An Open-Source Package for Thermal and Multispectral Image Analysis for Plants in Glasshouse

Article


Sharma, Neelesh, Banerjee, Bikram Pratap, Hayden, Matthew and Kant, Surya. 2023. "An Open-Source Package for Thermal and Multispectral Image Analysis for Plants in Glasshouse." Plants. 12 (2). https://doi.org/10.3390/plants12020317
Article Title

An Open-Source Package for Thermal and Multispectral Image Analysis for Plants in Glasshouse

ERA Journal ID213962
Article CategoryArticle
AuthorsSharma, Neelesh, Banerjee, Bikram Pratap, Hayden, Matthew and Kant, Surya
Journal TitlePlants
Journal Citation12 (2)
Article Number317
Number of Pages19
Year2023
PublisherMDPI AG
Place of PublicationSwitzerland
ISSN2223-7747
Digital Object Identifier (DOI)https://doi.org/10.3390/plants12020317
Web Address (URL)https://www.mdpi.com/2223-7747/12/2/317
Abstract

Advanced plant phenotyping techniques to measure biophysical traits of crops are helping to deliver improved crop varieties faster. Phenotyping of plants using different sensors for image acquisition and its analysis with novel computational algorithms are increasingly being adapted to measure plant traits. Thermal and multispectral imagery provides novel opportunities to reliably phenotype crop genotypes tested for biotic and abiotic stresses under glasshouse conditions. However, optimization for image acquisition, pre-processing, and analysis is required to correct for optical distortion, image co-registration, radiometric rescaling, and illumination correction. This study provides a computational pipeline that optimizes these issues and synchronizes image acquisition from thermal and multispectral sensors. The image processing pipeline provides a processed stacked image comprising RGB, green, red, NIR, red edge, and thermal, containing only the pixels present in the object of interest, e.g., plant canopy. These multimodal outputs in thermal and multispectral imageries of the plants can be compared and analysed mutually to provide complementary insights and develop vegetative indices effectively. This study offers digital platform and analytics to monitor early symptoms of biotic and abiotic stresses and to screen a large number of genotypes for improved growth and productivity. The pipeline is packaged as open source and is hosted online so that it can be utilized by researchers working with similar sensors for crop phenotyping.

Keywordsco-registration; illumination correction; image processing; multispectral; segmentation; thermal
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020309999. Other agricultural, veterinary and food sciences not elsewhere classified
400999. Electronics, sensors and digital hardware not elsewhere classified
Byline AffiliationsAgriculture Victoria
La Trobe University
Permalink -

https://research.usq.edu.au/item/z307y/an-open-source-package-for-thermal-and-multispectral-image-analysis-for-plants-in-glasshouse

Download files


Published Version
plants-12-00317.pdf
License: CC BY 4.0
File access level: Anyone

  • 17
    total views
  • 71
    total downloads
  • 0
    views this month
  • 5
    downloads this month

