Vis-Nir Spectrometry, Soil Phosphate Extraction Methods and Interactions of Soil Attributes

Oliveira, José Francirlei de; Brossard, Michel; Corazza, Edemar Joaquim; Marchão, Robélio Leandro; Vendrame, Pedro Rodolfo Siqueira; Brito, Osmar Rodrigues; Guimarães, María de Fátima

doi:10.5935/0100-4042.20150009

Cited by 5 publications

(7 citation statements)

References 3 publications

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“…Furthermore, low contents found in highly weathered soils (Oxisoil) might compromise even more its detection. The presence of high portion of organic P could improve the spectral response and allow better modeling performance, because organic compounds can be more easily excited by irradiation (Niederberger et al, 2015;Oliveira et al, 2015). However, most tropical soils present low organic matter content, as we found in our study (Table 1) and, therefore, tend to show low portion of organic P, limiting efficiency of soil spectroscopy.…”

Section: Quantification Of Soil P Availabilitymentioning

confidence: 67%

“…As sampling of a single plot experiment did not generate satisfactory results, since the only factor that changed between samples was the P content, we test-ed spatial sampling (Field-B), because the variation of other soil properties could allow the creation of predictive models from Vis-NIR spectra (Oliveira et al, 2015). However, this approach also showed limitations.…”

Section: Quantification Of Soil P Availabilitymentioning

confidence: 99%

“…The model was classified as E category by the RPD value (RPD values are shown in Figure 2), that is, with poor and unreliable performance to predict variables of interest (Viscarra Rossel et al, 2006). The main difficulties to obtain good prediction results of available P via spectroscopy are that this fraction is related to the soil solution and chemistry of the soil matrix (Janik et al, 1998) and does not present direct spectral response (Stenberg et al, 2010;Oliveira et al, 2015). Still, Coutinho et al (2019) argue that available level of P shows relationship with iron and aluminum oxyhydroxides in the soil, allowing its indirect prediction via spectroscopy.…”

Section: Quantification Of Soil P Availabilitymentioning

confidence: 99%

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Estimation of soil phosphorus availability via visible and near-infrared spectroscopy

Souza

Franco

Amaral

2020

Sci. agric. (Piracicaba, Braz.)

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Spectroscopic techniques have great potential to evaluate soil properties. However, there are still questions regarding the applicability of spectroscopy to analyze soil phosphorous (P) availability, especially in tropical soils with low nutrient contents. Therefore, this study evaluated the possibility to estimate P availability in soil and its pools (labile, moderately labile and non-labile) via Vis-NIR spectroscopy based on intra-field calibration. We used soils from two different locations, a plot experiment that received application of phosphate fertilizers (Field-A) and a cultivated field where a grid soil sampling was performed (Field-B). We used the technique of diffuse reflectance in the visible and near-infrared (Vis-NIR) to obtain the spectra of soil samples. Predictive modeling for P availability and labile, moderately labile and non-labile pools of P in soil were obtained via partial least squares (PLS) regression; classification modeling was performed via Soft Independent Modeling of Class Analogy (SIMCA) on three P availability levels in order to overcome the limitation on quantifying P via Vis-NIR spectroscopy. We found that isolating P contents as the only variable (Field-A), Vis-NIR spectroscopy does not allow estimating P pools in the soil. In addition, quantification of P available in the soil via predictive modeling has limitations in tropical soils. On the other hand, estimating P content in soil through classes of availability is a feasible and promising alternative.

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Section: Quantification Of Soil P Availabilitymentioning

confidence: 67%

Section: Quantification Of Soil P Availabilitymentioning

confidence: 99%

Section: Quantification Of Soil P Availabilitymentioning

confidence: 99%

See 1 more Smart Citation

Estimation of soil phosphorus availability via visible and near-infrared spectroscopy

Souza

Franco

Amaral

2020

Sci. agric. (Piracicaba, Braz.)

