Determination of organic matter in soils by FTIR/diffuse reflectance and multivariate calibration

Masserschmidt, I.; Cuelbas, C. J.; Poppi, R J; Andrade, Juliane Custódio de; Abreu, Cleide Aparecida de; Davanzo, Celso U.

doi:10.1002/(sici)1099-128x(199905/08)13:3/4<265::aid-cem552>3.3.co;2-5

Cited by 6 publications

(7 citation statements)

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“…This latter study was not restricted to agricultural soils as the previous studies (some of which included a number of samples similar to that of Reeves&Smith (2009) (2006) did not find a relationship between DRIFT spectra and phosphorous (R 2 <0.40). For organic matter, very good results were obtained using photoacoustic spectroscopy (Du et al 2007(Du et al , 2009b and DRIFT (Masserschmidt et al 1999), with R 2 values above 0.90 in all three studies. However, very poor correlation between DRIFT spectra and organic matter content was reported by Canasveras et al (2010).…”

Section: Estimation Of Soil Nutrients and Organic Mattermentioning

confidence: 99%

Application of FTIR Spectroscopy to Agricultural Soils Analysis

Linker¹

2011

Fourier Transforms - New Analytical Approaches and FTIR Strategies

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Section: Estimation Of Soil Nutrients and Organic Mattermentioning

confidence: 99%

Application of FTIR Spectroscopy to Agricultural Soils Analysis

Linker¹

2011

Fourier Transforms - New Analytical Approaches and FTIR Strategies

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“…A utilização do PLS juntamente com a DRIFT 41,[49][50][51][52][53][54][55][56] , no IV próximo ou médio, representa o último avanço na previsão de propriedades do solo. Sudduth e Hummel 41 construíram modelos com RLM, PCR e PLS, para prever MO no IV próximo, e concluíram que o PLS fornecia os melhores resultados.…”

Section: Determinação De Matéria Orgânica E Outras Propriedades Do Sounclassified

“…Masserschmidt et al 52 obtiveram ótimos resultados para a previsão de MO no IV médio. Este artigo chama a atenção para a importância da escolha da região espectral correta, a fim de eliminar interferências espectrais drásticas, e para o pré-tratamento dos dados.…”

Section: Determinação De Matéria Orgânica E Outras Propriedades Do Sounclassified

Avaliação do uso de métodos quimiométricos em análise de solos

Sena¹,

Poppi²,

Frighetto³

et al. 2000

Quím. Nova

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EVALUATION OF THE USE OF CHEMOMETRIC METHODS IN SOIL ANALYSIS. One of the major interests in soil analysis is the evaluation of its chemical, physical and biological parameters, which are indicators of soil quality (the most important is the organic matter).Besides there is a great interest in the study of humic substances and on the assessment of pollutants, such as pesticides and heavy metals, in soils. Chemometrics is a powerful tool to deal with these problems and can help soil researchers to extract much more information from their data. In spite of this, the presence of these kinds of strategies in the literature has obtained projection only recently. The utilization of chemometric methods in soil analysis is evaluated in this article. The applications will be divided in four parts (with emphasis in the first two): (i) descriptive and exploratory methods based on Principal Component Analysis (PCA); (ii) multivariate calibration methods (MLR, PCR and PLS); (iii) methods such as Evolving Factor Analysis and SIMPLISMA; and (iv) artificial intelligence methods, such as Artificial Neural Networks.Keywords: chemometrics; soil analysis; principal component analysis. DIVULGAÇÃO INTRODUÇÃOCom a crescente sofisticação das técnicas instrumentais de análise química, impulsionada pela invasão de microprocessadores e microcomputadores no laboratório, técnicas de tratamentos de dados mais complexas do ponto de vista matemáti-co e estatístico tornaram-se necessárias 1 . A análise de dados é uma parte essencial em todo experimento, sendo univariada quando somente uma variável é medida sistematicamente para várias amostras. Há muito tempo a estatística univariada vem sendo aplicada a problemas químicos, mas a sua utilização tornou-se limitada. Nas últimas décadas, a aná-lise multivariada foi introduzida no tratamento de dados quími-cos, ganhando rapidamente popularidade e dando origem a uma nova disciplina, batizada de Quimiometria. O modelo estatístico dos métodos multivariados considera a correlação entre muitas variáveis analisadas simultaneamente, permitindo a extração de uma quantidade muito maior de informação.Neste artigo será avaliada a utilização de métodos quimiométricos em análise de solos. O solo é uma estrutura complexa formada pela influência de fatores geológicos, topográficos, climáticos, temporais e antropogênicos; sendo a parte mais importante da geosfera e de onde provêm a maior parte dos nossos alimentos. Além disso, ele funciona como uma espécie de filtro ambiental para a purificação da água e do ar 2 . O interesse maior na análise de solos está na avaliação de seus parâmetros químicos (concentração de metais e nutrientes, pH, etc.), físicos (compactação, umidade, etc.) e biológicos (microrganismos, etc.), os quais são um indicador de sua qualidade. Dentre os constituintes do solo, o mais estudado é a matéria orgânica (MO). Esta controla muitas de suas propriedades e é um fator central na manutenção de sistemas agrícolas sustentá-veis. Práticas que favoreçam a conservação da MO melhoram as propriedades ...

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“…The use of predictive calibration models provides one means of disentangling this information and extracting both qualitative and quantitative information about lake sediments and the conditions that create them. MIRS is often used in soil science where predictive models enable a wide range of chemical parameters (Table 1) [17,[20][21][22][23][26][27][28][29][30] to be reliably determined more quickly and cheaply than traditional analyses [31,32]. Given that MIRS can be used to quantify a range of variables in dried soils, it should be equally suitable for inferring similar properties of dried lake sediments.…”

Section: Introductionmentioning

confidence: 99%

Mid-Infrared Spectroscopy as a Potential Tool for Reconstructing Lake Salinity

Cunningham

Tibby

Forrester

et al. 2016

Water

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Many aquatic ecosystems in Australia are impacted or threatened by salinisation; however, there is a paucity of records detailing the changes in salinity of individual water bodies that extend beyond a few decades. One way to overcome this issue is the use of inference models, which have typically been based on biological proxies. This pilot project investigates the potential for mid-infrared spectroscopy (MIRS) to provide an alternative method of reconstructing past salinity levels in Australian lakes. A small (19 lakes) calibration dataset was used to develop a MIRS-based lake water salinity inference model (measured vs. inferred salinity, based on leave-one-out cross-validation, R 2 = 0.64). This model and a previously published diatom-salinity model were both used to infer salinity levels in Tower Hill Lake in south-eastern Australia, over the last 60 years. Comparisons between these reconstructions and measured salinity data from Tower Hill Lake indicate that salinities inferred by the MIRS model more closely resembled the measured values than those produced using the diatom model, predominantly in terms of the actual values inferred, but also with regard to the trends observed. This supports the hypothesis that MIRS can provide a valuable new tool for reconstructing lake salinity.

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Determination of organic matter in soils by FTIR/diffuse reflectance and multivariate calibration

Cited by 6 publications

References 0 publications

Application of FTIR Spectroscopy to Agricultural Soils Analysis

Application of FTIR Spectroscopy to Agricultural Soils Analysis

Avaliação do uso de métodos quimiométricos em análise de solos

Mid-Infrared Spectroscopy as a Potential Tool for Reconstructing Lake Salinity

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