Irrigator Pro: Progression of a Peanut Irrigation Scheduling Decision Support System

2020 ◽  
Vol 36 (5) ◽  
pp. 785-795
Author(s):  
Christopher L Butts ◽  
Ronald B Sorensen ◽  
Marshall C Lamb
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Soil Temperature ◽  
Water Potential ◽  
Soil Water ◽  
Support System ◽  
Soil Water Potential ◽  
Irrigation Scheduling ◽  
List Type ◽  
Web Based

HighlightsThe logic used in developing a decision support system for irrigating peanut based on max/min soil temperature is describedLogic to transform decision support system from peanut to irrigate corn and cotton with and without soil sensors.Progression of a decision support system from a desktop program to a web/mobile applicationAbstract. Irrigator Pro is a decision support tool for scheduling irrigation events in peanut. It was deployed in 1995 as a rule-based system using crop history, yield potential, soil type, in-season irrigation/rainfall and maximum/minimum soil temperature. As computing platforms have progressed from desktop personal computers to mobile web-based platforms, Irrigator Pro has been updated and is now deployed as a web-based program and an application for mobile devices. Irrigator Pro not only works for peanuts but has been modified to irrigate both corn and cotton. The irrigation decisions are now based on in-field soil water potential measurements in addition to the traditional checkbook with max/min soil temperatures. Users are individual growers, extension agents, and agronomic consultants. The objective of this manuscript is to document the initial development of Irrigator Pro as an expert system combining data and experiential knowledge and the progression from a checkbook-based decision support system to a hybrid system using observed weather data and soil moisture measurement. The background knowledge, equations, and thresholds for triggering irrigation recommendations are included. Keywords: Decision support system, Irrigation scheduling, Irrigator Pro, Mobile app, Peanut, Soil water potential.

scholarly journals Soil Moisture Sensor Test with Mississippi Delta Soils

2019 ◽  
Vol 62 (2) ◽  
pp. 363-370
Author(s):  
Ruixiu Sui ◽  
Horace C. Pringle ◽  
Edward M. Barnes
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Water Potential ◽  
Water Content ◽  
Soil Water ◽  
Measurement Accuracy ◽  
Mississippi Delta ◽  
Soil Water Potential ◽  
Gravimetric Method ◽  
Irrigation Scheduling

Abstract. One of the methods for irrigation scheduling is to use sensors to measure the soil moisture level in the plant root zone and apply water if there is a water shortage for the plants. The measurement accuracy and reliability of the soil moisture sensors are critical for sensor-based irrigation management. This study evaluated the measurement accuracy and repeatability of the EC-5 and 5TM soil volumetric water content (SVWC) sensors, the MPS-2 and 200SS soil water potential (SWP) sensors, and the 200TS soil temperature sensor. Six 183 cm × 183 cm × 71 cm wooden compartments were built inside a greenhouse, and each compartment was filled with one type of soil from the Mississippi Delta. A total of 66 sensors with 18 data loggers were installed in the soil compartments to measure SVWC, SWP, and soil temperature. Soil samples were periodically collected from the compartments to determine SVWC using the gravimetric method. SVWC measured by the sensors was compared with that determined by the gravimetric method. The SVWC readings from the sensors had a linear regression relationship with the gravimetric SVWC (r2 = 0.82). This relationship was used to calibrate the sensor readings. The SVWC and SWP sensors could detect the general trend of soil moisture changes. However, their measurements varied significantly among the sensors. To obtain accurate absolute soil moisture measurements, the sensors require individual and soil-specific calibration. The 5TM, MPS-2, and 200TS sensors performed well in soil temperature measurement tests. Individual temperature readings from these sensors were very close to the mean of all sensor readings. Keywords: Irrigation, Sensors, Soil types, Soil water content, Soil water potential.

AQUAMAN: a web-based decision support system for irrigation scheduling in peanuts

2011 ◽  
Vol 31 (3) ◽  
pp. 271-283 ◽  
Author(s):  
Yashvir S. Chauhan ◽  
Graeme C. Wright ◽  
Dean Holzworth ◽  
Rao C. N. Rachaputi ◽  
José O. Payero
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Irrigation Scheduling ◽  
Web Based

IrrigaSys – a decision support system for irrigation management in the Sorraia Valley region, Portugal

2020 ◽  
Author(s):  
Lucian Simionesei ◽  
Tiago B. Ramos ◽  
Jorge Palma ◽  
Ana R. Oliveira ◽  
Ramiro Neves
Keyword(s):  
Decision Support ◽  
Water Balance ◽  
Decision Support System ◽  
Soil Water ◽  
Support System ◽  
Weather Forecast ◽  
Irrigation Scheduling ◽  
Mobile App ◽  
Soil Water Balance ◽  
Sentinel 2

