This study focused on evaluating the growth and productivity of Coffea arabica var. Esperanza L4A5 in different agroforestry systems in the Caribbean region of Costa Rica, a non-traditional area for coffee cultivation due to its low altitude and challenging climatic conditions. Three tree coverages were investigated, in combination with two types of differentiated fertilization (physical and chemical), comparing the results with full sun coffee plots as a control: (1) Albizia saman, (2) Hymenaea courbaril + Erythrina poeppigiana, and (3) Anacardium excelsum + Erythrina poeppigiana. The results showed that tree associations significantly reduced the mortality of coffee plants and increased both the height and mature cherry production compared to full sun treatments. In particular, the tree coverages associated with chemical and physical fertilization achieved the highest growth and production rates, with A. excelsum + E. poeppigiana and H. courbaril + E. poeppigiana standing out with maximum mature cherry productions of 3.35 t/ha and 3.28 t/ha, respectively. Growth analysis revealed that rapid initial growth, especially under chemical fertilization, is crucial for maximizing productivity, although a rapid slowdown in growth was also observed after reaching the peak. These findings underscore the importance of combining tree coverages with appropriate fertilization strategies to optimize coffee production in agroforestry systems, particularly in low-altitude areas like the Costa Rican Caribbean. This study concludes that agroforestry systems not only improve the resilience of coffee crops to adverse environmental conditions but can also be a viable strategy for increasing productivity in non-conventional regions. This suggests the need for further research to assess the long-term impacts on soil health, biodiversity, and the economic viability of these systems.

Introduction. Soil moisture is a very important variable in the water supply for agriculture and it is its main resource. However, its field measurement usually has limitations, so its prediction is necessary for various agricultural planning and research activities. Objective. To predict daily soil moisture at the crop scale from meteorological information through multiple linear regression models. Materials and methods. The study was carried out in Llano Brenes, Alajuela, Costa Rica. Time domain reflectometry (TDR) sensors were installed and soil moisture information was recorded every twenty minutes from November 2018 to December 2019. The soil was classified at the taxonomic level as Lithic Ustorthents, in a farm with coffee cultivation in production. Undisturbed soil samples were taken for TDR calibration and a temporal stability analysis was performed. The first model (RLM1) was a multiple linear regression with meteorological variables, in the second model (RLM2) in addition to the meteorological variables, the precipitation was separated into sub-periods which were introduced as dummy variables, while the third model (PCA) consisted of a main component analysis and a linear regression model. Results. The RLM2 (R2 = 0.838) and PCA (R2 = 0.823) models performed better than the RLM1 model (R2 = 0.540). However, the RLM2 model was considered more useful due to its simplicity and the fact that it presented the best goodness-of-fit indicators. Conclusion. The linear regression models with meteorological variables allowed estimating soil moisture, because it tends to follow seasonal patterns and variations in precipitation, as observed in the RLM2 with the separation of sub-periods.

Introduction. Water erosion is a natural phenomenon accelerated by human activity, which facilitates soil degradation and sediment transport to other areas. Objective. To quantify the surface runoff and erosion rate at the plot scale, under natural precipitation events in an Entisol soil cultivated with shaded coffee (Coffea arabica) and to determine the temporal dynamics and the influence of the main factors associated with this process. Materials and methods. The study was developed in Llano Brenes, Alajuela, Costa Rica. Nine runoff plots were installed, the data was collected between May 2018 and November 2019, each plot had a runoff meter and a container for collecting sediment samples. Three-time domain reflectometry sensors were installed for surface soil moisture content measurements. Data analysis was carried out on a monthly-annual, inter-event and intra-event scale. At the intra-event scale, the Diskin & Nazimov infiltration model was applied. Results. In the years 2018 and 2019, the following annual results were obtained, respectively: a) total runoff sheet of 90.99 and 102.66 mm, b) sediment concentration of 2.14 and 1.88 g L-1, and c) soil loss of 1612 and 1692 g m-2. The highest soil loss values were obtained in October of each year. The intra-event analysis explained the runoff generation based on the precipitation sheet and the initial moisture content in the event. Conclusion. The mean annual erosion rate and runoff were 1652 g m-2 and 96.8 mm. The precipitation sheet, intensities, and initial surface soil moisture content played an important role in runoff generation and soil loss.

La pandemia de COVID-19 ha transformado profundamente las estrategias educativas empleadas en diversos cursos universitarios. En particular, los cursos de Agronegocios no han sido ajenos a estos cambios. El objetivo del estudio fue explorar la percepción del estudiantado de Agronomía respecto a cómo las adaptaciones pedagógicas requeridas durante la pandemia, incluida la transición entre modalidades presenciales y virtuales, afectaron su motivación y capacidad de adaptación a las nuevas tecnologías. Se llevó a cabo un estudio con 84 estudiantes de grado de la carrera de Agronomía de la Universidad de Costa Rica, Sede Rodrigo Facio, durante el mes de junio de 2022. Las personas participantes completaron un cuestionario estructurado con 30 ítems, en el que se evaluaron aspectos como el perfil demográfico, la conectividad a Internet, la disponibilidad de equipamiento informático, la aceptación de tecnologías virtuales, la percepción sobre la calidad de los contenidos impartidos, y la motivación personal del estudiantado. Los datos recopilados fueron analizados utilizando modelos de ecuaciones estructurales para examinar las relaciones causales entre las variables de interés. Se observó que la motivación personal tuvo un efecto significativo (β=0.23) en la percepción del estudiantado sobre la enseñanza de Agronegocios durante la pandemia. Este estudio subraya la importancia que el estudiantado de Agronomía le otorga a la calidad de la enseñanza por parte del profesorado y a la realización de actividades prácticas como impulsoras clave de su motivación en el aprendizaje de los contenidos de Agronegocios.

This study focused on the phenology of Coffea arabica var. Esperanza L4A5, an F1 interspecific hybrid obtained by crossing commercial varieties with wild genotypes from Ethiopia and Sudan. Most phenological studies on C. arabica have been conducted in traditional high-altitude regions, leaving a gap in the understanding of its behavior in non-traditional areas such as the Caribbean region of Costa Rica. To establish a baseline on the phenological behavior of the Esperanza L4A5 hybrid in this region, we conducted a four-year study examining the effects of different agroforestry associations: (1) Albizia saman; (2) Hymenaea courbaril and Erythrina poeppigiana; (3) Anacardium excelsum and Erythrina poeppigiana; and coffee plots under full sun. Additionally, the phenology of the coffee plants was evaluated under differentiated fertilizations (physical, chemical, and without fertilization), considering meteorological factors such as temperature, humidity, and rainfall. The observed variables included the development of floral nodes, pre-anthesis, anthesis, and fruiting stages. To analyze the relationships between environmental factors, tree cover, fertilization, and the phenological stages, we employed multiple linear regression (MLR), which revealed that both tree cover and physical and chemical fertilizations had significant effects on the presence of developed floral nodes and, consequently, on fruit production. Furthermore, the random forest (RF) model was applied to capture complex interactions between variables and to rank the importance of meteorological factors, tree cover, and fertilization practices. These analyses demonstrated that the Esperanza L4A5 hybrid exhibited viable phenological development under the atypical conditions of the Caribbean region of Costa Rica, suggesting its potential to adapt and thrive in non-traditional coffee-growing areas.