29 research outputs found
Mapeamento das formas do relevo para estimativa de custos de fertilização em cana-de-açúcar
Use of corn height measured with an acoustic sensor improves yield estimation with ground based active optical sensors
AbstractCorn height measured manually has shown promising results in improving the relationship between active-optical (AO) sensor readings and crop yield. Manual measurement of corn height is not practical in US commercial corn production, so an alternative automatic method must be found in order to capture the benefit of including canopy height into in-season yield estimates and from there into in-season nitrogen (N) fertilizer applications. One existing alternative to measure canopy height is an acoustic height sensor. A commercial acoustic height sensor was utilized in these experiments at two corn growth stages (V6 and V12) along with AO sensors. Eight corn N rate sites in North Dakota, USA, were used to compare the acoustic height sensor as a practical alternative to manual height measurements as an additional parameter to increase the relationship between AO sensor readings and corn yield. Six N treatments, 0, 45, 90, 134, 179, and 224kgha−1, were applied before planting in a randomized complete block experimental design with four replications. Height measurement using the acoustic sensor provided an improved yield relationship compared to manual height at all locations. The level of improvement of the relationship between AO readings multiplied by acoustic sensor readings and yield was greater at V6 growth stage compared to the V12 growth stage. At V12, corn height measured manually and with the acoustic sensor multiplied by AO readings provided similar improvement to the relationship with yield compared to relating AO readings alone with yield at most locations. The acoustic height sensor may be useful in increasing the usefulness of AO sensor corn yield prediction algorithms for use in on-the-go in-season N application to corn particularly if the sensor height is normalized within site before combining multiple locations
Spring Wheat Response to Supplemental Nutrient Additions under Silty Clay Loam Soils of Minnesota
Updating North Carolina Corn Yields and Nitrogen Recommendations to Match Current Production Practices and New Hybrids
Variabilidade espacial de atributos químicos de um argissolo para aplicação de insumos à taxa variável em diferentes formas de relevo Spatial variability of chemical attributes in an alfisol for variable rates of inputs in different forms of relief
A agricultura de precisão implica análise da variabilidade espacial de fatores de produção e a aplicação de insumos de forma localizada. Várias são as causas que condicionam a variabilidade espacial dos solos, sendo o relevo um dos fatores mais importantes. O presente estudo teve por objetivo analisar a variabilidade espacial dos atributos químicos do solo e a elaboração de mapas de necessidade de aplicação de insumos de forma localizada, em áreas com diferentes formas de relevo. Duas parcelas de 1 ha cada foram delimitadas em áreas com topografia côncava e convexa. Foram retiradas, em cada área, 242 amostras de solos em 121 pontos, nas profundidades de solo de 0,00-0,20 m e 0,20-0,40 m. Os resultados de análise química foram submetidos às análises da estatística descritiva, geoestatística e interpolação por krigagem. A área convexa apresentou maior variabilidade espacial do solo em relação a área côncava. A adoção da agricultura de precisão possibilitou economia de aproximadamente 25 kg ha-1 de P2O5 na área côncava.<br>The precision agriculture implies an analysis of spatial variability of production factors and the inputs application of located form. There are several factors that cause spatial variability in soils; relief is one of the most important ones. The objective of this study was to analyze the spatial variability, the chemical attributes of the soil and the elaboration of maps necessity for input application of located form, in areas with different relief forms. Two parcels of one hectare each were delimited in areas with concave and convex shaped topography. A set of 242 samples were collected from each area at 121 points in depths of 0.00-0.20 m and 0.20-0.40 m. The data were submitted to the descriptive statistical analyses, geostatistics and interpolation for kriging. The convex area presented more spatial variability of the soil in relation the concave area. The adoption of precision agriculture made it possible to save approximately 25 kg ha-1 of P2O5 in the concave area