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Remote-sensing measurements are crucial for smart-farming applications, crop monitoring, and yield forecasting, especially in fields characterized by high heterogeneity. Therefore, in this study, Precision Viticulture (PV) methods using proximal- and remote-sensing technologies were exploited and compared in a table grape vineyard to monitor and evaluate the spatial variation of selected vegetation indices and biophysical variables throughout selected phenological stages (multi-seasonal data), from veraison to harvest. The Normalized Difference Vegetation Index and the Normalized Difference Red-Edge Index were calculated by utilizing satellite imagery (Sentinel-2) and proximal sensing (active crop canopy sensor Crop Circle ACS-470) to assess the correlation between the outputs of the different sensing methods. Moreover, numerous vegetation indices and vegetation biophysical variables (VBVs), such as the Modified Soil Adjusted Vegetation Index, the Normalized Difference Water Index, the Fraction of Vegetation Cover, and the Fraction of Absorbed Photosynthetically Active Radiation, were calculated, using the satellite data. The vegetation indices analysis revealed different degrees of correlation when using diverse sensing methods, various measurement dates, and different parts of the cultivation. The results revealed the usefulness of proximal- and remote-sensing-derived vegetation indices and variables and especially of Normalized Difference Vegetation Index and Fraction of Absorbed Photosynthetically Active Radiation in the monitoring of vineyard condition and yield examining, since they were demonstrated to have a very high degree of correlation (coefficient of determination was 0.87). The adequate correlation of the vegetation indices with the yield during the latter part of the veraison stage provides valuable information for the future estimation of production in broader areas.
Nicoleta Darra; Emmanouil Psomiadis; Aikaterini Kasimati; Achilleas Anastasiou; Evangelos Anastasiou; Spyros Fountas. Remote and Proximal Sensing-Derived Spectral Indices and Biophysical Variables for Spatial Variation Determination in Vineyards. Agronomy 2021, 11, 741 .
AMA StyleNicoleta Darra, Emmanouil Psomiadis, Aikaterini Kasimati, Achilleas Anastasiou, Evangelos Anastasiou, Spyros Fountas. Remote and Proximal Sensing-Derived Spectral Indices and Biophysical Variables for Spatial Variation Determination in Vineyards. Agronomy. 2021; 11 (4):741.
Chicago/Turabian StyleNicoleta Darra; Emmanouil Psomiadis; Aikaterini Kasimati; Achilleas Anastasiou; Evangelos Anastasiou; Spyros Fountas. 2021. "Remote and Proximal Sensing-Derived Spectral Indices and Biophysical Variables for Spatial Variation Determination in Vineyards." Agronomy 11, no. 4: 741.
In the past years, several machine-learning-based techniques have arisen for providing effective crop protection. For instance, deep neural networks have been used to identify different types of weeds under different real-world conditions. However, these techniques usually require extensive involvement of experts working iteratively in the development of the most suitable machine learning system. To support this task and save resources, a new technique called Automated Machine Learning has started being studied. In this work, a complete open-source Automated Machine Learning system was evaluated with two different datasets, (i) The Early Crop Weeds dataset and (ii) the Plant Seedlings dataset, covering the weeds identification problem. Different configurations, such as the use of plant segmentation, the use of classifier ensembles instead of Softmax and training with noisy data, have been compared. The results showed promising performances of 93.8% and 90.74% F1 score depending on the dataset used. These performances were aligned with other related works in AutoML, but they are far from machine-learning-based systems manually fine-tuned by human experts. From these results, it can be concluded that finding a balance between manual expert work and Automated Machine Learning will be an interesting path to work in order to increase the efficiency in plant protection.
Borja Espejo-Garcia; Ioannis Malounas; Eleanna Vali; Spyros Fountas. Testing the Suitability of Automated Machine Learning for Weeds Identification. AI 2021, 2, 34 -47.
AMA StyleBorja Espejo-Garcia, Ioannis Malounas, Eleanna Vali, Spyros Fountas. Testing the Suitability of Automated Machine Learning for Weeds Identification. AI. 2021; 2 (1):34-47.
Chicago/Turabian StyleBorja Espejo-Garcia; Ioannis Malounas; Eleanna Vali; Spyros Fountas. 2021. "Testing the Suitability of Automated Machine Learning for Weeds Identification." AI 2, no. 1: 34-47.
