Renata Andrade
Universidade Federal de Lavras
20 Papers
Renata Andrade is an academic researcher from Universidade Federal de Lavras. The author has contributed to research in topics: Environmental science & Soil test. The author has an hindex of 4, co-authored 6 publications.
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Papers
Prediction of soil fertility via portable X-ray fluorescence (pXRF) spectrometry and soil texture in the Brazilian Coastal Plains
Renata Andrade,Wilson Missina Faria,Sérgio Henrique Godinho Silva,Somsubhra Chakraborty,David C. Weindorf,Luiz Felipe Mesquita,Luiz Roberto Guimarães Guilherme,Nilton Curi +7 more
TL;DR: In this paper, the influence of soil management and mineralogy on elemental composition of soils and predict exchangeable Al3+, Ca2+, Mg2+, and available K+, and P contents from pXRF data alone and associated with soil texture through machine learning algorithms [stepwise generalized linear models (SGLM), and random forest (RF)] in soils of the Brazilian Coastal Plains (BCP).
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Assessing models for prediction of some soil chemical properties from portable X-ray fluorescence (pXRF) spectrometry data in Brazilian Coastal Plains
Renata Andrade,Sérgio Henrique Godinho Silva,David C. Weindorf,Somsubhra Chakraborty,Wilson Missina Faria,Luiz Felipe Mesquita,Luiz Roberto Guimarães Guilherme,Nilton Curi +7 more
TL;DR: In this paper, the authors used portable X-ray fluorescence (pXRF) spectrometry to characterize the Brazilian Coastal Plains (BCP) soils and assess four machine learning algorithms [ordinary least squares regression (OLS), cubist regression (CR), XGBoost (XGB), and random forest (RF)] for prediction of total nitrogen (TN), cation exchange capacity (CEC), and soil organic matter (SOM) using pXRF data.
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Proximal sensor data fusion and auxiliary information for tropical soil property prediction: Soil texture
Renata Andrade,Marco Mancini,Anita Fernanda dos Santos Teixeira,Sérgio Henrique Godinho Silva,David C. Weindorf,Somsubhra Chakraborty,Luiz Roberto Guimarães Guilherme,Nilton Curi +7 more
TL;DR: In this paper , the authors evaluated proximal sensor data for predicting soil particle size fractions and soil textural classes (both Family particle size classes and USDA soil texture triangle) via random forest algorithm in tropical regions.
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Proximal sensing applied to soil texture prediction and mapping in Brazil
Renata Andrade,Sérgio Henrique Godinho Silva,Wilson Missina Faria,Giovana Clarice Poggere,Julierme Zimmer Barbosa,Luiz Roberto Guimarães Guilherme,Nilton Curi +6 more
TL;DR: In this article, the feasibility of combining portable X-ray fluorescence (pXRF) spectrometry and magnetic susceptibility (MS) is evaluated for the prediction and mapping of soil texture (sand, silt, and clay contents) through random forest algorithm.
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Micronutrients prediction via pXRF spectrometry in Brazil: Influence of weathering degree
Renata Andrade,Sérgio Henrique Godinho Silva,David C. Weindorf,Somsubhra Chakraborty,Wilson Missina Faria,Luiz Roberto Guimarães Guilherme,Nilton Curi +6 more
TL;DR: In this paper, the authors used portable X-ray fluorescence (pXRF) spectrometry data for the prediction of available micronutrients in 1514 samples from variable soil classes (from Entisols to Oxisols) from seven Brazilian states using machine learning algorithms and to assess the influence of soil weathering degree on such prediction models.
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