Resultados de investigación

Understanding the genetic basis of adaptation and plasticity in trees constitutes a knowledge gap. In this study we analysed 20-year tree-ring series of 130 trees, structured in 23 populations grown in a common garden experiment. We tested for genotype by environment interactions (G×E) of indexed ring width (RWI) and indexed early to latewood ratios (ELI) using factorial regression analyses, that describes G×E as differential gene sensitivity to climate. The data include raw tree-ring series, indexed ring-width and early to latewood ratio series, 20 SNPs, climate variables at site, populations sensitivity to particular climate factors, and climate at origin of populations.

The file contains experimental data obtained from pH meaurements and data from calculations of the DOM charge, representing the experimental points of Figure 3 in the article, according to the legend of the figure. It also contains pH measurements and the corresponding NICA model simulations used in the Figure 3 of the article (solid lines). These data allow to represent Figure 3 of the article and test other binding models.

Fruit detection and 3D location in photogrammetry-derived 3D point clouds. This project is a matlab implementation to project image detections (instance segmentation masks) onto 3D point clouds generated using structure-from-motion.

The agricultural LiDAR data to evaluate scan matching techniques (AgLiMatch dataset) is comprised of a set of Velodyne VLP-16 LiDAR captures and the corresponding GNSS-RTK tracks acquired in a Fuji apple orchard using an autonomous platform. This dataset was used in [1] to evaluate scan matching techniques by comparing the platform path calculated using LiDAR scan matching techniques and the actual platform path ground truth measured with a GNSS-RTK system. The correspondence between each LiDAR file (inside /velodyne_data folder) and GNSS track file (inside /GNSS_data folder) is detailed in “Velodyne-GNSS_correspondence-data.xlsx” file. The relative position between the LiDAR sensor and the GNSS rover is shown in “experimental_setup.png”. Distance units are in mm.

This project is a matlab implementation for fruit detection in 3D point clouds acquired with LiDAR sensor Velodyne VLP-16 (Velodyne LIDAR Inc., San Jose, CA, USA). This implementation was used to evaluate the LFuji-air dataset, which contains 3D LiDAR data of 11Fuji apple trees with the corresponding fruit position annotations.

Matlab implementation to evaluate RGB-D sensor performance in orchard environments. This project is a matlab implementation to evaluate RGB-D sensor performances by analysing RGB-D data acquired in different orchard conditions. The code follows the assessment methodology presented in [1], and it was used to evaluate the performance of Microsoft Kinect v2 by using the KEvOr dataset.

AKFruitData - AK_FRAEX: Tool for extracting frames from video files produced with Azure Kinect cameras. RGB-D camera, Data acquisition, Data extraction, Fruit yield trials, Precision fruticulture.https://doi.org/10.1016/j.softx.2022.101231. Python-based GUI tool to extract frames from video files produced with Azure Kinect cameras. Visit the project site at https://pypi.org/project/ak-frame-extractor/ and check the source code at https://github.com/GRAP-UdL-AT/ak_frame_extractor/

This project is a python implementation for fruit detection and tracking using YOLOv5 and ByteTrack. The project was build to be tested jointly with AMIGA robot for in-field fruit conting purposes. It was tested in the Farm@thon organized by Lleida Drone, where it was recognized with the first prize. The code was prepared to be used with a ZED camera, but it could be easily adapted for other cameras such as Oak-D.

Matlab implementation to generate 3D point clouds from data acquired with VLP-16 and GNSS GPS1200+. This project is a Matlab implementation to generate 3D point clouds from data acquired with a mobile terrestrial laser scanner (MTLS) comprised of a LiDAR sensor Velodyne VLP-16 (Velodyne LIDAR Inc., San Jose, CA, USA) and a GNSS position sensor GPS1200+ (Leica Geosystems AG, Heerbrugg, Swizeland). This implementation was used to generate the point clouds provided in LFuji-air dataset, which contains 3D LiDAR data of 11Fuji apple trees with the corresponding fruit position annotations.

Referencias completas y datos sintetizados en formato tabla de la revisión sistemática realizada sobre los estudios empíricos centrados en la violencia digital contra las mujeres.