A three-year experiment was carried out in Central Greece to assess the use of different tillage practices (Conventional, Reduced, and No tillage) for seedbed preparation, in a double cropping per year rotation of irrigated and rainfed energy crops for biomass production for first- and second-generation biofuel production. A life cycle assessment (LCA) study was performed for the first year of crop rotation to evaluate the environmental impact of using different tillage practices, identifying the processes with greater influence on the overall environmental burden (hotspots) and demonstrating the potential environmental benefits from the land management change. LCA results revealed that fertilizer application and diesel fuel consumption, as well as their production stages, were the hot-spot processes for each treatment. In the present study, different tillage treatments compared using mass- and area-based functional unit (FU), revealing that reduced tillage, using strip tillage for spring crop and disc harrow for winter crops, and no tillage treatment had the best environmental performance, respectively. Comparison between the prevailing in the area monoculture cotton crop with the proposed double energy crop rotation adopting conservation tillage practices, using mass and energy value FU, showed that cotton crop had higher environmental impact.
Anna Vatsanidou; Christos Kavalaris; Spyros Fountas; Nikolaos Katsoulas; Theofanis Gemtos. A Life Cycle Assessment of Biomass Production from Energy Crops in Crop Rotation Using Different Tillage System. Sustainability 2020, 12, 6978 .
AMA StyleAnna Vatsanidou, Christos Kavalaris, Spyros Fountas, Nikolaos Katsoulas, Theofanis Gemtos. A Life Cycle Assessment of Biomass Production from Energy Crops in Crop Rotation Using Different Tillage System. Sustainability. 2020; 12 (17):6978.
Chicago/Turabian StyleAnna Vatsanidou; Christos Kavalaris; Spyros Fountas; Nikolaos Katsoulas; Theofanis Gemtos. 2020. "A Life Cycle Assessment of Biomass Production from Energy Crops in Crop Rotation Using Different Tillage System." Sustainability 12, no. 17: 6978.
Precision Agriculture (PA) is a crop site-specific management system that aims for sustainability, adopting agricultural practices more friendly to the environment, like the variable rate application (VRA) technique. Many studies have dealt with the effectiveness of VRA to reduce nitrogen (N) fertilizer, while achieving increased profit and productivity. However, only limited attention was given to VRA’s environmental impact. In this study an International Organization for Standardization (ISO) based Life Cycle Assessment (LCA) performed to identify the environmental effects of N VRA on a small pear orchard, compared to the conventional uniform application. A Cradle to Gate system with a functional unit (FU) of 1 kg of pears was analyzed including high quality primary data of two productive years, including also the non-productive years, as well as all the emissions during pear growing and the supply chains of all inputs, projecting them to the lifespan of the orchard. A methodology was adopted, modelling individual years and averaging over the orchard’s lifetime. Results showed that Climate change, Water scarcity, Fossil fuels and Particulate formation were the most contributing impact categories to the overall environmental impact of the pear orchard lifespan, where climate change and particulates were largely determined by CO2, N2O, and NH3 emissions to the air from fertilizer production and application, and as CO2 from tractor use. Concerning fertilization practice, when VRA was combined with a high yield year, this resulted in significantly reduced environmental impact. LCA evaluating an alternative fertilizer management system in a Greek pear orchard revealed the environmental impact reduction potential of that system.
Anna Vatsanidou; Spyros Fountas; Vasileios Liakos; George Nanos; Nikolaos Katsoulas; Theofanis Gemtos. Life Cycle Assessment of Variable Rate Fertilizer Application in a Pear Orchard. Sustainability 2020, 12, 6893 .
AMA StyleAnna Vatsanidou, Spyros Fountas, Vasileios Liakos, George Nanos, Nikolaos Katsoulas, Theofanis Gemtos. Life Cycle Assessment of Variable Rate Fertilizer Application in a Pear Orchard. Sustainability. 2020; 12 (17):6893.
Chicago/Turabian StyleAnna Vatsanidou; Spyros Fountas; Vasileios Liakos; George Nanos; Nikolaos Katsoulas; Theofanis Gemtos. 2020. "Life Cycle Assessment of Variable Rate Fertilizer Application in a Pear Orchard." Sustainability 12, no. 17: 6893.
