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Decision support systems and models for aiding irrigation and nutrient management of vegetable crops

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  • Gallardo, Marisa
  • Elia, Antonio
  • Thompson, Rodney B.

Abstract

Vegetable growers in Europe are continually under increasing pressure to optimize irrigation and nutrient management. This results from the widespread effects of climate change and of competition from other sectors for water, and increasing societal pressure to reduce nutrient contamination of water bodies. The widespread and growing adoption of drip irrigation and fertigation provides vegetable growers with the technical infrastructure for greatly improved irrigation and nutrient management. However, quantitative decisions to achieve optimal irrigation and nutrient management, and increasingly of the two together, require complex decision-making. Numerous factors regarding climate, soil characteristics, field infrastructure, and crop characteristics need to be considered. Decision Support Systems (DSSs) and simulation models are tools that process large and diverse amounts of information to provide irrigation and nutrient recommendations that are specific to individual crops and sites. Commonly, DSSs incorporate simulation models, which enables site and crop specific assessment, and the possibility for dynamic responses to fluctuations in climate etc. There is an on-going trend for web-based DSSs that can access on-line data bases such as of climate and soil data, and that users consult with smartphone Apps. This article firstly reviews several general aspects regarding the use of DSSs/models in commercial vegetable production, such as how to enhance their user-friendliness. Subsequently, it describes DSSs/models that have been developed or are being used to assist with irrigation or nutrient management, or both, of vegetable crops. The most relevant aspects of these DSSs/models are highlighted. In addition to DSSs/models for practical on-farm management, the use of DSSs/models for scenario analysis to demonstrate theoretical case studies to policy makers, growers and advisors is discussed. A focus throughout is on how to make these products attractive and effective to potential users. The geographical focus is on Europe; however, particularly relevant cases from elsewhere are also considered. With the current state of Information and Communication Technology (ICT), and considering the inevitable future developments, DSSs can provide vegetable growers with effective and user-friendly tools to assist them to optimize irrigation and nutrient management.

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  • Gallardo, Marisa & Elia, Antonio & Thompson, Rodney B., 2020. "Decision support systems and models for aiding irrigation and nutrient management of vegetable crops," Agricultural Water Management, Elsevier, vol. 240(C).
    • Handle: RePEc:eee:agiwat:v:240:y:2020:i:c:s0378377420303267
    DOI: 10.1016/j.agwat.2020.106209
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    Cited by:

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    5. Tei, Francesco & De Neve, Stefaan & de Haan, Janjo & Kristensen, Hanne Lakkenborg, 2020. "Nitrogen management of vegetable crops," Agricultural Water Management, Elsevier, vol. 240(C).
    6. Mar Carreras-Sempere & Rafaela Caceres & Marc Viñas & Carmen Biel, 2021. "Use of Recovered Struvite and Ammonium Nitrate in Fertigation in Tomato ( Lycopersicum esculentum ) Production for boosting Circular and Sustainable Horticulture," Agriculture, MDPI, vol. 11(11), pages 1-15, October.
    7. Xu, Xiangying & Wang, Chao & Wang, Hongjiang & Zhang, Yonglong & Cao, Zhuangzhuang & Zhang, Zhiping & Dai, Haibo & Miao, Minmin, 2023. "Development and performance evaluation of an APP for vegetable fertilization and irrigation management originated from EU-Rotate_N," Agricultural Water Management, Elsevier, vol. 289(C).
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    9. Campana, P.E. & Lastanao, P. & Zainali, S. & Zhang, J. & Landelius, T. & Melton, F., 2022. "Towards an operational irrigation management system for Sweden with a water–food–energy nexus perspective," Agricultural Water Management, Elsevier, vol. 271(C).
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    11. Gallego-Elvira, B. & Reca, J. & Martin-Gorriz, B. & Maestre-Valero, J.F. & Martínez-Alvarez, V., 2021. "Irriblend-DSW: A decision support tool for the optimal blending of desalinated and conventional irrigation waters in dry regions," Agricultural Water Management, Elsevier, vol. 255(C).
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    13. Savvas, Dimitrios & Giannothanasis, Evangelos & Ntanasi, Theodora & Karavidas, Ioannis & Drakatos, Stefanos & Panagiotakis, Ioannis & Neocleous, Damianos & Ntatsi, Georgia, 2023. "Improvement and validation of a decision support system to maintain optimal nutrient levels in crops grown in closed-loop soilless systems," Agricultural Water Management, Elsevier, vol. 285(C).
    14. Alexander Kocian & Luca Incrocci, 2020. "Learning from Data to Optimize Control in Precision Farming," Stats, MDPI, vol. 3(3), pages 1-7, July.
    15. Benjamin Ruch & Margita Hefner & André Sradnick, 2023. "Excessive Nitrate Limits the Sustainability of Deep Compost Mulch in Organic Market Gardening," Agriculture, MDPI, vol. 13(5), pages 1-13, May.
    16. So Pyay Thar & Thiagarajah Ramilan & Robert J. Farquharson & Deli Chen, 2021. "Identifying Potential for Decision Support Tools through Farm Systems Typology Analysis Coupled with Participatory Research: A Case for Smallholder Farmers in Myanmar," Agriculture, MDPI, vol. 11(6), pages 1-20, June.
    17. Sotirios Pilafidis & Eleftherios Kosmas & Ioannis Livieratos & Vasileios D. Gkisakis, 2024. "Assessing energy use and greenhouse gas emissions in Cretan vineyards for the development of a crop-specific decision support tool," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(9), pages 24415-24452, September.
    18. Gallardo, Marisa & Peña-Fleitas, María Teresa & Giménez, Carmen & Padilla, Francisco M. & Thompson, Rodney B., 2023. "Adaptation of VegSyst-DSS for macronutrient recommendations of fertigated, soil-grown, greenhouse vegetable crops," Agricultural Water Management, Elsevier, vol. 278(C).

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