Digital platform for experimental and technical support to the cultivation of cactus pear

Vista sencilla de ítem
dc.creatorBruno Vinícius Castro Guimarães
dc.creatorSérgio Luiz Rodrigues Donato
dc.creatorIgnacio Aspiazú
dc.creatorAlcinei Mistico Azevedo
dc.creatorFábio dos Santos Lima
dc.creatorSamuel Victor Medeiros de Macêdo
dc.creatorCleiton Fernando Barbosa Brito
dc.creatorHiago Fagundes Couto
dc.date2023
dc.date.accessioned2026-07-07T03:52:02Z
dc.descriptionAmong the forage species, especially in semiarid ecosystems, cactus pear is exceptional because of its high tolerance to adverse conditions and high productivity. Due to this alone, several studies have been conducted to identify the main technologies for this crop. Despite being consolidated and integrated, the cactus pear production system has limited accessibility, technical assistance, and availability of information for those dedicated to its production. This study aimed to present a digital platform, website, and applications to provide technical information on the cactus pear and demonstrate the efficiency of these applications through experimental data. On this digital platform, applications were made available for predicting the productivity of cactus pear using artificial neural networks (ANN) on a computer with routines in the R software and by simple linear regression (SLR) on smartphones on the Android system of the MIT App Inventor 2 platform. In addition, using the smartphone app, it is possible to obtain the cladode area through multiple linear regression (MLR). It is also possible to obtain the estimates of the experimental plot sizes by the maximum modified curvature, linear and quadratic methods with plateau response, relative information, comparison of variances, and convenient plot size. The platform provides technical information associated with the cactus pear crop from different sources (dissertations, theses, articles) and formats (video classes and teaching resources), offline for applications, and online with download for publications, dissertations, theses and articles, video classes, and several didactic resources. The biomathematical models integrated with the applications were highly precise in predicting the phenomena, in which the variation explained by the models in the prediction of responses for future observations had R² values of 0.95, 0.72, and 0.92, respectively, for productivity with computer-ANN and smartphone-SLR, and for the cladode area with a smartphone - MLR.
dc.formatapplication/pdf
dc.identifier1679-9275
dc.identifierhttps://www.redalyc.org/articulo.oa?id=303075473024
dc.identifierhttps://www.redalyc.org/journal/3030/303075473024/
dc.identifierhttps://www.redalyc.org/journal/3030/303075473024/html/
dc.identifierhttps://www.redalyc.org/journal/3030/303075473024/303075473024.epub
dc.identifierhttps://www.redalyc.org/journal/3030/303075473024/movil
dc.identifier10.4025/actasciagron.v45i1.57407
dc.identifier.urihttp://hdl.handle.net/123456789/445384
dc.languageen
dc.publisherUniversidade Estadual de Maringá
dc.relationhttp://www.redalyc.org/revista.oa?id=3030
dc.rightsActa Scientiarum. Agronomy
dc.sourceActa Scientiarum. Agronomy (Brasil) Vol.45
dc.subjectAgrociencias
dc.titleDigital platform for experimental and technical support to the cultivation of cactus pear
dc.typeartículo científico

Archivos

Colecciones

Acta Scientiarum. Agronomy - Universidade Estadual de Maringá