Farming faces challenges that increase the adverse effects on farms’ economics, labor, and the environment. Smart farming technologies (SFTs) are expected to assist in reverting this situation. In this work, 1064 SFTs were derived from scientific papers, research projects, and industrial products. They were classified by technology readiness level (TRL), typology, and field operation, and they were assessed for their economic, environmental, and labor impact, as well as their adoption readiness from end-users. It was shown that scientific articles dealt with SFTs of lower TRL than research projects. In scientific articles, researchers investigated mostly recording technologies, while, in research projects, they focused primarily on farm management information systems and robotic/automation systems. Scouting technologies were the main SFT type in scientific papers and research projects, but variable rate application technologies were mostly located in commercial products. In scientific papers, there was limited analysis of economic, environmental, and labor impact of the SFTs under investigation, while, in research projects, these impacts were studied thoroughly. Further, in commercial SFTs, the focus was on economic impact and less on labor and environmental issues. With respect to adoption readiness, it was found that all of the factors to facilitate SFT adoption became more positive moving from SFTs in scientific papers to fully functional commercial SFTs, indicating that SFTs reach the market when most of these factors are addressed for the benefit of the farmers. This SFT analysis is expected to inform researchers on adapting their research, as well as help policy-makers adjust their strategy toward digitized agriculture adoption and farmers with the current situation and future trends of SFTs.
Athanasios T. Balafoutis; Frits K. Van Evert; Spyros Fountas. Smart Farming Technology Trends: Economic and Environmental Effects, Labor Impact, and Adoption Readiness. Agronomy 2020, 10, 743 .
AMA StyleAthanasios T. Balafoutis, Frits K. Van Evert, Spyros Fountas. Smart Farming Technology Trends: Economic and Environmental Effects, Labor Impact, and Adoption Readiness. Agronomy. 2020; 10 (5):743.
Chicago/Turabian StyleAthanasios T. Balafoutis; Frits K. Van Evert; Spyros Fountas. 2020. "Smart Farming Technology Trends: Economic and Environmental Effects, Labor Impact, and Adoption Readiness." Agronomy 10, no. 5: 743.
Modern agriculture is related to a revolution that occurred in a large group of technologies (e.g., informatics, sensors, navigation) within the last decades. In crop production systems, there are field operations that are quite labour-intensive either due to their complexity or because of the fact that they are connected to sensitive plants/edible product interaction, or because of the repetitiveness they require throughout a crop production cycle. These are the key factors for the development of agricultural robots. In this paper, a systematic review of the literature has been conducted on research and commercial agricultural robotics used in crop field operations. This study underlined that the most explored robotic systems were related to harvesting and weeding, while the less studied were the disease detection and seeding robots. The optimization and further development of agricultural robotics are vital, and should be evolved by producing faster processing algorithms, better communication between the robotic platforms and the implements, and advanced sensing systems.
Spyros Fountas; Nikos Mylonas; Ioannis Malounas; Efthymios Rodias; Christoph Hellmann Santos; Erik Pekkeriet. Agricultural Robotics for Field Operations. Sensors 2020, 20, 2672 .
AMA StyleSpyros Fountas, Nikos Mylonas, Ioannis Malounas, Efthymios Rodias, Christoph Hellmann Santos, Erik Pekkeriet. Agricultural Robotics for Field Operations. Sensors. 2020; 20 (9):2672.
Chicago/Turabian StyleSpyros Fountas; Nikos Mylonas; Ioannis Malounas; Efthymios Rodias; Christoph Hellmann Santos; Erik Pekkeriet. 2020. "Agricultural Robotics for Field Operations." Sensors 20, no. 9: 2672.
Data of canopy morphology are crucial for cultivation tasks within orchards. In this study, a 2D light detection and range (LiDAR) laser scanner system was mounted on a tractor, tested on a box with known dimensions (1.81 m × 0.6 m × 0.6 m), and applied in an apple orchard to obtain the 3D structural parameters of the trees (n = 224). The analysis of a metal box which considered the height of four sides resulted in a mean absolute error (MAE) of 8.18 mm with a bias (MBE) of 2.75 mm, representing a root mean square error (RMSE) of 1.63% due to gaps in the point cloud and increased incident angle with enhanced distance between laser aperture and the object. A methodology based on a bivariate point density histogram is proposed to estimate the stem position of each tree. The cylindrical boundary was projected around the estimated stem positions to segment each individual tree. Subsequently, height, stem diameter, and volume of the segmented tree point clouds were estimated and compared with manual measurements. The estimated stem position of each tree was defined using a real time kinematic global navigation satellite system, (RTK-GNSS) resulting in an MAE and MBE of 33.7 mm and 36.5 mm, respectively. The coefficient of determination (R2) considering manual measurements and estimated data from the segmented point clouds appeared high with, respectively, R2 and RMSE of 0.87 and 5.71% for height, 0.88 and 2.23% for stem diameter, as well as 0.77 and 4.64% for canopy volume. Since a certain error for the height and volume measured manually can be assumed, the LiDAR approach provides an alternative to manual readings with the advantage of getting tree individual data of the entire orchard.
