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Related Experiment Video

Updated: Jun 24, 2026

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images

Published on: February 2, 2019

Remote-sensing of crop yields.

S B Idso, R D Jackson, R J Reginato

Science (New York, N.Y.)

|April 1, 1977

Summary

The Stress-Degree-Day (SDD) concept enables crop yield estimation using remote sensing of canopy and air temperatures during critical growth stages. This method also shows potential for remote sensing-based irrigation scheduling in durum wheat.

Area of Science:

Agricultural Science
Remote Sensing Technology
Crop Physiology

Background:

Durum wheat yield prediction and irrigation management are critical for food security.
Accurate crop monitoring requires integrating environmental data with plant physiological responses.
Remote sensing offers a non-invasive approach to assess crop status over large areas.

Purpose of the Study:

To introduce and validate the Stress-Degree-Day (SDD) concept for durum wheat.
To assess the feasibility of using remote sensing for crop yield estimation.
To explore the potential of SDD for remote sensing-based irrigation scheduling.

Main Methods:

Development of the Stress-Degree-Day (SDD) concept based on canopy and air temperatures.
Utilizing remotely acquired canopy temperature and auxiliary air temperature data.

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Employing canopy albedo measurements to define critical growth periods.

Generating trifactor nomograms from linear regression equations.

Main Results:

The SDD concept allows for crop yield estimation using remote sensing data.
Canopy albedo measurements effectively delineate the critical growth period for SDD application.
The developed technique shows potential for remote sensing-based crop yield prediction.
Trifactor nomograms indicate the SDD concept's utility for remote irrigation scheduling.

Conclusions:

The SDD concept provides a viable method for durum wheat yield estimation via remote sensing.
Remote sensing of canopy temperature and albedo can delineate critical growth phases.
SDD holds promise for optimizing irrigation management through remote sensing technology.