vitisFlower®: Development and testing of a novel android-smartphone application for assessing the number of grapevine flowers per inflorescence using artificial vision techniques

Grapevine flowering and fruit set greatly determine crop yield. This paper presents a new smartphone application for automatically counting, non-invasively and directly in the vineyard, the flower number in grapevine inflorescence photos by implementing artificial vision techniques. The application,...

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Detalles Bibliográficos
Autores: Aquino, A. [0000-0003-4054-4232], Millan, B. [0000-0001-9313-5104], Gaston, D., Diago, M.-P. [0000-0003-4049-0879], Tardaguila, J. [0000-0002-6639-8723]
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Institución:Universidad de La Rioja (UR)
Repositorio:RIUR. Repositorio Institucional de la Universidad de La Rioja
OAI Identifier:oai:portal.dialnet.es:doc/5bbc6813b750603269e80201
Acceso en línea:https://investigacion.unirioja.es/documentos/5bbc6813b750603269e80201
Access Level:acceso abierto
Palabra clave:Android application
Grapevine flower counting
Image analysis
OpenCV library
OpenCV4Android
Precision agriculture
Precision viticulture
Vitis vinifera L
Yield prediction
Descripción
Sumario:Grapevine flowering and fruit set greatly determine crop yield. This paper presents a new smartphone application for automatically counting, non-invasively and directly in the vineyard, the flower number in grapevine inflorescence photos by implementing artificial vision techniques. The application, called vitisFlower®, firstly guides the user to appropriately take an inflorescence photo using the smartphone’s camera. Then, by means of image analysis, the flowers in the image are detected and counted. vitisFlower® has been developed for Android devices and uses the OpenCV libraries to maximize computational efficiency. The application was tested on 140 inflorescence images of 11 grapevine varieties taken with two different devices. On average, more than 84% of flowers in the captures were found, with a precision exceeding 94%. Additionally, the application’s efficiency on four different devices covering a wide range of the market’s spectrum was also studied. The results of this benchmarking study showed significant differences among devices, although indicating that the application is efficiently usable even with low-range devices. vitisFlower is one of the first applications for viticulture that is currently freely available on Google Play. © 2015 by the authors; licensee MDPI, Basel, Switzerland.