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Prof. João Serrano
University of Évora

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0 Precision Agriculture
0 Animal and dairy science
0 Sensors in Agriculture
0 pasture management
0 Rural Engineering

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Precision Agriculture
pasture management

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Journal article
Published: 10 March 2021 in Agronomy
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Extensive livestock production in Mediterranean climate conditions and acidic soils requires animal feed supplementation. This occurs during the summer and, frequently, also in the autumn and winter, depending on the prevailing rainfall patterns. The purpose of this study was to evaluate the effect of dolomitic limestone application and of tree canopy on availability, quality, and floristic composition of a permanent pasture, grazed by sheep. At the end of autumn, winter, and spring of 2018/2019 and 2019/2020 pasture green and dry matter production (GM and DM, respectively), crude protein (CP), and fiber (neutral detergent fiber) were monitored in 24 sampling points. Half of these points were located in areas amended with dolomitic limestone (COR) and half in unamended areas (UCOR). In each of these, half of the sampling points were located under tree canopy (UTC) and half outside tree canopy (OTC). Pasture floristic composition was monitored in spring 2020. The results show, in autumn, a positive and significant effect (i) of soil pH amendment on pasture DM and CP daily growth rate (kg·ha−1·day−1) (+28.8% and +42.6%, respectively), and (ii) of tree canopy on pasture CP daily growth rate (+26.4%). Both factors affect pasture floristic composition. Pasture species were identified as potential bio-indicators, characteristic of each field area. These results show the practical interest of the soil pH correction to reduce the animal supplementation needs in the critical autumn period in the Mediterranean montado ecosystem.

ACS Style

João Serrano; Shakib Shahidian; Francisco Costa; Emanuel Carreira; Alfredo Pereira; Mário Carvalho. Can Soil pH Correction Reduce the Animal Supplementation Needs in the Critical Autumn Period in Mediterranean Montado Ecosystem? Agronomy 2021, 11, 514 .

AMA Style

João Serrano, Shakib Shahidian, Francisco Costa, Emanuel Carreira, Alfredo Pereira, Mário Carvalho. Can Soil pH Correction Reduce the Animal Supplementation Needs in the Critical Autumn Period in Mediterranean Montado Ecosystem? Agronomy. 2021; 11 (3):514.

Chicago/Turabian Style

João Serrano; Shakib Shahidian; Francisco Costa; Emanuel Carreira; Alfredo Pereira; Mário Carvalho. 2021. "Can Soil pH Correction Reduce the Animal Supplementation Needs in the Critical Autumn Period in Mediterranean Montado Ecosystem?" Agronomy 11, no. 3: 514.

Journal article
Published: 03 March 2021 in Sustainability
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The Montado is an agro-silvo-pastoral ecosystem characteristic of the Mediterranean region. Pasture productivity and, consequently, the possibilities for intensifying livestock production depend on soil fertility. Soil organic matter (SOM) and phosphorus (P2O5) are two indicators of the evolution of soil fertility in this ecosystem. However, their conventional analytical determination by reference laboratory methods is costly, time consuming, and laborious and, thus, does not meet the needs of current production systems. The aim of this study was to evaluate an alternative approach to estimate SOM and soil P2O5 based on near infrared spectroscopy (NIRS) combined with multivariate data analysis. For this purpose, 242 topsoil samples were collected in 2019 in eleven fields. These samples were subjected to reference laboratory analysis and NIRS analysis. For NIRS, 165 samples were used during the calibration phase and 77 samples were used during the external validation phase. The results of this study showed significant correlation between NIRS calibration models and reference methods for quantification of these soil parameters. The coefficient of determination (R2, 0.85 for SOM and 0.76 for P2O5) and the residual predictive deviation (RPD, 2.7 for SOM and 2.2 for P2O5) obtained in external validation indicated the potential of NIRS to estimate SOM and P2O5, which can facilitate farm managers’ decision making in terms of dynamic management of animal grazing and differential fertilizer application.

ACS Style

João Serrano; Shakib Shahidian; José Marques da Silva; Luís Paixão; Mário de Carvalho; Francisco Moral; Julio Nogales-Bueno; Ricardo Teixeira; Marjan Jongen; Tiago Domingos; Ana Rato. Evaluation of Near Infrared Spectroscopy (NIRS) for Estimating Soil Organic Matter and Phosphorus in Mediterranean Montado Ecosystem. Sustainability 2021, 13, 2734 .

AMA Style

João Serrano, Shakib Shahidian, José Marques da Silva, Luís Paixão, Mário de Carvalho, Francisco Moral, Julio Nogales-Bueno, Ricardo Teixeira, Marjan Jongen, Tiago Domingos, Ana Rato. Evaluation of Near Infrared Spectroscopy (NIRS) for Estimating Soil Organic Matter and Phosphorus in Mediterranean Montado Ecosystem. Sustainability. 2021; 13 (5):2734.

Chicago/Turabian Style

João Serrano; Shakib Shahidian; José Marques da Silva; Luís Paixão; Mário de Carvalho; Francisco Moral; Julio Nogales-Bueno; Ricardo Teixeira; Marjan Jongen; Tiago Domingos; Ana Rato. 2021. "Evaluation of Near Infrared Spectroscopy (NIRS) for Estimating Soil Organic Matter and Phosphorus in Mediterranean Montado Ecosystem." Sustainability 13, no. 5: 2734.

