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Francesco Marinello is researcher in the field of Agricultural Engineering and professor on Agricultural Mechanics, Precision Farming, Applied Statistics and Unmanned Aerial Vehicles for Agriculture. Research activities: - development and testing of new sensors monitoring soil, plants and machines and enhancement of precision agricultural practices - study, modeling and testing of agricultural tools and machines - agricultural practices impact on environment. mail: [email protected]
As the cornerstone of biodiversity conservation, the core value of protected areas (PAs) is to maintain an area’s natural conditions (both day and night) and to restrict human-caused disturbances to biology and the environment. Although the value of PAs has been universally recognized, light pollution within them is worsening as a result of the widespread use of artificial illumination devices. Previous studies have focused on light pollution in PAs and evaluated light radiation using nighttime light imagery. However, given the scale and span of these studies (national scale and over short periods), PA light pollution research should be advanced further. In this paper, we conducted long-term (1992–2018) monitoring and evaluation of light pollution in African PAs using aligned multi-sensor NTL data. The results showed that 1) Africa PAs were impacted by increasingly severe artificial lights during 1992–2018, with all three light indices showing an accelerating increasing trend. 2) The number of light-polluted PAs also rapidly increased, with more than 80% of PAs experiencing aggravated light pollution as of 2018. Different types of PAs had heterogeneous light pollution, which penetrates indiscriminately into all PA regulation levels. 4) Light pollution in African PAs was divided into three types, including outside invasion, internal sources, and mixed pollution. 5) Human activity intensity surrounding the PAs was highly correlated with light pollution within them, with a maximum effect distance of approximately 245 km. This paper provides new approaches for understanding the patterns of light pollution within PAs, and is a valuable reference for future PA planning.
Zihao Zheng; Zhifeng Wu; Yingbiao Chen; Guanhua Guo; Zheng Cao; Zhiwei Yang; Francesco Marinello. Africa's protected areas are brightening at night: A long-term light pollution monitor based on nighttime light imagery. Global Environmental Change 2021, 69, 102318 .
AMA StyleZihao Zheng, Zhifeng Wu, Yingbiao Chen, Guanhua Guo, Zheng Cao, Zhiwei Yang, Francesco Marinello. Africa's protected areas are brightening at night: A long-term light pollution monitor based on nighttime light imagery. Global Environmental Change. 2021; 69 ():102318.
Chicago/Turabian StyleZihao Zheng; Zhifeng Wu; Yingbiao Chen; Guanhua Guo; Zheng Cao; Zhiwei Yang; Francesco Marinello. 2021. "Africa's protected areas are brightening at night: A long-term light pollution monitor based on nighttime light imagery." Global Environmental Change 69, no. : 102318.
The exploitation of bioenergy plays a key role in the process of decarbonising the economic system. Huge efforts have been made to develop bioenergy and other renewable energy systems, but it is necessary to investigate the costs and problems associated with these technologies. Soil consumption and, in particular, soil sealing are some of these aspects that should be carefully evaluated. Agricultural biogas plants (ABPs) often remove areas dedicated to agricultural activities and require broad paved areas for the associated facilities. This study aimed to (i) assess the surfaces destined to become facilities and buildings in ABPs, (ii) correlate these surfaces with each other and to the installed powers of the plants, and (iii) estimate the consumption of soil in bioenergy applications in Italy. Two hundred ABPs were sampled from an overall population of 1939, and the extents of the facilities were measured by aerial and satellite observations. An ABP with an installed power of 1000 kW covers an average surface area of up to 23,576 m2. Most of this surface, 97.9%, is obtained from previously cultivated areas. The ABP analysis proved that 24.7 m2 of surface area produces 1 kW of power by bioenergy. The obtained model estimated a total consumption of soil by ABPs in Italy of 31,761,235 m2. This research can support stakeholders in cost-benefit analyses to design energy systems based on renewable energy sources.
Giovanni Ferrari; Federico Ioverno; Marco Sozzi; Francesco Marinello; Andrea Pezzuolo. Land-Use Change and Bioenergy Production: Soil Consumption and Characterization of Anaerobic Digestion Plants. Energies 2021, 14, 4001 .
AMA StyleGiovanni Ferrari, Federico Ioverno, Marco Sozzi, Francesco Marinello, Andrea Pezzuolo. Land-Use Change and Bioenergy Production: Soil Consumption and Characterization of Anaerobic Digestion Plants. Energies. 2021; 14 (13):4001.
Chicago/Turabian StyleGiovanni Ferrari; Federico Ioverno; Marco Sozzi; Francesco Marinello; Andrea Pezzuolo. 2021. "Land-Use Change and Bioenergy Production: Soil Consumption and Characterization of Anaerobic Digestion Plants." Energies 14, no. 13: 4001.
