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The degree of olive maturation is a very important factor to consider at harvest time, as it influences the organoleptic quality of the final product, for both oil and table use. The Jaén index, evaluated by measuring the average coloring of olive fruits (peel and pulp), is currently considered to be one of the most indicative methods to determine the olive ripening stage, but it is a slow assay and its results are not objective. The aim of this work is to identify the ripeness degree of olive lots through a real-time, repeatable, and objective machine vision method, which uses RGB image analysis based on a k-nearest neighbors classification algorithm. To overcome different lighting scenarios, pictures were subjected to an automatic colorimetric calibration method—an advanced 3D algorithm using known values. To check the performance of the automatic machine vision method, a comparison was made with two visual operator image evaluations. For 10 images, the number of black, green, and purple olives was also visually evaluated by these two operators. The accuracy of the method was 60%. The system could be easily implemented in a specific mobile app developed for the automatic assessment of olive ripeness directly in the field, for advanced georeferenced data analysis.
Luciano Ortenzi; Simone Figorilli; Corrado Costa; Federico Pallottino; Simona Violino; Mauro Pagano; Giancarlo Imperi; Rossella Manganiello; Barbara Lanza; Francesca Antonucci. A Machine Vision Rapid Method to Determine the Ripeness Degree of Olive Lots. Sensors 2021, 21, 2940 .
AMA StyleLuciano Ortenzi, Simone Figorilli, Corrado Costa, Federico Pallottino, Simona Violino, Mauro Pagano, Giancarlo Imperi, Rossella Manganiello, Barbara Lanza, Francesca Antonucci. A Machine Vision Rapid Method to Determine the Ripeness Degree of Olive Lots. Sensors. 2021; 21 (9):2940.
Chicago/Turabian StyleLuciano Ortenzi; Simone Figorilli; Corrado Costa; Federico Pallottino; Simona Violino; Mauro Pagano; Giancarlo Imperi; Rossella Manganiello; Barbara Lanza; Francesca Antonucci. 2021. "A Machine Vision Rapid Method to Determine the Ripeness Degree of Olive Lots." Sensors 21, no. 9: 2940.
Spraying pesticides using air induction nozzles is a well-known method to reduce drift. These drift-reducing nozzles have been tested on many different tree crops (such as apples, citrus, and grapes), but we are still lacking information on their utilization on hazelnut (Corylus avellana L.) groves, although hazelnut is a major nut crop in Italy, and in recent years its cultivated area has been constantly growing. This paper reports a comparison between treatments carried out with cone and flat-fan low-drift nozzles versus two conventional nozzles. The distribution quality, the number of droplets per cm2 of the target area, and the drift in non-target trees adjacent to those treated were evaluated by analyzing the impact of the droplets on water-sensitive papers placed on the tree canopies. The results show that because no significative differences in terms of application quality were found between the tested nozzles, low-drift nozzles can be a good alternative to the standard nozzles to reduce the drift of pesticide applications in hazelnuts without altering the chosen distribution of the pesticide.
Marcello Biocca; Maurizio Cutini; Elio Romano; Federico Pallottino; Pietro Gallo. Evaluation of Drift-Reducing Nozzles for Pesticide Application in Hazelnut (Corylus avellana L.). AgriEngineering 2021, 3, 230 -239.
AMA StyleMarcello Biocca, Maurizio Cutini, Elio Romano, Federico Pallottino, Pietro Gallo. Evaluation of Drift-Reducing Nozzles for Pesticide Application in Hazelnut (Corylus avellana L.). AgriEngineering. 2021; 3 (2):230-239.
Chicago/Turabian StyleMarcello Biocca; Maurizio Cutini; Elio Romano; Federico Pallottino; Pietro Gallo. 2021. "Evaluation of Drift-Reducing Nozzles for Pesticide Application in Hazelnut (Corylus avellana L.)." AgriEngineering 3, no. 2: 230-239.
Precision irrigation represents those strategies aiming to feed the plant needs following the soil’s spatial and temporal characteristics. Such a differential irrigation requires a different approach and equipment with regard to conventional irrigation to reduce the environmental impact and the resources use while maximizing the production and thus profitability. This study described the development of an open source soil moisture LoRa (long-range) device and analysis of the data collected and updated directly in the field (i.e., weather station and ground sensor). The work produced adaptive supervised predictive models to optimize the management of agricultural precision irrigation practices and for an effective calibration of other agronomic interventions. These approaches are defined as adaptive because they self-learn with the acquisition of new data, updating the on-the-go model over time. The location chosen for the experimental setup is a cultivated area in the municipality of Tenna (Trentino, Alto Adige region, Italy), and the experiment was conducted on two different apple varieties during summer 2019. The adaptative partial least squares time-lag time-series modeling, in operative field conditions, was a posteriori applied in the consortium for 78 days during the dry season, producing total savings of 255 mm of irrigated water and 44,000 kW of electricity, equal to 10.82%.