Nikos Tsoulias; Dimitrios S. Paraforos; Spyros Fountas; Manuela Zude-Sasse. Estimating Canopy Parameters Based on the Stem Position in Apple Trees Using a 2D LiDAR. Agronomy 2019, 9, 740 .
AMA StyleNikos Tsoulias, Dimitrios S. Paraforos, Spyros Fountas, Manuela Zude-Sasse. Estimating Canopy Parameters Based on the Stem Position in Apple Trees Using a 2D LiDAR. Agronomy. 2019; 9 (11):740.
Chicago/Turabian StyleNikos Tsoulias; Dimitrios S. Paraforos; Spyros Fountas; Manuela Zude-Sasse. 2019. "Estimating Canopy Parameters Based on the Stem Position in Apple Trees Using a 2D LiDAR." Agronomy 9, no. 11: 740.
Spray drift is one of the most important causes of pollution from plant protection products and it puts the health of the environment, animals, and humans at risk. There is; thus, an urgent need to develop measures for its reduction. Among the factors that affect spray drift are the weather conditions during application of spraying. The objective of this study was to develop and evaluate a spray drift evaluation tool based on an existing model by TOPPS-Prowadis to improve the process of plant protection products’ application and to mitigate spray drift for specific meteorological conditions in Greece that are determined, based on weather forecast, by reassessing the limits for wind speed and direction, temperature, and air relative humidity set in the tool. The new limits were tested by conducting experimental work in the vineyard of the Agricultural University of Athens with a trailed air-assisted sprayer for bush and tree crops, using the ISO 22866:2005 methodology. The results showed that the limits set are consistent with the values of the spray drift measured and follows the tool’s estimates of low, medium, and high risk of spray drift.
Georgios Bourodimos; Michael Koutsiaras; Vasilios Psiroukis; Athanasios Balafoutis; Spyros Fountas. Development and Field Evaluation of a Spray Drift Risk Assessment Tool for Vineyard Spraying Application. Agriculture 2019, 9, 181 .
AMA StyleGeorgios Bourodimos, Michael Koutsiaras, Vasilios Psiroukis, Athanasios Balafoutis, Spyros Fountas. Development and Field Evaluation of a Spray Drift Risk Assessment Tool for Vineyard Spraying Application. Agriculture. 2019; 9 (8):181.
Chicago/Turabian StyleGeorgios Bourodimos; Michael Koutsiaras; Vasilios Psiroukis; Athanasios Balafoutis; Spyros Fountas. 2019. "Development and Field Evaluation of a Spray Drift Risk Assessment Tool for Vineyard Spraying Application." Agriculture 9, no. 8: 181.
Table grapes are a crop with high nutritional value that need to be monitored often to achieve high yield and quality. Non-destructive methods, such as satellite and proximal sensing, are widely used to estimate crop yield and quality characteristics, and spectral vegetation indices (SVIs) are commonly used to present site specific information. The aim of this study was the assessment of SVIs derived from satellite and proximal sensing at different growth stages of table grapes from veraison to harvest. The study took place in a commercial table grape vineyard (Vitis vinifera cv. Thompson Seedless) during three successive cultivation years (2015–2017). The Normalized Difference Vegetation Index (NDVI) and Green Normalized Difference Vegetation Index (GNDVI) were calculated by employing satellite imagery (Landsat 8) and proximal sensing (Crop Circle ACS 470) to assess the yield and quality characteristics of table grapes. The SVIs exhibited different degrees of correlations with different measurement dates and sensing methods. Satellite-based GNDVI at harvest presented higher correlations with crop quality characteristics (r = 0.522 for berry diameter, r = 0.537 for pH, r = 0.629 for berry deformation) compared with NDVI. Proximal-based GNDVI at the middle of veraison presented higher correlations compared with NDVI (r = −0.682 for berry diameter, r = −0.565 for berry deformation). Proximal sensing proved to be more accurate in terms of table grape yield and quality characteristics compared to satellite sensing.
Evangelos Anastasiou; Athanasios Balafoutis; Nikoleta Darra; Vasileios Psiroukis; Aikaterini Biniari; George Xanthopoulos; Spyros Fountas. Satellite and Proximal Sensing to Estimate the Yield and Quality of Table Grapes. Agriculture 2018, 8, 94 .