Journal article
Published: 17 February 2021 in AgriEngineering
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Dryland pastures provide the basis for animal sustenance in extensive production systems in Iberian Peninsula. These systems have temporal and spatial variability of pasture quality resulting from the diversity of soil fertility and pasture floristic composition, the interaction with trees, animal grazing, and a Mediterranean climate characterized by accentuated seasonality and interannual irregularity. Grazing management decisions are dependent on assessing pasture availability and quality. Conventional analytical determination of crude protein (CP) and fiber (neutral detergent fiber, NDF) by reference laboratory methods require laborious and expensive procedures and, thus, do not meet the needs of the current animal production systems. The aim of this study was to evaluate two alternative approaches to estimate pasture CP and NDF, namely one based on near-infrared spectroscopy (NIRS) combined with multivariate data analysis and the other based on the Normalized Difference Vegetation Index (NDVI) measured in the field by a proximal active optical sensor (AOS). A total of 232 pasture samples were collected from January to June 2020 in eight fields. Of these, 96 samples were processed in fresh form using NIRS. All 232 samples were dried and subjected to reference laboratory and NIRS analysis. For NIRS, fresh and dry samples were split in two sets: a calibration set with half of the samples and an external validation set with the remaining half of the samples. The results of this study showed significant correlation between NIRS calibration models and reference methods for quantifying pasture quality parameters, with greater accuracy in dry samples (R2 = 0.936 and RPD = 4.01 for CP and R2 = 0.914 and RPD = 3.48 for NDF) than fresh samples (R2 = 0.702 and RPD = 1.88 for CP and R2 = 0.720 and RPD = 2.38 for NDF). The NDVI measured by the AOS shows a similar coefficient of determination to the NIRS approach with pasture fresh samples (R2 = 0.707 for CP and R2 = 0.648 for NDF). The results demonstrate the potential of these technologies for estimating CP and NDF in pastures, which can facilitate the farm manager’s decision making in terms of the dynamic management of animal grazing and supplementation needs.

ACS Style

João Serrano; Shakib Shahidian; Ângelo Carapau; Ana Rato. Near-Infrared Spectroscopy (NIRS) and Optical Sensors for Estimating Protein and Fiber in Dryland Mediterranean Pastures. AgriEngineering 2021, 3, 73 -91.

AMA Style

João Serrano, Shakib Shahidian, Ângelo Carapau, Ana Rato. Near-Infrared Spectroscopy (NIRS) and Optical Sensors for Estimating Protein and Fiber in Dryland Mediterranean Pastures. AgriEngineering. 2021; 3 (1):73-91.

Chicago/Turabian Style

João Serrano; Shakib Shahidian; Ângelo Carapau; Ana Rato. 2021. "Near-Infrared Spectroscopy (NIRS) and Optical Sensors for Estimating Protein and Fiber in Dryland Mediterranean Pastures." AgriEngineering 3, no. 1: 73-91.

Journal article
Published: 06 December 2020 in Water
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Climate change, especially the trend towards global warming, will significantly affect the global hydrological cycle, leading to a general reduction of the water available for agriculture. In this scenario, it is essential that research should focus on the development of ‘water saving’ techniques and technologies. This work summarizes the methodology followed in a project for large scale implementation of variable rate irrigation (VRI) systems using center pivots in corn crop. This is based on technologies for monitoring (i) soil electrical conductivity (ECa) and altimetry, (ii) soil moisture content, (iii) vegetation indices (Normalized Difference Vegetation Index, NDVI) obtained from satellite images, and automatic pivot travel speed control technologies. ECa maps were the basis for the definition of first homogeneous management zones (HMZ) in an experimental corn field of 28 ha. NDVI time-series were used to establish the subsequent HMZ and the respective dynamic prescription irrigation maps. The main result of this study was the reduction of spatial yield variability with the VRI management in 2017 compared to the conventional irrigation management. This study demonstrates how a relatively simple approach could be designed and implemented on a large scale, which represents an important and sustainable contribution to the resolution of practical farmer issues.

ACS Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Luís Paixão; Francisco Moral; Rafael Carmona-Cabezas; Sónia Garcia; José Palha; João Noéme. Mapping Management Zones Based on Soil Apparent Electrical Conductivity and Remote Sensing for Implementation of Variable Rate Irrigation—Case Study of Corn under a Center Pivot. Water 2020, 12, 3427 .

AMA Style

João Serrano, Shakib Shahidian, José Marques Da Silva, Luís Paixão, Francisco Moral, Rafael Carmona-Cabezas, Sónia Garcia, José Palha, João Noéme. Mapping Management Zones Based on Soil Apparent Electrical Conductivity and Remote Sensing for Implementation of Variable Rate Irrigation—Case Study of Corn under a Center Pivot. Water. 2020; 12 (12):3427.

Chicago/Turabian Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Luís Paixão; Francisco Moral; Rafael Carmona-Cabezas; Sónia Garcia; José Palha; João Noéme. 2020. "Mapping Management Zones Based on Soil Apparent Electrical Conductivity and Remote Sensing for Implementation of Variable Rate Irrigation—Case Study of Corn under a Center Pivot." Water 12, no. 12: 3427.

Journal article
Published: 28 June 2020 in Applied Sciences
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Pasture quality monitoring is a key element in the decision making process of a farm manager. Laboratory reference methods for assessing quality parameters such as crude protein (CP) or fibers (neutral detergent fiber: NDF) require collection and analytical procedures involving technicians, time, and reagents, making them laborious and expensive. The objective of this work was to evaluate two technological and expeditious approaches for estimating and monitoring the evolution of the quality parameters in biodiverse Mediterranean pastures: (i) near infrared spectroscopy (NIRS) combined with multivariate data analysis and (ii) remote sensing (RS) based on Sentinel-2 imagery to calculate the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI). Between February 2018 and March 2019, 21 sampling processes were carried out in nine fields, totaling 398 pasture samples, of which 315 were used during the calibration phase and 83 were used during the validation phase of the NIRS approach. The average reference values of pasture moisture content (PMC), CP, and NDF, obtained in 24 tests carried out between January and May 2019 in eight fields, were used to evaluate the RS accuracy. The results of this study showed significant correlation between NIRS calibration models or spectral indices obtained by remote sensing (NDVIRS and NDWIRS) and reference methods for quantifying pasture quality parameters, both of which open up good prospects for technological-based service providers to develop applications that enable the dynamic management of animal grazing.

