Associate Professor
Department of Viticulture and Oenology, Faculty of AgriSciences, Stellenbosch University, South Africa.
Coordinator of the Digital Agriculture Research Group, South African Grape and Wine Research Institute (SAGWRI), Stellenbosch University, South Africa.
e-mail: cpe@sun.ac.za

Profesor Asociado en Agricultura Digital y Gestión del Agua de la Facultad de Ciencias Agrarias de la Universidad de Stellenbosch (Sudáfrica). Coordinador del Grupo de Investigación en Agricultura Digital en el Instituto Sudafricano de Investigación (SAGWRI). Su trabajo se centra en la integración de nuevas tecnologías y agricultura digital para mejorar la sostenibilidad de los cultivos agrícolas y su resiliencia frente al cambio climático. Sus líneas de investigación incluyen el desarrollo y aplicación de Inteligencia Artificial (IA) y herramientas computacionales para optimizar prácticas agrícolas; el uso de tecnologías de teledetección y sensores proximales (termografía, robótica y drones); y la estimación de requerimientos hídricos mediante sensores avanzados y modelos. Su trabajo académico conecta la investigación de vanguardia con soluciones prácticas para enfrentar los desafíos de la agricultura moderna.

Poblete-Echeverría, C., Hernández, I., Iñiguez, R., Gutiérrez, S., Barrio, I., Y Tardáguila, J. (2025). Using artificial intelligence for automatic and fast detection of downy mildew symptoms in grapevine canopies. European Journal of Agronomy, 170, 127755. https://doi.org/10.1016/j.eja.2025.127755

Íñiguez, R., Wolela, F., Gonzalez Pavez, M. I., Barrio, I., Tardáguila, J., Venter, T., Y Poblete-Echeverria, C.(2025). Artificial intelligence-driven classification method of grapevine major phenological stages using conventional RGB imaging: This article is part of the special issue of the GiESCO 2025 meeting. OENO One, 59(2).https://doi.org/10.20870/oeno-one.2025.59.2.9306

Poblete-Echeverria, C., Berry, A., Venter, T., Velez, S., González Pavez, M. I., Y Iñiguez, R. (2025). Morphological image analysis for estimating grape bunch weight under different irrigation regimes in Cabernet-Sauvignon: This article is part of the special issue of the GiESCO 2025 meeting. OENO One, 59(2). https://doi.org/10.20870/oeno-one.2025.59.2.9309

González-Pavez, M.I., Ortega-Farias, S., Poblete-Echeverria, C., Gamboa, M.J., Y Vargas, S. (2025). Application of spectral index-based contour mapping for non-destructive ripeness monitoring in water stressed Vitis vinifera L. (Cabernet-Sauvignon): This article is part of the special issue of the GiESCO 2025 meeting. OENO One, 59(2). https://doi.org/10.20870/oeno-one.2025.59.2.9308

Berry, A., Vivier, M.A. Y Poblete-Echeverria, C.* (2025). Evaluation of canopy fraction-based vegetation indices, derived from multispectral UAV imagery, to map water status variability in a commercial vineyard. Irrigation Science. 43, 135–153. https://doi.org/10.1007/s00271-023-00907-1

Towers, P., Roulet, S., Poblete-Echeverria, C.* (2025). Vine yield estimation from block to regional scale employing remote sensing, weather, and management data. Information Processing in Agriculture, 12, 2, 195-208. https://doi.org/10.1016/j.inpa.2024.06.001.

Duncan S., McLeod A., Poblete-Echeverria, C*. (2024). Application of UAV and satellite technologies for assessing phytophthora root rot severity in avocado orchards. Frontiers in Agronomy (6). https://doi=10.3389/fagro.2024.1419479

Herrera-Poyato, D., Domínguez-Rull, J., Montes, R., Hernández, I., Barrio, I., Poblete-Echeverria, C., Tardáguila, J., Herrera-Poyatos, A. (2024). Small data deep learning methodology for in-field disease detection. arXiv eprint = 2409.17119.https://arxiv.org/abs/2409.17119

Íñiguez, R., Gutiérrez, S., Poblete-Echeverria, C., Hernández, I., Barrio, I., Tardáguila, J. (2024). Deep learning modelling for non-invasive grape bunch detection under diverse occlusion conditions. Computers and Electronics in Agriculture, Elsevier. Volume 226, 109421, ISSN 0168-1699,https://doi.org/10.1016/j.compag.2024.109421.

