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September 10, 2025Agricultural Power Journal

Integrative Application of Deep Learning and Multispectral Remote Sensing for Predictive Crop Management in Precision Agriculture

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ZHZuhra Hariati

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Overview

This integrative approach improves crop classification accuracy by 97.8% using multispectral data and deep learning, suggesting better resource efficiency in agriculture.

Key Points

  • The deep learning model achieved up to 97.8% accuracy in crop classification, outpacing traditional methods.
  • Predicted crop conditions showed a strong correlation (r = 0.89) with actual field data, validating the model's effectiveness.
  • Field implementation indicated potential yield increases of 18% along with a 28% reduction in agricultural input usage.
  • The approach offers strong scalability for various crop types and regions, enhancing sustainability in precision farming.

Cite This Study

Zuhra Hariati (2024) studied this question.

synapsesocial.com/papers/68c1e07554b1d3bfb60fcd5fhttps://doi.org/10.70076/apj.v1i2.80
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