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[EN] Ridolfia segetum (L.) Moris is a weed native to the Mediterranean basin that causes yield losses in both winter and summer crops in southern Spain. Modeling its emergence is crucial for developing appropriate management strategies. Currently, the predominant technique for predicting weed emergence is non-linear parametric regression, but this approach has some statistical limitations. The Weed Biology and Agroecology Group (BAMh) conducted a study to describe and predict the emergence pattern of R. segetum using a non-parametric regression with a Gaussian distribution. For its development, emergence was studied in five experimental plots in Barcelona, Lleida, Madrid, Seville, and Zaragoza during the 2016/17 season, and the trial was repeated in the following season in Barcelona, Madrid, and Zaragoza. In each plot, 100 seeds from an experimental farm in Seville were sown in 25 x 25 cm grids (4 replicates). For the model, a cumulative kernel density curve was used to relate emergence to a hydrothermal integral based on a two segment equation. A base, optimal, and maximum temperature of -1.0 ºC, 8.1 ºC, and 26.0 ºC, respectively, and a base water potential of -0.6 MPa were established. This model reaches 10 %, 50 %, and 90 % of cumulative emergence at 43.2, 74.7, and 97.4 hydrothermal degrees, respectively. On average, the model exhibited a root mean square error of 16.81%, ranging between 9.1 % and 32.5 %., [ES] Ridolfia segetum (L.) Moris es una mala hierba originaria de la cuenca mediterránea que causa pérdidas de rendimiento en cultivos de invierno y de verano en el sur de España. Modelizar su emergencia es crucial para desarrollar estrategias de manejo adecuadas. Actualmente, la técnica predominante para predecir la emergencia de malas hierbas son las regresiones paramétricas no lineales pero este enfoque tiene algunas limitaciones estadísticas. El grupo de Biología y Agroecología de las Malas Hierbas (BAMh) llevó a cabo un estudio para describir y predecir el patrón de emergencia de R. segetum mediante una regresión no paramétrica con una distribución gaussiana. Para su desarrollo, se estudió la emergencia en cinco parcelas experimentales en Barcelona, Lleida, Madrid, Sevilla y Zaragoza durante la campaña 2016/17 y se repitió el ensayo en la campaña siguiente en Barcelona, Madrid y Zaragoza. En cada parcela se sembraron 100 semillas procedentes de una finca experimental de Sevilla en cuadriculas de 25 x 25 cm (4 repeticiones). Para el modelo se utilizó una curva acumulada de la densidad de Kernel que relacionó la emergencia con una integral hidrotérmica basada en una ecuación de dos segmentos. Se estableció una temperatura base, óptima y máxima de -1,0 ºC, 8,1 ºC y 26,0 ºC, respectivamente y un potencial hídrico base de -0,6 MPa. Este modelo alcanza el 10 %, 50 % y 90 % de la emergencia acumulada a 43,2, 74,7 y 97,4 grados hidrotérmicos, respectivamente. En promedio, el modelo presentó un RMSE (root mean square error) de 16,81 %, oscilando entre 9,1 % y 32,5 %.

