Open Access
Canopy Temperature Bias from Soil Variability Enhanced at High Temperatures
Author(s) -
Kendall C. DeJonge,
Huihui Zhang,
Saleh Taghvaeian,
Thomas J. Trout
Publication year - 2020
Publication title -
transactions of the asabe
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.396
H-Index - 101
eISSN - 2151-0040
pISSN - 2151-0032
DOI - 10.13031/trans.13554
Subject(s) - canopy , soil water , irrigation , environmental science , soil texture , agronomy , soil science , ecology , biology
HighlightMaize canopy temperature ( T c ) was evaluated among four replicates of seven irrigation treatments. Individual replicates showed T c bias correlated with soil electroconductivity and increasing T c . At high T c values (above 35°C), T c bias was up to 5.0°C among plots with the same irrigation schedule.ABSTRACT. Maize canopy temperature was monitored on a continuous basis for two growing seasons in a limited-irrigation maize experiment with seven separate irrigation treatments and four replicates of each treatment. Soil electroconductivity (EC) was measured and mapped to quantify the variation in soil texture throughout the plots and was correlated with the average field capacity of the soil (R 2 = 0.51). At lower canopy temperatures, indicating little or no water stress, very little difference was observed between replicates within the same treatment. However, at higher temperatures, soil texture had a greater influence on temperature, with soils having lower EC (and therefore lower water-holding capacity) showing more water stress. More specifically, at canopy temperatures above 29°C, the influence of soil texture biased the temperature by up to 2.0°C over the EC range of 16.9 to 40.2 mS m -1 ; at mean canopy temperatures of 35°C, this bias could be more than 5.0°C between field replicates. Results similar to the continuous infrared thermometry were found using nadir thermal images. This study demonstrates the importance of understanding the potential effects of soil variability on canopy temperature, which could have profound implications for spatially variable field-based management using thermal imaging or similar technologies. Keywords: Canopy temperature, Infrared thermometry, Limited irrigation, Soil variability.