On the potential of Wireless Sensor Networks for the in-situ assessment of crop leaf area index

DC ElementWertSprache
dc.contributor.authorBauer, Jan
dc.contributor.authorSiegmann, Bastian
dc.contributor.authorJarmer, Thomas
dc.contributor.authorAschenbruck, Nils
dc.date.accessioned2021-12-23T16:01:34Z-
dc.date.available2021-12-23T16:01:34Z-
dc.date.issued2016
dc.identifier.issn01681699
dc.identifier.urihttps://osnascholar.ub.uni-osnabrueck.de/handle/unios/5044-
dc.description.abstractA precise and continuous in-situ monitoring of bio-physical crop parameters is crucial for the efficiency and sustainability in modern agriculture. The leaf area index (LAI) is an important key parameter allowing to derive vital crop information. As it serves as a valuable indicator for yield-limiting processes, it contributes to situational awareness ranging from agricultural optimization to global economy. This paper presents a feasible, robust, and low-cost modification of commercial off-the-shelf photosynthetically active radiation (PAR) sensors, which significantly enhances the potential of Wireless Sensor Network (WSN) technology for non-destructive in-situ LAI assessment. In order to minimize environmental influences such as direct solar radiation and scattering effects, we upgrade such a sensor with a specific diffuser combined with an appropriate optical band-pass filter. We propose an implementation of a distributed WSN application based on a simplified model of light transmittance through the canopy and validate our approach in various field campaigns exemplarily conducted in maize cultivars. Since a ground truth LAI is very difficult to obtain, we use the LAI-2200, one of the most widely established standard instruments, as a reference. We evaluate the accuracy of LAI estimates derived from the analysis of PAR sensor data and the robustness of our sensor modification. As a result, an extensive comparative analysis emphasizes a strong linear correlation (r(2) = 0.88, RMSE = 0.28) between both approaches. Hence, the proposed WSN-based approach enables a promising alternative for a flexible and continuous LAI monitoring. (C) 2016 Elsevier B.V. All rights reserved.
dc.description.sponsorshipStifterverband fur die Deutsche Wissenschaft [H170 5701 5020 20951]; This work was supported by the ``Stifterverband fur die Deutsche Wissenschaft'' (H170 5701 5020 20951).
dc.language.isoen
dc.publisherELSEVIER SCI LTD
dc.relation.ispartofCOMPUTERS AND ELECTRONICS IN AGRICULTURE
dc.subjectAgriculture
dc.subjectAgriculture, Multidisciplinary
dc.subjectComputer Science
dc.subjectComputer Science, Interdisciplinary Applications
dc.subjectCrop parameter
dc.subjectGap fraction
dc.subjectHEMISPHERICAL PHOTOGRAPHY
dc.subjectLAI-2200
dc.subjectLeaf area index
dc.subjectPrecision agriculture
dc.subjectWireless Sensor Network
dc.titleOn the potential of Wireless Sensor Networks for the in-situ assessment of crop leaf area index
dc.typejournal article
dc.identifier.doi10.1016/j.compag.2016.08.019
dc.identifier.isiISI:000385473300017
dc.description.volume128
dc.description.startpage149
dc.description.endpage159
dc.identifier.eissn18727107
dc.publisher.placeTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
dcterms.isPartOf.abbreviationComput. Electron. Agric.
crisitem.author.deptFB 06 - Mathematik/Informatik-
crisitem.author.deptidfb06-
crisitem.author.orcid0000-0002-4652-1640-
crisitem.author.orcid0000-0002-5861-8896-
crisitem.author.parentorgUniversität Osnabrück-
crisitem.author.netidJaTh054-
crisitem.author.netidAsNi712-
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