AMA StyleEvangelos Anastasiou, Athanasios Balafoutis, Nikoleta Darra, Vasileios Psiroukis, Aikaterini Biniari, George Xanthopoulos, Spyros Fountas. Satellite and Proximal Sensing to Estimate the Yield and Quality of Table Grapes. Agriculture. 2018; 8 (7):94.
Chicago/Turabian StyleEvangelos Anastasiou; Athanasios Balafoutis; Nikoleta Darra; Vasileios Psiroukis; Aikaterini Biniari; George Xanthopoulos; Spyros Fountas. 2018. "Satellite and Proximal Sensing to Estimate the Yield and Quality of Table Grapes." Agriculture 8, no. 7: 94.
Precision viticulture is the application of site-specific techniques to vineyard production to improve grape quality and yield and minimize the negative effects on the environment. While there are various studies on the inherent spatial and temporal variability of vineyards, the assessment of the environmental impact of variable rate applications has attracted limited attention. In this study, two vineyards planted with different grapevine cultivars (Sauvignon Blanc and Syrah) were examined for four consecutive growing seasons (2013–2016). The first year, the two vineyards were only studied in terms of soil properties and crop characteristics, which resulted in the delineation of two distinct management zones for each field. For the following three years, variable rate nutrient application was applied to each management zone based on leaf canopy reflectance, where variable rate irrigation was based on soil moisture sensors, meteorological data, evapotranspiration calculation, and leaf canopy reflectance. Life cycle assessment was carried out to identify the effect of variable rate applications on vineyard agro-ecosystems. The results of variable rate nutrients and water application in the selected management zones as an average value of three growing seasons were compared to the conventional practice. It was found that the reduction of product carbon footprint (PCF) of grapes in Sauvignon Blanc between the two periods was 25% in total. Fertilizer production and distribution (direct) and application (indirect) was the most important sector of greenhouse gas (GHG) emissions reduction, accounting for 17.2%, and the within-farm energy use was the second ranked sector with 8.8% (crop residue management increase GHG emissions by 1.1%, while 0.1% GHG reduction is obtained by pesticide use). For the Syrah vineyard, where the production was less intensive, precision viticulture led to a PCF reduction of 28.3% compared to conventional production. Fertilizers contributed to this decrease by 27.6%, while within-farm energy use had an impact of 2.2% that was positive even though irrigation was increased, due to yield rise. Our results suggest that nutrient status management offers the greatest potential for reducing GHG emissions in both vineyard types. Variable rate irrigation also showed differences in comparison to conventional treatment, but to a lesser degree than variable rate fertilization. This difference between conventional practices and precision viticulture is noteworthy, and shows the potential of precision techniques to reduce the effect of viticulture on GHG emissions.
Athanasios T. Balafoutis; Stefanos Koundouras; Evangelos Anastasiou; Spyros Fountas; Konstantinos Arvanitis. Life Cycle Assessment of Two Vineyards after the Application of Precision Viticulture Techniques: A Case Study. Sustainability 2017, 9, 1997 .
AMA StyleAthanasios T. Balafoutis, Stefanos Koundouras, Evangelos Anastasiou, Spyros Fountas, Konstantinos Arvanitis. Life Cycle Assessment of Two Vineyards after the Application of Precision Viticulture Techniques: A Case Study. Sustainability. 2017; 9 (11):1997.
Chicago/Turabian StyleAthanasios T. Balafoutis; Stefanos Koundouras; Evangelos Anastasiou; Spyros Fountas; Konstantinos Arvanitis. 2017. "Life Cycle Assessment of Two Vineyards after the Application of Precision Viticulture Techniques: A Case Study." Sustainability 9, no. 11: 1997.
In the case of forests located in the close proximity of urban centres, the functions and conventional roles of the forests have to be largely reconsidered. An experimental study area was located in Făget Forest, near the city of Cluj-Napoca, North-West of Romania, as a subject to evaluate different natural risks, especially landslides. Although most of this area is stabilized, human activity became in the last period the most aggressive and active factor that can induce changes in slopes stability. The evaluation based on new changes on the terrain and constructions has clearly revealed the effect of the unprecedented urban sprawl and the expansion of infrastructure elements and residential buildings. Landslide susceptibility map was elaborated using a multivariate statistical analysis and the Geographical Information System (GIS) technology on a predetermined path inside the forest, as well as obtaining valuable information about the tree species. Based on 14 surveys, each of them covering an area of 500 m2 on a longitudinal transect of the forest, there were identified relatively few tree species with a significant share: Carpinus betulus (42.9%), Fagus sylvatica (24.9%), Quercus petraea (23.2%), Q. robur (6.3%), Prunus avium (1.2%). Their positive roles on avoiding or limiting the flow on slopes, flooding, landslides etc. are different depending on the position, terrain, forest composition, trees density, slope, exposition, but it is fundamental beneficial. However, these species can assure productive (as wood), ameliorative, ecological, landscape, cultural, educational, relaxation roles, and consequently inestimable values.
