Digital soil mapping outputs on soil classification and sugarcane production in Brazil

Mendes, Wanderson de Sousa; Demattê, José A.M.

doi:10.1016/j.jsames.2022.103881

Cited by 5 publications

(1 citation statement)

References 55 publications

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“…Soil maps, which can be efectively produced with statistical models in digital soil mapping (DSM), contain vital information on the spatial distribution of soil properties used in felds such as water and land management and climate studies [29]. Currently, Mendes and Demattê [30] and Hartemink and Bockheim [31] explained that soil maps at regional and farm levels are essential for the best management of agricultural practices.…”

Section: Introductionmentioning

confidence: 99%

Characterization and Mapping of Soil-Landscape for Site-Specific Soil Management in Ayiba Watershed, Northern Highlands of Ethiopia

Seifu

Elias

Gebresamuel

et al. 2023

Applied and Environmental Soil Science

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The characterization of soil landscapes is becoming increasingly important for making decisions regarding site-specific agriculture systems and soil management. This study was initiated for the purpose of identifying landscape-scale spatial soil variation using a toposequence model so that site-specific fertilization could be achieved. According to the finding, the soils were shallow to very deep in depth, moderately acidic to moderately alkaline in soil reaction, nonsaline in salinity, and clay to sandy loam in texture. The soils were found very low to low levels in most soil nutrients, very low to very high levels of base saturation, and deficient in zinc but have adequate levels of iron, copper, and manganese. The soil exchange complex was mainly dominated by Ca and Mg where the order of occurrence was Ca > mg > K > Na. The CEC values were in high to very high range. Following the field survey and soil analytical results, five main reference soil groups of the World Soil Resource Base—Leptosols (56%), Luvisols (8.5%), Fluvisols (14.4%), Vertisols (13%), and Cambisol (8.2%)—were identified and mapped. Leptosols cover the largest landmass of the watershed and mostly found at the summit and hill back slopes. On the other hand, Luvisols, Fluvisols, Vertisols, and Cambisols were found on the middle and foot slopes. According to the findings, the variation in soil source indicating that topography is the primary pedogenic element in the formation of the soil in the watershed that was under research. Therefore, having local-scale-specific soil information can assist the site-specific application of soil nutrients and amendments based on spatial variability which is tailored to the soil requirements.

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Section: Introductionmentioning

confidence: 99%

Characterization and Mapping of Soil-Landscape for Site-Specific Soil Management in Ayiba Watershed, Northern Highlands of Ethiopia

Seifu

Elias

Gebresamuel

et al. 2023

Applied and Environmental Soil Science

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Digital mapping of the soil available water capacity: tool for the resilience of agricultural systems to climate change

Gomez

Lier

Silvero

et al. 2023

Science of The Total Environment

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A soil productivity system reveals most Brazilian agricultural lands are below their maximum potential

Greschuk,

Demattê,

Silvero

et al. 2023

Sci Rep

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Food production is extremely dependent on the soil. Brazil plays an important role in the global food production chain. Although only 30% of the total Brazilian agricultural areas are used for crop and livestock, the full soil production potential needs to be evaluated due to the environmental and legal impossibility to expand agriculture to new areas. A novel approach to assess the productive potential of soils, called “SoilPP” and based on soil analysis (0–100 cm) - which express its pedological information - and machine learning is presented. Historical yields of sugarcane and soybeans were analyzed, allowing to identify where it is still possible to improve crop yields. The soybean yields were below the estimated SoilPP in 46% of Brazilian counties and could be improved by proper management practices. For sugarcane, 38% of areas can be improved. This technique allowed us to understand and map the food yield situation over large areas, which can support farmers, consultants, industries, policymakers, and world food security planning.

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Digital soil mapping outputs on soil classification and sugarcane production in Brazil

Cited by 5 publications

References 55 publications

Characterization and Mapping of Soil-Landscape for Site-Specific Soil Management in Ayiba Watershed, Northern Highlands of Ethiopia

Characterization and Mapping of Soil-Landscape for Site-Specific Soil Management in Ayiba Watershed, Northern Highlands of Ethiopia

Digital mapping of the soil available water capacity: tool for the resilience of agricultural systems to climate change

A soil productivity system reveals most Brazilian agricultural lands are below their maximum potential

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