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| Hauptseite > Publikationsdatenbank > Processing and filtering of leaf area index time series assessed by in-situ wireless sensor networks > print |
| Hauptseite > Publikationsdatenbank > Processing and filtering of leaf area index time series assessed by in-situ wireless sensor networks > print |
| 001 | 867784 | ||
| 005 | 20210130003903.0 | ||
| 024 | 7 | _ | |a 10.1016/j.compag.2019.104867 |2 doi |
| 024 | 7 | _ | |a 0168-1699 |2 ISSN |
| 024 | 7 | _ | |a 1872-7107 |2 ISSN |
| 024 | 7 | _ | |a WOS:000488143100001 |2 WOS |
| 037 | _ | _ | |a FZJ-2019-06394 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 004 |
| 100 | 1 | _ | |a Bauer, Jan |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Processing and filtering of leaf area index time series assessed by in-situ wireless sensor networks |
| 260 | _ | _ | |a Amsterdam [u.a.] |c 2019 |b Elsevier Science |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1576587351_32427 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a A precise and up-to-date situational awareness of crop conditions is important for precision farming. The temporallycontinuous monitoring of relevant crop parameters has recently been shown to assist in a large number ofapplications. In this context, the leaf area index (LAI) is a key parameter. However, continuous LAI monitoringusing traditional assessment methods is hardly possible and very expensive. For this reason, low-cost sensorsbased on Wireless Sensor Network (WSN) technology have been developed and interconnected to agricultural insitu sensor networks that seem promising for LAI assessment. In this paper, an approach for the processing andfiltering of distributed in situ sensor data for a credible LAI estimation is proposed. This approach is developedbased on a long-term WSN deployment in experimental plots with different wheat cultivars (Triticum aestivum L.)and water regimes. Non-negligible environmental impacts on radiation-based LAI assessment are also taken intoaccount. A comparative analysis with a conventional LAI instrument shows that WSNs with adequately processeddata gathered by low-cost sensors have the potential to produce credible LAI trajectories with hightemporal resolution, that fit the dynamic crop growth process. Moreover, they are also shown to be able to detectyield-limiting trends and even to differentiate between individual wheat cultivars. Hence, those WSNs enablenew applications and can greatly support modern crop management, cultivation, and plant breeding. |
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| 700 | 1 | _ | |a Jarmer, Thomas |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Schittenhelm, Siegfried |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Siegmann, Bastian |0 P:(DE-Juel1)172711 |b 3 |
| 700 | 1 | _ | |a Aschenbruck, Nils |0 P:(DE-HGF)0 |b 4 |
| 773 | _ | _ | |a 10.1016/j.compag.2019.104867 |g Vol. 165, p. 104867 - |0 PERI:(DE-600)2016151-7 |p 104867 - |t Computers and electronics in agriculture |v 165 |y 2019 |x 0168-1699 |
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