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Advanced Modeling for the Identification of Different Pathogen Tolerant Vines to Reduce Fungicides and Energy Consumption

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Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA)—Centro di Ricerca Viticoltura ed Enologia—Via Cantina Sperimentale, 1, 00049 Velletri (Rome), Italy
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Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA)—Centro di ricerca Ingegneria e Trasformazioni agroalimentari—Via della Pascolare, 16, 00015 Monterotondo (Rome), Italy
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STAPHYT, contract research organization (CRO) in the fields of Agrosciences and Regulatory Affairs. Main facility Italy, Via della Meccanica, 28, 04011 Aprilia (LT), Italy
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Agenzia Regionale per lo Sviluppo e l’Innovazione dell’Agricoltura del Lazio (ARSIAL)—Via Rodolfo Lanciani, 38, 00162 Rome, Italy
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Author to whom correspondence should be addressed.
Sustainability 2020, 12(5), 1900; https://doi.org/10.3390/su12051900
Received: 29 January 2020 / Revised: 27 February 2020 / Accepted: 28 February 2020 / Published: 3 March 2020
(This article belongs to the Section Sustainable Agriculture)
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. View Full-Text
Keywords: powdery mildew; phenotyping; artificial dataset; viticulture sustainability; energy efficiency; SIMCA powdery mildew; phenotyping; artificial dataset; viticulture sustainability; energy efficiency; SIMCA
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MDPI and ACS Style

Cecchini, F.; Serra, M.C.; Bevilacqua, N.; Costa, C.; Valori, R.; Pallottino, F.; Casadei, G.; Menesatti, P.; Antonucci, F. Advanced Modeling for the Identification of Different Pathogen Tolerant Vines to Reduce Fungicides and Energy Consumption. Sustainability 2020, 12, 1900. https://doi.org/10.3390/su12051900

AMA Style

Cecchini F, Serra MC, Bevilacqua N, Costa C, Valori R, Pallottino F, Casadei G, Menesatti P, Antonucci F. Advanced Modeling for the Identification of Different Pathogen Tolerant Vines to Reduce Fungicides and Energy Consumption. Sustainability. 2020; 12(5):1900. https://doi.org/10.3390/su12051900

Chicago/Turabian Style

Cecchini, Francesca, Maria C. Serra, Noemi Bevilacqua, Corrado Costa, Roberto Valori, Federico Pallottino, Giorgio Casadei, Paolo Menesatti, and Francesca Antonucci. 2020. "Advanced Modeling for the Identification of Different Pathogen Tolerant Vines to Reduce Fungicides and Energy Consumption" Sustainability 12, no. 5: 1900. https://doi.org/10.3390/su12051900

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