What question did this study set out to answer?

To review the current applications, opportunities, and limitations of artificial intelligence technologies in optimizing agricultural irrigation scheduling and nutrient management.

September 25, 2023International Journal of Environment and Climate ChangeOpen Access

Optimizing Irrigation and Nutrient Management in Agriculture through Artificial Intelligence Implementation

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Authors

JKJeetendra KumarJawaharlal Nehru Medical College RCRitik ChawlaLovely Professional University DKDrishty KatiyarIntegral University

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Implication

Comprehensive review demonstrates AI-driven optimization of irrigation and nutrient management in agriculture, highlighting pathways to enhance crop yield and resource conservation.

Key Points

To review the current applications, opportunities, and limitations of artificial intelligence technologies in optimizing agricultural irrigation scheduling and nutrient management.
Synthesized recent research literature and case studies on the integration of artificial intelligence into agricultural management.
Evaluated the roles of machine learning, remote sensing, and data analytics alongside implementation barriers such as data quality, model interpretability, and farmer adoption.
Artificial intelligence models enhance the precision of irrigation timing and targeted nutrient application, supporting resource conservation and improved crop yield.
Adoption is primarily constrained by challenges involving variable data quality, lack of algorithmic interpretability, and low farmer trust and acceptance.

Cite This Study

Kumar et al. (2023) studied this question.

synapsesocial.com/papers/6a708e0bfebe604dd709531c https://doi.org/10.9734/ijecc/2023/v13i103077

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Implication

Comprehensive review demonstrates AI-driven optimization of irrigation and nutrient management in agriculture, highlighting pathways to enhance crop yield and resource conservation.

Optimizing Irrigation and Nutrient Management in Agriculture through Artificial Intelligence Implementation

Discussion

Member takes

Implication

Key Points

Cite This Study

Optimizing Irrigation and Nutrient Management in Agriculture through Artificial Intelligence Implementation

Discussion

Member takes

Implication

Key Points

Cite This Study

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