ACS Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Luís Paixão; Emanuel Carreira; Rafael Carmona-Cabezas; Julio Nogales-Bueno; Ana Elisa Rato. Evaluation of Near Infrared Spectroscopy (NIRS) and Remote Sensing (RS) for Estimating Pasture Quality in Mediterranean Montado Ecosystem. Applied Sciences 2020, 10, 4463 .

AMA Style

João Serrano, Shakib Shahidian, José Marques Da Silva, Luís Paixão, Emanuel Carreira, Rafael Carmona-Cabezas, Julio Nogales-Bueno, Ana Elisa Rato. Evaluation of Near Infrared Spectroscopy (NIRS) and Remote Sensing (RS) for Estimating Pasture Quality in Mediterranean Montado Ecosystem. Applied Sciences. 2020; 10 (13):4463.

Chicago/Turabian Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Luís Paixão; Emanuel Carreira; Rafael Carmona-Cabezas; Julio Nogales-Bueno; Ana Elisa Rato. 2020. "Evaluation of Near Infrared Spectroscopy (NIRS) and Remote Sensing (RS) for Estimating Pasture Quality in Mediterranean Montado Ecosystem." Applied Sciences 10, no. 13: 4463.

Journal article
Published: 06 May 2020 in Sustainability
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The Montado ecosystem, predominant in the Mediterranean region, consists of poor soils, a sparse cover of cork and holm with an understory of natural biodiverse pastures, grazed by animals in extensive regime. The recommended procedure for increasing productivity of these pastures is based on the application of phosphate fertilizer. One of the main productivity-limiting factors is, however, associated with soil acidity. The objective of this work was to evaluate the simultaneous effect of the holm oak canopy and the application of dolomitic lime on the productivity and quality of a permanent biodiverse pasture, grazed by sheep, in an acid soil (pH = 5.4 ± 0.3). Pasture was monitored at the end of autumn 2018 and winter and spring 2019. The results show that amendment of soil acidity is a slow and gradual process that improves soil Mg/Mn ratio and has a positive impact on pasture productivity and quality. Pasture crude protein availability (CP, kg·ha−1), which is based on both pasture dry matter yield (kg·ha−1) and quality (CP, %), proved to be a very practical indicator of the contributions of tree canopy and soil acidity correction to the holistic management of the Montado ecosystem.

ACS Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Francisco Moral; Fernando Carvajal-Ramirez; Emanuel Carreira; Alfredo Pereira; Mário De Carvalho. Evaluation of the Effect of Dolomitic Lime Application on Pastures—Case Study in the Montado Mediterranean Ecosystem. Sustainability 2020, 12, 3758 .

AMA Style

João Serrano, Shakib Shahidian, José Marques Da Silva, Francisco Moral, Fernando Carvajal-Ramirez, Emanuel Carreira, Alfredo Pereira, Mário De Carvalho. Evaluation of the Effect of Dolomitic Lime Application on Pastures—Case Study in the Montado Mediterranean Ecosystem. Sustainability. 2020; 12 (9):3758.

Chicago/Turabian Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Francisco Moral; Fernando Carvajal-Ramirez; Emanuel Carreira; Alfredo Pereira; Mário De Carvalho. 2020. "Evaluation of the Effect of Dolomitic Lime Application on Pastures—Case Study in the Montado Mediterranean Ecosystem." Sustainability 12, no. 9: 3758.

Journal article
Published: 25 April 2020 in AgriEngineering
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The estimation of pasture productivity is of great interest for the management of animal grazing. The standard method of assessing pasture mass requires great effort and expense to collect enough samples to accurately represent a pasture. This work presents the results of a long-term study to calibrate a Grassmaster II capacitance probe to estimate pasture productivity in two phases: (i) the calibration phase (2007–2018), which included measurements in 1411 sampling points in three parcels; and (ii) the validation phase (2019), which included measurements in 216 sampling points in eight parcels. A regression analysis was performed between the capacitance (CMR) measured by the probe and values of pasture green matter and dry matter (respectively, GM and DM, in kg ha−1). The results showed significant correlations between GM and CMR and between DM and CMR, especially in the early stages of pasture growth cycle. The analysis of the data grouped by classes of pasture moisture content (PMC) shows higher correlation coefficients for PMC content >80% (r = 0.775; p < 0.01; RMSE = 4806 kg ha−1 and CVRMSE = 28.1% for GM; r = 0.750; p < 0.01; RMSE = 763 kg ha−1 and CVRMSE = 29.7% for DM), with a clear tendency for the accuracy to decrease when the pasture vegetative cycle advances and, consequently, the PMC decreases. The validation of calibration equations when PMC > 80% showed a good approximation between GM or DM measured and GM or DM predicted (r = 0.959; p < 0.01; RMSE = 3191 kg ha−1; CVRMSE = 23.6% for GM; r = 0.953; p 80%.

ACS Style

João Serrano; Shakib Shahidian; Francisco Moral; Fernando Carvajal-Ramirez; José Marques Da Silva. Estimation of Productivity in Dryland Mediterranean Pastures: Long-Term Field Tests to Calibration and Validation of the Grassmaster II Probe. AgriEngineering 2020, 2, 240 -255.

