4 resultados para pasture

em Repositório Científico da Universidade de Évora - Portugal


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Estimation of pasture productivity is an important step for the farmer in terms of planning animal stocking, organizing animal lots, and determining supplementary feeding needs throughout the year. The main objective of this work was to evaluate technologies which have potential for monitoring aspects related to spatial and temporal variability of pasture green and dry matter yield (respectively, GM and DM, in kg/ha) and support to decision making for the farmer. Two types of sensors were evaluated: an active optical sensor(OptRx®, which measures the NDVI, Normalized Difference Vegetation Index) and a capacitance probe (GrassMaster II which estimates plant mass). The results showed the potential of NDVI for monitoring the evolution of spatial and temporal patterns of vegetative growth of biodiverse pasture. Higher NDVI values were registered as pasture approached its greatest vegetative vigor, with a significant fall in the measured NDVI at the end of Spring, when the pasture began to dry due to the combination of higher temperatures and lower soil moisture content. This index was also effective for identifying different plant species (grasses/legumes) and variability in pasture yield. Furthermore, it was possible to develop calibration equations between the capacitance and the NDVI (R2 = 0.757; p < 0.01), between capacitance and GM (R2 = 0.799; p<0.01), between capacitance and DM (R2 = 0.630; p<0.01), between NDVI and GM (R2=0.745; p < 0.01), and between capacitance and DM (R2=0.524; p<0.01). Finally, a direct relationship was obtained between NDVI and pasture moisture content (PMC, in %) and between capacitance and PMC (respectively, R2 = 0.615; p<0.01 and R2=0.561; p <0.01) in Alentejo dryland farming systems.

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Accurate assessment of standing pasture biomass in livestock production systems is a major factor for improving feed planning. Several tools are available to achieve this, including the GrassMaster II capacitance meter. This tool relies on an electrical signal, which is modified by the surrounding pasture. There is limited knowledge on how this capacitance meter performs in Mediterranean pastures. Therefore, we evaluated the GrassMaster II under Mediterranean conditions to determine (i) the effect of pasture moisture content (PMC) on the meter’s ability to estimate pasture green matter (GM) and dry matter (DM) yields, and (ii) the spatial variability and temporal stability of corrected meter readings (CMR) and DM in a bio-diverse pasture. Field tests were carried out with typical pastures of the southern region of Portugal (grasses, legumes, mixture and volunteer annual species) and at different phenological stages (and different PMC). There were significant positive linear relations between CMR and GM (r2 = 0.60, P < 0.01) and CMR and DM (r2 = 0.35, P < 0.05) for all locations (n = 347). Weak relationships were found for PMC (%) v. slope and coefficient of determination for both GM and DM. A significant linear relation existed for CMR v. GM and DM for PMC >80% (r2= 0.57, P < 0.01, RMSE = 2856.7 kg ha–1, CVRMSE=17.1% to GM; and r2= 0.51, P < 0.01,RMSE = 353.7 kg ha–1, CVRMSE = 14.3% to DM). Therefore, under the conditions of this current study there exists an optimum PMC (%) for estimating both GM and DM with the GrassMaster II. Repeated-measurements taken at the same location on different dates and conditions in a bio-diverse pasture showed similar and stable patterns between CMR and DM (r2= 0.67, P < 0.01, RMSE = 136.1 kg ha–1, CVRMSE = 6.5%). The results indicate that the GrassMaster II in-situ technique could play a crucial role in assessing pasture mass to improve feed planning under Mediterranean conditions.

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Silvo-pastoral are mixed systems of trees and grass, which have been proposed as a means to extend the benefits of forest to farmed land. Agro-forestry systems under semi-arid Mediterranean conditions, called montados in Portugal and dehesas in Spain, cover substantial areas in the world. These silvo-pastoral systems are the most extensive European agro-forestry system, as they cover 3.5–4.0 Mha in Spain and Portugal. Long-term studies are essential to assess the magnitude of the temporal nutrient flow dynamics in terrestrial ecosystems and to understand the response of these systems to fertilizer management. In order to implement the conservation task and recovery of resources through silvo-pastoral systems it is necessary to know and correct potential limiting factors, especially the soil factor, and this requires agronomic knowledge as well as the implmentation of the available new technologies. In this context, this task aims at a better understanding of the contribution of the two components of montado ecosystem (trees and herbaceous vegetation) on the soil nutrient and water dynamics, that allow for the interpretation of the variability of pasture dry matter yield and help the farmer in the management of tree density. Collaterally the task will evaluate and calibrate new technologies that simplify the monitoring of soil, grassland, trees and grazing animals.

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Site-specific management (SSM) is a form of precision agriculture whereby decisions on resource application and agronomic practices are improved to better match soil and crop requirements as they vary in the field. SSM enables the identification of regions (homogeneous management zones) within the area delimited by field boundaries. These subfield regions constitute areas that have similar permanent characteristics. Traditional soil and pasture sampling and the necessary laboratory analysis are time-consuming, labour-intensive and cost prohibitive, not viable from a SSM perspective because it needs a large number of soil and pasture samples in order to achieve a good representation of soil properties, nutrient levels and pasture quality and productivity. The main objective of this work was to evaluate technologies which have potential for monitoring aspects related to spatial and temporal variability of soil nutrients and pasture green and dry matter yield (respectively, GM and DM, in kg/ha) and support to decision making for the farmer. Three types of sensors were evaluated in a 7ha pasture experimental field: an electromagnetic induction sensor (“DUALEM 1S”, which measures the soil apparent electrical conductivity, ECa), an active optical sensor ("OptRx®", which measures the NDVI, “Normalized Difference Vegetation Index”) and a capacitance probe ("GrassMaster II" which estimates plant mass). The results indicate the possibility of using a soil electrical conductivity probe as, probably, the best tool for monitoring not only some of the characteristics of the soil, but also those of the pasture, which could represent an important help in simplifying the process of sampling and support SSM decision making, in precision agriculture projects. On the other hand, the significant and very strong correlations obtained between capacitance and NDVI and between any of these parameters and the pasture productivity shows the potential of these tools for monitoring the evolution of spatial and temporal patterns of the vegetative growth of biodiverse pasture, for identifying different plant species and variability in pasture yield in Alentejo dry-land farming systems. These results are relevant for the selection of an adequate sensing system for a particular application and open new perspectives for other works that would allow the testing, calibration and validation of the sensors in a wider range of pasture production conditions, namely the extraordinary diversity of botanical species that are characteristic of the Mediterranean region at the different periods of the year.