[EN] PalmerNET is a Research Network (RED2022-134285-T), financed by the Agencia Española de Investigación, tofi ght against Amaranthus palmeri (A. palmeri) S. Wats., an invasive weed species established in Lleida, Huesca and Extremadura, with the ability to evolve herbicide resistance. Under the leadership of researcher Joel Torra, the Agrotechnology Research CERCA Centre (Agrotecnio) and the Universitat de Lleida (UdL) have started PalmerNET, where three other universities participate, namely the Universidad Pública de Navarra, the Universidad de Vigo and the Universitat Politècnica de València, and three other research institutes namely the Centro de Investigación y Tecnología Agraria de Aragón (CITA), the Instituto Nacional de Investigaciones Agrarias of Madrid (INIA-CSIC) and the Centro de Investigaciones Científicas y Tecnológicas de Extremadura (CICYTEX). A total of 25 people, including researchers, professors and PhD students, integrate PalmerNET. The net will promote the collaboration and research between these research groups to understand and contribute to containing the spread of this invasive weed, and disseminate the available knowledge regarding this worrying crop protection problem. During the period of the network PalmerNET (from 2023 to 2025), several activities will be undertaken, like technical seminars with the sector, periodic meetings of the net members, and the creation of a web page. This network will foster cooperation between the participating members to reach a global view of the problem and join research and action efforts., [ES] PalmerNET es una Red de Investigación (RED2022-134285-T), financiada por la Agencia Española de Investigación, para combatir Amaranthus palmeri (A. palmeri) S. Wats., especie invasora establecida en Lleida, Huesca y Extremadura, con capacidad de generar resistencias a herbicidas. Bajo la dirección del investigador Joel Torra, la Fundación Centro de Investigación en Agrotecnología (Agrotecnio) y la Universitat de Lleida (UdL) han puesto en marcha PalmerNET, donde participan, además, otras tres universidades: la Universidad Pública de Navarra, la Universidad de Vigo y la Universitat Politècnica de València, y otros tres centros de investigación: el Centro de Investigación y Tecnología Agraria de Aragón (CITA), el Instituto Nacional de Investigaciones Agrarias de Madrid (INIA-CSIC) y el Centro de Investigaciones Científicas y Tecnológicas de Extremadura (CICYTEX). Un total de 25 personas, entre investigadores, profesores y estudiantes predoctorales, integran PalmerNET. La red promoverá la colaboración e investigación entre los grupos participantes para comprender y poder contener la expansión de la mala hierba y divulgar el concimiento disponible sobre este grave problema fitosanitario. Durante la vigencia de la red PalmerNET (de 2023 a 2025), se realizarán Jornadas Técnicas de divulgación, se actualizará la información mediante reuniones de los miembros y la creación de una página web. La red potenciará la cooperación entre los investigadores participantes para alcanzar una visión global del problema, uniendo esfuerzos de investigación y de actuación.

[EN] The Weed Biology and Agroecology group (BAMh) of the Spanish Society of Weed Science (SEMh) is currently composed of 15 people working in 4 universities; Universitat de Lleida (UdL), Universitat Politècnica de València (UPV), Universidad de Sevilla (US) and Universitat Politècnica de Catalunya (UPC) and in 5 research centers in Spain and Portugal: Centro de Investigación y Tecnología Agraria de Aragón (CITA), CN Instituto Nacional de Investigaciones y Tecnología Agraria y Alimentaria (INIA-CSIC), Centro de Investigaciones Científicas y Tecnológicas de Extremadura (CICYTEX), Instituto Andaluz de Investigación y Formación Agraria, Pesquera, Alimentaria y de la Producción Ecológica (IFAPA), Instituto Navarro de Tecnologías e Infraestructuras Agroalimentaria (INTIA) and Instituto Nacional de Investigação Agrária e Veterinária (INIAV). This group has initiated a new trial (2023-2025) to validate for the Iberian Peninsula the emergence models developed in Italy for the weeds Chenopodium album L., Sorghum halepenseL., Abutilon theophrasti Medik, Digitaria sanguinalis (L.) Scop. and Amaranthus retroflexus L. The seeds collected by the groups at their locations will be sown in mid-autumn in experimental plots in Aragón, Barcelona, Sevilla, Córdoba, Lleida, Madrid, Valencia, Navarra and Oeiras (Portugal). The emergence will be evaluated and the base, optimum and ceiling temperatures and the base water potential will be obtained under controlled conditions for the germination of those species that do not fit the model. The recalibration and optimization of these models for their application in the Iberian Peninsula will contribute to achieve an integrated management of weeds in summer crops., [ES] El grupo de Biología y Agroecología de las Malas Hierbas (BAMh) de la Sociedad Española de Malherbología (SEMh) está actualmente integrado por 15 personas que trabajan en 4 universidades; Universitat de Lleida (UdL), Universitat Politècnica de València (UPV), Universidad de Sevilla (US) y Universitat Politècnica de Catalunya (UPC) y en 5 centros de investigación de España y Portugal: el Centro de Investigación y Tecnología Agraria de Aragón (CITA), el CN Instituto Nacional de Investigaciones y Técnología Agraria y Alimentaria (INIA-CSIC), el Centro de Investigaciones Científicas y Tecnológicas de Extremadura (CICYTEX), el Instituto Andaluz de Investigación y Formación Agraria, Pesquera, Alimentaria y de la Producción Ecológica (IFAPA), el Instituto Navarro de Tecnologías e Infraestructuras Agroalimentaria (INTIA) y el Instituto Nacional de Investigação Agrária e Veterinária (INIAV). Se ha planteado un nuevo ensayo (2023-2025) para validar en la Península Ibérica los modelos de emergencia desarrollados en Italia para las malas hierbas Chenopodium album L., Sorghum halepense L., Abutilon theophrasti Medik., Echinochloa crus-galli (L.) Beauv. Digitaria sanguinalis (L.) Scop. y Amaranthus retroflexus L. Las semillas recogidas en 2023 se sembraran a mediados de otoño en parcelas experimentales de Aragón, Barcelona, Sevilla, Córdoba, Lleida, Madrid, Valencia, Navarra y Oeiras (Portugal). Se evaluará la emergencia y se obtendrá en condiciones controladas, la temperatura base, óptima, techo y el potencial hídrico base de las especies cuya germinación no se ajuste al modelo. La recalibración de estos modelos para la Península Ibérica contribuirá a conseguir un adecuado manejo integrado de las malas hierbas en cultivos de verano.

