A5066340362- Soil Geostatistics and Mapping
- Spectroscopy and Chemometric Analyses
- Remote Sensing in Agriculture
- Geochemistry and Geologic Mapping
- Geography and Environmental Studies
- Leaf Properties and Growth Measurement
- Soil erosion and sediment transport
- Smart Agriculture and AI
- Sugarcane Cultivation and Processing
- Soil and Land Suitability Analysis
- Environmental and biological studies
- Mineral Processing and Grinding
- Remote Sensing and LiDAR Applications
- Soil Moisture and Remote Sensing
- Soil Carbon and Nitrogen Dynamics
- Image Processing and 3D Reconstruction
- Insect Pest Control Strategies
- Wood and Agarwood Research
- Agricultural and Food Sciences
- Natural Products and Biological Research
- Rural Development and Agriculture
- Soil Management and Crop Yield
- Hydrology and Watershed Management Studies
- Banana Cultivation and Research
- Genetics and Plant Breeding
Universidade de São Paulo
2014-2024
Forest Science and Research Institute
2024
Hospital Universitário da Universidade de São Paulo
2024
Universidade Metodista de São Paulo
2023
Coordenação de Aperfeicoamento de Pessoal de Nível Superior
2022
Fundação de Amparo à Pesquisa do Estado de São Paulo
2022
Escola Superior de Jornalismo
2012-2021
Secretaria de Agricultura e Abastecimento
2016
Methodist University of Piracicaba
2000-2010
Universidade Estadual do Oeste do Paraná
2004
Nitrogen is one of the essential nutrients for production agricultural crops, participating in a complex interaction among soil, plant and atmosphere. Therefore, its monitoring important both economically environmentally. The aim this work was to estimate leaf nitrogen contents sugarcane from hyperspectral reflectance data during different vegetative stages plant. assessments were performed an experiment designed completely randomized blocks, with increasing doses (0, 60, 120 180 kg ha
The total or partial removal of sugarcane (Saccharum spp. L.) straw for bioenergy production may deplete soil quality and consequently affect negatively crop yield. Plants with lower yield potential present concentration leaf-tissue nutrients, which in turn changes light reflectance canopy different wavelengths. Therefore, vegetation indexes, such as the normalized difference index (NDVI) associated nutrients could be a useful tool monitoring under management. Two sites São Paulo state,...
Digital soil mapping is an alternative for the recognition of classes in areas where pedological surveys are not available. The main aim this study was to obtain a digital map using artificial neural networks (ANN) and environmental variables that express soil-landscape relationships. This carried out area 11,072 ha located Barra Bonita municipality, state São Paulo, Brazil. A survey obtained from reference approximately 500 center studied. With units identified together with elevation,...
Objetivou-se neste trabalho caracterizar diferentes solos por espectrorradiometria de reflectância ao longo uma topossequência na região Piracicaba, SP. Amostras solo foram coletadas e analisadas em campo, laboratório análises químicas sensores Vis-NIR (400-2500 nm). Alterações nos da identificáveis nas informações espectrais. Constituintes dos solos, tais como, matéria orgânica, mineralogia, formas óxidos ferro granulometria determinantes variações das feições absorção intensidades...
Wet chemistry methods to extract soil properties such as Fe2O3, TiO2, MnO and clay are cost effective, time consuming environmental polluter. Moreover, a large set of samples has be collected for precise spatial mapping. Ordinary surface mapping is problematic method. Accordingly, non destructive technologies, remote sens- ing can provide important vantages. The objective the present work was estimate attributes by labora- tory orbital sensors compare these results with classification. study...
Nitrogen (N) is the main nutrient element that maintains productivity in forages; it inextricably linked to dry matter increase and plant support capacity. In recent years, high spectral spatial resolution remote sensors, e.g., European Space Agency (ESA)’s Sentinel satellite missions, have become freely available for agricultural science, proven be powerful monitoring tools. The use of vegetation indices has been essential crop biomass estimation models. objective this work test demonstrate...
