Introduction: In Colombia, 45% of the continental and insular surface presents some degree of susceptibility or propensity to soil degradation due to salinization. The high concentration of salts negatively affects the biologicals of the soil, causing a decrease in crop productivity. Objective: The bibliographic information available on the factors associated with the salinization of soils in agricultural areas of the Caribbean region and different strategies for the recovery of saline soils was reviewed. Method: A literature review was carried out in which the biophysical and anthropic factors of the salinization of soils and the associated consequences are documented. Additionally, a review was made of international and national scientific articles that address different strategies for the recovery of saline soils in which it was analyzed which ones have been more successful from the environmental point of view. Results: The salinity of the soils was related to the climatic conditions, irrigation with poor quality water, chemical fertilization, the scarce use of vegetal covers and the low contents of organic matter in the soils. Soil washing is a viable alternative if good quality water is available. The most feasible alternative was the use of organic fertilizers Conclusions: The salinity of the soils was related to the use of irrigation water with high saline content, little plant cover, low content of organic matter in the soil and the use of fertilizers. The most viable recovery strategy is the application of organic fertilizers and amendments.

For this research, the objective was established to financially evaluate the technology in dairy production: improvements in profitability and agricultural administrative management. Regarding the study, it is descriptive in nature, with absolute and relative frequency statistics, carried out through intentional opinion sampling of thirty (30) production units (P.U.), representative of the study universe made up of 154 farms. . They were surveyed with the purpose of obtaining the necessary data on these production systems, which indicate the following: first, the units were classified by blocks according to the surface in order to be able to evaluate their productivity in relation to productive indicators, such as productivity by area, productivity per animal unit (A.U.) and productivity per labor force. Of all the farms subject to study, twenty-nine (29) were located at the medium technology level according to their productive indicators; the productivity per surface is 3.23 liters (L.) per hectare (has); Productivity per animal unit (U.A.) is 5.94 L./U.A. and labor 134.2 L. per hour subtracting one (1) U.P. which presented a productivity of 2.2L/ha for surface, 2.5 L. U.A. and for labor 50 L./H. It should be noted that these productivities were compared; From these comparisons, differences were found in terms of productivity indicators in percentage terms: 96.70% of the units were of the medium technology level since they have the technological requirements; Therefore, producers were recommended to establish consolidation programs that take into account technology based on the productive performances that were demonstrated through the aforementioned productive indicators and the existing relationship between technology and productivity. Para esta investigación se estableció como objetivo evaluar financieramente la tecnología en la producción lechera: mejoras en la rentabilidad y la gestión administrativa agropecuaria. Respecto al estudio, el mismo es de carácter descriptivo, con estadísticas de frecuencias absolutas y relativas, realizado a través de un muestreo opinático de manera intencional de treinta (30) unidades de producción (U.P.), representativo del universo de estudio conformando por 154 fincas. Se encuestaron con el propósito de obtener los datos necesarios de estos sistemas de producción los cuales indican los siguientes: primero, se clasificaron las unidades por bloques de acuerdo con la superficie a fin de poder evaluar su productividad con relación a los indicadores productivos, como productividad por superficie, productividad por unidad animal (U.A) y productividad por mano de obra. De todas las fincas sujetas a estudio veinte y nueve (29) fueron ubicadas en el nivel de medias tecnologías según sus indicadores productivos; la productividad por superficie es de 3,23 litros (L.) por hectárea (has); la productividad por unidad animal (U.A.) es 5,94 L. /U.A. y de la mano de obra 134,2 L. por hora restando una (1) U.P. que presento una productividad de 2,2L/has para superficie, 2.5 L. U.A. y para la mano de obra 50 L./H. cabe destacar que estas productividades fueron comparadas; de estas comparaciones se encontraron diferencias en cuanto a los indicadores de productividad en términos porcentuales el 96,70% de las unidades fueron del nivel de tecnologías media ya que cuentan con los requerimientos tecnológicos; por lo que se recomendó a los productores establecer programas de consolidación que tomen en cuenta a la tecnología basada en los rendimientos productivos que se demostraron a través de los indicadores productivos antes mencionados y la relación existente entre la tecnología y la productividad.

The main source of N in the soil is organic matter; therefore, its availability depends on its quantity and quality, microbial activity, soil characteristics and management. An efficient way to quantify available N is by mineralizing it as ammonium (N-NH ) and nitrate (N-NO ). Therefore, in this study, the total and available N was determined in soil samples 0-20 cm deep from two plots with plantain plants (Musa AAB plantain subgroup cv. Hartón) with high and low vigor (AV and BV, respectively), in the South of Lake Maracaibo. Total N was determined by the Kjeldalh method and the mineralization of available N by incubation under laboratory conditions for 10 weeks. The accumulated mineralized N (Nm), the constant mineralization rate of (k) and the potentially mineralizable N (N0) were calculated. A one-way analysis of variance was applied, when it was significant (p<0.05), a Tukey test was applied for multiple comparisons of means. Total N was low (<0.025 %) and did not present statistical differences (p<0.05) between AV and BV. The accumulated mineralized N-NO was statistically (p<0.05) higher (524.47 mg.kg-1) in BV, while the N-NH did not present differences between AV and BV. Only k was statistically higher (0.07 ± 0.03; p<0.05) in BV. Nitrification was the process that prevailed especially in BV where organic carbon was higher and presented a higher percentage of sand.

