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Weather based decision support for managing pests and diseases of crops requires use of information technology. This paper details a system developed using ontology, semantic web rule language and image processing techniques for management of pests and diseases on wines, particularly in hot tropical region of India. It aims at minimising use of pes...
Contexts in source publication
Context 1
... IoT is key player in precision agriculture, use of sensors is inevitable (Antonio et al., 2011). Some pesticides should be applied in the presence of soil moisture. ...
Context 2
... in sensor ontology for soil moisture (see online version for colours) Figure 11 Effect of diseases on grape leaves (see online version for colours) Figure 12 Grape leaf image segmentation by K-means clustering (see online version for colours) Figure 13 Mobile application for grapes growers (see online version for colours) ...
Context 3
... in sensor ontology for soil moisture (see online version for colours) Figure 11 Effect of diseases on grape leaves (see online version for colours) Figure 12 Grape leaf image segmentation by K-means clustering (see online version for colours) Figure 13 Mobile application for grapes growers (see online version for colours) ...
Context 4
... in sensor ontology for soil moisture (see online version for colours) Figure 11 Effect of diseases on grape leaves (see online version for colours) Figure 12 Grape leaf image segmentation by K-means clustering (see online version for colours) Figure 13 Mobile application for grapes growers (see online version for colours) ...
Context 5
... grower interacts with PDMGrapes using android based application shown in Figure 13. Grape grower can ask of pest/disease probability by selecting his location. ...
Similar publications
Weather based decision support for managing pests and diseases of crops requires use of information technology. This paper details a system developed using ontology, semantic web rule language and image processing techniques for management of pests and diseases on wines, particularly in hot tropical region of India. It aims at minimising use of pes...
Citations
... A domain ontology is therefore a key for the success of exchanges in this context [20]. However, the only ontology cannot provide to the actors in the field the desired level of information. ...
... The authors proposed expert system that solves problems such as the lack of expert knowledge of the farmer. The authors of [20] and [23] promote an ontology-based system, a semantic web rules language and image processing techniques for the management of pests and diseases of certain plants. The authors of [22] and are more particularly interested in cotton plant diseases by proposing an expert system based on ontology. ...
Cotton cultivation in the Côte d’Ivoire is subject to enormous pressure from pests. This situation has important consequences on the yield of this crop. To improve yield, a strategy based on phytosanitary surveillance has been elaborated by the National Agronomic Research Center (CNRA). In this paper, we propose a digital solution for the implementation of this strategy. This solution is founded on an ontology (ontoSySParCotCI). It includes two main modules. The first module is a data collection and an alert system. It has a mobile interface for data collection and a web interface for access to data by researchers. The second module is a semantic wiki which is an interface for sharing and co-constructing knowledge on cotton cultivation. A prototype of the first module was presented as well as a satisfaction survey for its use.
... Therefore, effective pest management in viticulture should adopt an integrated approach encompassing optimal farming practices, advanced forecasting models, decision support systems (DSSs), biological controls, and judicious use of chemical sprays to minimize pesticide usage (Pertot et al., 2017) [37] . Chougule et al. (2019) [15] developed "PDMGrapes," a decision support system for grape crop protection in India's hot tropical regions, employing ontology, semantic web rule language, and image processing techniques to manage insect pests and diseases effectively. ...
... Therefore, effective pest management in viticulture should adopt an integrated approach encompassing optimal farming practices, advanced forecasting models, decision support systems (DSSs), biological controls, and judicious use of chemical sprays to minimize pesticide usage (Pertot et al., 2017) [37] . Chougule et al. (2019) [15] developed "PDMGrapes," a decision support system for grape crop protection in India's hot tropical regions, employing ontology, semantic web rule language, and image processing techniques to manage insect pests and diseases effectively. ...
