Development and Field Validation of a Smartphone-Based Web Application for Diagnosing Optimal Timing of Mid-Season Drainage in Rice Cultivation via Canopy Image-Derived Tiller Estimation

  • 0Chiba Prefectural Agriculture and Forestry Research Center, Chiba Prefectural Office, 180-1 Ookanazawa-Cho, Midori-Ku, Chiba-City 266-0014, Japan.

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Summary

This summary is machine-generated.

A new smartphone app estimates rice tiller numbers from canopy images to determine optimal midseason drainage timing. This technology aids farmers in improving rice quality and water management in warm regions.

Area Of Science

  • Agricultural Science
  • Agronomy
  • Crop Science

Background

  • High temperatures during early rice growth cause excessive tillering, leading to quality deterioration in warm regions.
  • Precise midseason drainage timing is crucial for rice production but is challenging due to yearly and cultivar variations.

Purpose Of The Study

  • To develop a smartphone-based application for estimating rice tiller numbers and determining optimal midseason drainage timing.
  • To provide farmers with a tool for labor-saving and improved water management in rice cultivation.

Main Methods

  • Developed a smartphone web application utilizing HTML5 canvas for pixel extraction and JavaScript for computation.
  • Employed Google Apps Script for backend processing to estimate tiller numbers from canopy images.
  • Conducted field experiments with three rice cultivars to validate the system's accuracy.

Main Results

  • A strong linear relationship was observed between estimated and actual tiller numbers (R² = 0.9439).
  • The system showed a root mean square error (RMSE) of 42.6 tillers m⁻², with a slight underestimation bias.
  • The error margin was deemed acceptable for decision-making, corresponding to 1-3 days of growth progression.

Conclusions

  • The smartphone application reliably estimates relative rice growth dynamics and supports drainage timing decisions.
  • This innovative approach offers rapid, on-site decision support for rice farmers using only a smartphone.
  • The system contributes to labor savings and enhanced water management practices in rice production.

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