Export as

Related outputs

Geotechnical characterisation of coal spoil piles using high-resolution optical and multispectral data: A machine learning approach
Thiruchittampalam, Sureka, Banerjee, Bikram Pratap, Glenn, Nancy F. and Raval, Simit. 2024. "Geotechnical characterisation of coal spoil piles using high-resolution optical and multispectral data: A machine learning approach." Engineering Geology. 329. https://doi.org/10.1016/j.enggeo.2024.107406
Canopy Scale High-Resolution Forest Biophysical Parameter (LAI, fAPAR, and fCover) Retrieval Through Machine Learning and Cloud Computation Approach
Bandopadhyay, Subhajit, Barnali, Das, Sánchez, Alexander Cotrina, Banerjee, Sankar Prasad, Banerjee, Bikram P. and Ghosh, Subhasis. 2023. "Canopy Scale High-Resolution Forest Biophysical Parameter (LAI, fAPAR, and fCover) Retrieval Through Machine Learning and Cloud Computation Approach." 2023 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS). Hyderabad, India 27 - 29 Jan 2023 Hyderabad, India. https://doi.org/10.1109/MIGARS57353.2023.10064558
Evaluation of Segmentation Methods for Spoil Pile Delineation Using UAV Images
Thiruchittampalam, S., Banerjee, B. P., Singh, S. K., Glenn, N. F. and Raval, S.. 2023. "Evaluation of Segmentation Methods for Spoil Pile Delineation Using UAV Images." IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium. United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/IGARSS52108.2023.10283351
Spoil characterisation using UAV‑based optical remote sensing in coal mine dumps
Thiruchittampalam, Sureka, Singh, Sarvesh Kumar, Banerjee, Bikram Pratap, Glenn, Nancy F. and Raval, Simit. 2023. "Spoil characterisation using UAV‑based optical remote sensing in coal mine dumps." International Journal of Coal Science and Technology. 10 (1). https://doi.org/10.1007/s40789-023-00622-4
Dissecting Physiological and Agronomic Diversity in Safflower Populations Using Proximal Phenotyping
Thoday-Kennedy, Emily, Banerjee, Bikram, Panozzo, Joe, Maharjan, Pankaj, Hudson, David, Spangenberg, German, Hayden, Matthew and Kant, Surya. 2023. "Dissecting Physiological and Agronomic Diversity in Safflower Populations Using Proximal Phenotyping." Agriculture. 13 (3). https://doi.org/10.3390/agriculture13030620
Mapping Sensitive Vegetation Communities in Mining Eco-space using UAV-LiDAR
Banerjee, Bikram Pratap and Raval, Simit. 2022. "Mapping Sensitive Vegetation Communities in Mining Eco-space using UAV-LiDAR." International Journal of Coal Science and Technology. 9 (1), pp. 1-16. https://doi.org/10.1007/s40789-022-00509-w
Automated hyperspectral vegetation index derivation using a hyperparameter optimisation framework for high-throughput plant phenotyping
Koh, Joshua C. O., Banerjee, Bikram P., Spangenberg, German and Kant, Surya. 2022. "Automated hyperspectral vegetation index derivation using a hyperparameter optimisation framework for high-throughput plant phenotyping." New Phytologist. 233 (6), pp. 2659-2670. https://doi.org/10.1111/nph.17947
Roots’ Drought Adaptive Traits in Crop Improvement
Shoaib, Mirza, Banerjee, Bikram P., Hayden, Matthew and Kant, Surya. 2022. "Roots’ Drought Adaptive Traits in Crop Improvement." Plants. 11 (17). https://doi.org/10.3390/plants11172256
Automated rock mass discontinuity set characterisation using amplitude and phase decomposition of point cloud data
Singh, Sarvesh Kumar, Banerjee, Bikram Pratap, Lato, Matthew J., Sammut, Claude and Raval, Simit. 2022. "Automated rock mass discontinuity set characterisation using amplitude and phase decomposition of point cloud data." International Journal of Rock Mechanics and Mining Sciences. 152, pp. 1-17. https://doi.org/10.1016/j.ijrmms.2022.105072
Estimating early season growth and biomass of field pea for selection of divergent ideotypes using proximal sensing
Tefera, Abeya Temesgen, Banerjee, Bikram Pratap, Pandey, Babu Ram, James, Laura, Puri, Ramesh Raj, Cooray, Onella, Marsh, Jasmine, Richards, Mark, Kant, Surya, Fitzgerald, Glenn J. and Cooray, Onella. 2022. "Estimating early season growth and biomass of field pea for selection of divergent ideotypes using proximal sensing." Field Crops Research. 277. https://doi.org/10.1016/j.fcr.2021.108407
A Particle Swarm Optimization Based Approach to Pre-tune Programmable Hyperspectral Sensors
Banerjee, Bikram Pratap and Raval, Simit. 2021. "A Particle Swarm Optimization Based Approach to Pre-tune Programmable Hyperspectral Sensors." Remote Sensing. 13 (16). https://doi.org/10.3390/rs13163295
Machine Learning Regression Analysis for Estimation of Crop Emergence Using Multispectral UAV Imagery
Banerjee, Bikram P., Sharma, Vikas, Spangenberg, German and Kant, Surya. 2021. "Machine Learning Regression Analysis for Estimation of Crop Emergence Using Multispectral UAV Imagery." Remote Sensing. 13 (15). https://doi.org/10.3390/rs13152918