AMA Style

João Serrano, Shakib Shahidian, Francisco Moral, Fernando Carvajal-Ramirez, José Marques Da Silva. Estimation of Productivity in Dryland Mediterranean Pastures: Long-Term Field Tests to Calibration and Validation of the Grassmaster II Probe. AgriEngineering. 2020; 2 (2):240-255.

Chicago/Turabian Style

João Serrano; Shakib Shahidian; Francisco Moral; Fernando Carvajal-Ramirez; José Marques Da Silva. 2020. "Estimation of Productivity in Dryland Mediterranean Pastures: Long-Term Field Tests to Calibration and Validation of the Grassmaster II Probe." AgriEngineering 2, no. 2: 240-255.

Journal article
Published: 03 February 2020 in Agronomy
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Montado is an agro-silvo-pastoral system characterized by a high complexity as a result of the interactions between climate, soil, pasture, trees, and animals. It is in this context that management decisions must be made, for example with respect to soil fertilization, grazing, or animal supplementation. In this work, the effect of the tree canopy on the spatial and temporal variability of the soil and productivity, quality, and floristic composition of the pasture was evaluated. Precision agriculture (PA) technologies for monitoring soil and pasture were also evaluated. The study was carried out between October 2015 and June 2018 in an experimental field of 2.3 ha. The results showed: (i) The positive impact of trees and animal grazing on soil fertility; (ii) the influence of inter-annual variability of precipitation on the pattern of pasture vegetative cycle; (iii) the positive effect of trees in pasture quality; (iv) the negative effect of trees in pasture productivity; (v) the role of pasture floristic composition as an indicator of soil limitations or climatic changes; (vi) the potential of technologies associated with the concept of PA as express tools to decision making support and for the optimization of the herbaceous stratum and the dynamic management of grazing in this ecosystem in a holistic and sustainable form.

ACS Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Luís Paixão; Emanuel Carreira; Alfredo Pereira; Mário Carvalho. Climate Changes Challenges to the Management of Mediterranean Montado Ecosystem: Perspectives for Use of Precision Agriculture Technologies. Agronomy 2020, 10, 218 .

AMA Style

João Serrano, Shakib Shahidian, José Marques Da Silva, Luís Paixão, Emanuel Carreira, Alfredo Pereira, Mário Carvalho. Climate Changes Challenges to the Management of Mediterranean Montado Ecosystem: Perspectives for Use of Precision Agriculture Technologies. Agronomy. 2020; 10 (2):218.

Chicago/Turabian Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Luís Paixão; Emanuel Carreira; Alfredo Pereira; Mário Carvalho. 2020. "Climate Changes Challenges to the Management of Mediterranean Montado Ecosystem: Perspectives for Use of Precision Agriculture Technologies." Agronomy 10, no. 2: 218.

Journal article
Published: 02 December 2019 in AgriEngineering
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Dryland pastures in the Alentejo region, located in the south of Portugal, normally occupy soils that have low fertility but, simultaneously, important spatial variability. Rational application of fertilizers requires knowledge of spatial variability of soil characteristics and crop response, which reinforces the interest of technologies that facilitates the identification of homogeneous management zones (HMZ). In this work, a pasture field of about 25 ha, integrated in the Montado mixed ecosystem (agro-silvo-pastoral), was monitored. Surveys of apparent soil electrical conductivity (ECa) were carried out in November 2017 and October 2018 with a Veris 2000 XA contact sensor. A total of 24 sampling points (30 × 30 m) were established in tree-free zones to allow readings of normalized difference vegetation index (NDVI) and normalized difference water index (NDWI). Historical time series of these indices were obtained from satellite imagery (Sentinel-2) in winter and spring 2017 and 2018. Three zones with different potential productivity were defined based on the results obtained in terms of spatial variability and temporal stability of the measured parameters. These are the basis for the elaboration of differentiated prescription maps of fertilizers with variable application rate technology, taking into account the variability of soil characteristics and pasture development, contributing to the sustainability of this ecosystem.

ACS Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Luís Paixão; José Calado; Mário De Carvalho. Integration of Soil Electrical Conductivity and Indices Obtained through Satellite Imagery for Differential Management of Pasture Fertilization. AgriEngineering 2019, 1, 567 -585.

AMA Style

João Serrano, Shakib Shahidian, José Marques Da Silva, Luís Paixão, José Calado, Mário De Carvalho. Integration of Soil Electrical Conductivity and Indices Obtained through Satellite Imagery for Differential Management of Pasture Fertilization. AgriEngineering. 2019; 1 (4):567-585.

Chicago/Turabian Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Luís Paixão; José Calado; Mário De Carvalho. 2019. "Integration of Soil Electrical Conductivity and Indices Obtained through Satellite Imagery for Differential Management of Pasture Fertilization." AgriEngineering 1, no. 4: 567-585.

