Introducción. El control de malezas es una actividad permanente en sistemas agrícolas y forestales tropicales. El aprendizaje profundo ofrece posibilidades para su detección, identificación y manejo. Objetivo. Describir los principales avances y aplicaciones del aprendizaje profundo para la identificación y localización de malezas y analizar su aplicabilidad como herramienta de apoyo para el manejo de malezas en sistemas agrícolas y forestales de Mesoamérica. Desarrollo. Se realizó una revisión de literatura científica mediante la búsqueda de artículos publicados entre 2016 y 2025 en Scopus, Web of Science, ScienceDirect y SpringerLink. La revisión se basó principalmente en 15 estudios que aplicaron técnicas de aprendizaje profundo y reportaron métricas de desempeño, y 15 artículos de revisión. Se identificaron los componentes del proceso y se propuso una ruta metodológica para su implementación en Mesoamérica, considerando las particularidades de los sistemas agrícolas y forestales tropicales. Los modelos de aprendizaje profundo han mostrado un desempeño favorable para el reconocimiento de malezas en diversos sistemas agrícolas. No se encontraron estudios en plantaciones forestales en la búsqueda realizada, aunque se identificó un potencial de aplicación durante las etapas iniciales de establecimiento. La hoja de ruta contempla la priorización de cultivos, especies forestales y malezas de mayor impacto, el desarrollo coordinado de bases de datos y el entrenamiento e implementación de modelos. Conclusiones. El aprendizaje profundo presenta avances relevantes para la identificación y localización de malezas. Su implementación en Mesoamérica podría contribuir al manejo mediante estrategias de agricultura y silvicultura de precisión, pero requiere datos representativos, validación en campo e integración con sistemas de apoyo a la toma de decisiones.
Introduction. District-level soil assessments may obscure local constraints relevant to cacao soil management. Objective. To characterize and prioritize environmental edaphic constraints in cacao soils of the Peruvian Amazon, with emphasis on soil acidity, available phosphorus, aluminum saturation, and available cadmium at the locality scale. Materials and methods. A total of 1,842 surface soil samples (0–20 cm), collected between April and July 2021 in 84 localities in the districts of Puerto Bermúdez and Constitución, were analyzed. Physical and chemical soil variables were evaluated using descriptive statistics, district-level comparisons, locality-level summaries, co-occurrence analysis, bivariate relationships, principal component analysis, and exploratory clustering. Results. Median soil pH was 4.65, median available phosphorus was 5.27 mg kg⁻¹, and median aluminum saturation was 39.21% (1,539 valid determinations). The co-occurrence of pH below 5.5, available phosphorus below 7 mg kg⁻¹, and aluminum saturation of at least 30% was observed in 757 samples (41.1%), indicating the combined occurrence of acidity, low phosphorus, and high aluminum saturation. Available cadmium had a median of 0.035 mg kg⁻¹ but showed a heterogeneous distribution, with localized signals in 13 localities. Conclusions. The locality scale distinguished widespread chemical constraints from localized available-cadmium signals and provided criteria for prioritizing soil monitoring.
The National Center of Food Science and Technology (CITA) and the Food Technology Department (ETA) of the University of Costa Rica have made substantial contributions throughout the years to research, academic training, and scientific and technical support to Costa Rica’s food sector. This bibliometric review documents the scientific output of 328 publications from both units during the 2005-2024 period and highlights their contribution to the advancement of knowledge, as well as to strengthening research and technology transfer efforts in food science and technology. Academic publications were analyzed, including scientific articles, book chapters, and other contributions in which at least one author was affiliated with CITA or ETA. The results reflect the sustained commitment of both academic units to the generation, dissemination, and transfer of scientific knowledge, highlighting their growing national and international presence in the field of food science and technology.
Introduction. A comprehensive evaluation of hydroponic production systems relative to conventional approaches is essential for understanding their performance, particularly regarding resource-use efficiency and spatial intensification. Objective. To compare the spatial productivity and water use efficiency of hydroponic and soil-based Lactuca sativa L. production systems. Materials and methods. The experiment was conducted at the Instituto Nacional de Tecnología Agropecuaria, Mendoza Research Station, Luján de Cuyo, Argentina, from August to October 2025. Four production systems were compared: indoor hydroponic vertical farming with artificial lighting (A), greenhouse hydroponic vertical farming with supplemental artificial lighting (B), conventional horizontal hydroponic cultivation in a greenhouse without artificial lighting (C), and soil-based cultivation in a greenhouse (D). Each system consisted of three independent experimental units, and the data were analyzed using a linear mixed-effects model. Yield, water consumption, water productivity, water consumption per unit of horizontal area, and lettuce nutritional status were evaluated. Results. Vertical systems (A and B) achieved higher yields per unit of horizontal area than C and D, while D produced greater individual plant biomass. System A showed the highest daily productivity and the lowest water consumption per production cycle. Hydroponic systems required significantly less water per plant and per cycle than D. For water consumption per unit of surface area, A showed the lowest value, B and C showed similar intermediate values, and D the highest. Foliar nutrient concentrations and chlorophyll index differed among systems. Conclusions. Vertical systems achieved greater spatial productivity, while hydroponic systems showed lower water consumption than soil-based cultivation.
Introduction. Sowing density is a key agronomic factor for regulating plant competition and optimizing the phenological and productive expression of quinoa in high-Andean environments. Objective. To evaluate the effect of sowing density and its interaction with genotype on phenology, plant architecture, and grain yield of commercial checks and improved quinoa families under high-Andean conditions in the municipality of Silvia, Cauca, Colombia. Materials and methods. The study was conducted during the second semester of 2024 in Silvia, Cauca, Colombia, at 2570 m a.s.l. Five quinoa genotypes were evaluated: two commercial checks, Blanca de Jericó and Aurora, and three improved families, Fel56, FelSJ, and Fel86. A randomized complete block design with a 3 × 5 factorial arrangement and three replications was used. Three sowing arrangements were evaluated: spacings of 0.80 × 0.50 m and 0.70 × 0.10 m, and continuous row sowing with 0.70 m between rows. Morpho-agronomic, phenological, and productive variables were recorded, and data were analyzed using analysis of variance and Tukey’s test (α = 0.05). Results. Sowing density, genotype, and their interaction affected most of the evaluated variables. The widest spacing favored vegetative growth and prolonged the phenological cycle, whereas continuous row sowing accelerated development and reduced productive performance. The intermediate density resulted in the highest yields in FelSJ and Fel56. Conclusions. The sowing density × genotype interaction explained differences in plant architecture, phenological duration, and productive efficiency. The improved families showed a greater response to the intermediate spatial arrangement, providing criteria to guide agronomic management and the selection of quinoa materials in high-Andean environments.
