Surface soil moisture is an important hydrological parameter in agricultural areas. Periodic measurements in tropical mountain environments are poorly representative of larger areas, while satellite resolution is too coarse to be effective in these topographically varied landscapes, making spatial resolution an important parameter to consider. The Las Palmas catchment area near Medellin in Colombia is a vital water reservoir that stores considerable amounts of water in its andosol. In this tropical Andean setting, we use an unmanned aerial vehicle (UAV) with multispectral (visible, near infrared) sensors to determine the correlation of three agricultural land uses (potatoes, bare soil, and pasture) with surface soil moisture. Four vegetation indices (the perpendicular drought index, PDI; the normalized difference vegetation index, NDVI; the normalized difference water index, NDWI, and the soil-adjusted vegetation index, SAVI) were applied to UAV imagery and a 3 m resolution to estimate surface soil moisture through calibration with in situ field measurements. The results showed that on bare soil, the indices that best fit the soil moisture results are NDVI, NDWI and PDI on a detailed scale, whereas on potatoes crops, the NDWI is the index that correlates significantly with soil moisture, irrespective of the scale. Multispectral images and vegetation indices provide good soil moisture understanding in tropical mountain environments, with 3 m remote sensing images which are shown to be a good alternative to soil moisture analysis on pastures using the NDVI and UAV images for bare soil and potatoes.

The intensive cattle production on the Colombian Atlantic coast causes soil degradation and low productivity on pastures. Silvopastoral systems in Colombia are based on introduced species due to a lack of native species knowledge and a cultural trend to overestimate introduced species. It is necessary to study native species in association with the established pastures to increase productivity and to improve soil properties. This research was based on the Sinú River Valley (18 masl), under Tropical dry forest, in Colombia. The aim of this study was to determine changes in nutrient cycling when native trees are incorporated into grassland systems, according to their diversity. Leaf litter decomposition of two grass species and seven forestry native species were evaluated on four experimental blocks. The results showed that residual dry matter decreased over time and facilitated nutrient release associated with species diversity and its interaction. Nutrient liberation was specie-dependent being markedly higher on G. ulmifolia and P. quinata. The concentration of N/P, P, and Mg was significant and had the highest correlation with leaf litter decomposition. The tested decomposition models showed good performance and small significant differences between them, which confirms its reliability to use them under Colombian tropical conditions.

El aguacate ha sido plantado y consumido desde hace más de nueve mil años sobre la Tierra, sin embargo, solo hacia finales del siglo XX se dio un aumento sostenido de su cultivo y producción, que sobrepasó, en 2018, los 5,6 millones de toneladas. Además ha adquirido una gran valor en la dieta humana para su consumo en fresco debido a sus calidades nutricionales y organolépticas. No obstante, la composición y las cualidades nutricionales de los frutos son muy variables, pues dependen del clima, el suelo, la temperatura, la humedad, la cantidad de lluvia durante el desarrollo del fruto y las prácticas de manejo del cultivo, además de las diferencias genotípicas entre cultivares. Dado que Colombia aún no cuenta con toda la información técnica necesaria para acompañar el incremento de nuevas áreas de cultivo y salvaguardar las actuales, este manual compendia una cantidad importante de temas clave para su cultivo.

Remote sensing technologies, such as spectral imaging, have great potential for crop monitoring. Spectral systems measure the energy reflected and emitted by a surface, typically between the visible and near-infrared regions of the electromagnetic spectrum. This paper presents a spectral characterization of avocado (Persea americana Mill. cv. Hass) using spectrophotometry and spectral imaging. The study uses data from four avocado farms, which were collected in situ using spectrometers and GreenSeeker sensors and remotely using satellites such as Landsat 8 and Sentinel 2. The spectral signatures captured by the in situ and remote sensors were compared and subsequently related to vegetation indices. Spectrometry revealed differences between young and mature leaves, particularly in the 480 nm to 650 nm region of the spectrum, which showed color changes in young avocado leaves. The analysis of satellite data highlighted significant differences between Sentinel 2 and Landsat 8 spectral signatures. These differences are likely due to several factors, including collection date, preprocessing, and spatial resolution of the data. Finally, the vegetation indices derived from in situ and satellite measurements displayed different scales. For in situ data, the Normalized Difference Vegetation Index (NDVI) values were around 0.9 for the spectrometers and 0.7 for the GreenSeeker sensors. However, the NDVI values derived from satellite data were around 0.4 for Sentinel 2 and 0.3 for Landsat 8.

El libro presenta las características biofísicas y socioeconómicas de áreas productoras y potenciales de las zonas aptas para aguacate Hass (escala semidetallada 1:25.000) en once municipios del departamento del Cauca (Colombia): Cajibío, Caldono, Caloto, Corinto, El Tambo, Morales, Piendamó, Popayán, Sotará, Toribío y Timbío. Aplicando la metodología de evaluación de tierras y zonificación, describe y analiza información sobre las condiciones de suelos, paisajes y clima, requerimientos del cultivo y variables socioeconómicas que determinan la competitividad del sector y la cadena productiva. Esta información contribuye a establecer las limitantes del cultivo y la tecnología que se necesita para la planificación de nuevas áreas y el mejoramiento de la productividad y competitividad del sistema de producción a nivel regional.