CBM: An IoT Enabled LiDAR Sensor for In-Field Crop Height and Biomass Measurements

Article

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
Article Title

CBM: An IoT Enabled LiDAR Sensor for In-Field Crop Height and Biomass Measurements

ERA Journal ID210199
Article CategoryArticle
AuthorsBanerjee, Bikram Pratap, Spangenberg, German and Kant, Surya
Journal TitleBiosensors
Journal Citation12 (1), pp. 1-19
Article Number16
Number of Pages19
Year2021
Place of PublicationSwitzerland
ISSN2079-6374
Digital Object Identifier (DOI)https://doi.org/10.3390/bios12010016
Web Address (URL)https://www.mdpi.com/2079-6374/12/1/16
Abstract

The phenotypic characterization of crop genotypes is an essential, yet challenging, aspect of crop management and agriculture research. Digital sensing technologies are rapidly advancing plant phenotyping and speeding-up crop breeding outcomes. However, off-the-shelf sensors might not be fully applicable and suitable for agricultural research due to the diversity in crop species and specific needs during plant breeding selections. Customized sensing systems with specialized sensor hardware and software architecture provide a powerful and low-cost solution. This study designed and developed a fully integrated Raspberry Pi-based LiDAR sensor named CropBioMass (CBM), enabled by internet of things to provide a complete end-to-end pipeline. The CBM is a low-cost sensor, provides high-throughput seamless data collection in field, small data footprint, injection of data onto the remote server, and automated data processing. The phenotypic traits of crop fresh biomass, dry biomass, and plant height that were estimated by CBM data had high correlation with ground truth manual measurements in a wheat field trial. The CBM is readily applicable for high-throughput plant phenotyping, crop monitoring, and management for precision agricultural applications.

KeywordsGNSS; LiDAR; Raspberry Pi; high-throughput plant phenotyping; internet of things; precision agriculture
ANZSRC Field of Research 2020400906. Electronic sensors
401304. Photogrammetry and remote sensing
300406. Crop and pasture improvement (incl. selection and breeding)
Byline AffiliationsAgriculture Victoria
La Trobe University
Permalink -

https://research.usq.edu.au/item/z3087/cbm-an-iot-enabled-lidar-sensor-for-in-field-crop-height-and-biomass-measurements

Log in to edit

Download files

Published Version
biosensors-12-00016-v3.pdf
License: CC BY 4.0
File access level: Anyone

  • 62
    total views
  • 35
    total downloads
  • 4
    views this month
  • 0
    downloads this month

Export as

Related outputs

Granular characterisation of coal spoil dump using unmanned aerial vehicle data to enhance stability analysis
Thiruchittampalam, Sureka, Banerjee, Bikram Pratap, Glenn, Nancy Fraser, McQuillan, Alison and Raval, Simit. 2024. "Granular characterisation of coal spoil dump using unmanned aerial vehicle data to enhance stability analysis." Journal of Rock Mechanics and Geotechnical Engineering. https://doi.org/10.1016/j.jrmge.2024.09.044
Comparative analysis of traditional and transfer learning algorithms for coal spoil classification via close-range imagery
Thiruchittampalam, Sureka, Shanmugalingam, Kuruparan, Banerjee, Bikram P, Glenn, Nancy F. and Raval, Simit. 2024. "Comparative analysis of traditional and transfer learning algorithms for coal spoil classification via close-range imagery." Georisk: assessment and management of risk for engineered systems and geohazards. https://doi.org/10.1080/17499518.2024.2422490
Integrative approaches in modern agriculture: IoT, ML and AI for disease forecasting amidst climate change
Delfani, Payam, Thuraga, Vishnukiran, Banerjee, Bikram and Chawade, Aakash. 2024. "Integrative approaches in modern agriculture: IoT, ML and AI for disease forecasting amidst climate change." Precision Agriculture. 25, pp. 2589-2613. https://doi.org/10.1007/s11119-024-10164-7
Applying a solar model to LiDAR images of an agrivoltaic pear orchard
Bonzi, L., Scalisi, A., O'Connell, M.G., Banerjee, B.P., Rallo, G., Remorini, D., Valluri, N. and Goodwin, I.. 2024. "Applying a solar model to LiDAR images of an agrivoltaic pear orchard." O'Connell, M. (ed.) II International Symposium on Precision Management of Orchards and Vineyards. Tatura, Australia 03 - 08 Dec 2023 Australia. https://doi.org/10.17660/ActaHortic.2024.1395.15
Unlocking precision horticulture through machine learning-driven 3D canopy analysis
Banerjee, B.P., Scalisi, A., Valluri, N., Bonzi, L., O'Connell, M.G., Fitzgerald, G.J. and Goodwin, I.. 2024. "Unlocking precision horticulture through machine learning-driven 3D canopy analysis." O'Connell, M. (ed.) II International Symposium on Precision Management of Orchards and Vineyards. Tatura, Australia 03 - 08 Dec 2023 Australia. https://doi.org/10.17660/ActaHortic.2024.1395.13
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
An Open-Source Package for Thermal and Multispectral Image Analysis for Plants in Glasshouse
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
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
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