Simone Figorilli; Federico Pallottino; Giacomo Colle; Daniele Spada; Claudio Beni; Francesco Tocci; Simone Vasta; Francesca Antonucci; Mauro Pagano; Marco Fedrizzi; Corrado Costa. An Open Source Low-Cost Device Coupled with an Adaptative Time-Lag Time-Series Linear Forecasting Modeling for Apple Trentino (Italy) Precision Irrigation. Sensors 2021, 21, 2656 .
AMA StyleSimone Figorilli, Federico Pallottino, Giacomo Colle, Daniele Spada, Claudio Beni, Francesco Tocci, Simone Vasta, Francesca Antonucci, Mauro Pagano, Marco Fedrizzi, Corrado Costa. An Open Source Low-Cost Device Coupled with an Adaptative Time-Lag Time-Series Linear Forecasting Modeling for Apple Trentino (Italy) Precision Irrigation. Sensors. 2021; 21 (8):2656.
Chicago/Turabian StyleSimone Figorilli; Federico Pallottino; Giacomo Colle; Daniele Spada; Claudio Beni; Francesco Tocci; Simone Vasta; Francesca Antonucci; Mauro Pagano; Marco Fedrizzi; Corrado Costa. 2021. "An Open Source Low-Cost Device Coupled with an Adaptative Time-Lag Time-Series Linear Forecasting Modeling for Apple Trentino (Italy) Precision Irrigation." Sensors 21, no. 8: 2656.
Microbial inoculants are widely accepted as potential alternatives or complements to chemical fertilizers and pesticides in agriculture. However, there remains a lack of knowledge regarding their application and effects under field conditions. Thus, a quantitative description of the scientific literature related to soil microbial inoculants was conducted, adopting a science mapping approach to observe trends, strengths, and weaknesses of their application during the period of 2000–2020 and providing useful insights for future research. Overall, the study retrieved 682 publications with an increasing number during the 2015–2020 period, confirming China, India, and the U.S. as leading countries in microbial inoculants research. Over the last decade, the research field emphasized the use of microbial consortia rather than single strains, with increasing attention paid to sustainability and environmental purposes by means of multidisciplinary approaches. Among the emerging topics, terms such as “persistence” indicate the actual need for detecting and monitoring the persistence and fate of soil microbial inoculants. On the other hand, the low occurrence of terms related to failed studies as well as formulation processes may have limited the overall comprehension of the real potential of microbial inoculants to date. In conclusion, successful application of soil microbial inoculants in agriculture requires filling the fundamental knowledge gaps related to the processes that govern dynamics and interactions of the inoculants with soil and its native microbiota.
Loredana Canfora; Corrado Costa; Federico Pallottino; Stefano Mocali. Trends in Soil Microbial Inoculants Research: A Science Mapping Approach to Unravel Strengths and Weaknesses of Their Application. Agriculture 2021, 11, 158 .
AMA StyleLoredana Canfora, Corrado Costa, Federico Pallottino, Stefano Mocali. Trends in Soil Microbial Inoculants Research: A Science Mapping Approach to Unravel Strengths and Weaknesses of Their Application. Agriculture. 2021; 11 (2):158.
Chicago/Turabian StyleLoredana Canfora; Corrado Costa; Federico Pallottino; Stefano Mocali. 2021. "Trends in Soil Microbial Inoculants Research: A Science Mapping Approach to Unravel Strengths and Weaknesses of Their Application." Agriculture 11, no. 2: 158.
The beer production chain includes some crucial steps regarding processing, delivery, service, and consumption that can benefit from the implementation of IoT (Internet of Things) based technologies. Large breweries implemented the use of sensors and digitization before smaller ones among which are craft breweries. Internet of Beer (IoB) technologies are becoming accessible to mid and small sized brewing companies. Therefore, the objective of this work is to review mainly low-cost IoB smart technologies that can be implemented from the mash to the final product and its service, to improve the brewing production, control, delivery, and final quality increasing profitability. The reviewed applications were retrieved both from the scientific databases and from the web. The work is structured in three macro areas such as beer processing, product logistics and traceability, and service. The results show a future trend characterized by a very fast increase in the use of IoB (also open source) systems to drive efficiency, productivity, quality, and safety. This will be done by real-time monitoring and a data-driven decision support system (DSS). Crucial aspects needing further investigation are data ownership and data standardization. The access price of IoB devices and software is destined for a significant decrease while their diversification on the market will grow leading to a massive future implementation within all the production levels.
Simona Violino; Simone Figorilli; Corrado Costa; Federico Pallottino. Internet of Beer: A Review on Smart Technologies from Mash to Pint. Foods 2020, 9, 950 .
AMA StyleSimona Violino, Simone Figorilli, Corrado Costa, Federico Pallottino. Internet of Beer: A Review on Smart Technologies from Mash to Pint. Foods. 2020; 9 (7):950.
Chicago/Turabian StyleSimona Violino; Simone Figorilli; Corrado Costa; Federico Pallottino. 2020. "Internet of Beer: A Review on Smart Technologies from Mash to Pint." Foods 9, no. 7: 950.
