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Pubblicazioni

Agrofiliere

Detecting downy mildew symptoms on wild rocket leaves by hyperspectral imaging. Proceedings of the XXV Congress of the Italian Phytopathological Society (SIPaV).

Santonicola L., Villecco D., Pentangelo A., Pane C., 2019.
J Plant Pathol 101, 811–848


Valutazione non distruttiva del contenuto in antociani e caroteni in diversi genotipi di patata con spettroscopia di riflettanza risolta nel tempo.

Vanoli M., Spinelli L., Torricelli A., Ibrahim A., Parisi B., Lo Scalzo R., Rizzolo A., 2019.
Abstract presentato al Convegno Postraccolta dei prodotti ortoflorofrutticoli, 28-29 Ottobre, Università degli Studi di Milano.


Problematiche nella rivelazione non distruttiva dei difetti interni di tuberi di patata cv “El Beida”

Ibrahim, A., Grassi M., Lovati F., Parisi B., Spinelli L., Torricelli A., Rizzolo A., Vanoli M., 2019.
Abstract presentato al Convegno Postraccolta dei prodotti ortoflorofrutticoli, 28-29 Ottobre, Università degli Studi di Milano.


A blockchain implementation prototype for the electronic open source traceability of wood along the whole supply chain.

Figorilli S., Antonucci F., Costa C., Pallottino F., Raso L., Castiglione M., Pinci E., Del Vecchio D., Colle G., Proto A.R., Sperandio G., Menesatti P., 2018.
Sensors, 18, 3133.
Link: https://www.mdpi.com/1424-8220/18/9/3133


Optoelectronic proximal sensing vehicle-mounted technologies in precision agriculture: a review.

Pallottino F., Antonucci F., Costa C., Bisaglia C., Figorilli S., Menesatti P., 2019
Computers and Electronics in Agriculture, 162: 859-873.
doi: https://doi.org/10.1016/j.compag.2019.05.034


Food traceability: a term map analysis basic review.

Violino S., Antonucci F., Pallottino F., Cecchini C., Figorilli S., Costa C., 2019.
European Food Research and Technology, 245: 2089-2099.
doi: https://doi.org/10.1007/s00217-019-03321-0


A Review on blockchain applications in the agri-food sector.

Antonucci F., Figorilli S., Costa C., Pallottino F., Raso L., Menesatti P., 2019
Journal of The Science of Food and Agriculture, 99: 6129–6138.
doi: https://doi.org/10.1002/jsfa.9912


Light drone-based application to assess soil tillage quality parameters.

Fanigliulo R., Antonucci F., Figorilli S., Pochi D., Pallottino F., Fornaciari L., Grilli R., Costa C., 2020.
Sensors, 20, 728.
doi: https://doi.org/10.3390/s20030728


Precision aquaculture: a short review on engineering innovations.

Antonucci F., Costa C., 2020.
Aquaculture International, 28: 41–57.
doi: https://doi.org/10.1007/s10499-019-00443-w


Potential blockchain applications in animal production and health sector.

Makkar, H. P. S., Costa, C., 2020.
CAB Reviews, 15(035), 1-8.
doi: http://dx.doi.org/10.1079/PAVSNNR202015035


Greenhouse application of light-drone imaging technology for assessing weeds severity occurring on baby-leaf red lettuce beds approaching fresh-cutting.

Pallottino, F., Pane, C., Figorilli, S., Pentangelo, A., Antonucci., F., Costa, 2020.
Spanish Journal of Agricultural Research, 18(3), e0207.
Link: https://dialnet.unirioja.es/servlet/articulo?codigo=7698685 


Alta tecnologia per difendere le baby leaf.

Pane C., Nicastro N., 2020.
Terra e Vita, 31, 40-44.


High-tech e baby-leaf.

Pane C., Nicastro N., 2020.
Colture Protette, 9, 28-33.


Miglioramento genetico della barbabietola da zucchero, con applicazione di sensoristica finalizzato al risparmio idrico nell’ambito degli adattamenti al cambiamento climatico.

Alberti, I., Costa, C., Montanari, M., Pallottino, F., Colombo, M., Pieri, S., Ortenzi, L., Campagna G., 2020.
L’industria saccarifera italiana, 113(5), 78-88.


