Spatial decision support system for Medfly control in citrus

Cohen, Yafit; Cohen, Alon; Hetzroni, Amots; Alchanatis, V.; Broday, David M.; Gazit, Yoav; Timar, D.

doi:10.1016/j.compag.2007.12.005

Cited by 43 publications

(29 citation statements)

References 41 publications

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“…The contour maps successfully highlighted the spatio-temporal dynamics that developed during the season, the presence of C. capitata inside and outside orchards, and the role of cultivated host plants and landscape elements in the spatial distribution of adults. Spatial decision support systems and maps are important tools in an Integrated Pest Management programme that uses semiochemicals for the monitoring of fruit pest populations (Sciarretta et al 2001;Nestel et al 2004;Trematerra et al 2004;Israely et al 2005b;Sciarretta and Trematerra 2006;Batllori et al 2008;Cohen et al 2008).…”

Section: Discussionmentioning

confidence: 99%

Spatio-temporal distribution of Ceratitis capitata population in a heterogeneous landscape in Central Italy

Sciarretta

Trematerra

2011

Journal of Applied Entomology

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The spatio‐temporal dynamics of the Mediterranean fruit fly, Ceratitis capitata (Wiedemann), was investigated to evaluate the effect of the landscape elements and host plants on pest distribution, in an agricultural landscape of 500 ha located in Central Italy. Two farms (farm 1 and farm 2) are located in the experimental area, composing mixed fruit orchards and surrounded by hedgerows, small woodlots, private gardens and cereal fields. Ceratitis capitata population fluctuation was monitored, from 2006 to 2008, using traps baited with trimedlure. Geostatistical methods such as Inverse distance squared weighted were used to obtain distributional maps of adults, mainly males. Results showed that the adult Mediterranean fruit flies were primarily distributed inside farm 1, with the maximum density found in the months of September and October. Away from the principal host plants, particularly in cereal fields, the number of trapped individuals was always low or zero. In both farms, flies were caught sequentially in traps located on host plants (i.e. peach, apple, pear, oriental persimmon and prickly pear) at varying times of maturation, especially when fruits remained on the trees. Distributional maps provided evidence that allowed to identify habitats in which the fly developed early in the season (mixed peach orchards) and afterwards during the periodic flights.

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Section: Discussionmentioning

confidence: 99%

Spatio-temporal distribution of Ceratitis capitata population in a heterogeneous landscape in Central Italy

Sciarretta

Trematerra

2011

Journal of Applied Entomology

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“…In that context, precision and accuracy proved insufficient, requiring the development of spatial management features (Thorp et al, 2008;Cohen et al, 2008;Cardín-Pedrosa and Alvarez-López, 2012). The advent of PA information technologies and electronic communication along with the development of more accurate Global Positioning Systems (GPS) at reasonable costs have enabled farmers to acquire large amounts of data to be used effectively in site-specific crop management (Stafford, 2000;Tozer, 2009).…”

Section: Fmis For Precision Agriculturementioning

confidence: 99%

“…They are very often based on probabilistic methods (Kamran and DePuy, 2011), including methodologies such as linear programming (Sante-Riveira et al, 2008), dynamic programming (Parsons et al, 2009), rule-based management (Shaffer and Brodahl, 1998), decision trees (Cohen et al, 2008), eExpert heuristics (Trépos et al, 2012), fuzzy optimization (Papadopoulos et al, 2011), generic algorithms (Hameed et al, 2012), and smart elements (Lilburne et al, 1998) to model, solve, and generate optimal strategies.…”

Section: Reportingmentioning

confidence: 99%

Farm management information systems: Current situation and future perspectives

Fountas

Carli

Sørensen

et al. 2015

Computers and Electronics in Agriculture

282

122

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a b s t r a c tFarm Management Information Systems (FMIS) in agriculture have evolved from simple farm recordkeeping into sophisticated and complex systems to support production management. The purpose of current FMIS is to meet the increased demands to reduce production costs, comply with agricultural standards, and maintain high product quality and safety. This paper presents current advancements in the functionality of academic and commercial FMIS. The study focuses on open-field crop production and centeres on farm managers as the primary users and decision makers. Core system architectures and application domains, adoption and profitability, and FMIS solutions for precision agriculture as the most information-intensive application area were analyzed. Our review of commercial solutions involved the analysis of 141 international software packages, categorized into 11 functions. Cluster analysis was used to group current commercial FMIS as well as examine possible avenues for further development. Academic FMIS involved more sophisticated systems covering compliance to standards applications, automated data capture as well as interoperability between different software packages. Conversely, commercial FMIS applications targeted everyday farm office tasks related to budgeting and finance, such as recordkeeping, machinery management, and documentation, with emerging trends showing new functions related to traceability, quality assurance and sales.

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“…Most often, the decision will be to use non-area-wide methods, such as bait sprays or attract and kill tools (mass trapping or bait stations). Steps have been initiated in the Middle East and Europe (Pontikakos et al 2010;Cohen et al 2008) to integrate spatial elements into expert systems (a computer system that emulates the decisionmaking ability of a human expert). Individual producers often focus on preventing losses to their crops, without paying attention to the fly population in the region at large or the effect of future host availability (i.e., other crops surrounding the crop area, abundant enough to sustain a fruit fly population, but at that moment are not yet sufficiently mature to be infested).…”

Section: Future Directionsmentioning

confidence: 99%