Extra virgin olive oil (EVOO) represents a crucial ingredient of the Mediterranean diet. Being a first-choice product, consumers should be guaranteed its quality and geographical origin, justifying the high purchasing cost. For this reason, it is important to have new reliable tools able to classify products according to their geographical origin. The aim of this work was to demonstrate the efficiency of an open source visible and near infra-red (VIS-NIR) spectrophotometer, relying on a specific app, in assessing olive oil geographical origin. Thus, 67 Italian and 25 foreign EVOO samples were analyzed and their spectral data were processed through an artificial intelligence algorithm. The multivariate analysis of variance (MANOVA) results reported significant differences (p < 0.001) between the Italian and foreign EVOO VIS-NIR matrices. The artificial neural network (ANN) model with an external test showed a correct classification percentage equal to 94.6%. Both the MANOVA and ANN tested methods showed the most important spectral wavelengths ranges for origin determination to be 308–373 nm and 594–605 nm. These are related to the absorption of phenolic components, carotenoids, chlorophylls, and anthocyanins. The proposed tool allows the assessment of EVOO samples’ origin and thus could help to preserve the “Made in Italy” from fraud and sophistication related to its commerce.
Simona Violino; Luciano Ortenzi; Francesca Antonucci; Federico Pallottino; Cinzia Benincasa; Simone Figorilli; Corrado Costa. An Artificial Intelligence Approach for Italian EVOO Origin Traceability through an Open Source IoT Spectrometer. Foods 2020, 9, 834 .
AMA StyleSimona Violino, Luciano Ortenzi, Francesca Antonucci, Federico Pallottino, Cinzia Benincasa, Simone Figorilli, Corrado Costa. An Artificial Intelligence Approach for Italian EVOO Origin Traceability through an Open Source IoT Spectrometer. Foods. 2020; 9 (6):834.
Chicago/Turabian StyleSimona Violino; Luciano Ortenzi; Francesca Antonucci; Federico Pallottino; Cinzia Benincasa; Simone Figorilli; Corrado Costa. 2020. "An Artificial Intelligence Approach for Italian EVOO Origin Traceability through an Open Source IoT Spectrometer." Foods 9, no. 6: 834.
The traceability of extra virgin olive oil (EVOO) could guarantee the authenticity of the product and the protection of the consumer if it is part of a system able to certify the traceability information. The purpose of this paper was to propose and apply a complete electronic traceability prototype along the entire EVOO production chain of a small Italian farm and to verify its economic sustainability. The full traceability of the EVOO extracted from 33 olive trees from three different cultivars (Carboncella, Frantoio and Leccino) was considered. The technological traceability system (TTS; infotracing) consists of several open source devices (based on radio frequency identification (RFID) and QR code technologies) able to track the EVOO from the standing olive tree to the final consumer. The infotracing system was composed of a dedicated open source app and was designed for easy blockchain integration. In addition, an economic analysis of the proposed TTS, with reference to the semi-mechanized olive harvesting process, was conducted. The results showed that the incidence of the TTS application on the whole production varies between 3% and 15.5%, (production from 5 to 60 kg tree−1). The application at the consortium level with mechanized harvesting is fully sustainable in economic terms. The proposed TTS could not only provide guarantees to the final consumer but could also direct the farmer towards precision farming management.
Simona Violino; Federico Pallottino; Giulio Sperandio; Simone Figorilli; Luciano Ortenzi; Francesco Tocci; Simone Vasta; Giancarlo Imperi; Corrado Costa. A Full Technological Traceability System for Extra Virgin Olive Oil. Foods 2020, 9, 624 .
AMA StyleSimona Violino, Federico Pallottino, Giulio Sperandio, Simone Figorilli, Luciano Ortenzi, Francesco Tocci, Simone Vasta, Giancarlo Imperi, Corrado Costa. A Full Technological Traceability System for Extra Virgin Olive Oil. Foods. 2020; 9 (5):624.
Chicago/Turabian StyleSimona Violino; Federico Pallottino; Giulio Sperandio; Simone Figorilli; Luciano Ortenzi; Francesco Tocci; Simone Vasta; Giancarlo Imperi; Corrado Costa. 2020. "A Full Technological Traceability System for Extra Virgin Olive Oil." Foods 9, no. 5: 624.
The aim of this study is the application of advanced modeling techniques to identify powdery mildew tolerant cultivars and reduce fungicides and energy consumption. The energy savings resulting from the increased efficiency of the use of fungicides is an innovative aspect investigated within the project AGROENER researching on energy efficiency. In this preliminary study, investigations through phenotyping methods could represent a potential solution, especially if they are used in combination with tools and algorithms able to extract and convert a large amount of data. Twelve different grapevine cultivars were tested. The construction of an artificial model, characterized by absolute optima of response to a pathogen (i.e., low values of disease incidence and severity and first day of the pathogen appearance), allowed us to cover the potential variability of a real dataset. To identify the cultivars that tolerate powdery mildew the most, two Soft Independent Modeling of Class Analogy (SIMCA) models were built. The modeling efficiencies, indicated by sensitivity value, were equal to 100%. These statistical multivariate classifications identified some of these tolerant cultivars, as the best responding to the pathogen.
