In semi-arid areas of the world agriculture is often challenged by numerous interconnected issues that are related to water availability, soil deterioration, climate fluctuations and increased susceptibility of crops to environmental and biological stress factors. As many of these factors seldom exist alone, the relationships between irrigation practices, the status of the soil and the health of plants develop and evolve over time through multiple interactions at different spatial and temporal levels. Yet, many current decision support tools are limited to single agronomic criteria; therefore, they do not adequately address the complexities of managing agricultural production under realistic field conditions. In response to the need for integrated crop management, this research addresses the dynamic interdependencies of soil, water and plant health in semi-arid agricultural systems. Therefore, the emphasis of this proposed methodology will be on coordinated interpretation versus separate prediction capabilities which will result in decision making that is both consistent with agronomic best practices and more reliable. Through analysis of soil moisture variability, irrigation sensitivities and disease pressures from an integrated point of view, the objectives of this research are to demonstrate that multidimensional decision-making processes may lead to improved crop resilience and decreased risk associated with management decisions. Ultimately, the objective of this research is to emphasize the need for comprehensive decision support tools that support sustainable and adaptable agricultural production in data-limited, semi-arid environments.
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M. El Mouedden
Driss Azdem
Jamal Mabrouki
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Mouedden et al. (Wed,) studied this question.
www.synapsesocial.com/papers/6988291e0fc35cd7a8849254 — DOI: https://doi.org/10.1051/bioconf/202621503014/pdf
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