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.

Summary In the quantification and analysis of the distribution of soil basic components, factors such as spatial resolution, scales of observation and analytical techniques used to interpret digital images of microscopic platforms are critical to obtain reproducible results. In addition, individual or discrete images, sometimes with high spatial resolution, distort features or basic components when zooming in or out, which limits their classification. This research proposes the use of micromorphological tools, spatially referenced mosaics with high resolution, image analysis and composite images to elaborate thematic maps of soil components. Therefore, we created mosaics with sequential digital images from soil thin sections (up to 3850 mm2) of different diagnostic horizons, with different magnifications (2×, 10× and 20×) and light sources. The mosaics (between 0.25 and 2.6 μm2 per pixel, and between 2 and 8 GB file size) were processed by image analysis (segmentation, supervised classification and accuracy assessments) for delimiting their basic soil components from composite images and with spatial operators to elaborate thematic maps at the microscopic level. The RGB (red, green, blue) brightness values of each soil component with different light sources enabled us to identify and quantify size classes of aggregates, voids, pedofeatures and organic matter with different degrees of decomposition at a high level of precision (up to 99% overall accuracy). It was also possible to develop good‐quality thematic maps of such components from high‐resolution spatially referenced mosaics and composite images Thematic maps of soil components can be explored without losing their spatial reference and analysed on multiple scales from a whole soil thin section. Highlights Micromorphology and digital cartography to develop thematic maps of soil components High spatial resolution mosaics from thin sections and image analysis were used for mapping RGB brightness values of different light sources facilitated mapping of soil features Accurate maps enabled quantification and analysis of spatial relations of soil components

Sweet sorghum (Sorghum bicolor [L.] Moench) is a crop that is well known for its high production of biomass and sugars in the stem juice. The objective of this work was to evaluate the productivity of sweet sorghum 'Roger' based on the dynamics of sugar production and dry biomass by considering different production methods and plant phenological stages. The experimental design consisted of different tillage and fertilization methods established in a randomized complete block design with a split plot arrangement. Tillage treatments were assigned to the plot using the three levels of minimum tillage, traditional tillage, and traditional tillage that included a subsoil operation. Fertilization treatments were assigned to the subplot using the three levels of organic fertilizer, inorganic fertilizer, and without fertilizer. Data collection was performed at different plant phenological stages from anthesis to physiological maturity. Results showed that evaluated agronomic parameters depended on the phenological stage (P < 0.05) rather than the production methods (P > 0.05). Thus, the distribution and accumulation of sugar by stem internodes was associated with plant phenological components. The highest values of the concentration of total soluble solids (14.89%), juice sugar content (22.91 g), juice sugar concentration (527.46 mg g-1 DW), dry biomass (60.04%), and dry biomass yield (19.01 t ha-1) were observed at the physiological maturity stage of the plant.

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Biodynamic agriculture, which considered biodynamic preparations (BP) and compost as essential to farms sustainability, surged as an alternative almost a century ago. Composting is a way to obtain either biofertilizers or soil amendments, whereas the static piles method reduces energy and cost because no turnings are needed. The present study aims to evaluate the BP effect on physical, chemical and biological properties of static piles compost from prickly pear cactus and moringa crop wastes (regional principal substrates) over 100 days of composting. The experiment was carried out in an organic farm (Nuevo León, Mexico) considering four treatments: T1, Prickly pear cactus+BP; T2, Moringa+BP; T3, Prickly pear cactus and T4, Moringa. Results showed significantly higher bacterial activity (p<0.05) in T1 (until 1.38x1010 CFU), therefore it had the highest temperatures and mineralization. Treatments with prickly pear cactus attained the highest temperatures, compared with those with moringa (significantly in 71% of total sampling days, p<0.05). An aerobic environment was maintained by the passive aeration system (holed PVC pipes placed at the bottom layer). The final material was considered to be sanitized, according to Enterobacteriaceae, Escherichia coli and Salmonella/Shigella analysis for quality control. Results indicate the BP efficiency on regional substrates decomposition, by using the static piles method.

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Changes in soil structure can be monitored in undisturbed soil samples through the micromorphometric analysis of thin sections. In this methodology, it is common that individual images (three to ten repetitions) are used and that they cannot be related in different scales between soil components; in addition, although a minimum study area is established, its representativeness in the soil components is unknown. The objective of this study was to quantify the soil constituent (pores, aggregates, and roots) and to compare the values obtained from individual images versus high-resolution mosaics from a complete thin section. Unaltered samples were collected in three soils with different clay contents (Entisols, Inceptisols, and Vertisols) and presence of maize roots in the same phenological development stage (physiological maturity). Three thin sections of each soil (5 × 7 cm × 30 μm 1865 mm 2) were prepared and sequential images of 11.1× 7.4 mm (63 in total) were obtained at 2× magnification using a petrographic microscope and plane polarized light (PPL). The high-resolution mosaics (2.6 µm píxel-1) at a colour depth 24 bits (8 bits × 3 bands in standard RGB) were built using space operators; subsequently, three, five and ten images were randomly selected. The individual images and the mosaics were transformed by principal component analysis in ArcGis® and soil constituents were delimited according to their variances values. The results indicate that individual images are recommended only to quantify porosity or in homogeneous systems in structure and color, but not in heterogeneous systems where the data obtained show high variability. Even when the results are similar to those calculated in the mosaics, the dispersion of the data is high (variance 5 times greater than the mean) and with little representation. In contrast, high-resolution mosaics offer the total quantification of the thin section and soil components can be grouped into classes or categories to observe intra or inter relations in the soil system. In addition, the soil components can be related to different scales, for example macroaggregates and roots.