Introduction: Fungal diseases in tomato cultivation are the main phytosanitary factor that reduces yields. The objective of the investigation was to evaluate the potential biocontroller of Trichoderma harzianum in mushrooms associated with cultivation. Methods: The samples of leaves, roots and stems of diseased plants were collected and processed by the fungal isolation method in vegetable tissue and papa dextrose agar (PDA), the growths were purified, typified and tested for pathogenicity. The potential biocontroller was evaluated under in vitro conditions with the dual cultivation technique in PDA confronting the antagonist with each pathogen. The study employed an random design, with 7 treatments and 4 repetitions, conformed by: 3 dual cultures, 4 witnesses corresponding to each pathogen and the antagonist. The degree of mycoparasitism, the percentage of inhibition of the radial growth (PCR) of the antagonist and the presence of antibiosis between the antagonist and the pathogens were evaluated every 24 hours for 15 days. Results: The fungi were identified: Alternaria alternata, Fusarium oxysporum and Pythium sp. The tests of confrontation evidenced the presence of the mechanisms of action characteristic of this species of biocontroller, although it varies according to the species. The antagonistic capacity for micoparasític action was grade 4 with A. alternata and Pythium and grade 3 with F. oxysporum, the strangulation and enzymatic lysis were observable at the microscopic level. The action of antibiosis was present with all pathogens, while the action of competition in growth was significant only with A. alternata and F. oxysporum. When evaluating the PICR it was found that the antagonist showed high and significant inhibition with A. alternata (55.43%) and F. oxysporum (31.01%), while no inhibition was found with Pythium, although when entering contact, the antagonist showed mycopasitic action stopping the growth and invading the pathogen until it sporulates on it. Conclusions: That T. harzianum has the potential to be used as a biocontrol agent in fungal diseases associated with tomato cultivation.

Los agronegocios necesitan de maximizar la eficiencia de utilización de recurso, y para ello, poseen herramientas avanzadas para el logro de objetivos organizacionales como lo es la agrogestión. El estudio tuvo como objetivo analizar la agrogestión avanzada como mecanismo de rendimiento de las Unidades de Producción. En este sentido, se apoyó en una investigación tipo descriptiva con un diseño de campo no experimental. Por otra parte, la población estuvo conformada por cincuenta (50) sujetos. En tal sentido, la información fue recolectada a través de un cuestionario contentivo treinta y seis (36), preguntas con alternativas en escala de Likert (S, Cs, Av, Cn y N), el mismo fue validado mediante el proceso de juicio de expertos. Los resultados arrojaron que se precisa el inadecuado aprovechamiento de los recursos agrícolas, sin definir un proceso competitivo agropecuario, para cumplir con el apoyo técnico agrícola necesitado por el talento humano de las unidades de producción

La inteligencia artificial (IA) ha dejado de ser una aspiración futurista para convertirse en un instrumento tangible que redefine la producción agropecuaria. El crecimiento demográfico y el aumento de la demanda alimentaria, asociados a los retos de sostenibilidad ambiental y cambio climático, presionan al sector a evolucionar hacia sistemas más eficientes y resilientes. Diversos estudios internacionales reportan que el aprendizaje automático y otras técnicas de IA mejoran la productividad agrícola, reducen costos y permiten gestionar grandes volúmenes de datos, aunque enfrentan desafíos relacionados con la calidad y disponibilidad de datos, la infraestructura tecnológica y la capacitación de los productores. Este artículo presenta una revisión de literatura sobre las principales tendencias, aplicaciones, beneficios y retos de la IA en el sector agropecuario a nivel global. Se analiza la adopción de distintas tecnologías, desde algoritmos de aprendizaje automático y redes neuronales profundas hasta herramientas de Internet de las cosas (IoT) y robótica, en áreas como la detección temprana de plagas y enfermedades, la gestión del riego y los nutrientes, el mapeo agrícola, la ganadería y la acuicultura. Además, se contrasta la producción científica mundial con la generada en Colombia, evidenciando avances importantes, pero también una limitada producción nacional. Se sintetizan datos sobre los artículos revisados (año, país, tecnología, sector y resultados) y se incluyen gráficas que ilustran la distribución temporal, geográfica y sectorial de las investigaciones. Finalmente, se discuten los hallazgos a la luz de la agenda de desarrollo agropecuario colombiano y se proponen líneas futuras de investigación.