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“…A baixa eficiência da calibração do NIR para a predição do P-ext, extraído pelo Mehlich-1, pode estar relacionada à solubilização da matéria orgânica e outras reações químicas, durante o processo de extração pelo Mehlich-1, o que limita as correlações entre os espectros e a quantidade dessa fração de P nos solos (Oliveira et al, 2015).…”

Section: Resultsunclassified

“…Bogrekci & Lee (2006) e Maleki et al (2006) utilizaram a espectroscopia Vis-NIR para predizer a concentração de P obtida pelos métodos Olsen, lactato de amônio e Mehlich-1 em solos de clima temperado, e obtiveram boas correlações. Todavia, Vendrame et al (2012) e Oliveira et al (2015), em estudo sobre solos intemperizados da região do Cerrado, não obtiveram resultados satisfatórios para a predição dos teores de P extraível (Mehlich-1) e de P remanescente. Wu et al (2009) observaram, ainda, que a espectroscopia NIRS é fortemente dependente do tamanho das partículas, o que pode ocasionar a sobreposição de picos de absorção e dificultar a observação da relação entre os comprimentos de onda e os atributos de interesse (White & Roth, 1986).…”

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Predição de fósforo, carbono e nitrogênio em solos de basalto, por meio de espectroscopia NIR

Felix

Vendrame

Marchão

et al. 2016

Pesq. agropec. bras.

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Resumo -O objetivo deste trabalho foi avaliar o emprego da espectroscopia de infravermelho próximo (NIRS) para a predição de formas de P, C e N, em solos desenvolvidos de basalto, com uso de modelos multivariados e de amostras com diferentes granulometrias. Amostras de Latossolos e Nitossolos provenientes de áreas de cultivo, pastagem e vegetação nativa foram coletadas nas camadas de 0,0-0,20 e de 0,60-0,80 m, e analisadas quanto aos teores de P disponível, P remanescente, C orgânico, C total e N total. Os espectros na região entre 1.100 e 2.500 nm foram obtidos de amostras com granulometria menor do que 2,0 e 0,2 mm. Modelos multivariados de predição foram construídos e validados a partir dos resultados obtidos pelos métodos de referência e dos espectros. O peneiramento das amostras em malha de 0,2 mm melhorou a relação entre os comprimentos de onda no NIRS e os teores de C orgânico, C total e N total no solo, o que permitiu a obtenção de melhores modelos de calibração e predição para esses atributos. Independentemente do tamanho das partículas, os modelos não apresentam robustez, acurácia e precisão adequadas de predição para o P extraível e o P remanescente.Termos para indexação: Latossolos, Nitossolos, regressão por mínimos quadrados parciais, tamanho de partícula. Phosphorus, carbon, and nitrogen prediction in basaltic soils by NIR spectroscopyAbstract -The objective of this work was to evaluate the use of near-infrared spectroscopy (NIRS) to predict P, C, and N forms in soils developed from basalt, using multivariate models and soil samples with different granulometries. Samples from Oxisols and Alfisols from croplands, pasture, and native vegetation areas were collected at the 0.0-0.20 and 0.60-0.80-m soil layers, and analyzed for contents of available P, remaining P, organic C, total C, and total N. Spectra in the region between 1,100 and 2,500 nm were obtained on samples with granulometry smaller than 2.0 and 0.2 mm. Multivariate prediction models were constructed and validated from the results obtained by the reference methods and spectra. Sample screenings through 0.2 mm mesh improved the relationship between wavelengths in NIRS and the contents of organic C, total C, and total N in the soil, which allowed better calibration and prediction models for these attributes. Irrespectively of particle sizes, the models did not show appropriate robustness, accuracy, and precision for extractable P and remaining P. IntroduçãoTécnicas espectroscópicas por reflectância difusa têm-se mostrado promissoras para a predição das propriedades químicas do solo. De acordo com Chang et al. (2005), a espectroscopia no infravermelho próximo (NIRS) por reflectância é uma técnica rápida, não destrutiva, que pode ser utilizada para a caracterização e quantificação de propriedades em amostras sólidas. Além dessas vantagens, ela dispensa o emprego de reagentes no escopo da química verde.Entre as propriedades e atributos químicos mais estudados com a técnica NIRS na ciência do solo, podem-se destacar os conteúdos de C total e C or...

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Comment on “Potential of integrated field spectroscopy and spatial analysis for enhanced assessment of soil contamination: A prospective review” by Horta et al.

Baveye

Laba

2016

Geoderma

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Vis-Nir Spectrometry, Soil Phosphate Extraction Methods and Interactions of Soil Attributes

Cited by 5 publications

References 3 publications

Estimation of soil phosphorus availability via visible and near-infrared spectroscopy

Estimation of soil phosphorus availability via visible and near-infrared spectroscopy

Predição de fósforo, carbono e nitrogênio em solos de basalto, por meio de espectroscopia NIR

Comment on “Potential of integrated field spectroscopy and spatial analysis for enhanced assessment of soil contamination: A prospective review” by Horta et al.

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