Journal article
Published: 03 November 2019 in Remote Sensing
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Management and control operations are crucial for preventing forest fires, especially in Mediterranean forest areas with dry climatic periods. One of them is prescribed fires, in which the biomass fuel present in the controlled plot area must be accurately estimated. The most used methods for estimating biomass are time-consuming and demand too much manpower. Unmanned aerial vehicles (UAVs) carrying multispectral sensors can be used to carry out accurate indirect measurements of terrain and vegetation morphology and their radiometric characteristics. Based on the UAV-photogrammetric project products, four estimators of phytovolume were compared in a Mediterranean forest area, all obtained using the difference between a digital surface model (DSM) and a digital terrain model (DTM). The DSM was derived from a UAV-photogrammetric project based on the structure from a motion algorithm. Four different methods for obtaining a DTM were used based on an unclassified dense point cloud produced through a UAV-photogrammetric project (FFU), an unsupervised classified dense point cloud (FFC), a multispectral vegetation index (FMI), and a cloth simulation filter (FCS). Qualitative and quantitative comparisons determined the ability of the phytovolume estimators for vegetation detection and occupied volume. The results show that there are no significant differences in surface vegetation detection between all the pairwise possible comparisons of the four estimators at a 95% confidence level, but FMI presented the best kappa value (0.678) in an error matrix analysis with reference data obtained from photointerpretation and supervised classification. Concerning the accuracy of phytovolume estimation, only FFU and FFC presented differences higher than two standard deviations in a pairwise comparison, and FMI presented the best RMSE (12.3 m) when the estimators were compared to 768 observed data points grouped in four 500 m2 sample plots. The FMI was the best phytovolume estimator of the four compared for low vegetation height in a Mediterranean forest. The use of FMI based on UAV data provides accurate phytovolume estimations that can be applied on several environment management activities, including wildfire prevention. Multitemporal phytovolume estimations based on FMI could help to model the forest resources evolution in a very realistic way.

ACS Style

Fernando Carvajal-Ramírez; João Manuel Pereira Ramalho Serrano; Francisco Agüera-Vega; Patricio Martínez-Carricondo. A Comparative Analysis of Phytovolume Estimation Methods Based on UAV-Photogrammetry and Multispectral Imagery in a Mediterranean Forest. Remote Sensing 2019, 11, 2579 .

AMA Style

Fernando Carvajal-Ramírez, João Manuel Pereira Ramalho Serrano, Francisco Agüera-Vega, Patricio Martínez-Carricondo. A Comparative Analysis of Phytovolume Estimation Methods Based on UAV-Photogrammetry and Multispectral Imagery in a Mediterranean Forest. Remote Sensing. 2019; 11 (21):2579.

Chicago/Turabian Style

Fernando Carvajal-Ramírez; João Manuel Pereira Ramalho Serrano; Francisco Agüera-Vega; Patricio Martínez-Carricondo. 2019. "A Comparative Analysis of Phytovolume Estimation Methods Based on UAV-Photogrammetry and Multispectral Imagery in a Mediterranean Forest." Remote Sensing 11, no. 21: 2579.

Journal article
Published: 27 June 2019 in Soil and Tillage Research
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The first stage to implement site-specific crop management (SSCM) within an agricultural field consists in determining subfields of similar production potential, that is, management zones (MZ). Different approaches have been proposed to delineate MZ, but sometimes results are inaccurate and unsatisfactory. In this study, the formulation of the Rasch measurement model, as an objective method which synthesizes data with different units into a uniform analytical framework, is considered to calculate measures of production potential at some locations of an olive orchard. Later, they can be used to delimit MZ. With the aim of illustrating this approach, nine soil properties (soil apparent electrical conductivity, clay, sand, and silt content, organic matter, total nitrogen, available phosphorous and potassium, and cation exchange capacity) measured from soil samples taken at 40 locations in a field were considered. The main results, after applying the Rasch model, were a ranking of all locations according to the soil production potential and another one in which the influence on the production potential of each individual soil property is shown. Moreover, those soil samples or properties which have any anomaly where highlighted; this information can be necessary to conduct site-specific treatments, leading to a more cost-effective and sustainable field management. Additionally, estimates using geostatistical algorithms were utilised to map soil production potential and to delineate with a rational basis the MZ in the field.

ACS Style

F.J. Moral; F.J. Rebollo; C. Campillo; João Serrano. Using an objective and probabilistic model to delineate homogeneous zones in hedgerow olive orchards. Soil and Tillage Research 2019, 194, 104308 .

AMA Style

F.J. Moral, F.J. Rebollo, C. Campillo, João Serrano. Using an objective and probabilistic model to delineate homogeneous zones in hedgerow olive orchards. Soil and Tillage Research. 2019; 194 ():104308.

Chicago/Turabian Style

F.J. Moral; F.J. Rebollo; C. Campillo; João Serrano. 2019. "Using an objective and probabilistic model to delineate homogeneous zones in hedgerow olive orchards." Soil and Tillage Research 194, no. : 104308.

Journal article
Published: 26 April 2019 in Remote Sensing
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Fire severity is a key factor for management of post-fire vegetation regeneration strategies because it quantifies the impact of fire, describing the amount of damage. Several indices have been developed for estimation of fire severity based on terrestrial observation by satellite imagery. In order to avoid the implicit limitations of this kind of data, this work employed an Unmanned Aerial Vehicle (UAV) carrying a high-resolution multispectral sensor including green, red, near-infrared, and red edge bands. Flights were carried out pre- and post-controlled fire in a Mediterranean forest. The products obtained from the UAV-photogrammetric projects based on the Structure from Motion (SfM) algorithm were a Digital Surface Model (DSM) and multispectral images orthorectified in both periods and co-registered in the same absolute coordinate system to find the temporal differences (d) between pre- and post-fire values of the Excess Green Index (EGI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Red Edge (NDRE) index. The differences of indices (dEGI, dNDVI, and dNDRE) were reclassified into fire severity classes, which were compared with the reference data identified through the in situ fire damage location and Artificial Neural Network classification. Applying an error matrix analysis to the three difference of indices, the overall Kappa accuracies of the severity maps were 0.411, 0.563, and 0.211 and the Cramer’s Value statistics were 0.411, 0.582, and 0.269 for dEGI, dNDVI, and dNDRE, respectively. The chi-square test, used to compare the average of each severity class, determined that there were no significant differences between the three severity maps, with a 95% confidence level. It was concluded that dNDVI was the index that best estimated the fire severity according to the UAV flight conditions and sensor specifications.

