A new decision-support system for the historical analysis of integrated pest management activities on olive crops based on climatic data

Zaza, Claudio; Bimonte, Sandro; Faccilongo, Nicola; Sala, Piermichele La; Contò, Francesco; Gallo, Crescenzio

doi:10.1016/j.compag.2018.03.015

Cited by 15 publications

(10 citation statements)

References 44 publications

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“…Then, FMIS (Farm Management Information System) and DSS (Decision Support Systems) can be the basis for successful information exploitation. After having all necessary information, using FMIS and DSS, it is possible to analyze and make them available in a useful form to the agricultural entrepreneur to improve the decision-making process and the farming system as a whole (Zaza et al, 2018;Paraforos et al, 2016). This means that farmers will be offered with choices that solve the problems regarding to production process and environmental impact (Fig.…”

Section: The Benefits Of Adoption Of It In Agricultural Practicesmentioning

confidence: 99%

Ecosystem for Successful Agriculture. Collaborative Approach as a Driver for Agricultural Development

Adamashvili

Fiore

Contò

et al. 2020

European Countryside

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The development of agribusiness sector is given gradually increasing importance. This works aims at identifying the elements that create the successful ecosystem for agricultural development, their benefits and application in agri-food systems; additionally, to bring on a light of the role of agricultural policies in these processes. For this purpose, the authors have carried out an analysis of the concern related literature and present a preliminary theoretical framework/model as a tool for supporting local development and incorporate a successful effective ecosystem. The key implications of this paper include an increased attention to agricultural research, to the role of the collaboration between relevant stakeholders, as well as of the agriculture, which uses information technologies for the better utilization of natural resources, and what is the most important is, the role of agricultural policies.

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Section: The Benefits Of Adoption Of It In Agricultural Practicesmentioning

confidence: 99%

Ecosystem for Successful Agriculture. Collaborative Approach as a Driver for Agricultural Development

Adamashvili

Fiore

Contò

et al. 2020

European Countryside

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“…Phenology models are beneficial tools for targeting the germplasm to specific environments. It decreases the risk of crop losses and decisions making about the timing of fungicides (Coffi and Rossi, 2018), pesticides (Zaza et al, 2018), and fertilizers (Arora et al, 2007). Herndl (2008) stated that estimating the times of development has the importance to accurately model the morphogenesis and yield components in wheat.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of open-pollinated offspring in Cyclamen persicum using vegetative phenology models in a primitive breeding population

Shafiei-Masouleh

Moghaddam

2021

Ornam. Hortic.

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Cyclamen is commercially cultivated to produce the pot and garden flowering plants by sowing the seeds, and the number of leaves is an important trait for the beginning of the initiations of flower buds and flowering. The yield potential is affected by the life cycle of a plant and the plant breeders can have good decisions making with the prediction of plant phenology. In this study, a polynomial function was proposed for modeling behavior of cyclamen offspring during the vegetative growth. This modeling is based on information on environmental changes and plant morphology up to the flowering stage. For this purpose, 30 pots (individuals) from a 121-individual population, which were the same in the size, were considered for sampling of data. The data were recorded as time series that include temperature (°C), relative humidity (%), leaf width (mm) and number of leaves. The output of this model is the number of leaves and the recorded inputs are the time (growth cycle; days), temperature, relative humidity and leaf width. Using the Quantum-behaved Particle Swarm Optimization (QPSO) algorithm, the constant coefficients of the proposed function (linear model) was calculated to match the input and output values to each other. To illustrate the robustness and efficiency of model, the growth rates of all individuals were compared using this proposed model. The result of root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R 2 ) between the estimated and observed values for each individual showed that 63% of the tested open-pollinated (OP) population is marketable. Therefore, phenology model could be a good estimation of the vigor of the OP population for commercial production. It should be noted that in obtaining the model, only five individuals were used randomly as training data, and the obtained model was fitted to the others as test dataset without changing the coefficients. Furthermore, a Gaussian model of the whole dataset showed that the OP seeds of cyclamen could be utilized to produce the potted flowering cyclamen without any worry about non-uniformity of harvest for the market if the optimum temperature would be adjusted.

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“…This multifunctional role requires appropriate support in order to attain the planning and management of sustainable high-quality olive sustainable approaches (La Scalia et al, 2016;Russo et al, 2015;Caruso et al, 2014), (ii) pest management by webGIS application, DSS and olive fly modelling (Zaza et al, 2018;Doitsidis et al, 2017;Pontikakos et al, 2012). Many of these approaches are based on modelling; models applied to olive grove are typically classified as either empirical/statistical or dynamic.…”

Section: Introductionmentioning

confidence: 99%

“…multiple regressions), are generally intuitive and well accepted. They include those based on climate data (Zaza et al, 2018;Iglesias et al, 2010), those based on remotely sensed indices (Blum et al, 2013(Blum et al, , 2015 and those based on multicriteria analysis (Carmona-Torres et al, 2014). Although highly used, these models have various weak points, such as the high degree of calibration required (when applied to a new environment) and -most importantly -the fact that they do not address the non-linear relationships between factors involved in the cultivation systems (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, it is important to stress that the majority of these olive grove models when integrated into operational DSSs architectures, refer to the only pest control (Zaza et al, 2018;Doitsidis et al, 2017;Pontikakos et al, 2012), operate at farm level and are marketed as commercial services. Moreover, while fully recognizing the great importance of the described approaches, it is also important to highlight that these systems do not adapt easily to territorial complexity and its space-time variability.…”

Section: Introductionmentioning

confidence: 99%

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A geospatial decision support system to assist olive growing at the landscape scale

Manna

Bonfante

Colandrea³

et al. 2020

Computers and Electronics in Agriculture

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A new decision-support system for the historical analysis of integrated pest management activities on olive crops based on climatic data

Cited by 15 publications

References 44 publications

Ecosystem for Successful Agriculture. Collaborative Approach as a Driver for Agricultural Development

Ecosystem for Successful Agriculture. Collaborative Approach as a Driver for Agricultural Development

Evaluation of open-pollinated offspring in Cyclamen persicum using vegetative phenology models in a primitive breeding population

A geospatial decision support system to assist olive growing at the landscape scale

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