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

Autor(en): Bauer, Jan
Siegmann, Bastian
Jarmer, Thomas 
Aschenbruck, Nils 
Stichwörter: Agriculture; Agriculture, Multidisciplinary; Computer Science; Computer Science, Interdisciplinary Applications; Crop parameter; Gap fraction; HEMISPHERICAL PHOTOGRAPHY; LAI-2200; Leaf area index; Precision agriculture; Wireless Sensor Network
Erscheinungsdatum: 2016
Herausgeber: ELSEVIER SCI LTD
Journal: COMPUTERS AND ELECTRONICS IN AGRICULTURE
Volumen: 128
Startseite: 149
Seitenende: 159
Zusammenfassung: 
A 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.
ISSN: 01681699
DOI: 10.1016/j.compag.2016.08.019

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