Farmer’s management decisions and environmental factors are the main drivers for field spatial and temporal yield variability. In this study, a 22 ha field cultivated with corn for more than ten years using different prescription maps of nitrogen application rates was investigated. Prescription maps were developed based on archived yield maps, soil analysis and recently integrated with Sentinel 2 satellite images. In addition, farmer experience and availability of variable rate application (VRA) requirements had an influence on the development of the homogeneous management zones. The initial approach with VRA was quite simple, based on a simple partitioning of the field into three rectangular zones (defined mainly based on previous yield maps and farmer experience). The partitioning changed with time and knowledge, evolving to the final five irregularly shaped zones (defined based on Farm works decision support software). Furthermore, since 2010 the farmer began using soil moisture sensor for irrigation decisions. Results of the present study highlight an improvement in corn yield and a reduction in total applied nitrogen. Corn yield improved on average by 31% on a ten years basis to reach more than 14 ton/ha dm. in 2018. At the beginning of VRA, yield maps showed a high spatial variation between field zones compared to reduced variation in the following seasons. In addition, the nitrogen applied reduced by around 23% while the total yield was improving. These results showed an increase in the partial factor productivity from less than 54 to around 87 kg of corn grain per kg of nitrogen applied. This promising result shows that farmer management decisions can improve every season by continuous monitoring of crop performance, understanding field variability and taking advantage of recently developed decision support software tools.
Ahmed Kayad; Marco Sozzi; Simone Gatto; Brett Whelan; Luigi Sartori; Francesco Marinello. Ten years of corn yield dynamics at field scale under digital agriculture solutions: A case study from North Italy. Computers and Electronics in Agriculture 2021, 185, 106126 .
AMA StyleAhmed Kayad, Marco Sozzi, Simone Gatto, Brett Whelan, Luigi Sartori, Francesco Marinello. Ten years of corn yield dynamics at field scale under digital agriculture solutions: A case study from North Italy. Computers and Electronics in Agriculture. 2021; 185 ():106126.
Chicago/Turabian StyleAhmed Kayad; Marco Sozzi; Simone Gatto; Brett Whelan; Luigi Sartori; Francesco Marinello. 2021. "Ten years of corn yield dynamics at field scale under digital agriculture solutions: A case study from North Italy." Computers and Electronics in Agriculture 185, no. : 106126.
Compared with previous nighttime light (NTL) data, the Black Marble product developed by NASA in recent years is the most advanced NTL product, which plays an important role in regional activity monitoring and special events (process) tracking due to its excellent timeliness (near-real-time release) and global data coverage capability. Currently, among the Black Marble products, the VNP46A2 product is not updated in a timely manner and VN46AX is still under development. Thus, VNP46A1, which is released in near real time, has become a key product available to the public, although it is affected by cloud cover and moonlight. To obtain high-quality near-real-time monthly NTL images and reduce the data gaps before VNP46AX is released, a simple processing scheme based on VNP46A1 is proposed in this letter. The results show that the proposed processing chain can effectively filter cloud-polluted pixels and alleviate the interference of moonlight radiation. The near-real-time monthly NTL (NRTMNTL) data generated by the scheme achieve a higher correlation with VNP46A2 and present a better visual purity. The near-real-time data availability and parameter-free input make the proposed scheme more applicable for short-period events tracking.
Zihao Zheng; Zhifeng Wu; Yingbiao Chen; Guanhua Guo; Zhiwei Yang; Francesco Marinello. A Simple Method for Near-Real-Time Monthly Nighttime Light Image Production. IEEE Geoscience and Remote Sensing Letters 2021, PP, 1 -5.
AMA StyleZihao Zheng, Zhifeng Wu, Yingbiao Chen, Guanhua Guo, Zhiwei Yang, Francesco Marinello. A Simple Method for Near-Real-Time Monthly Nighttime Light Image Production. IEEE Geoscience and Remote Sensing Letters. 2021; PP (99):1-5.
Chicago/Turabian StyleZihao Zheng; Zhifeng Wu; Yingbiao Chen; Guanhua Guo; Zhiwei Yang; Francesco Marinello. 2021. "A Simple Method for Near-Real-Time Monthly Nighttime Light Image Production." IEEE Geoscience and Remote Sensing Letters PP, no. 99: 1-5.
Farm machinery selection, operation and management directly impact crop cultivation processes and outputs. A priori quantification of technical and financial needs allows definition of proportionate distribution and management of available resources and simplification of selection process. Appropriate planning, association and adjustment of the power unit and implement are required for soil cultivation. Consideration of functional parameters of the implement, their proper estimation and operation directly impact the soil structure, productivity and return on investment. Thus, a modelling approach was implemented for the definition of possible parameter-price relations for tillage equipment. The performed analysis allowed us to investigate the main relevant parameters, quantify their impact, and elaborate forecasting models for price, power, mass and working width. The significant relevance of the technical parameters and adjustment issues were outlined for each tillage implement group. For harrows and cultivators, the dependencies between studied parameters expressed better predictive qualities, especially for price-mass relation (R² > 0.8). While for ploughs power and mass relation had a primary output (R² = 0.7). The prediction features of the models provided reliable results for the estimation of the indicative values of the price and parameters of the implements.
Tatevik Yezekyan; Marco Benetti; Giannantonio Armentano; Samuele Trestini; Luigi Sartori; Francesco Marinello. Definition of Reference Models for Power, Mass, Working Width, and Price for Tillage Implements. Agriculture 2021, 11, 197 .
AMA StyleTatevik Yezekyan, Marco Benetti, Giannantonio Armentano, Samuele Trestini, Luigi Sartori, Francesco Marinello. Definition of Reference Models for Power, Mass, Working Width, and Price for Tillage Implements. Agriculture. 2021; 11 (3):197.
