Grup de Recerca en AgròTICa i Agricultura de Precisió
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El Grup de Recerca en AgròTICa i Agricultura de Precisió (GRAP) és un dels grups de referència en Tecnologies per a l'Aplicació de Productes Fitosanitaris a nivell de tot l'Estat Espanyol, amb diverses patents i models d'utilitat en aquest àmbit. El grup també és pioner en el disseny d'equips robotitzats i intel·ligents per a la Ramaderia de Precisió, amb una de les primeres patents en aquest àmbit i diversos equips instal·lats a França i a Canadà. A principis de 2014, el grup s'integra al centre de recerca Agrotecnio. [Més informació].
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Assessing the Performance of RGB-D Sensors for 3D Fruit Crop Canopy Characterization under Different Operating and Lighting Conditions
(MDPI, 2020-12-10)The use of 3D sensors combined with appropriate data processing and analysis has provided tools to optimise agricultural management through the application of precision agriculture. The recent development of low-cost ... -
Spatially variable pesticide application in vineyards: Part I, developing a geostatistical approach
(ElsevierAcademic Press, 2020-05-18)A geostatistical methodology is presented to optimise the dosage of plant protection products (PPP) in vineyards with spatial variability. Sprayers are commonly used in viticulture to apply a constant volume rate per unit ... -
Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry
(Elsevier, 2020)The present dataset contains colour images acquired in a commercial Fuji apple orchard (Malus domestica Borkh. cv. Fuji) to reconstruct the 3D model of 11 trees by using structure-from-motion (SfM) photogrammetry. The data ... -
Analyzing and overcoming the effects of GNSS error on LiDAR based orchard parameters estimation
(Elsevier, 2020)Currently, 3D point clouds are obtained via LiDAR (Light Detection and Ranging) sensors to compute vegetation parameters to enhance agricultural operations. However, such a point cloud is intrinsically dependent on the ... -
LFuji-air dataset: annotated 3D LiDAR point clouds of Fuji apple trees for fruit detection scanned under different forced air flow conditions
(Elsevier, 2020)This article presents the LFuji-air dataset, which contains LiDAR based point clouds of 11 Fuji apples trees and the corresponding apples location ground truth. A mobile terrestrial laser scanner (MTLS) comprised of a LiDAR ... -
Determination of spray drift and buffer zones in 3D crops using the ISO standard and new LiDAR methodologies
(Elsevier, 2020-01-15)Spray drift generated in the application of plant protection products in tree crops (3D crops) is a major source of environmental contamination, with repercussions for human health and the environment. Spray drift contamination ... -
Fruit detection, yield prediction and canopy geometric characterization using LiDAR with forced air flow
(Elsevier, 2019-11-29)Yield monitoring and geometric characterization of crops provide information about orchard variability and vigor, enabling the farmer to make faster and better decisions in tasks such as irrigation, fertilization, pruning, ... -
Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry
(Elsevier, 2020-01-02)The development of remote fruit detection systems able to identify and 3D locate fruits provides opportunities to improve the efficiency of agriculture management. Most of the current fruit detection systems are based on ... -
Special issue on 'Terrestrial laser scanning': editors' notes
(MDPI, 2019-10-21)In this editorial, we provide an overview of the content of the special issue on 'Terrestrial Laser Scanning'. The aim of this Special Issue is to bring together innovative developments and applications of terrestrial laser ... -
Fruit detection in an apple orchard using a mobile terrestrial laser scanner
(Academic Press. Published by Elsevier, 2019-09-21)The development of reliable fruit detection and localization systems provides an opportunity to improve the crop value and management by limiting fruit spoilage and optimised harvesting practices. Most proposed systems for ... -
Assessment of spray drift potential reduction for hollow-cone nozzles: Part 1. Classification using indirect methods
(Elsevier B.V., 2019-06-10)Spray drift is one of the main pollution sources identified when pesticides are sprayed on crops. In this work, in order to simplify the evaluation of hollow-cone nozzles according to their drift potential reduction, several ... -
Assessing ranked set sampling and ancillary data to improve fruit load estimates in peach orchards
(Elsevier, 2019-08-08)Fruit load estimation at plot level before harvest is a key issue in fruit growing. To face this challenge, two sampling methods to estimate fruit load in a peach tree orchard were compared: simple random sampling (SRS) ... -
Variable rate dosing in precision viticulture: Use of electronic devices to improve application efficiency
(Elsevier, 2010-03)Two different spray application methods were compared in three vine varieties at different crop stages. A conventional spray application with a constant volume rate per unit ground area (1 ha(-1)) was compared with a ... -
Spatial variability in commercial orange groves. Part 2: relating canopy geometry to soil attributes and historical yield
(Springer, 2018-10-16)Site-specific management strategies are usually dependant on the understanding of the underlying cause and effect relationships that occur at the within-field level. The assessment of canopy geometry of tree crops has been ... -
Spatial variability in commercial orange groves. Part 1: canopy volume and height
(Springer, 2018-09-22)Characterizing crop spatial variability is crucial for estimating the opportunities for site-specific management practices. In the context of tree crops, ranging sensor technology has been developed to assess tree canopy ... -
KFuji RGB-DS database: Fuji apple multi-modal images for fruit detection with color, depth and range-corrected IR data
(Elsevier Inc., 2019)This article contains data related to the research article entitle 'Multi-modal Deep Learning for Fruit Detection Using RGB-D Cameras and their Radiometric Capabilities' [1]. The development of reliable fruit detection and ... -
Assessment of spray drift potential reduction for hollow-cone nozzles: Part 2. LiDAR technique
(Elsevier B.V., 2019-06-11)Pesticide spray drift poses health hazards to humans and causes a significant impact on the environment. In this work the capacity of an ad hoc light detection and ranging (LiDAR) system to differentiate spray nozzles ... -
Multi-modal deep learning for Fuji apple detection using RGB-D cameras and their radiometric capabilities
(Elsevier, 2019-05-10)Fruit detection and localization will be essential for future agronomic management of fruit crops, with applications in yield prediction, yield mapping and automated harvesting. RGB-D cameras are promising sensors for fruit ... -
Stratified sampling in fruit orchards using cluster-based ancillary information maps: a comparative analysis to improve yield and quality estimates
(Springer, 2019-03-25)Estimation of yield or other fruit quality parameter is of great interest to farmers to decide on management actions just before harvesting and, in any case, to anticipate and plan harvesting operations. Making accurate ... -
Application of light detection and ranging and ultrasonic sensors to high-throughput phenotyping and precision horticulture: current status and challenges
(Springer Nature, 2018)Ultrasonic and light detection and ranging (LiDAR) sensors have been some of the most deeply investigated sensing technologies within the scope of digital horticulture. They can accurately estimate geometrical and structural ...