Francesca Cecchini; Maria Cecilia Serra; Noemi Bevilacqua; Corrado Costa; Roberto Valori; Federico Pallottino; Giorgio Casadei; Paolo Menesatti; Francesca Antonucci. Advanced Modeling for the Identification of Different Pathogen Tolerant Vines to Reduce Fungicides and Energy Consumption. Sustainability 2020, 12, 1900 .
AMA StyleFrancesca Cecchini, Maria Cecilia Serra, Noemi Bevilacqua, Corrado Costa, Roberto Valori, Federico Pallottino, Giorgio Casadei, Paolo Menesatti, Francesca Antonucci. Advanced Modeling for the Identification of Different Pathogen Tolerant Vines to Reduce Fungicides and Energy Consumption. Sustainability. 2020; 12 (5):1900.
Chicago/Turabian StyleFrancesca Cecchini; Maria Cecilia Serra; Noemi Bevilacqua; Corrado Costa; Roberto Valori; Federico Pallottino; Giorgio Casadei; Paolo Menesatti; Francesca Antonucci. 2020. "Advanced Modeling for the Identification of Different Pathogen Tolerant Vines to Reduce Fungicides and Energy Consumption." Sustainability 12, no. 5: 1900.
The evaluation of soil tillage quality parameters, such as cloddiness and surface roughness produced by tillage tools, is based on traditional methods ranging, respectively, from manual or mechanical sieving of ground samples to handheld rulers, non-contact devices or Precision Agriculture technics, such as laser profile meters. The aim of the study was to compare traditional methods of soil roughness and cloddiness assessment (laser profile meter and manual sieving), with light drone RGB 3D imaging techniques for the evaluation of different tillage methods (ploughed, harrowed and grassed). Light drone application was able to replicate the results obtained by the traditional methods, introducing advantages in terms of time, repeatability and analysed surface while reducing the human error during the data collection on the one hand and allowing a labour-intensive field monitoring solution for digital farming on the other. Indeed, the profilometer positioning introduces errors and may lead to false reading due to limited data collection. Future work could be done in order to streamline the data processing operation and so to produce a practical application ready to use and stimulate the adoption of new evaluation indices of soil cloddiness, such as Entropy and the Angular Second Moment (ASM), which seem more suitable than the classic ones to achieved data referred to more extended surfaces.
Roberto Fanigliulo; Francesca Antonucci; Simone Figorilli; Daniele Pochi; Federico Pallottino; Laura Fornaciari; Renato Grilli; Corrado Costa. Light Drone-Based Application to Assess Soil Tillage Quality Parameters. Sensors 2020, 20, 728 .
AMA StyleRoberto Fanigliulo, Francesca Antonucci, Simone Figorilli, Daniele Pochi, Federico Pallottino, Laura Fornaciari, Renato Grilli, Corrado Costa. Light Drone-Based Application to Assess Soil Tillage Quality Parameters. Sensors. 2020; 20 (3):728.
Chicago/Turabian StyleRoberto Fanigliulo; Francesca Antonucci; Simone Figorilli; Daniele Pochi; Federico Pallottino; Laura Fornaciari; Renato Grilli; Corrado Costa. 2020. "Light Drone-Based Application to Assess Soil Tillage Quality Parameters." Sensors 20, no. 3: 728.
Hops flowers are used to impart highly desirable hoppy aromas in beer. The emergence of craft brewing caused an increase in the popularity of intense hoppy beer determining a breeding trend for new hop flavour varieties that differ in terms of oil contents and compounds. The aim of this work is to examine the relationship between volatile organic compounds (VOCs) and sensory properties in an Italian craft beer brewed with 2 selected Italian wild hop varieties and a commercial one (Cascade) grown in 2 sites with different environmental condition. Since the beer aroma is represented by hop flowers and so they increase incise in the finished product. In this study, 6 beer samples produced by an Italian microbrewery using hop plants were collected and analysed for Volatile Organic Compounds (VOCs) profiles using a PTR-TOF-MS and a sensory evaluation (panel and consumer tests). Multivariate statistical analyses (PCA and CANOCO) showed as “Cascade commercial” sample marks with the highest intensity of taste in comparison to other samples. Results showed low interest for the aromas the hops imparted to the beers produced in relationships to the commercial variety grown and bought. In addition, the grown commercial cascade resulted to be interesting, producing a modified aroma profile when compared to its commercial counterpart. Finally, this study showed an initial contribution to screen other wild genotypes to identify new hops for direct use or breeding with new characteristics that can be used for the production of beer with a modified aroma.
Federico Pallottino; Cosimo Taiti; Simona Violino; Corrado Costa; Elisa Masi; Stefano Mancuso. Relationship Among Volatile Organic Compounds and Sensory Properties in Craft Beer. Food Science and Engineering 2020, 13 -26.
AMA StyleFederico Pallottino, Cosimo Taiti, Simona Violino, Corrado Costa, Elisa Masi, Stefano Mancuso. Relationship Among Volatile Organic Compounds and Sensory Properties in Craft Beer. Food Science and Engineering. 2020; ():13-26.
Chicago/Turabian StyleFederico Pallottino; Cosimo Taiti; Simona Violino; Corrado Costa; Elisa Masi; Stefano Mancuso. 2020. "Relationship Among Volatile Organic Compounds and Sensory Properties in Craft Beer." Food Science and Engineering , no. : 13-26.