ACS Style

Fernando Carvajal-Ramírez; José Rafael Marques Da Silva; Francisco Agüera-Vega; Patricio Martínez-Carricondo; João Serrano; Francisco Jesús Moral. Evaluation of Fire Severity Indices Based on Pre- and Post-Fire Multispectral Imagery Sensed from UAV. Remote Sensing 2019, 11, 993 .

AMA Style

Fernando Carvajal-Ramírez, José Rafael Marques Da Silva, Francisco Agüera-Vega, Patricio Martínez-Carricondo, João Serrano, Francisco Jesús Moral. Evaluation of Fire Severity Indices Based on Pre- and Post-Fire Multispectral Imagery Sensed from UAV. Remote Sensing. 2019; 11 (9):993.

Chicago/Turabian Style

Fernando Carvajal-Ramírez; José Rafael Marques Da Silva; Francisco Agüera-Vega; Patricio Martínez-Carricondo; João Serrano; Francisco Jesús Moral. 2019. "Evaluation of Fire Severity Indices Based on Pre- and Post-Fire Multispectral Imagery Sensed from UAV." Remote Sensing 11, no. 9: 993.

Journal article
Published: 25 January 2019 in Computers and Electronics in Agriculture
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Pasture soils can exhibit a high spatial variability which should be characterised to properly manage the yield potential of different within-field areas. Thus, with the aim of proposing an objective methodology to estimate the pasture soil fertility and, later, analyse its spatial pattern, the formulation of the probabilistic Rasch model constitutes a new approach in pasture fields. In this research, a case study was performed to illustrate the proposed method. Consequently, after taking some soil samples (34) and measuring different soil properties (sand, silt, and clay content, organic matter, phosphorus, potassium, moisture content, soil apparent electrical conductivity, elevation, and slope), the use of the Rasch model provides a integrated measure of pasture soil fertility at each sampling location, which can be computed using geostatistical algorithms to map its spatial distribution throughout the field. After verifying that data fit the model reasonably, the main outputs of the Rasch model were a ranking of all sampling locations according to the pasture soil fertility and another ranking of the soil properties according to their influence on the soil fertility, being the topographical properties (slope and elevation) the most influential. Later, the ordinary kriging algorithm was utilised to estimate soil fertility throughout the pasture field and the probability kriging algorithm was used to provide information for hazard assessment of pasture soil fertility, being both kriged maps the basis to delineate homogeneous zones. Finally, vegetation indices and pasture yield data at sampling points were employed to check that two zones previously determined were different. The analysis of zonal differences in pasture systems can lead to an optimal application of inputs and a more cost-effective management, with the associated environmental, economic, and energetic benefits.

ACS Style

F.J. Moral; F.J. Rebollo; J.M. Serrano. Estimating and mapping pasture soil fertility in a portuguese montado based on a objective model and geostatistical techniques. Computers and Electronics in Agriculture 2019, 157, 500 -508.

AMA Style

F.J. Moral, F.J. Rebollo, J.M. Serrano. Estimating and mapping pasture soil fertility in a portuguese montado based on a objective model and geostatistical techniques. Computers and Electronics in Agriculture. 2019; 157 ():500-508.

Chicago/Turabian Style

F.J. Moral; F.J. Rebollo; J.M. Serrano. 2019. "Estimating and mapping pasture soil fertility in a portuguese montado based on a objective model and geostatistical techniques." Computers and Electronics in Agriculture 157, no. : 500-508.

Journal article
Published: 01 January 2019 in Water
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Extensive animal production in Iberian Peninsula is based on pastures, integrated within the important agro-silvo-pastoral system, named “montado” in Portugal and “dehesa” in Spain. Temperature and precipitation are the main driving climatic factors affecting agricultural productivity and, in dryland pastures, the hydrological cycle of soil, identified by soil moisture content (SMC), is the main engine of the vegetation development. The objective of this work was to evaluate the normalized difference water index (NDWI) based on Sentinel-2 imagery as a tool for monitoring pasture seasonal dynamics and inter-annual variability in a Mediterranean agro-silvo-pastoral system. Forty-one valid NDWI records were used between January and June 2016 and between January 2017 and June 2018. The 2.3 ha experimental field is located within the “Mitra” farm, in the South of Portugal. Soil moisture content, pasture moisture content (PMC), pasture surface temperature (Tir), pasture biomass productivity and pasture quality degradation index (PQDI) were evaluated in 12 satellite pixels (10 m × 10 m). The results show significant correlations (p < 0.01) between NDWI and: (i) SMC (R2 = 0.7548); (ii) PMC (R2 = 0.8938); (iii) Tir (R2 = 0.5428); (iv) biomass (R2 = 0.7556); and (v) PQDI (R2 = 0.7333). These findings suggest that satellite-derived NDWI can be used in site-specific management of “montado” ecosystem to support farmers’ decision making.

ACS Style

João Serrano; Shakib Shahidian; José Marques Da Silva. Evaluation of Normalized Difference Water Index as a Tool for Monitoring Pasture Seasonal and Inter-Annual Variability in a Mediterranean Agro-Silvo-Pastoral System. Water 2019, 11, 62 .

AMA Style

João Serrano, Shakib Shahidian, José Marques Da Silva. Evaluation of Normalized Difference Water Index as a Tool for Monitoring Pasture Seasonal and Inter-Annual Variability in a Mediterranean Agro-Silvo-Pastoral System. Water. 2019; 11 (1):62.

