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A Method for Growing Bio-memristors from Slime Mold

A Method for Growing Bio-memristors from Slime Mold

Published on: November 2, 2017

A new nonlinear method for calculating growing degree days.

Guanglin Zhou^1,2, Quanjiu Wang^3,4

¹Institute of Water Resources and Hydro-electric Engineering, Xi'an University of Technology, Xi'an, 710048, China.

Scientific Reports

|July 7, 2018

Summary

A new nonlinear method for calculating growing degree days (GDD) improves crop simulation accuracy. This advanced GDD calculation precisely predicts crop development and dry matter accumulation, outperforming traditional linear methods.

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Area of Science:

Agricultural Science
Agronomy
Crop Physiology

Background:

Accurate growing degree days (GDD) calculations are crucial for crop simulation models and agricultural management.
Traditional GDD methods assume linear temperature responses, failing to account for developmental delays above optimal temperatures (Topt).

Purpose of the Study:

To develop and evaluate a novel nonlinear method for calculating GDD.
To compare the precision of the new nonlinear GDD method against traditional methods for corn and wheat.

Main Methods:

A new nonlinear GDD calculation method was developed.
The new method was evaluated by comparing its predictions of developmental stage dates and dry matter accumulation against traditional methods for corn and wheat.

Main Results:

The nonlinear GDD method reduced date prediction variations by 1 day.
Smaller errors in predicting dry matter accumulation were observed for winter wheat and corn using the new method.
The method showed particular promise for spring wheat and was more stable and precise than traditional methods, especially when Topt was below maximum air temperature.

Conclusions:

The developed nonlinear GDD method offers improved accuracy and stability for crop simulation.
This new approach enhances predictions of crop development and yield, particularly under non-ideal temperature conditions.