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 in | HighTech and innovation journal Vol. 1; no. 3; pp. 129 - 135 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Ital Publication
01.09.2020
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Subjects | |
Online Access | Get full text |
ISSN | 2723-9535 2723-9535 |
DOI | 10.28991/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 |
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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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Title | DSS LANDS: A Decision Support System for Agriculture in Sardinia |
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