The difference in the matrix present soil samples from different areas limits performance of nutrient analysis via XRF sensors, and only a few strategies to mitigate this effect ensure an accurate have been proposed so far. In context, research aimed compare predictive models, including simple linear regression (RS), multiple (MLR), partial least-squares (PLS), random forest (RF) models for prediction Ca K agricultural soils. RS were evaluated on data without (RS1) with (RS2) Compton...
ABSTRACT: This study applied spectroradiometry techniques with hyperspectral data to identify the correlations between sugarcane leaf reflectance and contents of Nitrogen (N), phosphorus (P), Potassium (K), Sulfur (S), Calcium (Ca) Magnesium (Mg). During harvests 2019/20 2020/21, was introduced nutritional stress by application limestone doses. Liming in a fractional way and, at end five years, amounts corresponded 0, 9, 15 21 t ha-1 dolomitic limestone. The state nutrients exponential...
Traditional soil analyses are time-consuming with high cost and environmental risks, thus the use of new technologies such as remote sensing have to be estimulated. The purpose this work was quantify attributes by laboratory orbital sensors a non-destructive non-pollutant method. study area in region Barra Bonita, state São Paulo, Brazil, 473 ha bare area. A sampling grid established (100 × 100 m), total 474 locations 948 samples. Each location georeferenced samples were collected for...
There is a consensus about the necessity to achieve quick soil spatial information with few human resources. Remote/proximal sensing and pedotransference are methods that can be integrated into this approach. On other hand, there still lack of strategies indicating on how put in practice, especially tropics. Thus, objective work was suggest strategy for prediction classes by using spectroscopy from ground laboratory spectra space images platform, as associated terrain attributes spectral...
Nitrogen management in crops is a key activity for agricultural production. Methods that can determine the levels of this element plants quick and non-invasive way are extremely important improving production systems. Within several fronts study on subject, proximal remote sensing methods promising techniques. In regard, research sought to demonstrate relationships between variations leaf nitrogen content (LNC) sugarcane spectral behaviour. The work was carried out three experimental areas...
Beans are the most widely used protein source in world and their productivity is directly linked to nitrogen (N). The short crop cycle imposes need for fast methodologies N quantification. In this work, we evaluated performance of four machine learning algorithms prediction using NIR spectroscopy. Increasing doses were applied plants leaf reflectance was collected. Weka software test algorithms. selection effective spectral zones made with VIP. Considering predictions whole NIR, best results...
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O objetivo deste trabalho foi desenvolver e avaliar um método para discriminação das classes de solos a partir suas respostas espectrais, utilizando-se sensor em laboratório. Os dados espectrais foram utilizados no desenvolvimento modelos estatísticos discriminar as uma área sudoeste do Estado São Paulo. Equações discriminantes desenvolvidas 18 classes. A resposta espectral obtida amostras da porção superficial subsuperficial dos estudo, num total 370 amostras. As coletadas 185 ha, com...
The objectives of this research were to: (i) develop hyperspectral narrow-band models to determine soil variables such as organic matter content (OM), sum cations (SC = Ca + Mg K), aluminum saturation (m%), (V%), exchangeable capacity (CEC), silt, sand and clay using visible-near infrared (Vis-NIR) diffuse reflectance spectra; (ii) compare the variations chemical spectroradiometric analysis (Vis-NIR). study area is located in São Paulo State, Brazil. soils sampled over an 473 ha divided into...
Although monitoring insect pest populations in the fields is essential crop management, it still a laborious and sometimes ineffective process. Imprecise decision-making an integrated management program may lead to control infested areas or excessive use of insecticides. In addition, high infestation levels diminish photosynthetic activity soybean, reducing their development yield. Therefore, we proposed that soybean could be identified classified field using hyperspectral proximal sensing....