Chicago/Turabian StyleTatevik Yezekyan; Marco Benetti; Giannantonio Armentano; Samuele Trestini; Luigi Sartori; Francesco Marinello. 2021. "Definition of Reference Models for Power, Mass, Working Width, and Price for Tillage Implements." Agriculture 11, no. 3: 197.
Over the last two decades, the dairy industry has adopted the use of Automatic Milking Systems (AMS). AMS have the potential to increase the effectiveness of the milking process and sustain animal welfare. This study assessed the state of the art of research activities on AMS through a systematic review of scientific and industrial research. The papers and patents of the last 20 years (2000–2019) were analysed to assess the research tendencies. The words appearing in title, abstract and keywords of a total of 802 documents were processed with the text mining tool. Four clusters were identified (Components, Technology, Process and Animal). For each cluster, the words frequency analysis enabled us to identify the research tendencies and gaps. The results showed that focuses of the scientific and industrial research areas complementary, with scientific papers mainly dealing with topics related to animal and process, and patents giving priority to technology and components. Both scientific and industrial research converged on some crucial objectives, such as animal welfare, process sustainability and technological development. Despite the increasing interest in animal welfare, this review highlighted that further progress is needed to meet the consumers’ demand. Moreover, milk yield is still regarded as more valuable compared to milk quality. Therefore, additional effort is necessary on the latter. At the process level, some gaps have been found related to cleaning operations, necessary to improve milk quality and animal health. The use of farm data and their incorporation on herd decision support systems (DSS) appeared optimal. The results presented in this review may be used as an overall assessment useful to address future research.
Alessia Cogato; Marta Brščić; Hao Guo; Francesco Marinello; Andrea Pezzuolo. Challenges and Tendencies of Automatic Milking Systems (AMS): A 20-Years Systematic Review of Literature and Patents. Animals 2021, 11, 356 .
AMA StyleAlessia Cogato, Marta Brščić, Hao Guo, Francesco Marinello, Andrea Pezzuolo. Challenges and Tendencies of Automatic Milking Systems (AMS): A 20-Years Systematic Review of Literature and Patents. Animals. 2021; 11 (2):356.
Chicago/Turabian StyleAlessia Cogato; Marta Brščić; Hao Guo; Francesco Marinello; Andrea Pezzuolo. 2021. "Challenges and Tendencies of Automatic Milking Systems (AMS): A 20-Years Systematic Review of Literature and Patents." Animals 11, no. 2: 356.
Over the last 20 years, the dairy industry has implemented new technologies related to automatic milking systems (AMS). AMSs have the potential to maximize milk production and animals’ welfare thanks to voluntary milking access, as well as to increase the resource efficiency and environmental sustainability of dairy farms. In this study we assessed the state of the art of research on AMS through a systematic review of patent trends in the last two decades. Patents from the last 20 years were extracted from the EspaceNet database. Terms appearing in titles and abstracts of a total of 154 patents were processed using a text mining approach, ignoring low-frequency and meaningless words, and including stemming analysis to aggregate variant forms of the same word. Four clusters were identified: Components, Sensors, Process and Animal. The results showed that the highest number of patents was yielded in the early 2000s, thus indicating great interest in AMS in the initial period. The cluster trend pointed out that the focus on the animal and sensing technologies has been constant over time. In recent years, the priority of research has shifted towards process efficiency and components. Detailed analysis of clusters allowed us to appreciate an increasing interest in the animals’ health and body conditions over time (+249% and +391% from 2000 to 2019, respectively). The processes which showed increasing relevance were the ones related to the cleaning of facilities (+291%). The study of new sensing technologies has focused primarily on imaging, allowing researchers to develop new decision models (+348%). The results suggest that AMS patents are moving their attention towards more efficient and sustainable systems. This trend represents an important opportunity for a significant increase in the sustainability of the dairy sector, not only for animals but also for the farmers through the efficient use of the resources, thus enhancing the consumer’s perception of sustainability.
Alessia Cogato; Marta Brščić; Francesco Marinello; Andrea Pezzuolo. A 20-Year Analysis of the Evolution of Automatic Milking Systems: Processes, Technologies and Livestock Environment. Proceedings of The 1st International Electronic Conference on Animals—Global Sustainability and Animals: Science, Ethics and Policy 2020, 73, 3 .
AMA StyleAlessia Cogato, Marta Brščić, Francesco Marinello, Andrea Pezzuolo. A 20-Year Analysis of the Evolution of Automatic Milking Systems: Processes, Technologies and Livestock Environment. Proceedings of The 1st International Electronic Conference on Animals—Global Sustainability and Animals: Science, Ethics and Policy. 2020; 73 (1):3.
Chicago/Turabian StyleAlessia Cogato; Marta Brščić; Francesco Marinello; Andrea Pezzuolo. 2020. "A 20-Year Analysis of the Evolution of Automatic Milking Systems: Processes, Technologies and Livestock Environment." Proceedings of The 1st International Electronic Conference on Animals—Global Sustainability and Animals: Science, Ethics and Policy 73, no. 1: 3.
