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Calibrating ultrasonic sensor measurements of crop canopy heights: a case study of maize and wheat

  • 0College of Water Resources and Civil Engineering, China Agricultural University, Beijing, China.
Frontiers in Plant Science +

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June 21, 2024

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June 21, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Ultrasonic sensors offer a low-cost method for measuring crop height, crucial for field management. Integrating normalized difference vegetation index (NDVI) with ultrasonic data significantly improved measurement accuracy for maize and wheat.

Area Of Science

  • Agricultural Engineering
  • Remote Sensing
  • Crop Science

Background

  • Canopy height is a key indicator of crop growth and informs field management decisions.
  • Ultrasonic sensors provide an inexpensive, durable solution for continuous crop height data collection.
  • Existing ultrasonic measurement accuracy is limited by acoustic wave properties and crop canopy structure.

Purpose Of The Study

  • To enhance the accuracy of ultrasonic sensor-based crop height measurements.
  • To investigate factors influencing ultrasonic measurement accuracy in maize and wheat.
  • To develop a calibration model for improved canopy height assessment.

Main Methods

  • Conducted a four-year field experiment (2018-2021) on maize and wheat.
  • Developed a measurement platform and performed single-factor experiments on observation angle, height, period, speed, density, and growth stage.
  • Constructed a double-input factor calibration model using normalized difference vegetation index (NDVI) and ultrasonic measurements via the least-squares method.

Main Results

  • Observation angle and planting density were significant factors affecting ultrasonic measurements (p<0.05).
  • The developed calibration model integrating NDVI and ultrasonic data significantly improved measurement accuracy.
  • Achieved root mean squared errors (RMSE) of 81.4-93.6 mm for maize and 37.1-47.2 mm for wheat.

Conclusions

  • Ultrasonic sensors, when calibrated with NDVI, offer an effective method for non-destructive crop height monitoring.
  • The integration of low-cost sensors with agricultural machinery platforms enables efficient crop information acquisition.
  • This approach supports precision agriculture by providing reliable crop height data for management decisions.

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