North African knapweed (Centaurea diluta Aiton) is an annual weed that is widespread in southern Spain and is of increasing concern in dryland cropping systems. Despite its expanding range in Spain, there is limited information on the emergence timing and pattern of this species, knowledge of which is critical for developing more timely and effective management strategies. Therefore, there is a need to develop simple and reliable models to predict the timing and emergence of this annual weed under dryland conditions. A multi-location field experiment was established across Spain in 2016 to 2017 to assess the emergence of C. diluta. At each of 11 locations, seeds were sown in the fall, and emergence was recorded. Overall emergence averaged 39% in the first year across all sites and 11% in the second year. In both years, the main emergence flush occurred at the beginning of the growing season. A three-parameter Weibull function best described seedling emergence of C. diluta. Emergence models were developed based on thermal time (TT) and hydrothermal time (HTT) and showed high predictability, as evidenced by root mean-square error prediction values of 10.8 and 10.7, respectively. Three cardinal points were established for TT and HHT at 0.5, 10, and 35 C for base, optimal, and ceiling temperatures, respectively, while base water potential was estimated at-0.5 MPa.

Lolium rigidum Gaudin is a troublesome weed worldwide, and its distribution may increase due to climate change. It has become resistant to several herbicides and, therefore, its control is problematic. On the other hand, its seed biology, with little dormancy and short-term viability, can play a major role in reducing its seed bank, which would improve control of this weed. For this reason, knowledge of the emergence patterns of this species entails improvements for its management. In this work seeds from one population of L. rigidum, collected in Northeastern Spain, were distributed and sown in 11 sites across Spain, and its emergence was followed every 2–7 days for two growing seasons (2016-17 and 2017–18). These emergence sequences were compared with previously published thermal time and hydrothermal time based models, and new models were developed afterwards. The hydrothermal time based model did not significantly improve models based solely on thermal time. The accuracy of these newly developed models varied from site to site, but in general, they worked better for Northern locations than for Southern locations. Thus, the experimental sites were split between North and South, and specific models for each region were developed. The model developed for Northern sites worked very well, but the one for Southern sites needs improvement. This works reveals that, with regard to this weed species, probably different models should be developed for different climatic conditions. The model developed with data from Northern sites should be validated with local populations, while the one developed with data from Southern sites will probably need to be revised or newly developed with data from more Southern populations.

Complaints about the lack of control of Rapistrum rugosum with tribenuron-methyl and iodosulfuron-methyl-sodium in winter cereals in Northeastern Spain motivated this study. During 2015–2018, greenhouse trials were conducted to test the responses of two possibly resistant (R1 and R2) and two susceptible populations to both active ingredients to determine the response of these populations to alternative herbicides. In the first trial that was repeated twice, populations were treated with both active ingredients (three rates, six replicates), and the lack of control confirmed resistance both times. The second trial was conducted on the self-pollinated progeny of the initial populations (13 rates, 6 replicates) to confirm the heritable character of resistance and to determine the resistance factors related to survival and biomass. Resistance factors based on biomass were 188 and 253 for tribenuron-methyl and 42 and 26 for iodosulfuron-methyl-sodium for R1 and R2, respectively, confirming the strong resistance of the progeny. In the third trial, nine active ingredients (a.i.) registered for broadleaved weed control in winter cereals were tested on the four populations (two rates, four replicates). All the alternative herbicides, except florasulam, results in important phytotoxicity to all tested populations, with 100% efficacy for several a.i. This work is the first report of R. rugosum that is resistant to iodosulfuron-methyl-sodium and the first report in Europe of R. rugosum that is resistant to tribenuron-methyl.