Agricultural land use plays a critical role in land planning sustainability. Employing a GIS-based decision-making protocol based on spatial and management data represents an appropriate tool for land planning. The Italian vineyards database presented here describes several spatial and management features of 3686 sample vineyards distributed throughout Italy. The dataset is presented as a centroid shapefile with the attribute table. The features were assessed with a GIS-based geospatial analysis. Parameters such as training system and shape of the vineyard block were attributed through visual assessment of Google Earth images. Row spacing, length-width ratio and headland size were determined using QGIS measuring tools. The mean and maximum slope was derived using a 20 m spatial resolution Digital Elevation Model (DEM). This database may help to establish planting criteria of new vineyards which comply with rational and sustainable requirements. Moreover, the dataset could be combined with other agricultural land use data for further analysis of land management. Furthermore, the database could be implemented to support global-scale vineyard management.
Alessia Cogato; Andrea Pezzuolo; Marco Sozzi; Francesco Marinello. A sample of Italian vineyards: Landscape and management parameters dataset. Data in Brief 2020, 33, 106589 .
AMA StyleAlessia Cogato, Andrea Pezzuolo, Marco Sozzi, Francesco Marinello. A sample of Italian vineyards: Landscape and management parameters dataset. Data in Brief. 2020; 33 ():106589.
Chicago/Turabian StyleAlessia Cogato; Andrea Pezzuolo; Marco Sozzi; Francesco Marinello. 2020. "A sample of Italian vineyards: Landscape and management parameters dataset." Data in Brief 33, no. : 106589.
Planting criteria of new vineyards should comply with rational and sustainable criteria, taking into account the potential mechanisability of existing viticultural areas. However, an established methodology for this assessment is still lacking. This study aimed at analysing the parameters which influence the vineyard mechanisability, with the objective to propose a new mechanisability index. The mechanisability index proposed was based on GIS-analysis of landscape and management parameters such as mean slope, shape of the vineyard block, length-width ratio, headland size, training system and row spacing. We identified a sample of 3686 vineyards in Italy. Based on the above-mentioned parameters, vineyards were categorised by their level of mechanisability (l.m.) into four classes. Moreover, we analysed the correlation between l.m. and economic indicators (area planted with vineyard and wine production). Results showed that the main factors limiting the mechanisability potential of some Italian regions are the elevated slopes, horizontal training systems and narrow vine spacings. The l.m. showed a moderate positive correlation with the size of vineyards and the volume and value of production. The methodology presented in this study may be easily applied to other viticultural areas around the world, serving as a management decision-making tool.
Alessia Cogato; Andrea Pezzuolo; Claus Grøn Sørensen; Roberta De Bei; Marco Sozzi; Francesco Marinello. A GIS-Based Multicriteria Index to Evaluate the Mechanisability Potential of Italian Vineyard Area. Land 2020, 9, 469 .
AMA StyleAlessia Cogato, Andrea Pezzuolo, Claus Grøn Sørensen, Roberta De Bei, Marco Sozzi, Francesco Marinello. A GIS-Based Multicriteria Index to Evaluate the Mechanisability Potential of Italian Vineyard Area. Land. 2020; 9 (11):469.
Chicago/Turabian StyleAlessia Cogato; Andrea Pezzuolo; Claus Grøn Sørensen; Roberta De Bei; Marco Sozzi; Francesco Marinello. 2020. "A GIS-Based Multicriteria Index to Evaluate the Mechanisability Potential of Italian Vineyard Area." Land 9, no. 11: 469.
Since China’s reform and development commenced, in the context of rapid urbanization and coordinated regional development, Chinese cities with a close geographic proximity and social ties have gradually formed an integrated city development model. As a new phenomenon in China’s urbanization process, existing research on China’s integrated cities mainly focuses on typical case studies, and most research has been limited to literature reviews and theoretical analyses. The growing application of remote sensing technology in urbanization research in recent years has provided new opportunities for the analysis of city integration. Therefore, based on multi-spectral Landsat-8 and nighttime light images (SNPP/VIIRS, Suomi National Polar-orbiting Platform/Visible Infrared Imaging Radiometer Suite), this paper selects four of the most representative integrated cities with different backgrounds in China to analyze the land-use conversion, plot light fluctuation, and light gravity center shift in the boundary zone between cities. The results show that (1) Guangfo has the highest level of integration and urban expansion is mainly concentrated in the south-central part of the boundary area; (2) Guanshen’s level of integration is second to Guangfo’s and is mainly concentrated in the west; (3) HuSu’s integration is still in the initial stage and its increase in light intensity lags behind the expansion of building land during the study period; (4) although the light intensity and building land area increased significantly during the study period in Xixian, the overall development level of Xixian still lagged behind coastal cities due to the restriction of its geographical location. Our application results expand the data sources for integrated city research and the obtained results can potentially support decision-making and planning in the process of urban development.
Zihao Zheng; Zhifeng Wu; Yingbiao Chen; Zhiwei Yang; Francesco Marinello. Detection of City Integration Processes in Rapidly Urbanizing Areas Based on Remote Sensing Imagery. Land 2020, 9, 378 .
AMA StyleZihao Zheng, Zhifeng Wu, Yingbiao Chen, Zhiwei Yang, Francesco Marinello. Detection of City Integration Processes in Rapidly Urbanizing Areas Based on Remote Sensing Imagery. Land. 2020; 9 (10):378.
Chicago/Turabian StyleZihao Zheng; Zhifeng Wu; Yingbiao Chen; Zhiwei Yang; Francesco Marinello. 2020. "Detection of City Integration Processes in Rapidly Urbanizing Areas Based on Remote Sensing Imagery." Land 9, no. 10: 378.
