Studies about soil electrical conductivity measurements

A condutividade elétrica é a capacidade que um material possui em conduzir corrente elétrica, e uma das suas utilidades na agricultura provém do fato de que a massa do solo com sua variabilidade na composição físico-química apresenta diferentes níveis de condutividade elétrica (CE). O objetivo do presente trabalho foi estudar o comportamento da CE no solo e avançar no entendimento dos fatores que regem seus níveis de variação e desenvolver sistemas que permitam a mensuração contínua da CE do solo para a geração de mapas. Construiu-se um sistema com várias configurações de mensuração da CE e, nas avaliações em campo, os resultados foram parcialmente satisfatórios. Num estudo detalhado utilizando apenas um sistema comercial para sua mensuração, obteve-se a indicação clara de que a CE responde às variações na textura do solo e em seus teores de umidade, o que demonstra o potencial que ela tem como ferramenta para facilitar e baratear o processo de obtenção de dados para a caracterização física dos solos.The electric conductivity is the capacity of a material in driving electric current and one of its usefulness in the agriculture comes from the fact that the soil electrical conductivity (EC) varies with its intrinsic physicochemical variability. The objective of this work was to study the EC behavior and advance on the factors understanding that affects its variability, and develops systems for measuring and mapping EC. We built a system with several measurement configurations, and on the field tests the results were partially satisfactory. In a detailed study using only a commercial EC measuring equipment the results clearly indicated that EC relates with soil texture and moisture, and may represent an important and low price tool for collecting data and characterizing soil physical properties.CNPqFAPES

Spatial variability of vegetation index and soil properties in an integrated crop-livestock system

The knowledge of soil property spatial variability is useful for determining the rational use of inputs, such as the site-specific application of lime and fertilizer. The objective of this study was to evaluate the vegetation index and spatial variability of physical and chemical soil properties in an integrated crop-livestock system (ICLS). Soil samples were taken from a 6.9 ha area in a regular hexagon grid at 0-0.20 m depths. Soil P, K, Ca, Mg, and cation exchange capacity - CEC; base saturation; clay and sand were analyzed. Soil electrical conductivity (ECa) was measured with a contact sensor. The site was evaluated at the end of the corn season (April) and during forage production (October) using Landsat 5 images, remote sensing techniques and a geographic information system (GIS). Results showed that the normalized difference vegetation index (NDVI) was associated with ECa and soil parameters, indicating crop and pasture variations in the ICLS. Geostatistics and GIS were effective tools for collecting data regarding the spatial variability of soil and crop indicators, identifying variation trends in the data, and assisting data interpretation to determine adequate management strategies.201

Spatial variability of vegetation index and soil properties in an integrated crop-livestock system

ABSTRACT The knowledge of soil property spatial variability is useful for determining the rational use of inputs, such as the site-specific application of lime and fertilizer. The objective of this study was to evaluate the vegetation index and spatial variability of physical and chemical soil properties in an integrated crop-livestock system (ICLS). Soil samples were taken from a 6.9 ha area in a regular hexagon grid at 0-0.20 m depths. Soil P, K, Ca, Mg, and cation exchange capacity - CEC; base saturation; clay and sand were analyzed. Soil electrical conductivity (ECa) was measured with a contact sensor. The site was evaluated at the end of the corn season (April) and during forage production (October) using Landsat 5 images, remote sensing techniques and a geographic information system (GIS). Results showed that the normalized difference vegetation index (NDVI) was associated with ECa and soil parameters, indicating crop and pasture variations in the ICLS. Geostatistics and GIS were effective tools for collecting data regarding the spatial variability of soil and crop indicators, identifying variation trends in the data, and assisting data interpretation to determine adequate management strategies

Zonal Application of Plant Growth Regulator in Cotton to Reduce Variability and Increase Yield in a Highly Variable Field

Variable-rate application has great potential to reduce variability and increase yield by spatially optimizing agricultural inputs. In cotton, plant growth regulators (PGRs) control excessive growth and provide suitable plant height for harvest operations. This study evaluates the effect of variable-rate PGR application compared to constant-rate application to reduce yield spatial variability and increase yield. The variable-rate approach was carried out in 2020 based on zonal applications defined by clustering analysis using soil electrical conductivity, vegetation indexes, and yield maps. Application doses and timings were determined by integrating plant height measurements for the whole field in 2019 and by zone in 2020. To compare the two procedures, cultivar and plant populations were kept constant; fertilization and accumulated rain were similar in both seasons. A reduction in yield spatial variability due to the zonal application was observed, with yield coefficient of variation (CV) decreasing from 18% in 2019 to 12% in 2020. Spatial and temporal analysis of Normalized Difference Vegetation Index satellite images showed higher CV values in 2019 (constant-rate) reaching 30% at the end of the season, whereas in 2020 (variable-rate) CV was constant (approximately 10%). Cotton yield increased from 3.5 to 4.3 t ha-1 between 2019 and 2020, which can be partially attributed to the variable-rate approach. The variable-rate approach based on application zones and plant height measurements was a viable strategy for reducing yield spatial variability and likely increasing yield in a highly variable cotton field