Chicago/Turabian Style

João Serrano; Shakib Shahidian; José Marques Da Silva. 2019. "Evaluation of Normalized Difference Water Index as a Tool for Monitoring Pasture Seasonal and Inter-Annual Variability in a Mediterranean Agro-Silvo-Pastoral System." Water 11, no. 1: 62.

Journal article
Published: 11 October 2018 in Water
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Montado is an agro-forestry system occupying a large surface in countries of the Mediterranean region. In this system, the natural dryland pasture is the principal source for animal feed in extensive grazing. The climatic seasonality associated with the inter-annual irregularity of precipitation greatly influences the development of pasture and its vegetative cycle. The end of spring is a critical period in terms of animal feed due to the notable reduction in the nutritive value of the plants. The objective of this work was to evaluate, through the correlation between pasture quality indexes (Pasture Quality Degradation Index, PQDI and Normalized Difference Vegetation Index, NDVI), two technological approaches for monitoring the evolution of the quality of a biodiverse pasture in the period of greatest vegetative development (between February and June). The technological approaches consisted of (i) proximal sensing (PS), with the use of an active optical sensor; and (ii) remote sensing (RS), using images captured by a Sentinel-2 satellite. The results of this study show strong and significant correlations between PQDI and NDVI (obtained by PS or RS). These two techniques (PS or RS) can, therefore, be used in a complementary way to identify and anticipate the food supplementation needs for animals and support farmers in decision making.

ACS Style

João Serrano; Shakib Shahidian; José Marques Da Silva. Monitoring Seasonal Pasture Quality Degradation in the Mediterranean Montado Ecosystem: Proximal versus Remote Sensing. Water 2018, 10, 1422 .

AMA Style

João Serrano, Shakib Shahidian, José Marques Da Silva. Monitoring Seasonal Pasture Quality Degradation in the Mediterranean Montado Ecosystem: Proximal versus Remote Sensing. Water. 2018; 10 (10):1422.

Chicago/Turabian Style

João Serrano; Shakib Shahidian; José Marques Da Silva. 2018. "Monitoring Seasonal Pasture Quality Degradation in the Mediterranean Montado Ecosystem: Proximal versus Remote Sensing." Water 10, no. 10: 1422.

Research article
Published: 15 March 2018 in Agroforestry Systems
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Montado is a silvo-pastoral ecosystem of the Mediterranean region, a mixed system of trees and grass, where livestock graze. The information about the spatial and temporal variability of pastures constitutes the basis to estimate available feed, a fundamental decision support tool for the farm manager to define the animal stocking or the rotation of the grazed paddocks. In this study, the intrinsic features of high spatial–temporal variability of Mediterranean grazed pastures were assessed with the objective of evaluating the suitability of two proximal sensing techniques (an active optical sensor, AOS and a capacitance probe) for easily monitoring seasonal variability of pasture productivity and quality linked to animal grazing patterns. The correlation between pasture and sensor parameters was consistent between capacitance and pasture productivity (r2 = 0.68, P < 0.01; and r2 = 0.87, P < 0.01, respectively for green pasture biomass, PB and pasture moisture content, PMC), between NDVI and pasture productivity (r2 = 0.73, P < 0.01; and r2 = 0.96, P < 0.01, respectively for PB and PMC) and between NDVI and pasture quality (r2 = 0.44, P < 0.05; r2 = 0.69, P < 0.01; and r2 = 0.78, P < 0.01, respectively for ash, crude protein, CP and neutral detergent fibre, NDF). The approach is a promising methodology for assessing seasonal changes in pasture that have values of biomass that range between 2000 and 85,000 kg ha−1 and vegetative sates from de green and leafy to dry. These results can be an important starting point for studies of evaluation and calibration of the optical sensor specifically for pasture quality assessment in different types of biodiverse pastures. This is a key factor for the management of animal grazing intensity and calculation of feed supplementation needs.

ACS Style

João Serrano; Elvira Sales-Baptista; Shakib Shahidian; J. Marques da Silva; I. Ferraz de Oliveira; J. Lopes de Castro; Alfredo Pereira; M. Cancela D’Abreu; Mário de Carvalho. Proximal sensors for monitoring seasonal changes of feeding sites selected by grazing ewes. Agroforestry Systems 2018, 95, 55 -69.

AMA Style

João Serrano, Elvira Sales-Baptista, Shakib Shahidian, J. Marques da Silva, I. Ferraz de Oliveira, J. Lopes de Castro, Alfredo Pereira, M. Cancela D’Abreu, Mário de Carvalho. Proximal sensors for monitoring seasonal changes of feeding sites selected by grazing ewes. Agroforestry Systems. 2018; 95 (1):55-69.

Chicago/Turabian Style

João Serrano; Elvira Sales-Baptista; Shakib Shahidian; J. Marques da Silva; I. Ferraz de Oliveira; J. Lopes de Castro; Alfredo Pereira; M. Cancela D’Abreu; Mário de Carvalho. 2018. "Proximal sensors for monitoring seasonal changes of feeding sites selected by grazing ewes." Agroforestry Systems 95, no. 1: 55-69.

