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Sensors 2017, 17(7), 1483; doi:10.3390/s17071483

Relationship between Remote Sensing Data, Plant Biomass and Soil Nitrogen Dynamics in Intensively Managed Grasslands under Controlled Conditions

1
Faculty of Life Sciences, Rhine-Waal University of Applied Sciences, Marie-Curie-Str. 1, 47533 Kleve, Germany
2
Versuchs- und Bildungszentrum Landwirtschaft Haus Riswick, Elsenpaß 5, 47533 Kleve, Germany
3
Faculty of Communication and Environment, Rhine-Waal University of Applied Sciences, Friedrich-Heinrich-Allee 25, 47475 Kamp-Lintfort, Germany
4
Grassland and Fodder Sciences, Faculty of Agriculture and the Environment, University of Rostock, Justus-von-Liebig-Weg 6, 18059 Rostock, Germany
*
Author to whom correspondence should be addressed.
Received: 13 April 2017 / Accepted: 18 June 2017 / Published: 23 June 2017
(This article belongs to the Special Issue Precision Agriculture and Remote Sensing Data Fusion)
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Abstract

The sustainable use of grasslands in intensive farming systems aims to optimize nitrogen (N) inputs to increase crop yields and decrease harmful losses to the environment at the same time. To achieve this, simple optical sensors may provide a non-destructive, time- and cost-effective tool for estimating plant biomass in the field, considering spatial and temporal variability. However, the plant growth and related N uptake is affected by the available N in the soil, and therefore, N mineralization and N losses. These soil N dynamics and N losses are affected by the N input and environmental conditions, and cannot easily be determined non-destructively. Therefore, the question arises: whether a relationship can be depicted between N fertilizer levels, plant biomass and N dynamics as indicated by nitrous oxide (N2O) losses and inorganic N levels. We conducted a standardized greenhouse experiment to explore the potential of spectral measurements for analyzing yield response, N mineralization and N2O emissions in a permanent grassland. Ryegrass was subjected to four mineral fertilizer input levels over 100 days (four harvests) under controlled environmental conditions. The soil temperature and moisture content were automatically monitored, and the emission rates of N2O and carbon dioxide (CO2) were detected frequently. Spectral measurements of the swards were performed directly before harvesting. The normalized difference vegetation index (NDVI) and simple ratio (SR) were moderately correlated with an increasing biomass as affected by fertilization level. Furthermore, we found a non-linear response of increasing N2O emissions to elevated fertilizer levels. Moreover, inorganic N and extractable organic N levels at the end of the experiment tended to increase with the increasing N fertilizer addition. However, microbial biomass C and CO2 efflux showed no significant differences among fertilizer treatments, reflecting no substantial changes in the soil biological pool size and the extent of the C mineralization. Neither the NDVI nor SR, nor the plant biomass, were related to cumulative N2O emissions or inorganic N at harvesting. Our results verify the usefulness of optical sensors for biomass detection, and show the difficulty in linking spectral measurements of plant traits to N processes in the soil, despite that the latter affects the former. View Full-Text
Keywords: precision agriculture; fertilizer response; vegetation indices; nitrous oxide emission; Lolium perenne; sensor network precision agriculture; fertilizer response; vegetation indices; nitrous oxide emission; Lolium perenne; sensor network
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Knoblauch, C.; Watson, C.; Berendonk, C.; Becker, R.; Wrage-Mönnig, N.; Wichern, F. Relationship between Remote Sensing Data, Plant Biomass and Soil Nitrogen Dynamics in Intensively Managed Grasslands under Controlled Conditions. Sensors 2017, 17, 1483.

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