Prediction of Parameters (Soluble Solid and pH) in Intact Plum using NIR Spectroscopy and Wavelength Selection

Costa, Rosangela Câmara; Lima, Kássio M. G.

doi:10.5935/0103-5053.20130172

Cited by 3 publications

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“…45 Jaiswal et al 35 using NIR and PLS regression to determine the soluble solids content in bananas found correlation coefficient values of 0.88 and 0.81 for calibration and validation, respectively. Already Costa and Lima 46 determined the soluble solids content in plums by PLS regression finding a correlation value of 0.95 for the prediction set data. However, to date, no study was found in which this property has been determined in green coffee samples.…”

Section: Who Determined Greenmentioning

confidence: 99%

Evaluation of chemical properties of intact green coffee beans using near‐infrared spectroscopy

et al. 2020

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BACKGROUND: The chemical compounds in coffee are important indicators of quality. Its composition varies according to several factors related to the planting and processing of coffee. Thus, this study proposed to use near-infrared spectroscopy (NIR) associated with partial least squares (PLS) regression to estimate quickly some chemical properties (moisture content, soluble solids, and total and reducing sugars) in intact green coffee samples. For this, 250 samples produced in Brazil were analyzed in the laboratory by the standard method and also had their spectra recorded. RESULTS: The calibration models were developed using PLS regression with cross-validation and tested in a validation set. The models were elaborated using original spectra and preprocessed by five different mathematical methods. These models were compared in relation to the coefficient of determination, root mean square error of cross-validation (RMSECV), root mean square error of test set validation (RMSEP), and ratio of performance to deviation (RPD) and demonstrated different predictive capabilities for the chemical properties of coffee. The best model was obtained to predict grain moisture and the worst performance was observed for the soluble solids model. The highest determination coefficients obtained for the samples in the validation set were equal to 0.810, 0.516, 0.694 and 0.781 for moisture, soluble solids, total sugar, and reducing sugars, respectively. CONCLUSION:The statistics associated with these models indicate that NIR technology has the potential to be applied routinely to predict the chemical properties of green coffee, and in particular, for moisture analysis. However, the soluble solid and total sugar content did not show high correlations with the spectroscopic data and need to be improved.

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Section: Who Determined Greenmentioning

confidence: 99%

Evaluation of chemical properties of intact green coffee beans using near‐infrared spectroscopy

et al. 2020

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“…This method can be summarized in five sequential steps: (1) an informative vector or a combination of more than one is obtained from a PLS model; (2) variables are differentiated according to their absolute values in the informative vector; (3) they are sorted in descending order; (4) regression models are built and evaluated by leave- N -out cross-validation; an initial variable window is selected; and increments are added; and (5) variable sets are compared on the basis of quality parameters of cross-validation, such as root-mean-square error of cross-validation (RMSECV) and correlation coefficient. OPS has been applied for optimizing multivariate calibration models obtained from spectrofluorimetric, Raman, and NIR , spectra, chromatographic signals, and quantitative structure–activity relationship problems …”

Section: Introductionmentioning

confidence: 99%

Use of Near-Infrared Spectroscopy, Partial Least-Squares, and Ordered Predictors Selection To Predict Four Quality Parameters of Sweet Sorghum Juice Used To Produce Bioethanol

et al. 2016

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Sweet sorghum juice is gaining importance as a raw material for the first-generation ethanol production in the period between harvests of sugar cane. Breeding programs are seeking to improve sorghum quality to increase productivity, what has generated an excessive number of samples to be analyzed. Thus, the aim of this paper was to develop rapid and low-cost methods based on partial least-squares (PLS) and near-infrared spectroscopy (NIRS) for the determination of four quality chemical parameters of sweet sorghum. Spectra were recorded with a transflectance accessory, and robust models were built with 500 samples obtained from more than 200 hybrids and inbred strains. Optimization by variable selection was carried out with ordered predictors selection (OPS), providing simpler, more interpretable and predictive multivariate calibration models. The methods were developed in the working ranges of 5.5−18.1°Brix, 1.2−5.2%, 0.3−13.0%, and 9.8−83.0% for degrees Brix, reducing sugars, polarizable sugars, and apparent purity, respectively. Root-mean-square errors of prediction (RMSEP) of 0.3°B rix, 0.3%, 0.6%, and 5.3% were obtained for these four parameters, respectively. Finally, a complete multivariate analytical validation was carried out, and the methods were considered linear, accurate, sensitive, and without bias.

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Determinação Simultânea De Antocianinas E Compostos Fenólicos Totais Em Frutos Intactos De Jambo (Eugenia Malaccensis) Empregando a Espectroscopia No Infravermelho Próximo (Nir) E Regressão Por Mínimos Quadrados Parciais (Pls2)

Viegas¹,

Duarte²,

Monteiro³

et al. 2015

Anais Do XX Congresso Brasileiro De Engenharia Química

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Prediction of Parameters (Soluble Solid and pH) in Intact Plum using NIR Spectroscopy and Wavelength Selection

Cited by 3 publications

References 0 publications

Evaluation of chemical properties of intact green coffee beans using near‐infrared spectroscopy

Evaluation of chemical properties of intact green coffee beans using near‐infrared spectroscopy

Use of Near-Infrared Spectroscopy, Partial Least-Squares, and Ordered Predictors Selection To Predict Four Quality Parameters of Sweet Sorghum Juice Used To Produce Bioethanol

Determinação Simultânea De Antocianinas E Compostos Fenólicos Totais Em Frutos Intactos De Jambo (Eugenia Malaccensis) Empregando a Espectroscopia No Infravermelho Próximo (Nir) E Regressão Por Mínimos Quadrados Parciais (Pls2)

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