Journal article
Published: 13 February 2018 in Sensors
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The Montado is a silvo-pastoral system characterized by open canopy woodlands with natural or cultivated grassland in the undercover and grazing animals. The aims of this study were to present several proximal sensors with potential to monitor relevant variables in the complex montado ecosystem and demonstrate their application in a case study designed to evaluate the effect of trees on the pasture. This work uses data collected between March and June 2016, at peak of dryland pasture production under typical Mediterranean conditions, in twenty four sampling points, half under tree canopy (UTC) and half outside tree canopy (OTC). Correlations were established between pasture biomass and capacitance measured by a commercial probe and between pasture quality and normalized difference vegetation index (NDVI) measured by a commercial active optical sensor. The interest of altimetric and apparent soil electrical conductivity maps as the first step in the implementation of precision agriculture projects was demonstrated. The use of proximal sensors to monitor soil moisture content, pasture photosynthetically active radiation and temperature helped to explain the influence of trees on pasture productivity and quality. The significant and strong correlations obtained between capacitance and pasture biomass and between NDVI and pasture nutritive value (in terms of crude protein, CP and neutral detergent fibre, NDF) can make an important contribution to determination of key components of pasture productivity and quality and implementation of site-specific pasture management. Animal tracking demonstrated its potential to be an important tool for understanding the interaction between various factors and components that interrelate in the montado ecosystem and to support grazing management decisions.

ACS Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Mário De Carvalho. A Holistic Approach to the Evaluation of the Montado Ecosystem Using Proximal Sensors. Sensors 2018, 18, 570 .

AMA Style

João Serrano, Shakib Shahidian, José Marques Da Silva, Mário De Carvalho. A Holistic Approach to the Evaluation of the Montado Ecosystem Using Proximal Sensors. Sensors. 2018; 18 (2):570.

Chicago/Turabian Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Mário De Carvalho. 2018. "A Holistic Approach to the Evaluation of the Montado Ecosystem Using Proximal Sensors." Sensors 18, no. 2: 570.

Journal article
Published: 01 January 2018 in Revista de Ciências Agrárias
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ACS Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Eliana Machado; Mário Carvalho. Avaliação do efeito das árvores sobre a produtividade e sobre a qualidade da pastagem no ecossistema montado: estudo de caso. Revista de Ciências Agrárias 2018, 41, 72 -81.

AMA Style

João Serrano, Shakib Shahidian, José Marques Da Silva, Eliana Machado, Mário Carvalho. Avaliação do efeito das árvores sobre a produtividade e sobre a qualidade da pastagem no ecossistema montado: estudo de caso. Revista de Ciências Agrárias. 2018; 41 (1):72-81.

Chicago/Turabian Style

João Serrano; Shakib Shahidian; José Marques Da Silva; Eliana Machado; Mário Carvalho. 2018. "Avaliação do efeito das árvores sobre a produtividade e sobre a qualidade da pastagem no ecossistema montado: estudo de caso." Revista de Ciências Agrárias 41, no. 1: 72-81.

Journal article
Published: 27 November 2017 in International Journal of Remote Sensing
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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 that 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, 24 geo-referenced composite soil samples (12 under tree canopy and 12 outside tree canopy) were collected from the 0.0–0.3 m soil layer. The soil samples were analysed 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 24 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 fibre. 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.

ACS Style

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; Mário de Carvalho. Tree influence on soil and pasture: contribution of proximal sensing to pasture productivity and quality estimation in montado ecosystems. International Journal of Remote Sensing 2017, 39, 4801 -4829.

AMA Style

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, Mário de Carvalho. Tree influence on soil and pasture: contribution of proximal sensing to pasture productivity and quality estimation in montado ecosystems. International Journal of Remote Sensing. 2017; 39 (14):4801-4829.

Chicago/Turabian Style

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; 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 39, no. 14: 4801-4829.

Journal article
Published: 01 January 2017 in Journal of Soil Science and Plant Nutrition
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Conventionally, vineyard fertilizer management has been based on information from composite soil samples and no account has been taken of the existing spatial variability in soil fertility. This study presents a quantitative analysis of soil phosphorus (P2O5) and potassium (K2O) content as well as pH carried out in an 80 ha vineyard, during 2011 and 2013 in order to identify their spatial variability and temporal stability. Additionally a quantitative analysis of plant P2O5 and K2O content was carried out in 2013 with the objective of evaluating the spatial variability of plant nutrients. In 2013 a contact sensor was used to survey soil apparent electrical conductivity (ECa) and an active optical sensor was used to measure the plant Normalized Difference Vegetation Index (NDVI). The results showed a low potential for implementing site-specific management of phosphorus fertilizer but an interesting potential for implementing site-specific management of potassium fertilizer and pH correction. The concentration of P2O5 and K2O in the plant showed a CV<30%, with adequate values in almost the entire area of the field, in contrast to the concentration of these main macronutrients in the topsoil. These results show that for differential nutrient management of vineyards, plant nutrient concentration is a more stable tool than soil nutrients concentration. The ECa and the NDVI presented weak correlations with soil and plant concentration of, , respectively, P2O5 and K2O, which shows that further development of vegetation operational sensors is needed to support decision making in the vineyard fertilization management

ACS Style

João Serrano; Luis Leopoldo Silva; S. Shahidian; Adélia Sousa; Fátima Baptista. Differential vineyard fertilizer management based on nutrient,s spatio-temporal variability. Journal of Soil Science and Plant Nutrition 2017, 17, 46 -61.

AMA Style

João Serrano, Luis Leopoldo Silva, S. Shahidian, Adélia Sousa, Fátima Baptista. Differential vineyard fertilizer management based on nutrient,s spatio-temporal variability. Journal of Soil Science and Plant Nutrition. 2017; 17 (1):46-61.

Chicago/Turabian Style

João Serrano; Luis Leopoldo Silva; S. Shahidian; Adélia Sousa; Fátima Baptista. 2017. "Differential vineyard fertilizer management based on nutrient,s spatio-temporal variability." Journal of Soil Science and Plant Nutrition 17, no. 1: 46-61.