A fuzzy control system for decision-making about fungicide applications against grape downy mildew

González‐Domínguez, Elisa; Caffi, Tito; Bodini, Alessandro; Galbusera, Luca; Rossi, Vittorio

doi:10.1007/s10658-015-0781-x

Cited by 8 publications

(7 citation statements)

References 31 publications

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“…For instance, among the climate data, the air temperature was widely used, probably because it is easy to measure and interpret in a biological context, being highly correlated with development of PM and DM in vineyards. Moreover, warning system models have grown to use different meteorological features, such as precipitation [ 24 ], humidity [ 25 ], leaf wetness with an hourly frequency [ 25 , 26 , 27 ], plant water stress [ 28 ], and others [ 10 , 29 ]. Field data and on-site measurements have also been employed to describe pathogen dynamics and modelling.…”

Section: Resultsmentioning

confidence: 99%

Current Trends and Perspectives on Predictive Models for Mildew Diseases in Vineyards

et al. 2022

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Environmental and economic costs demand a rapid transition to more sustainable farming systems, which are still heavily dependent on chemicals for crop protection. Despite their widespread application, powdery mildew (PM) and downy mildew (DM) continue to generate serious economic penalties for grape and wine production. To reduce these losses and minimize environmental impacts, it is important to predict infections with high confidence and accuracy, allowing timely and efficient intervention. This review provides an appraisal of the predictive tools for PM and DM in a vineyard, a specialized farming system characterized by high crop protection cost and increasing adoption of precision agriculture techniques. Different methodological approaches, from traditional mechanistic or statistic models to machine and deep learning, are outlined with their main features, potential, and constraints. Our analysis indicated that strategies are being continuously developed to achieve the required goals of ease of monitoring and timely prediction of diseases. We also discuss that scientific and technological advances (e.g., in weather data, omics, digital solutions, sensing devices, data science) still need to be fully harnessed, not only for modelling plant–pathogen interaction but also to develop novel, integrated, and robust predictive systems and related applied technologies. We conclude by identifying key challenges and perspectives for predictive modelling of phytopathogenic disease in vineyards.

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Section: Resultsmentioning

confidence: 99%

Current Trends and Perspectives on Predictive Models for Mildew Diseases in Vineyards

et al. 2022

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“…Therefore, we can consider that the FL model has an intuitive technology as a predictive model, is easy to transfer to farmers or field technicians, and, most importantly, is suitable as the connection for a decision support system. The most effective FL technique in this study (FRBCS.W) was developed in a similar way to that developed by [33]. To perform this, first, a set of rules was developed resulting from a combination between the different sublevels of each of the parameters considered in the study.…”

Section: Discussionmentioning

confidence: 99%

“…To perform this, first, a set of rules was developed resulting from a combination between the different sublevels of each of the parameters considered in the study. Subsequently, a result was obtained: a risk of VW development in this study or the decision of whether to apply a fungicide to Plasmopara viticola in a vineyard in the study by [33], obtaining the precision of the comparison between the results that the predictive model provided and what an expert would do in the same case. However, the precision levels of such an algorithm in this work were not very high (60.0%) compared to those found in the previously mentioned work (99.2%; [33]).…”

Section: Discussionmentioning

confidence: 99%

“…In this sense, fuzzy logic (FL) can handle the uncertainty of our knowledge and thus, it is especially useful when evaluating a system requires human experience that is expressed in 'linguistic' terms (e.g., a high risk of infection or low residual fungicide protection) [32]. As an example, this technique has been satisfactorily used to determine whether fungicide application is needed to control Plasmopara viticola, the causal agent of downy mildew, in a vineyard [33].…”

Section: Introductionmentioning

confidence: 99%

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Predicting the Risk of Verticillium Wilt in Olive Orchards Using Fuzzy Logic

López-Escudero,

Romero,

Bocanegra-Caro

et al. 2023

Agriculture

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Developing models to understand disease dynamics and predict the risk of disease outbreaks to facilitate decision making is an integral component of plant disease management. However, these models have not yet been developed for one of the most damaging diseases in Mediterranean olive-growing areas (verticillium wilt (VW), caused by the fungus Verticillium dahliae Kleb.), although there are parameters (e.g., level of V. dahliae inoculum in the soil, level of susceptibility of the olive cultivar, isothermality, coefficient of variation of seasonal precipitation, etc.) that have previously been correlated with the severity of the disease. Using the data from previous VW studies conducted in the Guadalquivir Valley of Andalusia (one of the most damaged areas worldwide), in this work, a set of fuzzy logic (FL) models is developed with the aforementioned disease and climatic parameters, and the results are compared with machine learning (ML) models, of known effectiveness, to predict the risk levels of VW appearance in an olive orchard. Under these conditions, both groups of models were less effective than those previously studied with simpler models or models used under controlled conditions. However, the accuracy achieved with the most efficient FL model (60%; classification system based on fuzzy rules using the Ishibuchi method with a weighting factor) was somewhat greater than the efficiency achieved with the most efficient ML model (59.0%; decision tree classifier), in addition to being more appropriate (from a practical point of view) for the incorporation into a decision support system by allowing the risk of appearance of each observation to be known by providing rules for each of the combinations of the different parameters with similar precision. Therefore, in this study, we propose the FL methodology as suitable to act as an expert system for the future creation of a decision support system for VW in olives.

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“…[24][25][26] The PR controller is a type of expert control system that is based on the system response. 27 Both the RST controller and the PR controller are easy to realize in microcontrol units.…”

Section: Introductionmentioning

confidence: 99%

A novel single-gimbal control moment gyroscope driven by an ultrasonic motor

Pan

Zhao

2019

Advances in Mechanical Engineering

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This article presents a structure-compacted single-gimbal control moment gyroscope, which is directly driven by an ultrasonic motor. The momentum wheel and the ultrasonic motor are designed and optimized based on software simulation. Considering the gyroscope's dynamic disturbance and the nonlinearities of the ultrasonic motor, an expert control algorithm combining a two-degree-of-freedom pole placement controller with a pattern reasoning controller is designed for the gimbal servo system. The presented controller realizes a wide-range closed-loop speed control of the gimbal from 0.2 mrad/s to 1.6 rad/s, which is the base of the high stability and high precision of the control moment gyroscope. The presented control moment gyroscope and its controller board are manufactured and assembled for experiments. The experimental results show that the momentum wheel has almost no impact on the gimbal servo system at high speeds, but with the decrease in the gimbal speed the impact increases gradually.

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A fuzzy control system for decision-making about fungicide applications against grape downy mildew

Cited by 8 publications

References 31 publications

Current Trends and Perspectives on Predictive Models for Mildew Diseases in Vineyards

Current Trends and Perspectives on Predictive Models for Mildew Diseases in Vineyards

Predicting the Risk of Verticillium Wilt in Olive Orchards Using Fuzzy Logic

A novel single-gimbal control moment gyroscope driven by an ultrasonic motor

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