Literature DB >> 15133055

Combining thermal and visible imagery for estimating canopy temperature and identifying plant stress.

Ilkka Leinonen1, Hamlyn G Jones.   

Abstract

Thermal imaging is a potential tool for estimating plant temperature, which can be used as an indicator of stomatal closure and water deficit stress. In this study, a new method for processing and analysing thermal images was developed. By using remote sensing software, the information from thermal and visible images was combined, the images were classified to identify leaf area and sunlit and shaded parts of the canopy, and the temperature statistics for specific canopy components were calculated. The method was applied to data from a greenhouse water-stress experiment of Vicia faba L. and to field data for Vitis vinifera L. Vaseline-covered and water-sprayed plants were used as dry and wet references, respectively, and two thermal indices, based on temperature differences between the canopy and reference surfaces, were calculated for single Vicia faba plants. The thermal indices were compared with measured stomatal conductance. The temperature distributions of sunlit and shaded leaf area of Vitis vinifera canopies from natural rainfall and irrigation treatments were compared. The present method provides two major improvements compared with earlier methods for calculating thermal indices. First, it allows more accurate estimation of the indices, which are consequently more closely related to stomatal conductance. Second, it gives more accurate estimates of the temperature distribution of the shaded and sunlit parts of canopy, and, unlike the earlier methods, makes it possible to quantify the relationship between temperature variation and stomatal conductance.

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Year:  2004        PMID: 15133055     DOI: 10.1093/jxb/erh146

Source DB:  PubMed          Journal:  J Exp Bot        ISSN: 0022-0957            Impact factor:   6.992


  18 in total

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2.  Temperature profile in apricot tree canopies under the soil and climate conditions of the Romanian Black Sea Coast.

Authors:  Cristian Paltineanu; Leinar Septar; Emil Chitu
Journal:  Int J Biometeorol       Date:  2015-07-19       Impact factor: 3.787

Review 3.  Signature Optical Cues: Emerging Technologies for Monitoring Plant Health.

Authors:  Oi Wah Liew; Pek Ching Jenny Chong; Bingqing Li; Anand K Asundi
Journal:  Sensors (Basel)       Date:  2008-05-16       Impact factor: 3.576

4.  Determining the leaf emissivity of three crops by infrared thermometry.

Authors:  Chiachung Chen
Journal:  Sensors (Basel)       Date:  2015-05-15       Impact factor: 3.576

Review 5.  A review of imaging techniques for plant phenotyping.

Authors:  Lei Li; Qin Zhang; Danfeng Huang
Journal:  Sensors (Basel)       Date:  2014-10-24       Impact factor: 3.576

6.  Rapid and efficient estimation of pea resistance to the soil-borne pathogen Fusarium oxysporum by infrared imaging.

Authors:  Nicolas Rispail; Diego Rubiales
Journal:  Sensors (Basel)       Date:  2015-02-09       Impact factor: 3.576

7.  A Direct Comparison of Remote Sensing Approaches for High-Throughput Phenotyping in Plant Breeding.

Authors:  Maria Tattaris; Matthew P Reynolds; Scott C Chapman
Journal:  Front Plant Sci       Date:  2016-08-03       Impact factor: 5.753

Review 8.  Coping with drought: stress and adaptive responses in potato and perspectives for improvement.

Authors:  Jude E Obidiegwu; Glenn J Bryan; Hamlyn G Jones; Ankush Prashar
Journal:  Front Plant Sci       Date:  2015-07-22       Impact factor: 5.753

9.  Automatic detection of regions in spinach canopies responding to soil moisture deficit using combined visible and thermal imagery.

Authors:  Shan-e-Ahmed Raza; Hazel K Smith; Graham J J Clarkson; Gail Taylor; Andrew J Thompson; John Clarkson; Nasir M Rajpoot
Journal:  PLoS One       Date:  2014-06-03       Impact factor: 3.240

10.  Automatic Coregistration Algorithm to Remove Canopy Shaded Pixels in UAV-Borne Thermal Images to Improve the Estimation of Crop Water Stress Index of a Drip-Irrigated Cabernet Sauvignon Vineyard.

Authors:  Tomas Poblete; Samuel Ortega-Farías; Dongryeol Ryu
Journal:  Sensors (Basel)       Date:  2018-01-30       Impact factor: 3.576

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