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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10174/35661
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Title: | Pasture quality monitoring based on proximal and remote optical sensors: case study in the Montado Mediterranean ecosystem |
Authors: | Serrano, João Marques, João Mendes, Sara Shahidian, Shakib Marques da Silva, José Moral, Francisco |
Editors: | Stafford, John |
Keywords: | pastures proximal sensing Sentinel-2 NDVI |
Issue Date: | 2-Jul-2023 |
Publisher: | Wageningen Academic Publishers |
Citation: | Serrano, J., Mendes, S.; Marques, J.; Shahidian, S., Marques da Silva, J., Moral, F. Pasture quality monitoring based on proximal and remote optical sensors: case study in the Montado Mediterranean ecosystem. In: “Precision Agriculture ‘23”, 14th European Conference on Precision Agriculture (ECPA 2023), Bolonha, Itália (2-6 Julho de 2023); John Stafford (Ed.); DOI: 10.3920/978-90-8686-3_23, Wageningen Academic Publishers, p. 1003-1009. |
Abstract: | Permanent dryland pastures are the basis of animal feed in extensive grazing systems.
Seasonality and inter-annual climatic variability, associated with shallow, acidic and not
very fertile soils result in low productivity and rapid degradation of pasture quality,
which requires the supplementation of animal feed. In this study, carried out in a
biodiverse pasture field in the Mediterranean region of Southern Portugal, the
vegetation index (NDVI, Normalized Difference Vegetation Index) obtained from
measurements performed by a proximal optical sensor (PS) and satellite images (RS)
was used to assess pasture quality parameters (pasture moisture content, PMC, crude
protein, CP and neutral detergent fiber, NDF). The monitoring was carried out
throughout the 2021/2022 pasture growing season. Significant correlations were
obtained between the NDVI obtained by PS and RS (R2
of 0.8372) and between the
NDVI (PS and RS) and the reference values of pasture parameters obtained in
laboratory protocols: PMC (R2
of 0.9094 and 0.8147, respectively), CP (R2
of 0.6675
and 0.6329, respectively), and NDF (R2
of 0.4966 and 0.4576, respectively). These
results show the pertinence of these technologies in supporting the decision making
process of the farm manager, namely to estimate the supplementation needs of animals
in critical phases, especially after the spring production peak and before the autumn
production peak. |
URI: | http://hdl.handle.net/10174/35661 |
Type: | article |
Appears in Collections: | ERU - Artigos em Livros de Actas/Proceedings MED - Artigos em Livros de Actas/Proceedings
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