Sensors 2015, 15(9), 21204-21218; https://doi.org/10.3390/s150921204
vitisFlower®: Development and Testing of a Novel Android-Smartphone Application for Assessing the Number of Grapevine Flowers per Inflorescence Using Artificial Vision Techniques
Instituto de Ciencias de la Vid y del Vino (University of La Rioja, CSIC, Gobierno de La Rioja), 26006 Logroño, Spain
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Author to whom correspondence should be addressed.
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These authors contributed equally to this work.
Academic Editor: Vittorio M. N. Passaro
Received: 1 July 2015 / Revised: 14 August 2015 / Accepted: 24 August 2015 / Published: 28 August 2015
(This article belongs to the Section Remote Sensors)
Abstract
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. View Full-TextKeywords:
Android application; OpenCV4Android; OpenCV library; image analysis; grapevine flower counting; yield prediction; Vitis vinifera L.; precision viticulture; precision agriculture
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Aquino, A.; Millan, B.; Gaston, D.; Diago, M.-P.; Tardaguila, J. vitisFlower®: Development and Testing of a Novel Android-Smartphone Application for Assessing the Number of Grapevine Flowers per Inflorescence Using Artificial Vision Techniques. Sensors 2015, 15, 21204-21218.