Spatial Rice Decision Support System for Effective Rice Crop Management

Sailaja, B.; Voleti, S. R.; Subrahmanyam, D.; Rao, P. Raghuveer; Gayatri, Siwi; Kumar, Rajeev; Meera, Shaik N.

doi:10.18520/cs/v116/i3/412-421

Cited by 9 publications

(5 citation statements)

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“…• More advances in DSSs development include; SRDSS [78] a spatial rice decision support system that primarily helps researchers, managers and planners to evaluate optimum rice sowing dates, management practices and yield for a set target yield in different locations. Geographic Information Systems (GISs)…”

Section: Other Dsssmentioning

confidence: 99%

Assessing Suitability of Irrigation Scheduling Decision Support Systems for Lowland Rice Farmers in Sub-Saharan Africa—A Review

Mubangizi¹,

Wanyama²,

Kiggundu³

et al. 2023

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Irrigation in lowland rice production systems in Sub-Saharan Africa (SSA) is mainly based on traditional surface irrigation methods with continuous flooding practices. This irrigation method ends up using a lot more water that would have otherwise been used to open more land and be used in other water-requiring sectors. Various studies suggest Alternate Wetting and Drying (AWD) as an alternative practice for water management that reduces water use without significantly affecting yield. However, this practice has not been well adopted by the farmers despite its significant benefits of reduced total water use. Improving the adoption of AWD using irrigation Decision Support Systems (DSSs) helps the farmer on two fronts; to know "how much water to apply" and "when to irrigate", which is very critical in maximizing productivity. This paper reviews the applicability of DSSs using AWD in lowland rice production systems in Sub-Saharan Africa.

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Section: Other Dsssmentioning

confidence: 99%

Assessing Suitability of Irrigation Scheduling Decision Support Systems for Lowland Rice Farmers in Sub-Saharan Africa—A Review

Mubangizi¹,

Wanyama²,

Kiggundu³

et al. 2023

View full text Add to dashboard Cite

show abstract

“…This is very useful information for both farmers for implementing necessary management practices and for authorities in arriving at accurate production estimates. While manly researchers have used RSbased vegetation indices and GIS for predicting crop yields, several researchers have combined GIS with crop simulation or physiological models and demonstrated their strong performance in yield prediction [116][117][118][119]. Crop simulation models came into prominence due to their utility in designing management practices, assessing the role of climate variations on crop performance, and predicting yields [120,121].…”

Section: Geographic Information Systems and Applications In Coastal S...mentioning

confidence: 99%

Geographic Information Systems and Applications in Coastal Studies

2022

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This book provides a comprehensive overview of techniques, approaches, and experiences in the rapidly growing field of geographical information systems (GIS) in coastal zones. It focuses on advances in GIS technology and applications. Most of the work represented in this book is based on innovative applications of geographic information in coastal environments and disasters, coastal resources, coastal social systems, and coastal urban environments as well as applications of new algorithms, big data processing, and deep learning at global, regional, or local scales. Specifically, the chapters discuss GIS in coastal asset mapping and management, shoreline change analysis, development of ancient cities, agriculture and land suitability analysis, solid waste management, impact of COVID-19 measures on air quality, dynamic modelling of LULC, strategic planning of hydroelectric projects, groundwater potential zone identification, and road optimization for effective management traffic and transport. This volume is a useful resource for those who have used GIS for monitoring, modeling, planning, and policymaking in earth sciences and coastal studies.

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“…The flow process is designed to help farmers make decisions through information dissemination. Therefore, a system capable of evaluating land suitability is needed to make it easier for those in need of crucial information on land productivity, such as farmers, to determine the right suitable crops to be grown in peatlands [22]. This is because the process of assessing and processing large amounts of data is always carried out quickly using a computerized process [17].…”

Section: Conceptual Reviewmentioning

confidence: 99%

Evaluation of Peatland Suitability for Rice Cultivation using Matching Method

Dalle¹,

Hastuti²,

Akmal³

2021

Pol. J. Environ. Stud.

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One of the common problems with peatlands is the infertile nature of the soil, therefore, farmers need to possess adequate knowledge on land evaluation techniques within a limited period to grow crops in this region optimally. Therefore, this research aims to design and build a computerized system to evaluate the suitability of land for rice cultivation by using the matching method based on FAO guidelines. This study develops a web application that enables users to store the various characteristics of the land and easily output suitable information with limiting factors. A total of 14 data inputs with 22 land characteristics parameters were used in the system trial phase. The result showed that the system testing results when compared with the manual calculations, obtained a 92.86% level of accuracy. Therefore, further research is needed on the use of the application on land suitability evaluation for growing other types of crops apart from lowland rice. In addition, the input parameters can be adjusted based on future land suitability evaluations, with the system developed to evaluate the criteria and pave the way for future research development in the field.

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Spatial Rice Decision Support System for Effective Rice Crop Management

Cited by 9 publications

References 0 publications

Assessing Suitability of Irrigation Scheduling Decision Support Systems for Lowland Rice Farmers in Sub-Saharan Africa—A Review

Assessing Suitability of Irrigation Scheduling Decision Support Systems for Lowland Rice Farmers in Sub-Saharan Africa—A Review

Geographic Information Systems and Applications in Coastal Studies

Evaluation of Peatland Suitability for Rice Cultivation using Matching Method

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