Remot controls of solar drier micro-plants for process standardization.

Cattaneo, T.M.P., Bisaglia, C., Cammerata, A., Stellari, A., Romano E., 2020
Proceedings at International Conference Safety Health Welfare in Agro-Systems. RAGUSA SHWA - September 16-19, Ragusa, Italy


Precision Agriculture Digital Technologies for Sustainable Fungal Disease Management of Ornamental Plants.

Traversari, S., Cacini, S., Galieni, A., Nesi, B., Nicastro, N., Pane, C., 2021.
Sustainability, 13, 3707.
doi: https://doi.org/10.3390/su13073707


Powdery Mildew Caused by Erysiphe cruciferarum on Wild Rocket (Diplotaxis tenuifolia): Hyperspectral Imaging and Machine Learning Modeling for Non-Destructive Disease Detection.

Pane, C., Manganiello, G., Nicastro, N., Cardi, T., Carotenuto, F., 2021.
Agriculture, 11, 337.
doi: https://doi.org/10.3390/agriculture11040337


Functional Hyperspectral Imaging by High-Related Vegetation Indices to Track the Wide-Spectrum Trichoderma Biocontrol Activity Against Soil-Borne Diseases of Baby-Leaf Vegetables.

Manganiello, G., Nicastro, N., Caputo, M., Zaccardelli, M., Cardi, T., Pane C., 2021.
Frontiers in Plant Science, 12, 630059.
doi: https://doi.org/10.3389/fpls.2021.630059


Semi-Automatic Guidance vs. Manual Guidance in Agriculture: A Comparison of Work Performance in Wheat Sowing.

Scarfone, A., Picchio, R., del Giudice, A., Latterini, F., Mattei, P., Santangelo, E., Assirelli, A., 2021.
Electronics, 10(7), 825.
doi: https://doi.org/10.3390/electronics10070825


Spatial Variations of Vegetation Index from Remote Sensing Linked to Soil Colloidal Status.

Bascietto, M., Santangelo, E., Beni, C., 2021.
Land, 10(1), 80
doi: https://doi.org/10.3390/land10010080


An open-source low-cost device coupled with an adaptative time-lag time series linear forecasting modelling for apple Trentino (Italy) precision irrigation.

Figorilli, S., Pallottino, F., Colle, G., Spada, D., Beni, C., Tocci, F., Vasta, S., Antonucci, F., Pagano, M., Fedrizzi, M., Costa, C., 2021.
Sensors, 21(8), 2656.
doi: https://doi.org/10.3390/s21082656


Light Drones for Basic In-Field Phenotyping and Precision Farming Applications: RGB Tools Based on Image Analysis.

Pallottino, F., Figorilli, S., Cecchini, C., Costa, C., 2021.
In Crop Breeding (pp. 269-278). Humana, New York, NY.


Nuovi sistemi di supporto a elevata integrazione.

Nesi B., Traversari, S., Pane C., Cacini S., 2021.
Colture Protette, 2, 50-53.


NIRS and Aquaphotomics for the Evaluation of the Efficiency of Solar Dehydration Processes.

Cattaneo, T.M.P., Cutini, M., Stellari, A., Marinoni, L., Bisaglia, C., Brambilla, M., 2021.
Book of Abstract al Simposio Nazionale NIRItalia, pp.94-95; 24-25 febbraio (on line Conference).


Food quality and process investigated through water absorption variations in NIR range.

Cattaneo, T.M.P., 2021.
Oral presentation at 4th Aquaphotomics International Conference March 20 22, Kobe Japan (on line Conference).

 

Agromodelli

The HADES Yield Prediction System – A Case Study on the Turkish Hazelnut Sector.

Bregaglio, S., Fischer, K., Ginaldi, F., Valeriano, T.T.B., Giustarini, L., 2021.  
Frontiers in Plant Science. 
doi: https://doi.org/10.3389/fpls.2021.665471 


Comparing process-based wheat growth models in their simulation of yield losses caused by plant diseases. 