With the rapid development of urbanization and population migration, since the 20th century, the natural and eco-environment of coastal areas have been under tremendous pressure due to the strong interference of human response. To objectively evaluate the coastal eco-environment condition and explore the impact from the urbanization process, this paper, by integrating daytime remote sensing and nighttime remote sensing, carried out a quantitative assessment of the coastal zone of China in 2000–2019 based on Remote Sensing Ecological Index (RSEI) and Comprehensive Nighttime Light Index (CNLI) respectively. The results showed that: 1) the overall eco-environmental conditions in China's coastal zone have shown a trend of improvement, but regional differences still exist; 2) during the study period, the urbanization process of cities continued to advance, especially in seaside cities and prefecture-level cities in Jiangsu and Shandong, which were much higher than the average growth rate; 3) the Coupling Coordination Degree (CCD) between the urbanization and eco-environment in coastal cities is constantly increasing, but the main contribution of environmental improvement comes from non-urbanized areas, and the eco-environment pressure in urbanized areas is still not optimistic. As a large-scale, long-term series of eco-environment and urbanization process change analysis, this study can provide theoretical support for mesoscale development planning, eco-environment condition monitoring and environmental protection policies from decision-makers.
Zihao Zheng; Zhifeng Wu; Yingbiao Chen; Zhiwei Yang; Francesco Marinello. Exploration of eco-environment and urbanization changes in coastal zones: A case study in China over the past 20 years. Ecological Indicators 2020, 119, 106847 .
AMA StyleZihao Zheng, Zhifeng Wu, Yingbiao Chen, Zhiwei Yang, Francesco Marinello. Exploration of eco-environment and urbanization changes in coastal zones: A case study in China over the past 20 years. Ecological Indicators. 2020; 119 ():106847.
Chicago/Turabian StyleZihao Zheng; Zhifeng Wu; Yingbiao Chen; Zhiwei Yang; Francesco Marinello. 2020. "Exploration of eco-environment and urbanization changes in coastal zones: A case study in China over the past 20 years." Ecological Indicators 119, no. : 106847.
Sensor applications are impacting the everyday objects that enhance human life quality. In this special issue, the main objective was to address recent advances of sensor applications in agriculture covering a wide range of topics in this field. A total of 14 articles were published in this special issue where nine of them were research articles, two review articles and two technical notes. The main topics were soil and plant sensing, farm management and post-harvest application. Soil-sensing topics include monitoring soil moisture content, drain pipes and topsoil movement during the harrowing process while plant-sensing topics include evaluating spray drift in vineyards, thermography applications for winter wheat and tree health assessment and remote-sensing applications as well. Furthermore, farm management contributions include food systems digitalization and using archived data from plowing operations, and one article in post-harvest application in sunflower seeds.
Ahmed Kayad; Dimitrios Paraforos; Francesco Marinello; Spyros Fountas. Latest Advances in Sensor Applications in Agriculture. Agriculture 2020, 10, 362 .
AMA StyleAhmed Kayad, Dimitrios Paraforos, Francesco Marinello, Spyros Fountas. Latest Advances in Sensor Applications in Agriculture. Agriculture. 2020; 10 (8):362.
Chicago/Turabian StyleAhmed Kayad; Dimitrios Paraforos; Francesco Marinello; Spyros Fountas. 2020. "Latest Advances in Sensor Applications in Agriculture." Agriculture 10, no. 8: 362.
This paper aims to provide a bibliometric analysis of publication trends on the themes of biomass and bioenergy worldwide. A wide range of studies have been performed in the field of the usage of biomass for energy production, in order to contribute to the green transition from fossil fuels to renewable energies. Over the past 20 years (from 2000 to 2019), approximately 10,000 articles have been published in the “Agricultural and Biological Sciences” field on this theme, covering all stages of production—from the harvesting of crops to the particular type of energy produced. Articles were obtained from the SCOPUS database and examined with a text mining tool in order to analyze publication trends over the last two decades. Publications per year in the bioenergy theme have grown from 91 in 2000 to 773 in 2019. In particular the analyses showed how environmental aspects have increased their importance (from 7.3% to 11.8%), along with studies related to crop conditions (from 10.4% to 18.6%). Regarding the use of energy produced, growing trends were recognized for the impact of biofuels (mentions moved from 0.14 times per article in 2000 to 0.38 in 2019) and biogases (from 0.14 to 0.42 mentions). Environmental objectives have guided the interest of researchers, encouraging studies on biomass sources and the optimal use of the energy produced. This analysis aims to describe the research evolution, providing an analysis that can be helpful to predict future scenarios and participation among stakeholders in the sector.
Giovanni Ferrari; Andrea Pezzuolo; Abdul-Sattar Nizami; Francesco Marinello. Bibliometric Analysis of Trends in Biomass for Bioenergy Research. Energies 2020, 13, 3714 .
AMA StyleGiovanni Ferrari, Andrea Pezzuolo, Abdul-Sattar Nizami, Francesco Marinello. Bibliometric Analysis of Trends in Biomass for Bioenergy Research. Energies. 2020; 13 (14):3714.
Chicago/Turabian StyleGiovanni Ferrari; Andrea Pezzuolo; Abdul-Sattar Nizami; Francesco Marinello. 2020. "Bibliometric Analysis of Trends in Biomass for Bioenergy Research." Energies 13, no. 14: 3714.
