The growing global demand for energy and the reduction of energy based on oil are driving the search for new sources of energy that are environmentally friendly. To achieve this goal, it is also necessary to optimize the related processes. In this study, the behavior of the agronomic parameters of, and the energy invested in, production systems based on a new variety of sweet sorghum (Sorghum bicolor (L.) Moench) called ROGER were determined to define the optimal production conditions. To this end, three methods of tillage (minimum, traditional, and traditional tillage with rupture of the plow layer) and three types of fertilizers (inorganic, organic, and without fertilizer) were established, and to estimate the energy efficiency, the inputs and the energy outputs of each system were considered. The traditional tillage with breaking of the plow layer and the organic fertilizer showed the highest values of plant height (2.45 and 2.39 m, respectively); total fresh weight of the plant (51.66 and 50.77 t·ha⁻¹, respectively), of the stem (42.7 and 41.05 t·ha⁻¹, respectively), and of the juice (21.89 and 22.57 t·ha⁻¹, respectively); the volume of the juice (20,783.12 and 22,529.59 L·ha⁻¹, respectively); and Brix degrees (16.04% and 15.01%, respectively). However, the highest energy efficiency was registered in the production system that used the minimum tillage, with a value of 15.11, as well as when no fertilizer was applied with 18.68.

The sustainability of the natural resources used in agricultural production is essential to meet the future food needs of the population. It is necessary to understand the characteristics of climate and soil changes through agroclimatic zoning models, even with non-existent or limited climatic and edaphic databases, to avoid a decline in production. The objective of the study was to determine the accuracy of the Global Agroecological Zoning (GAEZ), ECOCROP and Papadakis models for major cereals, vegetables and fruit trees in the state of Nuevo León, Mexico, using the databases of climatic stations and soil profiles collected by INEGI with random sampling in the field. The model with the best projection was ECOCROP, which predicted 37,609 km² of irrigated area for sorghum and 34,796 km² for wheat, in addition to identifying by soil characteristics rainfed areas with higher suitability for beans measuring 8470 km² and orange measuring 6175 km² with zoning predictions based on field information. In conclusion, the thematic maps obtained with ECOCROP had an accuracy greater than 50% for more than half of the crops analyzed, making it the best method for the study area. Therefore, the food production decisions of the producers must be directed towards cereal crops based on the projected area; however, it is necessary to establish an updating program and generate edaphoclimatic databases, updating thematic soil and climate maps with models that support the projections verified in the field.

Fire is a natural phenomenon and indispensable within the biogeochemical cycles of soils, especially those that sustain a forest vegetation as in the case of Andosols. Nevertheless, little is known about the temperatures that are reached in the soils in forest fires, and their immediate effect on their edaphic properties. In April 2017, field trips were conducted in San Pablo Ixayoc, Texcoco, State of Mexico, two days after the start of the forest fire. Composite and unaltered soil samples in the first 5 cm of soil were collected for the analysis of their edaphic and micro-morphological properties. The estimation of the temperature was made through a thermal experiment and mineralogical analysis. Based on the destruction, formation and dominance mainly of the oxides, ferromagnesian and pseudo-sands, the temperatures reached in the forest fires can be grouped in: < 250 degrees C for superficial and crown fires in Quercus sp. and Pinus sp., and 250 degrees C - 500 degrees C in fallen trees and tree roots that continued to be incinerated. The MO, pH, CIC, P, K+ Na+ and texture show direct and indirect tendencies according to the type of ashes and temperature and not with the severity and type of vegetation. Surface and crown fires immediately modified Andosols' properties and improved their quality, while, at those points where higher temperatures were reached, the soil is affected but there is less impact because fires occur in specific and small areas.

La región montañosa de Veracruz es un ecosistema complejo por su f isiografía y vegetación natural en donde ocurren sistemas productivos agroforestales de café que son de alto valor económico para los productores. Estos sistemas presentan múltiples factores bióticos y abióticos que dif icultan su zonif icación y clasif icación y por ende está limitada la transferencia de tecnología entre productores y técnicos. El objetivo de la presente investigación fue generar mapas temáticos de la distribución y aptitud de la tierra con potencial productivo de cultivo de café en los sistemas agroforestales de la zona montañosa del municipio de Huatusco, Veracruz. Para ello se emplearon técnicas de análisis de percepción remota (PR), con enfoque paramétrico sobre Sistemas de Información Geográf ica (GIS), clasif icación interpretativa de tierras y conocimiento local. En la zona de estudio se presentan dos componentes agroforestales: bosque mesóf ilo de montaña (BMM) (27%) y potreros (Po) (16%) y tres subcomponentes: policultivo tradicional (Pt) y comercial (Pc) (36%), monocultivo especializado (Me) (3%) y zonas urbanas (Zu) (2.9%), identif icados a través de su brillantez y textura en una imagen de satélite; sin embargo, hay confusión entre la vegetación nativa y comercial. Con la participación de los productores, estos componentes se identif icaron con una precisión de 78.9% (Pc), 87.5% (Pt) y 100% (BMM, Pot, Me). La zona de mayor aptitud para la producción de café se localiza en la zona centro (23%); mientras que los de baja calidad en el centro y noreste (45.5%) del municipio. Los BMM ocurren en áreas no aptas para la producción de cultivo de café. La combinación entre técnicas geoespaciales con el conocimiento local de la aptitud de las tierras permite identif icar zonas con potencial productivo agrícola de café y dar elementos para la conservación de otros ambientes como el BMM.

Vegetable production in intensive protected agriculture systems has evolved due to its intensity and economic importance. Sensors are increasingly common for decision-making in crop management and control of environmental variables, obtaining optimal yields, such as estimating vegetation indices. Innovation and technological advances in unmanned vehicle platforms have improved spatial, spectral, and temporal resolution. However, in protected agriculture systems, the use is limited due to the assumption of having controlled environmental conditions for indeterminate vegetable production. Therefore, sequential monitoring of NDVI is proposed during the 2022 and 2023 agricultural cycles using the Green Seeker^® sensor and agronomic variables. This has created a database to generate predictive models of development and yield as a function of nutrient status. The results obtained indicate high significance levels for the development and NDVI curves in all phenological stages; in contrast to the yield predictive models, this is due to the maximum values (close to one) recorded for NDVI inside the greenhouse in comparison to the yield prediction obtained from the 18th week of harvest. Evaluating the models between NDVI and agronomic variables is not an index that offers certainty in predicting yield in indeterminate crops in protected agriculture production systems. This is due to the constant optimal development in response to controlled environmental conditions, nutrient status, and water supply inside the greenhouse, without the sustainability of yield, which decreases in the final stages of production until production becomes economically unprofitable.