Bregaglio, S.,  Willocquet, L., Kersebaum, K.C., Asseng, S., Savary, S., 2021. 
Field Crops Research 265, 108108. 
doi: https://doi.org/10.1016/j.fcr.2021.108108 


Model-based evaluation of climate change impacts on rice grain quality in the main European rice district. 

Cappelli, G., Bregaglio, S., 2021.  
Food and Energy Security 
doi: https://doi.org/10.1002/fes3.307 


Agricultural land suitability in a changing climate: a case study for hazelnut in Australia.

Jha P.J., Materia S., Zizzi G., Costa Saura J., Trabucco A., Evans J., Bregaglio S., 2021. 
Agricultural Systems 186, 102982. 
doi: https://doi.org/10.1016/j.agsy.2020.102982 


A process-based model to simulate sugarcane orange rust severity from weather data in Southern Brazil.

Valeriano, T.T.B., de Souza Rolim, G., Manici, L.M., Giustarini, L., Bregaglio, S., 2021.   
International Journal of Biometeorology 65(12), 2037–2051. 
doi: https://link.springer.com/article/10.1007/s00484-021-02162-5 


Varietal susceptibility overcomes climate change effects on the future trends of rice blast disease in Northern Italy.

Wang, H., Mongiano, G., Fanchini, D., Titone, P., Tamborini, L., Bregaglio, S., 2021.  
Agricultural Systems 193, 103223 
doi: https://doi.org/10.1016/j.agsy.2021.103223 


Analysing the behaviour of a hazelnut simulation model across growing environments via sensitivity analysis and automatic calibration. 

Bregaglio, S., Giustarini, L., Suarez, E., Mongiano, G., De Gregorio, T., 2020. 
Agricultural Systems 181. 
doi: https://doi.org/10.1016/j.agsy.2020.102794 


Reuse of process-based models: automatic transformation into many programming languages and simulation platforms

Midingoyi, C.A., Pradal, C., Athanasiadis, I.N, Donatelli, M., Enders, A., Fumagalli, D., Garcia, F., Holzworth, D., Hoogenboom, G., Porter, C., Raynal, H., Thorburn, P., Martre, P., 2020.
Silico Plants, Volume 2, Issue 1, 2020, diaa007, Published: 06 October 2020
doi: https://doi.org/10.1093/insilicoplants/diaa007


Susceptibility of novel Italian rice varieties to panicle blast under field conditions

Mongiano, G., Titone, P., Bregaglio, S., Tamborini, L., 2020.
bioRxiv 2020.04.23.057554
doi: https://doi.org/10.1101/2020.04.23.057554


Understanding effects of genotype × environment × sowing window interactions for durum wheat in the Mediterranean basin.

Padovan, G., Martre, P., Semenov, M.A., Masoni, A,. Bregaglio, S., et al., 2020. 
Field Crops Research 259, 107969. 
doi: https://doi.org/10.1016/j.fcr.2020.107969 


Spatializing Crop Models for Sustainable Agriculture

Ginaldi F., Bajocco S., Bregaglio S., Cappelli G., 2019.
In: Farooq M., Pisante M. (eds) Innovations in Sustainable Agriculture. Springer, Cham, 2019.
doi: https://doi.org/10.1007/978-3-030-23169-9_20


Identifying the most promising agronomic adaptation strategies for the tomato growing systems in Southern Italy via simulation modeling

Giuliani, M.M., Gatta, G., Cappelli, G., Gagliardi, A., Donatelli, M., Fanchini, D., De Nart, D., Mongiano, G., Bregaglio, D., 2019.
European Journal of Agronomy, Volume 111, 2019, 125937, ISSN 1161-0301
doi: https://doi.org/10.1016/j.eja.2019.125937

 

 

Selvicoltura

 

 

Zootecnia

 

 

Viticoltura

Viticoltura "digitale" per il miglioramento della sostenibilità delle produzioni

Paolo Storchi, Riccardo Velasco
pubblicato su RRN MAGAZINE, Rivista della Rete Rurale Nazionale, N. 9 del 31 gennaio 2020


Il futuro preciso del vigneto

Paolo Storchi, Riccardo Velasco
pubblicato su Terra e Vita - rivista n.13 del 2019

 

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