In a climate-change context, the advancement of phenological stages may endanger viticultural areas in the event of a late frost. This study evaluated the potential of satellite-based remote sensing to assess the damage and the recovery time after a late frost event in 2017 in northern Italian vineyards. Several vegetation indices (VIs) normalized on a two-year dataset (2018–2019) were compared over a frost-affected area (F) and a control area (NF) using unpaired two-sample t-test. Furthermore, the must quality data (total acidity, sugar content and pH) of F and NF were analyzed. The VIs most sensitive in the detection of frost damage were Chlorophyll Absorption Ratio Index (CARI), Enhanced Vegetation Index (EVI), and Modified Triangular Vegetation Index 1 (MTVI1) (−5.26%, −16.59%, and −5.77% compared to NF, respectively). The spectral bands Near-Infrared (NIR) and Red Edge 7 were able to identify the frost damage (−16.55 and −16.67% compared to NF, respectively). Moreover, CARI, EVI, MTVI1, NIR, Red Edge 7, the Normalized Difference Vegetation Index (NDVI) and the Modified Simple Ratio (MSR) provided precise information on the full recovery time (+17.7%, +22.42%, +29.67%, +5.89%, +5.91%, +16.48%, and +8.73% compared to NF, respectively) approximately 40 days after the frost event. The must analysis showed that total acidity was higher (+5.98%), and pH was lower (−2.47%) in F compared to NF. These results suggest that medium-resolution multispectral data from Sentinel-2 constellation may represent a cost-effective tool for frost damage assessment and recovery management.
Alessia Cogato; Franco Meggio; Cassandra Collins; Francesco Marinello. Medium-Resolution Multispectral Data from Sentinel-2 to Assess the Damage and the Recovery Time of Late Frost on Vineyards. Remote Sensing 2020, 12, 1896 .
AMA StyleAlessia Cogato, Franco Meggio, Cassandra Collins, Francesco Marinello. Medium-Resolution Multispectral Data from Sentinel-2 to Assess the Damage and the Recovery Time of Late Frost on Vineyards. Remote Sensing. 2020; 12 (11):1896.
Chicago/Turabian StyleAlessia Cogato; Franco Meggio; Cassandra Collins; Francesco Marinello. 2020. "Medium-Resolution Multispectral Data from Sentinel-2 to Assess the Damage and the Recovery Time of Late Frost on Vineyards." Remote Sensing 12, no. 11: 1896.
Technical and performance parameters of agricultural machines directly impact the operational efficiency and entire crop production. Sometimes, overestimation of technical and dimensional parameters of harvesting equipment is carried out with the intention of enhancing the operational efficiency, but this approach might turn out to negatively impact productivity due to unbalanced system design, and ultimately lead to financial losses. Therefore, a balanced preliminary estimation of technical parameters of equipment needs to be carried out before investment quantification, especially on the large capital-intensive machinery units, such as harvesting systems. In addition, availability of ready to use, simplified models for the price estimation from input technical parameters would reduce the complexity involved in this latter analysis. The current study is an attempt to provide tools to address these issues. A large dataset of combine and forage harvesters has been analyzed to investigate relevant parameter-to-parameter and parameter-to-price relations. The study of the available data allowed the determination of indicative models for the estimation of machine price, power, weight, tank capacity and working width. A significant correlation between power and price (R2 > 0.8) has been observed for two groups of harvesting machines. For combine harvesters, satisfactory correlations were found between power and weight, and power and tank capacity. A regression model for combine harvesters showed a satisfactory behavior at predicting the average working width that can be operated by a given power. On the other hand, for the forage harvesting group, the relation between these quantities has lower values; therefore, for better accuracy of the association, more sophisticated considerations should be incorporated, taking into account other parameters.
Tatevik Yezekyan; Francesco Marinello; Giannantonio Armentano; Samuele Trestini; Luigi Sartori. Modelling of Harvesting Machines’ Technical Parameters and Prices. Agriculture 2020, 10, 194 .
AMA StyleTatevik Yezekyan, Francesco Marinello, Giannantonio Armentano, Samuele Trestini, Luigi Sartori. Modelling of Harvesting Machines’ Technical Parameters and Prices. Agriculture. 2020; 10 (6):194.
Chicago/Turabian StyleTatevik Yezekyan; Francesco Marinello; Giannantonio Armentano; Samuele Trestini; Luigi Sartori. 2020. "Modelling of Harvesting Machines’ Technical Parameters and Prices." Agriculture 10, no. 6: 194.
Rural mechanisation and fleet organisation have an essential impact on agricultural production and sustainable development of farm institutions. Machine functional parameters define the fleet composition and management and, thus, play an important role in economic and environmental performance of a farm. Programming methods and decision support systems are available in the market, however, there is still a lack of applicative tools which allow modelling and forecasting of technical parameters as well as costs to complete the decision tasks. Availability of such models in relation to dimensions, mass, power or working capacity, is then particularly necessary not only to support decisions at the different applied management levels (farmer, stakeholder, policy makers), but also to study the impact of farm machine on the environment and in general to understand trends in agricultural mechanization. The present research is aimed at identifying the most relevant parameters (including working width, overall dimensions, mass and power) for different groups of agricultural machines, modelled and characterised through the application of linear regression analyses. The study is defined on the basis of a database populated on purpose with more than 5000 agricultural machines models (30 machine groups) available in the market. Extracted equations give evidence of high correlations (R2 > 0.75) in particular between prices, mass and needed power, supporting the possibility of analyses on mechanisation trends, from both economical, management and environmental point of view.