CBM: An IoT Enabled LiDAR Sensor for In-Field Crop Height and Biomass Measurements
Banerjee, Bikram Pratap, Spangenberg, German and Kant, Surya. 2021. "CBM: An IoT Enabled LiDAR Sensor for In-Field Crop Height and Biomass Measurements." Biosensors. 12 (1), pp. 1-19. https://doi.org/10.3390/bios12010016
Three-Dimensional Unique-Identifier-Based Automated Georeferencing and Coregistration of Point Clouds in Underground Mines
Singh, Sarvesh Kumar, Banerjee, Bikram Pratap and Raval, Simit. 2021. "Three-Dimensional Unique-Identifier-Based Automated Georeferencing and Coregistration of Point Clouds in Underground Mines." Remote Sensing. 13 (16). https://doi.org/10.3390/rs13163145
Automated structural discontinuity mapping in a rock face occluded by vegetation using mobile laser scanning
Singh, Sarvesh Kumar, Raval, Simit and Banerjee, Bikram Pratap. 2021. "Automated structural discontinuity mapping in a rock face occluded by vegetation using mobile laser scanning." Engineering Geology. 285. https://doi.org/10.1016/j.enggeo.2021.106040
High-throughput phenotyping using digital and hyperspectral imaging-derived biomarkers for genotypic nitrogen response
Banerjee, Bikram P., Joshi, Sameer, Thoday-Kennedy, Emily, Pasam, Raj K., Tibbits, Josquin, Hayden, Matthew, Spangenberg, German and Kant, Surya. 2020. "High-throughput phenotyping using digital and hyperspectral imaging-derived biomarkers for genotypic nitrogen response." Journal of Experimental Botany. 71 (15), pp. 4604-4615. https://doi.org/10.1093/jxb/eraa143
UAV-hyperspectral imaging of spectrally complex environments
Banerjee, Bikram Pratap, Raval, Simit and Cullen, P. J.. 2020. "UAV-hyperspectral imaging of spectrally complex environments." International Journal of Remote Sensing. 41 (11), pp. 4136-4159. https://doi.org/10.1080/01431161.2020.1714771
Fusion of Spectral and Structural Information from Aerial Images for Improved Biomass Estimation
Banerjee, Bikram Pratap, Spangenberg, German and Kant, Surya. 2020. "Fusion of Spectral and Structural Information from Aerial Images for Improved Biomass Estimation." Remote Sensing. 12 (19). https://doi.org/10.3390/rs12193164
Roof bolt identification in underground coal mines from 3D point cloud data using local point descriptors and artificial neural network
Singh, Sarvesh Kumar, Raval, Simit and Banerjee, Bikram. 2020. "Roof bolt identification in underground coal mines from 3D point cloud data using local point descriptors and artificial neural network." International Journal of Remote Sensing. 42 (1), pp. 367-377. https://doi.org/10.1080/2150704x.2020.1809734
Evaluation of a UAV-LiDAR system for mapping geological structures in an open pit highwall
Raval, S, Banerjee, B P, Shen, X, Masoumi, H and Tannant, D. 2018. "Evaluation of a UAV-LiDAR system for mapping geological structures in an open pit highwall." The 4th Australasian Ground Control in Mining Conference (AusRock). Sydney, Australia 28 - 30 Nov 2018 https://www.ausimm.com/publications/conference-proceedings/the-fourth-australasian-ground-control-in-mining-conference-ausrock/evaluation-of-a-uav-lidar-system-for-mapping-geological-structures-in-an-open-pit-highwall/.
High-resolution mapping of upland swamp vegetation using an unmanned aerial vehicle-hyperspectral system
Banerjee, Bikram Pratap, Raval, Simit and Cullen, Patrick Joseph. 2017. "High-resolution mapping of upland swamp vegetation using an unmanned aerial vehicle-hyperspectral system." Journal of Spectral Imaging. 6 (1). https://doi.org/10.1255/jsi.2017.a6
Health condition assessment for vegetation exposed to heavy metal pollution through airborne hyperspectral data
Banerjee, Bikram Pratap, Raval, Simit, Zhai, Hao and Cullen, Patrick Joseph. 2017. "Health condition assessment for vegetation exposed to heavy metal pollution through airborne hyperspectral data." Environmental Monitoring and Assessment. 189 (12). https://doi.org/10.1007/s10661-017-6333-4
Evaluation of rainfall and wetland water area variability at Thirlmere Lakes using Landsat time-series data
Banerjee, B. P., Raval, S. and Timms, W.. 2016. "Evaluation of rainfall and wetland water area variability at Thirlmere Lakes using Landsat time-series data." International Journal of Environmental Science and Technology. 13, p. 1781–1792. https://doi.org/10.1007/s13762-016-1018-z
Improving yield potential in crops under elevated CO2: integrating the photosynthetic and nitrogen utilization efficiencies
Kant, Surya, Seneweera, Saman, Rodin, Joakim, Materne, Michael, Burch, David, Rothstein, Steven J. and Spangenberg, German. 2012. "Improving yield potential in crops under elevated CO2: integrating the photosynthetic and nitrogen utilization efficiencies ." Frontiers in Plant Science. 3, pp. 1-9. https://doi.org/10.3389/fpls.2012.00162