DSS LANDS: A Decision Support System for Agriculture in Sardinia

Recently, the use of DSSs application has been strongly increasing in the agricultural sector due to continuous climate change and the need to conduct more productive and sustainable agriculture. In this paper, we describe the prototype agricultural DSS LANDS developed for monitoring the main crop p...

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Published inHighTech and innovation journal Vol. 1; no. 3; pp. 129 - 135
Main Authors Fenu, Gianni, Malloci, Francesca Maridina
Format Journal Article
LanguageEnglish
Published Ital Publication 01.09.2020
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ISSN2723-9535
2723-9535
DOI10.28991/HIJ-2020-01-03-05

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Abstract Recently, the use of DSSs application has been strongly increasing in the agricultural sector due to continuous climate change and the need to conduct more productive and sustainable agriculture. In this paper, we describe the prototype agricultural DSS LANDS developed for monitoring the main crop production in Sardinia. The DSS collects, organizes, integrates, and analyzes several types of data with different mathematical models. In particular, a case study on forecasting potato late blight is presented. We employed the Negative Prognosis model and the Fry model to forecast the period in which it is opportune to carry out fungicide treatments useful against the appearance of the pathogen. The experiments allowed us to outline the best criteria for local conditions, and the evaluation showed the effectiveness of the approach in a concrete case study. Doi: 10.28991/HIJ-2020-01-03-05 Full Text: PDF
AbstractList Recently, the DSSs application is strongly increasing in the agricultural sector due to continuous climate changes and the need to conduct more productive and sustainable agriculture. In this paper, we describe the prototype agricultural DSS LANDS developed for monitoring the main crop productions in Sardinia. The DSS collects, organizes, integrates, and analyses several types of data with different mathematical models. In particular, a case study on forecasting potato late blight is presented. We employed the Negative Prognosis model and Fry model to forecast the period in which it is opportune to carry out fungicide treatments useful against the appearance of the pathogen. The experiments allowed to outline the best criteria for local conditions as well as the evaluation showed the effectiveness of the approach in a concrete case study.
Recently, the use of DSSs application has been strongly increasing in the agricultural sector due to continuous climate change and the need to conduct more productive and sustainable agriculture. In this paper, we describe the prototype agricultural DSS LANDS developed for monitoring the main crop production in Sardinia. The DSS collects, organizes, integrates, and analyzes several types of data with different mathematical models. In particular, a case study on forecasting potato late blight is presented. We employed the Negative Prognosis model and the Fry model to forecast the period in which it is opportune to carry out fungicide treatments useful against the appearance of the pathogen. The experiments allowed us to outline the best criteria for local conditions, and the evaluation showed the effectiveness of the approach in a concrete case study. Doi: 10.28991/HIJ-2020-01-03-05 Full Text: PDF
Author Malloci, Francesca Maridina
Fenu, Gianni
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StartPage 129
SubjectTerms data analysis
decision support system
decision-making
precision farming
Title DSS LANDS: A Decision Support System for Agriculture in Sardinia
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