<p>IrrigaSys is a decision support system (DSS) for irrigation water management based on online, open<br>access tools. The system includes remote access to local meteorological stations for weather<br>conditions, a MM5 model for weather forecast, the MOHID-Land model for the computation of the<br>soil water balance and irrigation scheduling, and a MySQL database for data repository. Despite its<br>complexity, the data necessary to run IrrigaSys is minimal, and include the location of the agricultural<br>field, crop type, sowing and harvest dates, soil texture, irrigation method, and daily/weekly irrigation<br>depths applied by the farmer. Based on this information, the system automatically downloads the<br>weather data from the meteorological station located closest to the agricultural plot, as well as the<br>weather forecast for the seven days following the current date. The soil water balance is then<br>computed for the previous and following week as well as the crop irrigation needs using the MOHIDLand<br>model. Results are made available via a web interface, a mobile app, SMS, and email. Besides the<br>model outputs, the IrrigaSys further provides the Normalized Difference Vegetation Index (NDVI) for<br>the agricultural field. The NDVI is computed from Sentinel 2 spectral bands with a resolution of 10m,<br>and is updated every time new Sentinel 2 imagery data (with cloud cover < 10%) is available. The<br>IrrigaSys has been developed in close cooperation with the Water Board Association of the Sorraia<br>Valley irrigation district (15360 ha), southern Portugal, over the last 5 years, supporting 103 plots of<br>30 farmers during the last irrigation season. As a result, the main limitation is naturally associated to<br>the difficulty in providing reliable estimates for all field plots based on calibrated model data. As the<br>next step, the service should start automatically identifying the culture status based on satellite<br>information as well as providing fertigation recommendations to farmers.</p>

Perancangan Sistem Pendukung Keputusan Pemilihan Pelanggan Terbaik Menggunakan Metode Simple Additive Weighting (SAW) Pada Bravo Supermarket Jombang

2016 ◽  
Vol 2 (1) ◽  
pp. 40
Author(s):  
Fatikhatus Sholikhah ◽  
Diema Hernyka Satyareni ◽  
Chandra Sukma Anugerah
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Customer Loyalty ◽  
Design Decision ◽  
Web Based ◽  
Business World ◽  
Election System ◽  
Simple Additive Weighting ◽  
The Town

Abstrak Persaingan merupakan hal yang biasa terjadi terutama dalam dunia bisnis, tidak terkecuali yang telah dialami oleh Bravo Supermarket Jombang. Bravo bukanlah satu-satunya supermarket di kota Jombang, sehingga Bravo harus bersaing dengan para kompetitornya agar Bravo bisa bersaing dan tetap produktif. Salah satu cara yang dapat digunakan dalam meningkatkan penjualan dan loyalitas pelanggan adalah dengan memberikan reward kepada para pelanggan terbaik. Oleh karena itu perlu dibuatlah sebuah perancangan sistem pendukung keputusan dalam pemilihan pelanggan terbaik pada Bravo. Dalam perancangan sistem yang dibuat nantinya berbasis web dengan metode SAW(Simple Additive Weighting)sebagai proses perhitungan pemilihan pelanggan terbaik. Hasil dari perancangan sistem pemilihan pelanggan terbaik pada Bravo Supermarket Jombang diharapkan dapat membantu pihak manajemen Bravo dalam pemilihan pelanggan terbaik yang akan menerima reward dan akhirnya akan mampu meningkatkan loyalitas pelanggan dan profit Bravo. Kata kunci: Bravo, sistem pendukung keputusan, pelanggan, SAW. Abstract Competition is a common thing, especially in the business world, is no exception has been experienced by Bravo Supermarket Jombang. Bravo is not the only supermarket in the town of Jombang, so that Bravo had to compete with its competitors in order Bravo to compete and remain productive. One way that can be used to increase sales and customer loyalty is to give rewards to the best customers. Therefore, it needs to be made to a design decision support system in the selection of the best customers on Bravo. In designing the system made later on a web-based method of SAW (Simple Additive weighting) as the process of calculating the best customer selection. The results of the election system design best customers at Bravo Supermarket Jombang expected to assist management in selecting the best customer Bravo who will receive rewards and will eventually be able to increase customer loyalty and profit Bravo. Key word: Bravo, decision support system, customers, SAW.

IMPLEMENTASI TEOREMA NAÏVE BAYES PADA SISTEM PENDUKUNG KEPUTUSAN UNTUK MENENTUKAN REKOMENDASI TEMPAT WISATA TERBAIK DISULAWESI SELATAN

2019 ◽  
Vol 2 (1) ◽  
pp. 40-46
Author(s):  
Rikardo Chandra ◽  
Izmy alwiah Musdar ◽  
Junaedy .
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Programming Language ◽  
Support System ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Web Based ◽  
Tourist Attractions ◽  
South Sulawesi

This study aims to design and build web-based decision support system applications used to recommend the best tourist attractions in South Sulawesi to tourists. The expected benefit of this research is to help the user get the best tourist recommendation information available in South Sulawesi based on the conditions in input factors. The theorem or method used in this study, namely the theorem Naïve Bayes. The design of the system isimplemented using PHP programming language and MYSQL database. Based on the results of the research, the authors have successfully built the application of decision support system to determine the recommendation of tourist attractions in South Sulawesi with 65% accuracy based on 20 tests conducted.

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