Paul Sestras; Mircea V. Bondrea; Horațiu Cetean; Tudor Sălăgean; Ştefan Bilaşco; Sanda Naș; Velibor Spalevic; Spyros Fountas; Sorin M. Cîmpeanu. Ameliorative, Ecological and Landscape Roles of Făget Forest, Cluj-Napoca, Romania, and Possibilities of Avoiding Risks Based on GIS Landslide Susceptibility Map. Notulae Botanicae Horti Agrobotanici Cluj-Napoca 2017, 46, 292 -300.
AMA StylePaul Sestras, Mircea V. Bondrea, Horațiu Cetean, Tudor Sălăgean, Ştefan Bilaşco, Sanda Naș, Velibor Spalevic, Spyros Fountas, Sorin M. Cîmpeanu. Ameliorative, Ecological and Landscape Roles of Făget Forest, Cluj-Napoca, Romania, and Possibilities of Avoiding Risks Based on GIS Landslide Susceptibility Map. Notulae Botanicae Horti Agrobotanici Cluj-Napoca. 2017; 46 (1):292-300.
Chicago/Turabian StylePaul Sestras; Mircea V. Bondrea; Horațiu Cetean; Tudor Sălăgean; Ştefan Bilaşco; Sanda Naș; Velibor Spalevic; Spyros Fountas; Sorin M. Cîmpeanu. 2017. "Ameliorative, Ecological and Landscape Roles of Făget Forest, Cluj-Napoca, Romania, and Possibilities of Avoiding Risks Based on GIS Landslide Susceptibility Map." Notulae Botanicae Horti Agrobotanici Cluj-Napoca 46, no. 1: 292-300.
Agriculture is one of the economic sectors that affect climate change contributing to greenhouse gas emissions directly and indirectly. There is a trend of agricultural greenhouse gas emissions reduction, but any practice in this direction should not affect negatively farm productivity and economics because this would limit its implementation, due to the high global food and feed demand and the competitive environment in this sector. Precision agriculture practices using high-tech equipment has the ability to reduce agricultural inputs by site-specific applications, as it better target inputs to spatial and temporal needs of the fields, which can result in lower greenhouse gas emissions. Precision agriculture can also have a positive impact on farm productivity and economics, as it provides higher or equal yields with lower production cost than conventional practices. In this work, precision agriculture technologies that have the potential to mitigate greenhouse gas emissions are presented providing a short description of the technology and the impacts that have been reported in literature on greenhouse gases reduction and the associated impacts on farm productivity and economics. The technologies presented span all agricultural practices, including variable rate sowing/planting, fertilizing, spraying, weeding and irrigation.
Athanasios Balafoutis; Bert Beck; Spyros Fountas; Jurgen Vangeyte; Tamme Van Der Wal; Iria Soto; Manuel Gómez-Barbero; Andrew Barnes; Vera Eory. Precision Agriculture Technologies Positively Contributing to GHG Emissions Mitigation, Farm Productivity and Economics. Sustainability 2017, 9, 1339 .
AMA StyleAthanasios Balafoutis, Bert Beck, Spyros Fountas, Jurgen Vangeyte, Tamme Van Der Wal, Iria Soto, Manuel Gómez-Barbero, Andrew Barnes, Vera Eory. Precision Agriculture Technologies Positively Contributing to GHG Emissions Mitigation, Farm Productivity and Economics. Sustainability. 2017; 9 (8):1339.
Chicago/Turabian StyleAthanasios Balafoutis; Bert Beck; Spyros Fountas; Jurgen Vangeyte; Tamme Van Der Wal; Iria Soto; Manuel Gómez-Barbero; Andrew Barnes; Vera Eory. 2017. "Precision Agriculture Technologies Positively Contributing to GHG Emissions Mitigation, Farm Productivity and Economics." Sustainability 9, no. 8: 1339.