Comunicacions a congressos (Ciència i Enginyeria Forestal i Agrícola)
Permanent URI for this collection
Browse
Recent Submissions
- ItemOpen AccessEfecto del sistema de laboreo y el tipo de fertilización sobre la sobre la volatilitzación de NH3 en secanos demiáridos del Valle del Ebro(CSIC; Universitat de Lleida; CITA; IAMZ, 2013) Ovejero, J.; Lampurlanés Castel, Jorge; Cantero-Martínez, Carlos; Plaza Bonilla, Daniel; Álvaro Fuentes, J.
- ItemOpen AccessA consensus map for quality traits in durum wheat based on genome-wide association studies and detection of ortho-meta QTL across cereal species(Frontiers, 2022) Marcotuli, Ilaria; Soriano Soriano, José Miguel; Gadaleta, AgataThe present work focused on the identification of durum wheat QTL hotspots from a collection of genome-wide association studies, for quality traits, such as grain protein content and composition, yellow color, fiber, grain microelement content (iron, magnesium, potassium, selenium, sulfur, calcium, cadmium), kernel vitreousness, semolina, and dough quality test. For the first time a total of 10 GWAS studies, comprising 395 marker-trait associations (MTA) on 57 quality traits, with more than 1,500 genotypes from 9 association panels, were used to investigate consensus QTL hotspots representative of a wide durum wheat genetic variation. MTA were found distributed on all the A and B genomes chromosomes with minimum number of MTA observed on chromosome 5B (15) and a maximum of 45 on chromosome 7A, with an average of 28 MTA per chromosome. The MTA were equally distributed on A (48%) and B (52%) genomes and allowed the identification of 94 QTL hotspots. Synteny maps for QTL were also performed in Zea mays, Brachypodium, and Oryza sativa, and candidate gene identification allowed the association of genes involved in biological processes playing a major role in the control of quality traits.
- ItemOpen AccessAnálisis de los efectos de la sequía en manzanos a través del índice Leafiness-LiDAR(Sociedad Española de Ciencias Hortícolas (SECH), 2024) Sandonís Pozo, Leire; Martínez Casasnovas, José Antonio; Pascual Roca, MiquelLa sequía es un factor ambiental significativo que puede afectar de manera considerable el desarrollo y la productividad los cultivos frutícolas. En manzanos (Malus sylvestris L.Mill.), diversos autores han demostrado que la productividad y la calidad de los frutos está directamente relacionada con la cantidad de radiación solar absorbida por las copas. La gestión adecuada del dosel foliar durante períodos de sequía es esencial para minimizar sus consecuencias sobre la productividad de los manzanos. En este sentido, los sensores LiDAR (Light Detection And Ranging), utilizados en Fruticultura de Precisión para la caracterización 3D de la vegetación, pueden aportar la información necesaria para cuantificar las características geométricas y estructurales del dosel foliar de las plantaciones. Concretamente, en el presente trabajo se ha utilizado el índice Leafiness-LiDAR Index (LLI) medido en una plantación comercial intensiva de manzanos (Malus sylvestris L.Mill.) cv UEB 3264/2 Opal®, en la que se diseñó un experimento con diferentes dosis regadío a fin de simular las condiciones de sequía (desde condiciones deficitarias en diferentes períodos hasta riego completo). Los resultados obtenidos del análisis LiDAR permiten estimar adecuadamente el índice de área foliar (LAI) de los árboles, pudiendo relacionar estos indicadores con diversos e importantes atributos cuantitativos: crecimiento vegetativo, frondosidad del seto y rendimiento.
- ItemOpen AccessVT9: Gestión multifuncional en bosques de pino laricio (Solsona)(Colegio Oficial de Ingenieros Técnicos Forestales, 2022) Coll Mir, Lluís; Cervera, Teresa; Piqué i Nicolau, Míriam; Larrañaga, Asier; Améztegui González, Aitor; Baiges Zapater, Teresa; Guixé, DavidEl pino laricio (Pinus nigra subsp. salzmannii) es la especie que domina los bosques submediterráneos del NE de la península ibérica, ocupando en Cataluña unas 140.000 ha (el 12 % de la superficie forestal), de las cuales 65.000 ha son masas mixtas. La mayor parte de estos bosques se localizan en los Prepirineos (Cataluña Central) en fincas forestales de propiedad privada.
- ItemOpen AccessVideo-Based Fruit Detection and Tracking for Apple Counting and Mapping(IEEE, 2023) Gené Mola, Jordi; Felip Pomés, Marc; Net-Barnés, Francesc; Morros Rubió, Josep Ramon; Miranda, Juan Carlos; Arnó Satorra, Jaume; Asin Jones, Luis; Lordan Sanahuja, Jaume; Ruiz-Hidalgo, Javier; Gregorio López, EduardAutomatic fruit counting systems have garnered interest from farmers and agronomists to monitor fruit production, predict yields in advance, and identify production variability across orchards. However, accurately counting fruits poses challenges, particularly due to occlusions. This study proposes a multi-view sensing approach using continuous motion videos captured by a camera moved along the row of trees, followed by fruit detection in all video frames and application of Multi-Object Tracking (MOT) algorithms to prevent double-counting. Three tracking methods, namely SORT, DeepSORT, and ByteTrack, are compared for fruit counting using the YOLOv5x object detector. The methodology is applied to map fruit production in an experimental apple orchard at two different dates: four weeks and one week before harvest. The results demonstrate that ByteTrack (MOTA=0.682; IDF1=0.837; HOTA=0.689) outperforms SORT and DeepSORT, indicating its superior tracking performance. Computational efficiency analysis reveals similar processing times between SORT and ByteTrack (about 15 ms), while DeepSORT requires significantly more processing time per image (128 ms). Fruit counting evaluation shows reasonably accurate yield predictions on both dates, with reduced errors and improved performance closer to the harvest date (MAPE=7.47 %; R2=0.70). The system proves effective in estimating orchard fruit production using computer vision technology, offering valuable insights for yield forecasting. These findings contribute to optimizing fruit production and supporting precision agriculture practices. The code and the dataset have been made publicly available and a video visualization of results is accessible at http://www.grap.udl.cat/en/publications/video_fruit_counting.