Fuzzy cognitive map based approach for predicting yield in cotton crop production as a basis for decision support system in precision agriculture application

Scientific researchers have applied newly developed technologies, such as sensors and actuators, to different fields, including environmental monitoring, traffic management, and precision agriculture. Using agricultural technology to assist crop fertilization is an important research innovation that can not only reduce the workload of farmers, but also reduce resource waste and soil pollution. This paper describes the design and development of a water-fertilizer control system based on the soil conductivity threshold. The system uses a low-cost wireless sensor network as a data collection and transmission tool and transmits the data to the decision support system. The decision support system considers the change in soil electrical conductivity (EC) and moisture content to guide the application of water-fertilizer, and then improves the fertilization accuracy of the water-fertilizer control system. In the experiment, the proposed water-fertilizer control system was tested, and it was concluded that, compared with the existing traditional water-fertilizer integration control system, the amount of fertilizer used by the system was reduced by 10.89% on average, and it could save 0.76–0.87 tons of fertilizer throughout the whole growth period of cotton.

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CropSAT – A Decision Support System for Practical Use of Satellite Images in Precision Agriculture

Advances in Smart Technologies Applications and Case Studies - Lecture Notes in Electrical Engineering ◽

10.1007/978-3-030-53187-4_45 ◽

2020 ◽

pp. 415-421

Author(s):

Omran Alshihabi ◽

Kristin Piikki ◽

Mats Söderström

Keyword(s):

Decision Support ◽

Decision Support System ◽

Support System ◽

Precision Agriculture ◽

Satellite Images

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Weed Control Decision Support System Based on Precision Agriculture Approach

TELKOMNIKA (Telecommunication Computing Electronics and Control) ◽

10.12928/telkomnika.v12i2.1982 ◽

2014 ◽

Vol 12 (2) ◽

pp. 475

Author(s):

Rizky Mulya Sampurno ◽

Kudang Boro Seminar ◽

Yuli Suharnoto

Keyword(s):

Decision Support ◽

Decision Support System ◽

Weed Control ◽

Support System ◽

Precision Agriculture ◽

Control Decision

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An Integrated Decision Support System for Intercropping

International Journal of Decision Support System Technology ◽

10.4018/jdsst.2010070104 ◽

2010 ◽

Vol 2 (3) ◽

pp. 51-66 ◽

Cited By ~ 3

Author(s):

A. S. Sodiya ◽

A. T. Akinwale ◽

K. A. Okeleye ◽

J. A. Emmanuel

Keyword(s):

Decision Support ◽

Decision Support System ◽

Support System ◽

Crop Production ◽

Large Scale ◽

Weather Condition ◽

Agricultural Practice ◽

Pests And Diseases ◽

General Decline ◽

Fertility Protection

Intercropping, which is the agricultural practice of growing two or more crops in the same land area, is not currently yielding adequate results in Africa. Despite the advantages of intercropping like improved soil fertility, protection against pests and diseases and eventual increase in farm yield, this farming practice is faced with challenges—inadequate planning, bad crop management and lack of required intercropping expertise. Consequently, this has resulted in inadequate reward for farmers and a general decline in crop production. In this regard, the authors present an Intelligent and Integrated Intercropping Decision Support System for Intercropping (IDSS-I) for improved crop production. The design adopts a forecasting component that provides farmers with the estimated yield and income depending on the size of land, soil type and weather condition. Although the implementation was carried out using JAVA and SQL, usability testing revealed 85% acceptance of the tool among the contacted 10 large scale farmers. It was also confirmed that the system provided 95% diagnosis information for 90% common Africa crop diseases.

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