UAV-thermal imaging and agglomerative hierarchical clustering techniques to evaluate and rank physiological performance of wheat genotypes on sodic soil

Das, Sumanta and Christopher, Jack and Apan, Armando ORCID: https://orcid.org/0000-0002-5412-8881 and Choudhury, Malini Roy and Chapman, Scott and Menzies, Neal W. and Dang, Yash P. (2021) UAV-thermal imaging and agglomerative hierarchical clustering techniques to evaluate and rank physiological performance of wheat genotypes on sodic soil. ISPRS Journal of Photogrammetry and Remote Sensing, 173. pp. 221-237. ISSN 0924-2716


Abstract

Sodicity is a major soil constraint in many arid and semi-arid regions worldwide, including Australia, which adversely affects the ability of crops to take up water and nutrients from the soil, reducing yield. Reliable methods and tools are required for appropriate selection of traits, may provide a better understanding of crop responses to multiple stresses, especially in sodic soil. A novel strategy was developed using unmanned aerial vehicle (UAV)-thermal imaging and agglomerative hierarchical clustering-based techniques to evaluate and rank the physiological performance of 18 contrasting wheat genotypes grown on a moderately sodic and a highly sodic soil in north-eastern Australia. We obtained UAV-thermal imaging data at different times of the day (9:30, 12:00, and 15:00 hrs) close to flowering stage. Crop biophysical parameters (Leaf potassium concentration, normalized difference vegetation index, crop water uptake, stomatal conductance, plant moisture content, and aboveground biomass) were measured at close to flowering by destructive plant sampling and ground-based proximal sensing and yield was machine harvested at maturity. Canopy temperatures derived from thermal imagery between 28.9 and 35.4 ◦C were observed at the moderately sodic site, and between 36.2 and 41.0 ◦C at the highly sodic site from 9:30 to 15:00 hrs. Canopy temperature was consistently higher than corresponding ambient air temperatures indicating plant water stress at both sites. While the air temperature was not significantly different (p >0.05) between the two sites, canopy temperature was significantly higher (p <0.01) on highly sodic soil compared to moderately sodic soil, indicating greater water stress at the highly sodic site. This difference was most likely due to the adverse impacts of sodic soil constraints and not primarily due to environmental variations. Hence, our study revealed that sodic soil constraints can intensify plant water stress. Statistical analysis between canopy temperature (9:30, 12:00, and 15:00 hrs) and crop biophysical parameters showed close negative correlations at both moderately sodic (R2 =0.54 to 0.83) and highly sodic (R2 =0.30 to 0.89) sites. A closer correlation was observed at 15:00 hrs for both sites. Thus, high-resolution UAV-thermal imaging has potential to detect water-stressed plants on sodic soil. Agglomerative hierarchical clustering was used as an unsupervised machine learning tool for ranking of physiological performance of wheat genotypes. Results suggest that UAV-thermal imaging and AHC techniques can discriminate cultivars tolerant to sodicity. The study improves our understanding of crop physiological behaviour and can assist farmers in selection of water stress tolerant genotypes to sustain food security in sodic soil under water-limited environments.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published version in accordance with the copyright policy of the publisher.
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 -)
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Sustainable Agricultural Systems (1 Aug 2018 -)
Date Deposited: 12 Jul 2021 07:03
Last Modified: 12 Jul 2021 07:03
Uncontrolled Keywords: canopy temperature; plant water stress; vegetation indices; agglomerative hierarchical clustering; wheat genotypes; sodic soil
Fields of Research (2008): 07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070104 Agricultural Spatial Analysis and Modelling
09 Engineering > 0909 Geomatic Engineering > 090999 Geomatic Engineering not elsewhere classified
Fields of Research (2020): 40 ENGINEERING > 4013 Geomatic engineering > 401399 Geomatic engineering not elsewhere classified
30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300206 Agricultural spatial analysis and modelling
Socio-Economic Objectives (2008): B Economic Development > 82 Plant Production and Plant Primary Products > 8205 Winter Grains and Oilseeds > 820507 Wheat
Socio-Economic Objectives (2020): 26 PLANT PRODUCTION AND PLANT PRIMARY PRODUCTS > 2603 Grains and seeds > 260312 Wheat
Identification Number or DOI: https://doi.org/10.1016/j.isprsjprs.2021.01.014
URI: http://eprints.usq.edu.au/id/eprint/42677

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