Traceability is the ability to follow the displacement of food through its entire chain. Extra virgin olive oil (EVOO) represents Italian excellence, with consumers’ increased awareness for traceability. The aim of this work is to propose and analyze the economic sustainability and consumers’ preference of three technological systems supporting traceability: Near Field Communication (NFC) based; tamper-proof device plus Radio Frequency Identification (RFID) and app; QR code tag plus “scratch and win” system and blockchain. An anonymous questionnaire to Italian consumers (n = 1120) was made to acquire consumers’ acceptability of the systems and estimating their willingness to pay additional premium prices for these. An economic analysis estimated and compared the technology costs at different production levels. Results show that 94% of the consumer respondents are interested in the implementation of such technologies, and among them 45% chose QR-code protected by a “scratch-and-win” system with a blockchain infotracing-platform (QR-B). The consumers interested are willing to pay a mean premium price of 17.8% and economic analysis reported evidenced an incidence always lower than mid-/high-production levels. The success of the QR-B could be ascribed to different aspects: the cutting-edge fashion trend of blockchain in the food sector, the use of incentives, the easy-to-use QR-code, and the gamification strategy.
Simona Violino; Federico Pallottino; Giulio Sperandio; Simone Figorilli; Francesca Antonucci; Vanessa Ioannoni; Daniele Fappiano; Corrado Costa. Are the Innovative Electronic Labels for Extra Virgin Olive Oil Sustainable, Traceable, and Accepted by Consumers? Foods 2019, 8, 529 .
AMA StyleSimona Violino, Federico Pallottino, Giulio Sperandio, Simone Figorilli, Francesca Antonucci, Vanessa Ioannoni, Daniele Fappiano, Corrado Costa. Are the Innovative Electronic Labels for Extra Virgin Olive Oil Sustainable, Traceable, and Accepted by Consumers? Foods. 2019; 8 (11):529.
Chicago/Turabian StyleSimona Violino; Federico Pallottino; Giulio Sperandio; Simone Figorilli; Francesca Antonucci; Vanessa Ioannoni; Daniele Fappiano; Corrado Costa. 2019. "Are the Innovative Electronic Labels for Extra Virgin Olive Oil Sustainable, Traceable, and Accepted by Consumers?" Foods 8, no. 11: 529.
The aim of this work is to realize a term map analysis on technological advancements, in the year and in the world, of scientific researches of food traceability. Quality protection needs efficient instruments to discriminate Protected Denomination of Origin and Protected Geographical Indication varieties in field and to trace them along the agri-food chain. This study attempts to analyze global scientific of food traceability researches (between 1999 and 2018). In this period, 2534 scientific publications by Scopus database were found. Publication trends, research topics and their geographical distribution were analyzed by science mapping (VOSviewer software). Term map evidenced four main groups: red cluster with terms about food product and analytical methods for the characterization of food; green cluster including terms related with consumer (e.g., “food safety” and “food packaging”); blue cluster associating terms with the technology for traceability and yellow cluster with identification of food by genetic marker. It is possible to observe many links (i.e., co-occurrence between terms) in the green and blue clusters and among them. The yellow cluster could be considered as a subcategory of red one. In addition, green cluster refers to consumer and food safety. Yellow and red clusters contain analytical methods to identify food product, while blue cluster refers to advancements technological transferring information about the product to the consumer. These clusters do not present many linkages, and the consumer is in-between these. Finally, this study contributes to a better knowing of food traceability, and to an enhanced scientific research of technological advancements in supply chain.
Simona Violino; Francesca Antonucci; Federico Pallottino; Cristina Cecchini; Simone Figorilli; Corrado Costa. Food traceability: a term map analysis basic review. European Food Research and Technology 2019, 245, 2089 -2099.
AMA StyleSimona Violino, Francesca Antonucci, Federico Pallottino, Cristina Cecchini, Simone Figorilli, Corrado Costa. Food traceability: a term map analysis basic review. European Food Research and Technology. 2019; 245 (10):2089-2099.
Chicago/Turabian StyleSimona Violino; Francesca Antonucci; Federico Pallottino; Cristina Cecchini; Simone Figorilli; Corrado Costa. 2019. "Food traceability: a term map analysis basic review." European Food Research and Technology 245, no. 10: 2089-2099.
This is the first work to introduce the use of blockchain technology for the electronic traceability of wood from standing tree to final user. Infotracing integrates the information related to the product quality with those related to the traceability [physical and digital documents (Radio Frequency IDentification—RFID—architecture)] within an online information system whose steps (transactions) can be made safe to evidence of alteration through the blockchain. This is a decentralized and distributed ledger that keeps records of digital transactions in such a way that makes them accessible and visible to multiple participants in a network while keeping them secure without the need of a centralized certification organism. This work implements a blockchain architecture within the wood chain electronic traceability. The infotracing system is based on RFID sensors and open source technology. The entire forest wood supply chain was simulated from standing trees to the final product passing through tree cutting and sawmill process. Different kinds of Internet of Things (IoT) open source devices and tags were used, and a specific app aiming the forest operations was engineered to collect and store in a centralized database information (e.g., species, date, position, dendrometric and commercial information).