Francesco Marinello; Tatevik Yezekyan; Giannantonio Armentano; Luigi Sartori. Modelling of Agricultural Machinery Trends for Power, Mass, Working Width and Price. Lecture Notes in Civil Engineering 2020, 481 -489.
AMA StyleFrancesco Marinello, Tatevik Yezekyan, Giannantonio Armentano, Luigi Sartori. Modelling of Agricultural Machinery Trends for Power, Mass, Working Width and Price. Lecture Notes in Civil Engineering. 2020; ():481-489.
Chicago/Turabian StyleFrancesco Marinello; Tatevik Yezekyan; Giannantonio Armentano; Luigi Sartori. 2020. "Modelling of Agricultural Machinery Trends for Power, Mass, Working Width and Price." Lecture Notes in Civil Engineering , no. : 481-489.
Monitoring and prediction of within-field crop variability can support farmers to make the right decisions in different situations. The current advances in remote sensing and the availability of high resolution, high frequency, and free Sentinel-2 images improve the implementation of Precision Agriculture (PA) for a wider range of farmers. This study investigated the possibility of using vegetation indices (VIs) derived from Sentinel-2 images and machine learning techniques to assess corn (Zea mays) grain yield spatial variability within the field scale. A 22-ha study field in North Italy was monitored between 2016 and 2018; corn yield was measured and recorded by a grain yield monitor mounted on the harvester machine recording more than 20,000 georeferenced yield observation points from the study field for each season. VIs from a total of 34 Sentinel-2 images at different crop ages were analyzed for correlation with the measured yield observations. Multiple regression and two different machine learning approaches were also tested to model corn grain yield. The three main results were the following: (i) the Green Normalized Difference Vegetation Index (GNDVI) provided the highest R2 value of 0.48 for monitoring within-field variability of corn grain yield; (ii) the most suitable period for corn yield monitoring was a crop age between 105 and 135 days from the planting date (R4–R6); (iii) Random Forests was the most accurate machine learning approach for predicting within-field variability of corn yield, with an R2 value of almost 0.6 over an independent validation set of half of the total observations. Based on the results, within-field variability of corn yield for previous seasons could be investigated from archived Sentinel-2 data with GNDVI at crop stage (R4–R6).
Ahmed Kayad; Marco Sozzi; Simone Gatto; Francesco Marinello; Francesco Pirotti. Monitoring Within-Field Variability of Corn Yield using Sentinel-2 and Machine Learning Techniques. Remote Sensing 2019, 11, 2873 .
AMA StyleAhmed Kayad, Marco Sozzi, Simone Gatto, Francesco Marinello, Francesco Pirotti. Monitoring Within-Field Variability of Corn Yield using Sentinel-2 and Machine Learning Techniques. Remote Sensing. 2019; 11 (23):2873.
Chicago/Turabian StyleAhmed Kayad; Marco Sozzi; Simone Gatto; Francesco Marinello; Francesco Pirotti. 2019. "Monitoring Within-Field Variability of Corn Yield using Sentinel-2 and Machine Learning Techniques." Remote Sensing 11, no. 23: 2873.
Heatwaves are common in many viticultural regions of Australia. We evaluated the potential of satellite-based remote sensing to detect the effects of high temperatures on grapevines in a South Australian vineyard over the 2016–2017 and 2017–2018 seasons. The study involved: (i) comparing the normalized difference vegetation index (NDVI) from medium- and high-resolution satellite images; (ii) determining correlations between environmental conditions and vegetation indices (Vis); and (iii) identifying VIs that best indicate heatwave effects. Pearson’s correlation and Bland–Altman testing showed a significant agreement between the NDVI of high- and medium-resolution imagery (R = 0.74, estimated difference −0.093). The band and the VI most sensitive to changes in environmental conditions were 705 nm and enhanced vegetation index (EVI), both of which correlated with relative humidity (R = 0.65 and R = 0.62, respectively). Conversely, SWIR (short wave infrared, 1610 nm) exhibited a negative correlation with growing degree days (R = −0.64). The analysis of heat stress showed that green and red edge bands—the chlorophyll absorption ratio index (CARI) and transformed chlorophyll absorption ratio index (TCARI)—were negatively correlated with thermal environmental parameters such as air and soil temperature and growing degree days (GDDs). The red and red edge bands—the soil-adjusted vegetation index (SAVI) and CARI2—were correlated with relative humidity. To the best of our knowledge, this is the first study demonstrating the effectiveness of using medium-resolution imagery for the detection of heat stress on grapevines in irrigated vineyards.
Alessia Cogato; Vinay Pagay; Francesco Marinello; Franco Meggio; Peter Grace; Massimiliano De Antoni Migliorati. Assessing the Feasibility of Using Sentinel-2 Imagery to Quantify the Impact of Heatwaves on Irrigated Vineyards. Remote Sensing 2019, 11, 2869 .
AMA StyleAlessia Cogato, Vinay Pagay, Francesco Marinello, Franco Meggio, Peter Grace, Massimiliano De Antoni Migliorati. Assessing the Feasibility of Using Sentinel-2 Imagery to Quantify the Impact of Heatwaves on Irrigated Vineyards. Remote Sensing. 2019; 11 (23):2869.
