http://hdl.handle.net/10174/11 2026-08-14T20:36:58Z http://hdl.handle.net/10174/42318 Title: Tecnologias integradas numa estratégia de apoio à rega de precisão no Milho Authors: Serrano, João M. P. R.; Noéme, J. Editors: Carmo, Vitor Abstract: Este trabalho resume a metodologia seguida no projeto “GO: Regadio de Precisão” (PDR2020-101-FEADER-032167) para implementação e demonstração de sistemas de rega de taxa variável (“Variable Rate Irrigation”, VRI) utilizando a rega por pivot na cultura do milho, num campo experimental de 28 ha (“Eucaliptos”, em Samora Correia; Figura 1-a). Este projeto baseia-se em tecnologias de monitorização: (i) da condutividade elétrica aparente do solo (CEa) e da altimetria; (ii) da produtividade da cultura; (iii) do teor de humidade e da fertilidade do solo; (iv) do índice de vegetação de diferença normalizada (“Normalized Difference Vegetation Index”, NDVI), obtido a partir de imagens de satélite; e em tecnologias de controlo automático da velocidade de deslocamento da rampa rotativa de rega (pivot; Figura 1-b, c e d). Os mapas de CEa e altimétrico serviram para a definição inicial de zonas de gestão de rega (ZG) e elaboração inicial de prescrição de rega (VRI-1). As séries temporais de NDVI obtidas ao longo do ciclo vegetativo da cultura, a partir do “Sentinel-2”, foram utilizadas para ajustar estas ZG e os respetivos mapas dinâmicos de prescrição da rega (VRI-2 e VRI-3). Esta estratégia de gestão espacialmente variável da rega, com o ajustamento da velocidade de deslocamento do pivot e, consequentemente, da dotação de rega em função das necessidades em cada local, tem um impacto imediato na economia de água. No estudo em causa levou ainda à redução da variabilidade espacial do rendimento de produção, em comparação com a gestão convencional da rega, o que representa uma contribuição importante para os desafios da produtividade e da sustentabilidade da produção agrícola. 2026-01-01T00:00:00Z http://hdl.handle.net/10174/42294 Title: Within-field soil variability in agro-silvo-pastoral systems: a baseline for Precision Agriculture adoption Authors: Horta Marques, J.; Carreira, E.; Lloberas, D.; Martins, M.; Ribeiro, H.; Serrano, João Abstract: The Montado represents a dominant agro-silvo-pastoral system across the Mediterranean basin. It integrates pastures, trees (cork oak and/or holm oak), and livestock (ruminants or swine), While Precision Agriculture is more commonly applied to purely agricultural systems, it offers significant potential to optimize Montado management, thereby increasing economic, environmental, social, and cultural sustainability. This study aims to quantify spatial soil variability within Montado plots to identify which essential nutrients for plant production exhibit the greatest distribution range. This study was conducted on two permanent applied research plots, grazed by cattle under a rotational grazing system (total area = 20 ha; location: Mitra/University of Évora, Portugal, Figure 1). Sampling’s carried out at 24 points: 12 under the tree canopy influence and 12 outside the canopy influence. The methodology’s described in Serrano et al (2023) and Horta Marques (2026). Results indicate high within-field variability (Coefficient of Variation around 40% or higher) in the levels of K2O, Mg, P2O5, Ca and all studied micronutrients except for Fe. The findings demonstrate that the observed within-field variability, alongside agronomic expertise and economic and environmental sustainability goals, justifies the implementation of Precision Agriculture in Mediterranean agro-silvo-pastoral systems. 2026-05-31T23:00:00Z http://hdl.handle.net/10174/42289 Title: Impact of Sheep Stocking Rates in Soil Compaction: Case Study in Montado Mediterranean Ecosystem Authors: Serrano, João; Carreira, Emanuel; Shahidian, S.; Paniagua, L.; Moral, F.; Pereira, A. Abstract: The economic return on extensive sheep farming (pasture-based systems) of the Southern of Portugal is low, as it occupies degraded soils. Therefore, the environmental perspective prevails, with the recovery of soil functionality and the preservation of the Montado as an ecosystem of high nature value. This study assesses the impact of two grazing management systems and stocking rates (SR), continuous grazing (CG) with low SR versus deferred grazing (DG) with high SR, on soil compaction. The study was carried out between December 2023 and June 2025 on a 4-ha pasture. This area of natu-ral grassland was divided into four grazing parks of 1 ha each, two under DG management and two under CG management. During the study, the cone index (CI, in kPa) was measured in the topsoil layer (0–30 cm) on eight dates, with an electronic cone penetrometer at 48 georeferenced areas. The results of CI measurement showed no significant differences between treat-ments in all depths measured (0–10, 10–20, and 20–30 cm). These findings are encouraging from the point of view of soil conservation and sustainabil-ity, revealing good prospects for the possible intensification of extensive livestock production. 2026-05-31T23:00:00Z http://hdl.handle.net/10174/42281 Title: Rising Plate Meter as a Tool for Pasture Dry Matter Estimation: Case Study in Mediterranean Dryland Pastures Authors: Serrano, João; Shahidian, S.; Charneca, R.; Paniagua, L.; Moral, F. Abstract: In ruminant-based extensive livestock systems, pastures are one of the main components and the main feeding source given that they are the most eco-nomical resource. Accurate information about pasture dry matter (DM, in kg ha-1) availability is a key parameter in the manager’s decision, particularly when calculating stocking rates and supplementation needs. This study evaluates an electronic sensor (rising plate meter, RPM) to estimate DM in biodiverse dryland pastures. The study was carried out between December 2023 and December 2025 on three pasture fields, two located in Portuguese Alentejo region (Southern Portugal), “Mitra” and “Tapada dos Números”, and one located in Spanish Extremadura region (Cubillos). The experimental work consisted of sensor measurements, followed by the collection of more than 200 pasture samples, distributed between different dates of the pasture vegetative cycles of 2023/2024 and 2024/2025. The best estimation models for DM were obtained based on measurements carried out in Autumn and Winter (R2 > 0.70) and decreased significantly when based on measurements carried out in Spring. These results show the potential for the research and development of proximal and remote sensing tools to support pasture moni-toring and animal production management. 2026-05-31T23:00:00Z