Simone Figorilli; Francesca Antonucci; Corrado Costa; Federico Pallottino; Luciano Raso; Marco Castiglione; Edoardo Pinci; Davide Del Vecchio; Giacomo Colle; Andrea Rosario Proto; Giulio Sperandio; Paolo Menesatti. A Blockchain Implementation Prototype for the Electronic Open Source Traceability of Wood along the Whole Supply Chain. Sensors 2018, 18, 3133 .
AMA StyleSimone Figorilli, Francesca Antonucci, Corrado Costa, Federico Pallottino, Luciano Raso, Marco Castiglione, Edoardo Pinci, Davide Del Vecchio, Giacomo Colle, Andrea Rosario Proto, Giulio Sperandio, Paolo Menesatti. A Blockchain Implementation Prototype for the Electronic Open Source Traceability of Wood along the Whole Supply Chain. Sensors. 2018; 18 (9):3133.
Chicago/Turabian StyleSimone Figorilli; Francesca Antonucci; Corrado Costa; Federico Pallottino; Luciano Raso; Marco Castiglione; Edoardo Pinci; Davide Del Vecchio; Giacomo Colle; Andrea Rosario Proto; Giulio Sperandio; Paolo Menesatti. 2018. "A Blockchain Implementation Prototype for the Electronic Open Source Traceability of Wood along the Whole Supply Chain." Sensors 18, no. 9: 3133.
A stereovision system for the in-field estimation of trees parameters such as height and diameter is proposed. The system includes a specifically developed mobile application for the management and georeferencing of stereo images. Stereo imaging allows the measurement of the distance between two points using triangulation formulas for the extraction of three-dimensional coordinates. The methodology is structured following three phases: training using system calibration through stereovision analysis of known artificial known objects; testing using measurements of standing tree diameters and heights acquired through stereovision system, laser rangefinder (height) and tree calliper (diameter); field application testing using direct height and diameter measurements in natural and urban woods. For this last phase an Android application was developed. The results show that the error between direct measurements and those measured with both stereovision and traditional reference methods (laser rangefinder and tree calliper) were quite low: 6.8 ± 6.6% between direct and laser rangefinder height measurements; 5.8 ± 5.5% between direct and stereovision height measurements; 4.2 ± 3.0% between direct and stereovision diameter measurements. No significant difference was found between the different methods for estimating height and diameter. Around 200 images matched to stereovision acquisitions were acquired and georeferenced using the application.
Corrado Costa; Simone Figorilli; Andrea Rosario Proto; Giacomo Colle; Giulio Sperandio; Pietro Gallo; Francesca Antonucci; Federico Pallottino; Paolo Menesatti. Digital stereovision system for dendrometry, georeferencing and data management. Biosystems Engineering 2018, 174, 126 -133.
AMA StyleCorrado Costa, Simone Figorilli, Andrea Rosario Proto, Giacomo Colle, Giulio Sperandio, Pietro Gallo, Francesca Antonucci, Federico Pallottino, Paolo Menesatti. Digital stereovision system for dendrometry, georeferencing and data management. Biosystems Engineering. 2018; 174 ():126-133.
Chicago/Turabian StyleCorrado Costa; Simone Figorilli; Andrea Rosario Proto; Giacomo Colle; Giulio Sperandio; Pietro Gallo; Francesca Antonucci; Federico Pallottino; Paolo Menesatti. 2018. "Digital stereovision system for dendrometry, georeferencing and data management." Biosystems Engineering 174, no. : 126-133.
As a result of mechanical fruit-thinning tests on various peach trees, difficulties in fruit detachment from branches were found for some cultivars. For this reason, and to create a database of the required detachment forces, the relationship between detachment and angle at which force is applied to the fruits was studied. The study was carried out in a peach orchard sited in Forlì, on four peach cultivars when the fruits were 20–40 mm in size. Using a dynamometer, the force required to detach fruits was measured, and different angles were evaluated to simulate the various ways in which the thinner hits fruits. The analysis of the different angles showed that, on average, fruits are detached more easily if the force is applied with a 90° angle respective to the fruit position on the branch. On the other hand, if the force is applied with an angle of 0°, the average force required is three times higher. The study highlighted that adaptability to mechanical thinning is higher in some cultivars than in others. The results also showed that it is important to consider the impact angle of the thinner on fruits when evaluating the efficiency of the thinner machine.
Alberto Assirelli; Giuseppina Caracciolo; Mattia Cacchi; Sandro Sirri; Federico Pallottino; Corrado Costa. Evaluation of the Detachment Force Needed for Mechanical Thinning of Green Peach Fruits. Sustainability 2018, 10, 2291 .
AMA StyleAlberto Assirelli, Giuseppina Caracciolo, Mattia Cacchi, Sandro Sirri, Federico Pallottino, Corrado Costa. Evaluation of the Detachment Force Needed for Mechanical Thinning of Green Peach Fruits. Sustainability. 2018; 10 (7):2291.