Luus, J., Els, D.N.J. and Poblete-Echeverría, C*. (2024). Automatic thermal image filtering for determining representative canopy temperatures in vineyards. Acta Hortic. 1390, 285-292. https://doi.org/10.17660/ActaHortic.2024.1390.35.

Palazzo, L. R., Acosta, G. L., Gil Montenegro, P., Mulidzi, A. R., Pizzolon, N., Zamorano Meriño, D., Poblete-Echeverría, C., Pastenes, C., Venter, T., Perez Peña, J. (2024). Towards a More Sustainable Viticulture: Integration of Solar Photovoltaic Projects in Vineyards of Argentina, Chile, and South Africa. AgriVoltaics Conference Proceedings, 1. https://doi.org/10.52825/agripv.v1i.612.

Poblete-Echeverría, C., Hernández, I., Gutiérrez, S., Íñiguez, R.; Barrio, I., Tardáguila, J. (2023). Using artificial intelligence (AI) for grapevine disease detection based on images. BIO Web Conf., Vol. 68, DOI: https://doi.org/10.1051/bioconf/20236801021.

Íñiguez, R., Poblete-Echeverría, C., Hernández, I., Gutiérrez, S., Barrio, I., Tardáguila, J. (2023). Artificial intelligence and computer vision to assess grape yield components in commercial vineyards. BIO Web Conf., Vol.68 – 01023 doi: https://doi.org/10.1051/bioconf/20236801023.

Poblete-Echeverría, C., Berry, A., Luus, J., Vivier M.A. (2023). Use of VIS-NIR data for characterizing grapevine canopies: remote and proximal sensing approaches at individual vine scale. Acta Hortic. 1360, 339-345. https://doi.org/10.17660/ActaHortic.2023.1360.41.

Poblete-Echeverría, C., Duncan, S.J., McLeod A. (2023). Detection of the spectral signature of Phytophthora root rot (PRR) symptoms using hyperspectral imaging. Acta Hortic. 1360, 77-84. https://doi.org/10.17660/ActaHortic.2023.1360.10.

von Dürckheim, K.E.M., Hoffman, L.C., Poblete-Echeverría, C., Bishop, J.M., Goodwin, T.E., Schulte, B.A., Leslie, A. (2022). A pachyderm perfume: odour encodes identity and group membership in African elephants. Sci Rep 12, 16768. https://doi.org/10.1038/s41598-022-20920-2.

Luus, J., Els, D., Poblete-Echeverría, C. (2022). A case study on grapevines. Automating reference temperature measurements for crop water stress index calculations: A case study on grapevines. Computers and Electronics in Agriculture, Vol. 202, 107329. ISSN 0168-1699. https://doi.org/10.1016/j.compag.2022.107329.

López-Olivari, R., Fuentes, S., Poblete-Echeverría, C., Quintulen-Ancapi, V., and Medina, L. (2022). Site-specific evaluation of canopy resistance models for estimating evapotranspiration over a drip-irrigated potato crop in southern Chile under water-limited conditions. Water. 14(13):2041. https://doi.org/10.3390/w14132041.

Victorino, G., Poblete-Echeverría, C. and Lopes, C.M. (2022). A multicultivar approach for grape bunch weight estimation using image analysis. Horticulturae. 8(3), 233. https://doi.org/10.3390/horticulturae8030233

Daniels, A., Poblete-Echeverría, C., Nieuwoudt, H. H., Botha, N., Opara, U. L. (2021). Classification of Browning on Intact Table Grape Bunches Using Near-Infrared Spectroscopy Coupled with Partial Least Squares-Discriminant Analysis and Artificial Neural Networks. Frontiers in Plant Science. Volume 12 – 2021.

Towers, P., Poblete-Echeverría, C. (2021). Effect of the Illumination Angle on NDVI data composed of mixed surface values obtained over Vertical-Shoot-Positioned Vineyards. Remote Sensing, Vol.13(5), 855; https://doi.org/10.3390/rs13050855.

Jasse, A., Berry, A., Aleixandre-Tudo, J.L., Poblete-Echeverría, C. (2021). Intra-block spatial and temporal variability of plant water status and its effect on grape and wine parameters. Agricultural and Water Management, Vol. 246. 106696, ISSN 0378-3774, https://doi.org/10.1016/j.agwat.2020.106696.

