Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/21599

Title: Tree influence on soil and pasture: contribution of proximal sensing to pasture productivity and quality estimation in montado ecosystems
Authors: Serrano, João
Shahidian, Shakib
Marques da Silva, J.
Sales-Baptista, E.
Ferraz de Oliveira, I.
Lopes de Castro, J.
Pereira, Alfredo
Cancela de Abreu, M.
Machado, Eliana
Carvalho, Mário
Keywords: tree canopy
sensors
soil
pasture productivity and quality
Issue Date: Nov-2017
Publisher: Taylor & Francis
Citation: João Serrano, Shakib Shahidian, J. Marques Da Silva, E. Sales-Baptista, I. Ferraz De Oliveira, J. Lopes De Castro, Alfredo Pereira, M. Cancela De Abreu, Eliana Machado and Mário de Carvalho (2017). "Tree influence on soil and pasture: contribution of proximal sensing to pasture productivity and quality estimation in montado ecosystems". International Journal of Remote Sensing (Publicado on-line em 27/11/2017). DOI: 10.1080/01431161.2017.1404166
Abstract: Montado is a silvo-pastoral ecosystem of the Mediterranean region, a mixed system of trees and pasture, subject to animal grazing. Farmers need information on pasture production and quality in order to assess the direct effect of tree presence on the productivity of their pastoral system, and to devise management that balances farm production and profitability with sustainable soil management. The main objectives of this work were (1) to evaluate tree influence on soil and pasture parameters; and (2) to evaluate the use of proximal sensing techniques which have potential for monitoring aspects related to spatial and temporal variability of pasture productivity and quality in montado ecosystems. Both objectives can support the decision making process of the farmer. The study field is located in Mitra farm, in Southern Portugal. During October 2015, twenty four geo-referenced composite soil samples (twelve under tree canopy and twelve outside tree canopy) were collected from the 0.0–0.3 m soil layer. The soil samples were analyzed for texture (sand, silt and clay content), moisture content, pH, organic matter, total nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg) and manganese (Mn). The evolution of the pasture was recorded in the twenty four sampling points at five monitoring dates: at the end of autumn (December 2015), at the end of winter (March 2016) and then monthly during spring 2016 (April, May and June). The following pasture parameters were measured: normalized difference vegetation index (NDVI), capacitance, temperature, green and dry matter, ash, crude protein (CP) and neutral detergent fiber (NDF). Soil under tree canopy had significantly higher levels of organic matter, N, P, K and Mg, and better pasture quality while the pasture productivity was higher outside tree canopy. The correlation between pasture direct measurements and sensor parameters was more consistent between capacitance and pasture productivity and between NDVI and CP. The use of fast and efficient tools associated with geo-referenced systems can greatly simplify the pasture monitoring process, which is the basis for estimating feed availability in the field. The knowledge of biomass quality and quantity is fundamental to support decision making regarding animal stocking rates and rotation among grazing parcels.
URI: http://hdl.handle.net/10174/21599
Type: article
Appears in Collections:ERU - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
ICAAM - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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