A new probabilistic forecasting model for canopy temperature with consideration of periodicity and parameter variation-Reference-Cited by-同舟云学术

A new probabilistic forecasting model for canopy temperature with consideration of periodicity and parameter variation

Published:2019-02 Issue: Volume:265 Page:88-98
ISSN:0168-1923
Container-title:Agricultural and Forest Meteorology
language:en
Short-container-title:Agricultural and Forest Meteorology

Author:

Shao Quanxi^ORCID,Bange Michael,Mahan James,Jin Huidong,Jamali Hizbullah^ORCID,Zheng Bangyou^ORCID,Chapman Scott C.

Funder

CSIRO

Australian Cotton Research Development Corporation

United States Department of Agriculture

Publisher

Elsevier BV

Subject

Atmospheric Science,Agronomy and Crop Science,Global and Planetary Change,Forestry

Reference20 articles.

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2. A model to estimate canopy temperature in the desert southwest;Brown;Proceedings of 1998 Beltwide Cotton Conferences, San Diego, CA. 5–9 Jan. 1998. Natl. Cotton Council,1998

3. Temperature-Time Thresholds for Irrigation Scheduling in Precision Application and Deficit Furrow Irrigated Cotton. Ph.D. Thesis;Conaty,2010

4. Determining the optimum plant temperature of cotton physiology and yield to improve plant-based irrigation scheduling;Conaty;Crop Sci.,2012

5. Predicting heat stress in cotton using probabilistic canopy temperature forecasts;Christ;Agron. J.,2016

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1. Current status and prospects of rice canopy temperature research;Food and Energy Security;2022-10-21

2. Improving temperature‐based predictions of the timing of flowering in cotton;Agronomy Journal;2022-08-09

3. Canopy Temperature as a Key Physiological Trait to Improve Yield Prediction under Water Restrictions in Potato;Agronomy;2021-07-20

4. Canopy temperature and heat stress are increased by compound high air temperature and water stress and reduced by irrigation – a modeling analysis;Hydrology and Earth System Sciences;2021-03-24

5. Evaluation of a new irrigation decision support system in improving cotton yield and water productivity in an arid climate;Agricultural Water Management;2020-05