Chicago/Turabian StyleAlberto Assirelli; Giuseppina Caracciolo; Mattia Cacchi; Sandro Sirri; Federico Pallottino; Corrado Costa. 2018. "Evaluation of the Detachment Force Needed for Mechanical Thinning of Green Peach Fruits." Sustainability 10, no. 7: 2291.
This paper presents a machine vision retrofit system designed for upgrading used tractors to allow the control of the tillage implements and enable real-time field operation. The retrofit package comprises an acquisition system placed in the cabin, a front-mounted RGB camera sensor, and a rear-mounted Peiseler encoder wheel. The method combines shape analysis and colorimetric k-nearest neighbor (k-NN) clustering for in-field weed discrimination. This low-cost retrofit package can use interchangeable sensors, supplying flexibility of use with different farming implements. Field tests were conducted within lettuce and broccoli crops to develop the image analysis system for the autonomous control of an intra-row hoeing implement. The performance showed by the system in the trials was judged in terms of accuracy and speed. The system was capable of discriminating weed plants from crop with few errors, achieving a fairly high performance, given the severe degree of weed infestation encountered. The actuation time for image processing, currently implemented in MATLAB integrated with the retrofit kit, was about 7 s. The correct detection rate was higher for lettuce (from 69% to 96%) than for broccoli (from 65% to 79%), also considering the negative effect of shadows. To be implementable, the experimental code needs to be optimized to reduce acquisition and processing times. A software utility was developed in Java to reach a processing time of two images per second.
Federico Pallottino; Paolo Menesatti; Simone Figorilli; Francesca Antonucci; Roberto Tomasone; Andrea Colantoni; Corrado Costa. Machine Vision Retrofit System for Mechanical Weed Control in Precision Agriculture Applications. Sustainability 2018, 10, 2209 .
AMA StyleFederico Pallottino, Paolo Menesatti, Simone Figorilli, Francesca Antonucci, Roberto Tomasone, Andrea Colantoni, Corrado Costa. Machine Vision Retrofit System for Mechanical Weed Control in Precision Agriculture Applications. Sustainability. 2018; 10 (7):2209.
Chicago/Turabian StyleFederico Pallottino; Paolo Menesatti; Simone Figorilli; Francesca Antonucci; Roberto Tomasone; Andrea Colantoni; Corrado Costa. 2018. "Machine Vision Retrofit System for Mechanical Weed Control in Precision Agriculture Applications." Sustainability 10, no. 7: 2209.
The relevance of precision agriculture produced a growth of the related literature over the years. However, a structured analysis of the published material is still missing. Thus, this study attempts to analyze the global scientific output of precision agriculture researches published during the period 2000–2016. By using a science mapping approach, mainly based on the application of network analysis tools, it was possible to investigate pivotal aspects of this research field such as publication trends, research topics and their geographical distribution. Using the Scopus database 17,756 scientific publications were retrieved from the chosen period. The number of publications increased after 2006, highlighting the vibrancy of the field. By authoring 35% of the publications, U.S.A. and China were the most active knowledge producer countries. Moreover, the generation of time resolved maps allowed us to identify agriculture engineering, computer science and agriculture studies as three main research areas characterizing precision agriculture panorama. The paper discusses the distribution of these topics at global level, among European countries and in Italy. Overall, this analysis represents the first holistic view of precision agriculture research providing valuable information for farmers, policy makers and researchers.
Federico Pallottino; Marcello Biocca; Pierfrancesco Nardi; Simone Figorilli; Paolo Menesatti; Corrado Costa. Science mapping approach to analyze the research evolution on precision agriculture: world, EU and Italian situation. Precision Agriculture 2018, 19, 1011 -1026.
AMA StyleFederico Pallottino, Marcello Biocca, Pierfrancesco Nardi, Simone Figorilli, Paolo Menesatti, Corrado Costa. Science mapping approach to analyze the research evolution on precision agriculture: world, EU and Italian situation. Precision Agriculture. 2018; 19 (6):1011-1026.
Chicago/Turabian StyleFederico Pallottino; Marcello Biocca; Pierfrancesco Nardi; Simone Figorilli; Paolo Menesatti; Corrado Costa. 2018. "Science mapping approach to analyze the research evolution on precision agriculture: world, EU and Italian situation." Precision Agriculture 19, no. 6: 1011-1026.
An increasing number of farm machines nowadays implement precision agriculture technologies. Most of these operate through proximal sensing using optical sensors (i.e. NIR or Vis-NIR). Imaging techniques in this context have received minor consideration due to the complex analysis of the data but on the other side offer great flexibility. This study reports a preliminary pilot imaging multi-sensor retrofit system to be applied independently on a wide range of agricultural machines and able to test different monitoring or control image-based applications for precision agriculture. The process, based on RGB image, was tested for in-field discrimination of weeds in lettuce and broccoli crops. It works by discriminating and extracting single plants from the soil and weeds. However, to be truly implementable, the experimental code should be optimized in order to shorten the time needed for acquisition and processing.
P. Menesatti; F. Pallottino; S. Figorilli; F. Antonucci; R. Tomasone; C. Costa. Multi-sensor imaging retrofit system to test precision agriculture machine-based applications. Advances in Animal Biosciences 2017, 8, 189 -192.
