture Sensor and Smart Monitoring Unit Operated by Solar Cells for Greenhouse Irrigation Management

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5387
Author(s):  
Abdelaziz M. Okasha ◽  
Hasnaa G. Ibrahim ◽  
Adel H. Elmetwalli ◽  
Khaled Mohamed Khedher ◽  
Zaher Mundher Yaseen ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Root Zone ◽  
Low Cost ◽  
Irrigation Management ◽  
Irrigation Scheduling ◽  
Moisture Sensor ◽  
Soil Moisture Sensor ◽  
Soil Moisture Sensors

Precise and quick estimates of soil moisture content for the purpose of irrigation scheduling are fundamentally important. They can be accomplished through the continuous monitoring of moisture content in the root zone area, which can be accomplished through automatic soil moisture sensors. Commercial soil moisture sensors are still expensive to be used by famers, particularly in developing countries, such as Egypt. This research aimed to design and calibrate a locally manufactured low-cost soil moisture sensor attached to a smart monitoring unit operated by Solar Photo Voltaic Cells (SPVC). The designed sensor was evaluated on clay textured soils in both lab and controlled greenhouse environments. The calibration results demonstrated a strong correlation between sensor readings and soil volumetric water content (θV). Higher soil moisture content was associated with decreased sensor output voltage with an average determination coefficient (R2) of 0.967 and a root-mean-square error (RMSE) of 0.014. A sensor-to-sensor variability test was performed yielding a 0.045 coefficient of variation. The results obtained from the real conditions demonstrated that the monitoring system for real-time sensing of soil moisture and environmental conditions inside the greenhouse could be a robust, accurate, and cost-effective tool for irrigation management.

EFFECT OF IRRIGATION AND PLANT POPULATION ON YIELD, FRUIT SPECK AND BLOSSOM-END ROT OF PROCESSING TOMATOES

1985 ◽  
Vol 65 (4) ◽  
pp. 1011-1018 ◽  
Author(s):  
C. S. TAN ◽  
B. N. DHANVANTARI
Keyword(s):  
Soil Moisture ◽  
Lycopersicon Esculentum ◽  
Pseudomonas Syringae ◽  
Tomato Fruit ◽  
Plant Population ◽  
Southern Ontario ◽  
Available Soil Moisture ◽  
Blossom End Rot ◽  
Irrigation Effects ◽  
Processing Tomatoes

Two tomato (Lycopersicon esculentum Mill.) cultivars, Heinz-2653 and Campbell-28, were grown on Fox loamy sand in the subhumid region of southern Ontario from 1979 to 1982. Irrigation increased the marketable yields of H-2653 in a dry year, 1982, but not in the other years. Irrigation substantially increased marketable yields of C-28 in 1979 and 1982. Irrigation, when the available soil moisture (ASM) level reached 50%, was no more effective than when the ASM level in the soil was allowed to drop to 25%. Without irrigation yield increased as plant population increased in normal and wet years, but not in a dry year. Blossom-end rot (BER) of C-28 cultivar was markedly reduced by irrigation. Effects of irrigation or plant population treatments on the incidence of fruit speck did not appear to be significant.Key words: Available soil moisture, Lycopersicon esculentum, Pseudomonas syringae pv. tomato, fruit speck

Performance of soil moisture sensors in gypsiferous and salt-affected soils

2021 ◽  
Vol 209 ◽  
pp. 200-209
Author(s):  
Adil K. Salman ◽  
Saad E. Aldulaimy ◽  
Huthaifa J. Mohammed ◽  
Yaareb M. Abed
Keyword(s):  
Soil Moisture ◽  
Soil Moisture Sensors ◽  
Salt Affected Soils

Soil moisture assessment based on Sentinel 1/2 and in-situ data: The vineyard case study

2021 ◽  
Author(s):  
Maria Paula Mendes ◽  
Ana Paula Falcão ◽  
Magda Matias ◽  
Rui Gomes
Keyword(s):  
Soil Moisture ◽  
Climate Models ◽  
Root Zone ◽  
Irrigation Management ◽  
Management Strategies ◽  
Winter Period ◽  
Classification Algorithms ◽  
Precipitation Regime ◽  
Terrain Attributes ◽  
Sentinel 2

<p>Vineyards are crops whose production has a major economic impact in the Portuguese economy (~750 million euros) being exported worldwide. As the climate models project a larger variability in precipitation regime, the water requirements of vineyards can change and drip irrigation can be responsible for salt accumulation in the root zone, especially when late autumn and winter precipitation is not enough to leach salts from the soil upper horizons, turning the soil unsuitable for grape production.</p><p>The aim of this work is to present a methodology to map surface soil moisture content (SMC) in a vineyard, (40 hectares) based on the application of two classification algorithms to satellite imagery (Sentinel 1 and Sentinel 2). Two vineyard plots were considered and three field campaigns (December 2017, January 2018 and May 2018) were conducted to measure soil moisture contents (SMC). A geostatistical method was used to estimate the SM class probabilities according to a threshold value, enlarging the training set (i.e., SMC data of the two plots) for the classification algorithms. Sentinel-1 and Sentinel-2 images and terrain attributes fed the classification algorithms. Both methods, Random Forest and Logistic Regression, classified the highest SMC areas, with probabilities above 14%, located close to a stream at the lower altitudes.</p><p>RF performed very well in classifying the topsoil zones with lower SMC during the autumn-winter period (F-measure=0.82).</p><p>This delineation allows the prevention of the occurrence of areas affected by salinization, indicating which areas will need irrigation management strategies to control the salinity, especially under climate change, and the expected increase in droughts.</p>

scholarly journals Design a Monitoring and Control in Irrigation Systems using Arduino Wemos with the Internet of Things

2021 ◽  
Vol 1 (1) ◽  
pp. 53-64
Author(s):  
Lukman Medriavin Silalahi ◽  
Setiyo Budiyanto ◽  
Freddy Artadima Silaban ◽  
Arif Rahman Hakim
Keyword(s):  
Soil Moisture ◽  
Water Level ◽  
Irrigation System ◽  
Ground Level ◽  
Prototype System ◽  
Monitoring And Control ◽  
Moisture Sensor ◽  
Turn On ◽  
Soil Moisture Sensors ◽  
Level Sensor

Irrigation door is a big issue for farmers. The factor that became a hot issue at the irrigation gate was the irresponsible attitude of the irrigation staff regarding the schedule of opening/closing the irrigation door so that it caused the rice fields to becoming dry or submerged. In this research, an automatic prototype system for irrigation system will be designed based on integrating several sensors, including water level sensors, soil moisture sensors, acidity sensors. This sensor output will be displayed on Android-based applications. The integration of communication between devices (Arduino Nano, Arduino Wemos and sensors supporting the irrigation system) is the working principle of this prototype. This device will control via an Android-based application to turn on / off the water pump, to open/close the irrigation door, check soil moisture, soil acidity in real time. The pump will automatically turn on based on the water level. This condition will be active if the water level is below 3cm above ground level. The output value will be displayed on the Android-based application screen and LCD screen. Based on the results of testing and analysis of the prototype that has been done in this research, the irrigation door will open automatically when the soil is dry. This condition occurs if the water level is less than 3 cm. The calibrated Output value, including acidity sensor, soil moisture sensor and water level sensor, will be sent to the server every 5 seconds and forwarded to an Android-based application as an output display.

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