Velez, S., Poblete-Echeverría, C., Rubio, J.A., Vacas, R., Barajas, E. (2021). Estimation of Leaf Area Index in vineyards by analysing projected shadows using UAV imagery. OenoOne, 55(4), 159–180. https://doi.org/10.20870/oeno-one.2021.55.4.4639.

Hacking, C., Poona, N., Poblete-Echeverria, C. (2020). Vineyard yield estimation using 2-D proximal sensing: a multitemporal approach. OenoOne, 54(4), 793–812. https://doi.org/10.20870/oeno-one.2020.54.4.3361.

Poblete-Echeverría, C., Daniels, A.J., Nieuwoudt, H.H. and Opara, U.L. (2020). Artificial neural network as alternative method for prediction of sugar and acidity using near-infrared spectroscopy in table grapes. Acta Hortic. 1292, 321-328. https://doi:10.17660/ActaHortic.2020.1292.42.

Poblete-Echeverría, C., Strever, A.E., Barnard, Y. and Vivier, M.A. (2020). Proximal detection using robotics for vineyard monitoring: a concept. Acta Hortic. 1279, 231-238. https://doi.org/10.17660/ActaHortic.2020.1279.34.

Daniels, A.J., Opara, U.L., Poblete-Echeverría, C. and Nieuwoudt, H.H. (2020). New technologies to maintain quality and reduce postharvest losses of table grapes. Acta Hortic. 1275, 113-120. https://doi.org/10.17660/ActaHortic.2020.1275.16.

Morán, A., Ferreyra, R., Sellés, G., Salgado, E., Cáceres-Mella, A., Poblete-Echeverría, C. (2020). Calibration of the Surface Renewal Method (SR) under Different Meteorological Conditions in an Avocado Orchard. Agronomy,10(5): 730. https://doi.org/10.3390/agronomy10050730.

Rebel, P., Poblete-Echeverría, C., van Zyl, J.G., Wessels, J.P.B., Coetzer, C., McLeod, A. (2020). Determining Mancozeb Deposition Benchmark Values on Apple Leaves for the Management of Venturia inaequalis. Plant Disease, 104(1):168-178. https://doi.org/10.1094/PDIS-04-19-0873-RE.

Vélez, S., Barajas, E., Rubio, J.A., Vacas, R., Poblete-Echeverría, C. (2020). Effect of Missing Vines on Total Leaf Area Determined by NDVI Calculated from Sentinel Satellite Data: Progressive Vine Removal Experiments. Applied Sciences, 10(10):3612. https://doi.org/10.3390/app10103612.

Low-cost Smart Irrigation System for Monitoring and Managing Water Usage in Vineyards. WATER RESEARCH COMMISSION. Number: 2025/2026-01829. (Principal Researcher).

Establishment of the technical and scientific bases for AI applications in wine production. Study case on viticulture, yield and phenology AI models. South African WINE. Contract Number S009918. (Principal Researcher).

Economic impact of stem cankers and dieback on pome and stone fruit orchards. HORTGRO. NP19-2024. (Researcher).

Smart Agritech programme. Telkom/Aizatron/Stellenbosh university. (Researcher).

Physical and chemical bunch characterization of table grapes using machine vision. SOUTH AFRICAN TABLE GRAPE INDUSTRY (SATI). (Principal Researcher).

Technical-commercial scaling of the sustainable SmartETo technology for irrigation monitoring that allows for increased water use efficiency and improved productivity. CORFO, CHILE. (Researcher).

Premiumisation and Value Growth of South African Chenin Blanc (CB) wines. CHENIN BLANC ASSOCIATION Y WINETECH. SAGWRI MAV24-01. (Researcher).

Winetech Water Programme Flagship 4. A model vineyard in pots to study grapevine/scion responses to water limitation. WINETECH. FSHIP WATER 4. NP14-2022. (Researcher).

Study of remote sensing techniques for mapping the severity of Phytophthora Root Rot (PRR) disease in Avocado orchards. SOUTH AFRICAN AVOCADO GROWERS' ASSOCIATION. SAAGA 06/22. (Principal Researcher).

Producing quality grapes with limited water. WATER RESEARCH COMMISSION. C2021/2022-00911. (Researcher).

Winetech Water Programme Flagship 3: Producing quality grapes with limited water. WINETECH. FSHIP WATER 3. NP11-2021. (Researcher).