AMA StyleP. Menesatti, F. Pallottino, S. Figorilli, F. Antonucci, R. Tomasone, C. Costa. Multi-sensor imaging retrofit system to test precision agriculture machine-based applications. Advances in Animal Biosciences. 2017; 8 (2):189-192.
Chicago/Turabian StyleP. Menesatti; F. Pallottino; S. Figorilli; F. Antonucci; R. Tomasone; C. Costa. 2017. "Multi-sensor imaging retrofit system to test precision agriculture machine-based applications." Advances in Animal Biosciences 8, no. 2: 189-192.
The estimation of operating costs of agricultural and forestry machineries is a key factor in both planning agricultural policies and farm management. Few works have tried to estimate operating costs and the produced models are normally based on deterministic approaches. Conversely, in the statistical model randomness is present and variable states are not described by unique values, but rather by probability distributions. In this study, for the first time, a multivariate statistical model based on Partial Least Squares (PLS) was adopted to predict the fuel consumption and costs of six agricultural operations such as: ploughing, harrowing, fertilization, sowing, weed control and shredding. The prediction was conducted on two steps: first of all few initial selected parameters (time per surface-area unit, maximum engine power, purchase price of the tractor and purchase price of the operating machinery) were used to estimate the fuel consumption; then the predicted fuel consumption together with the initial parameters were used to estimate the operational costs. Since the obtained models were based on an input dataset very heterogeneous, these resulted to be extremely efficient and so generalizable and robust. In details the results show prediction values in the test with r always ≥ 0.91. Thus, the approach may results extremely useful for both farmers (in terms of economic advantages) and at institutional level (representing an innovative and efficient tool for planning future Rural Development Programmes and the Common Agricultural Policy). In light of these advantages the proposed approach may as well be implemented on a web platform and made available to all the stakeholders.
Mirko Guerrieri; Marco Fedrizzi; Francesca Antonucci; Federico Pallottino; Giulio Sperandio; Mauro Pagano; Simone Figorilli; Paolo Menesatti; Corrado Costa. An innovative multivariate tool for fuel consumption and costs estimation of agricultural operations. Spanish Journal of Agricultural Research 2016, 14, 1 .
AMA StyleMirko Guerrieri, Marco Fedrizzi, Francesca Antonucci, Federico Pallottino, Giulio Sperandio, Mauro Pagano, Simone Figorilli, Paolo Menesatti, Corrado Costa. An innovative multivariate tool for fuel consumption and costs estimation of agricultural operations. Spanish Journal of Agricultural Research. 2016; 14 (4):1.
Chicago/Turabian StyleMirko Guerrieri; Marco Fedrizzi; Francesca Antonucci; Federico Pallottino; Giulio Sperandio; Mauro Pagano; Simone Figorilli; Paolo Menesatti; Corrado Costa. 2016. "An innovative multivariate tool for fuel consumption and costs estimation of agricultural operations." Spanish Journal of Agricultural Research 14, no. 4: 1.
Beer foam is one of the first characteristics consumers visually perceive. Even if their opinions vary, generally, beer foam should be stable and long lasting. In this work, the conventional foam head retention method developed by Rudin () was improved by resorting to three different automatic data acquisition systems. The first one made use of a mouse time tracking software offered at no cost. The second one was an system using a high-definition camera and a script written in MATLAB. Finally, the third one was an automatic incorporating a Raspberry Pi single-board computer and a camera module (Raspberry Pi Foundation, UK). The latter was able not only to acquire the whole foam decay curve but also to fit the time course of the beer–foam interface position and extract the characteristic beer foam half-life ( ). All the data acquisition systems yielded values practically coincident at the probability level of 0.05, this confirming their substantial equivalence. Once the lager beer had been laced with increasing doses of a foam agent (i.e., tetrahydro-iso-α-acid) to enhance its foam persistence, the resulting foam half-life, as estimated using the above Rudin-based methods, was highly correlated ( = 0.99) to the foam collapse time, as derived from the NIBEM Foam Stability Tester. Finally, thanks to the LCIA acquisition system developed here, the Rudin test might represent a fast, flexible, and cheaper alternative to the generally recommended but expensive NIBEM tester, as well as other commercial automated Rudin apparatuses.
Alessio Cimini; Federico Pallottino; Paolo Menesatti; Mauro Moresi. A Low-Cost Image Analysis System to Upgrade the Rudin Beer Foam Head Retention Meter. Food and Bioprocess Technology 2016, 9, 1587 -1597.
AMA StyleAlessio Cimini, Federico Pallottino, Paolo Menesatti, Mauro Moresi. A Low-Cost Image Analysis System to Upgrade the Rudin Beer Foam Head Retention Meter. Food and Bioprocess Technology. 2016; 9 (9):1587-1597.
Chicago/Turabian StyleAlessio Cimini; Federico Pallottino; Paolo Menesatti; Mauro Moresi. 2016. "A Low-Cost Image Analysis System to Upgrade the Rudin Beer Foam Head Retention Meter." Food and Bioprocess Technology 9, no. 9: 1587-1597.