Chicago/Turabian StyleAlessia Cogato; Vinay Pagay; Francesco Marinello; Franco Meggio; Peter Grace; Massimiliano De Antoni Migliorati. 2019. "Assessing the Feasibility of Using Sentinel-2 Imagery to Quantify the Impact of Heatwaves on Irrigated Vineyards." Remote Sensing 11, no. 23: 2869.
The wine sector is paying more attention to sustainable wine production practices, but this topic is highly debated because organic viticulture aims to a reduction of environmental impacts, while conventional viticulture ensures an increase of yield. This work provides an economic and environmental comparison using different indicators whereas no previous studies on viticulture have faced on both aspects of sustainability. Two distinct vineyards within the same case study farm were considered, where conventional and organic viticulture practices were applied for 5 years. For each type of production, we calculated the economic benefit and environmental indicators such as the Water Footprint, Carbon Footprint, and an indicator of environmental performance associated with the vineyard phase (“Vineyard Management” or “Vigneto” indicator part of the Italian VIVA certification framework). This latter considers six sub-indicators investigating pesticides management, fertilizers management, organic matter content, soil compaction, soil erosion, and landscape quality. The multi criteria approach is a novel framework assessing sustainability on vineyard management using environmental indicators from VIVA calculator and the economic aspect. Main results showed that organic management in viticulture can be applied without having economic losses and with the benefit of better preserving the natural capital.
Eros Borsato; Maria Zucchinelli; Daniele D'Ammaro; Elisa Giubilato; Alex Zabeo; Paolo Criscione; Lisa Pizzol; Yafit Cohen; Paolo Tarolli; Lucrezia Lamastra; Francesco Marinello. Use of multiple indicators to compare sustainability performance of organic vs conventional vineyard management. Science of The Total Environment 2019, 711, 135081 .
AMA StyleEros Borsato, Maria Zucchinelli, Daniele D'Ammaro, Elisa Giubilato, Alex Zabeo, Paolo Criscione, Lisa Pizzol, Yafit Cohen, Paolo Tarolli, Lucrezia Lamastra, Francesco Marinello. Use of multiple indicators to compare sustainability performance of organic vs conventional vineyard management. Science of The Total Environment. 2019; 711 ():135081.
Chicago/Turabian StyleEros Borsato; Maria Zucchinelli; Daniele D'Ammaro; Elisa Giubilato; Alex Zabeo; Paolo Criscione; Lisa Pizzol; Yafit Cohen; Paolo Tarolli; Lucrezia Lamastra; Francesco Marinello. 2019. "Use of multiple indicators to compare sustainability performance of organic vs conventional vineyard management." Science of The Total Environment 711, no. : 135081.
The Operational Linescan System (OLS) carried by the National Defense Meteorological Satellite Program (DMSP) can capture the weak visible radiation emitted from earth at night and produce a series of annual cloudless nighttime light (NTL) images, effectively supporting multi-scale, long-term human activities and urbanization process research. However, the interannual instability and sensor bias of NTL time series products greatly limit further studies of lighting data in time series with OLS. Several calibration models for OLS have been proposed to implement interannual corrections to improve the continuity and consistency of time series NTL products; however, due to the subjective factors intervention and insufficient automation in the calibration process, the interannual correction study of NTL time series images is still worth being developed further. Therefore, to avoid the involvement of subjective factors and to optimize the Pseudo-Invariant Features (PIF) identification, an interannual calibration model Pixel-based PIF (PBPIF) is proposed, which identifies PIF by pixel fluctuation characteristics. Results show that a PBPIF-based model can reduce subjective interference and improve the degree of automation during the NTL interannual calibration process. The calibration performance evaluation based on Total Sum of Lights (TSOL) and Sum of the Normalized Difference Index (SNDI) shows that compared to the traditional PIF-based (tPIF-based) and Ridgeline Sampling Regression based (RSR-based) models, the PBPIF-based one achieves better performance in reducing NTL interannual turbulence and minimizing the deviation between sensors. In addition, based on the corrected NTL time series products, pixel-level linear regression analysis is implemented to maximize the potential of the NTL resolution to produce global Light Intensity Change Coefficient (LICC). The results of global LICC can be widely applied to the detailed study of the characteristics of economic development and urbanization.
Zihao Zheng; Zhiwei Yang; Yingbiao Chen; Zhifeng Wu; Francesco Marinello. The Interannual Calibration and Global Nighttime Light Fluctuation Assessment Based on Pixel-Level Linear Regression Analysis. Remote Sensing 2019, 11, 2185 .
AMA StyleZihao Zheng, Zhiwei Yang, Yingbiao Chen, Zhifeng Wu, Francesco Marinello. The Interannual Calibration and Global Nighttime Light Fluctuation Assessment Based on Pixel-Level Linear Regression Analysis. Remote Sensing. 2019; 11 (18):2185.
Chicago/Turabian StyleZihao Zheng; Zhiwei Yang; Yingbiao Chen; Zhifeng Wu; Francesco Marinello. 2019. "The Interannual Calibration and Global Nighttime Light Fluctuation Assessment Based on Pixel-Level Linear Regression Analysis." Remote Sensing 11, no. 18: 2185.