Rapid monitoring of grapevine reserves using ATR'FT-IR and chemometrics

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Abstract

Calibrations employing SVM-regression provided the optimum predictive models for nitrogen (R2 = 0.98 and RMSEP = 0.07%DW) compared to PLS regression (R2 = 0.97 and RMSEP = 0.08%DW). The best predictive models for starch was obtained using PLS regression (R2 = 0.95 and RSMEP = 1.43%DW) compared to SVR (R2 = 0.95; RMSEP = 1.56%DW). The RMSEP for both nitrogen and starch is below the reported seasonal flux for these analytes in Vitis vinifera. Nitrogen and starch concentrations in grapevine tissues can thus be accurately determined using ATR-FT-IR, providing a rapid method for monitoring vine reserve status under commercial grape production.Predictions of grapevine yield and the management of sugar accumulation and secondary metabolite production during berry ripening may be improved by monitoring nitrogen and starch reserves in the perennial parts of the vine. The standard method for determining nitrogen concentration in plant tissue is by combustion analysis, while enzymatic hydrolysis followed by glucose quantification is commonly used for starch. Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FT-IR) combined with chemometric modelling offers a rapid means for the determination of a range of analytes in powdered or ground samples. ATR-FT-IR offers significant advantages over combustion or enzymatic analysis of samples due to the simplicity of instrument operation, reproducibility and speed of data collection. In the present investigation, 1880 root and wood samples were collected from Shiraz, Semillon and Riesling vineyards in Australia and Germany. Nitrogen and starch concentrations were determined using standard analytical methods, and ATR-FT- IR spectra collected for each sample using a Bruker Alpha instrument. Samples were randomly assigned to either calibration or test data sets representing two thirds and one third of the samples respectively. Signal preprocessing included extended multiplicative scatter correction for water and carbon dioxide vapour, standard normal variate scaling with second derivative and variable selection prior to regression. Excellent predictive models for percent dry weight (DW) of nitrogen (range 0.10'2.65%DW, median 0.45%DW) and starch (range 0.25'42.82%DW, median 7.77%DW) using partial least squares (PLS) or support vector machine (SVM) analysis for linear and nonlinear regression respectively, were constructed and cross validated with low root mean square errors of prediction (RMSEP).
Original languageEnglish
Pages (from-to)16-25
Number of pages10
JournalAnalytica Chimica Acta
Volume732
DOIs
Publication statusPublished - 2012

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Starch
Nitrogen
starch
Mean square error
Weights and Measures
Monitoring
monitoring
nitrogen
Fourier Transform Infrared Spectroscopy
prediction
Least-Squares Analysis
FTIR spectroscopy
reflectance
Support vector machines
vine
Vitis
Calibration
Tissue
Enzymatic hydrolysis
combustion

Cite this

@article{58231ced15fc4edbbfbd24e94e872f2d,
title = "Rapid monitoring of grapevine reserves using ATR'FT-IR and chemometrics",
abstract = "Calibrations employing SVM-regression provided the optimum predictive models for nitrogen (R2 = 0.98 and RMSEP = 0.07{\%}DW) compared to PLS regression (R2 = 0.97 and RMSEP = 0.08{\%}DW). The best predictive models for starch was obtained using PLS regression (R2 = 0.95 and RSMEP = 1.43{\%}DW) compared to SVR (R2 = 0.95; RMSEP = 1.56{\%}DW). The RMSEP for both nitrogen and starch is below the reported seasonal flux for these analytes in Vitis vinifera. Nitrogen and starch concentrations in grapevine tissues can thus be accurately determined using ATR-FT-IR, providing a rapid method for monitoring vine reserve status under commercial grape production.Predictions of grapevine yield and the management of sugar accumulation and secondary metabolite production during berry ripening may be improved by monitoring nitrogen and starch reserves in the perennial parts of the vine. The standard method for determining nitrogen concentration in plant tissue is by combustion analysis, while enzymatic hydrolysis followed by glucose quantification is commonly used for starch. Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FT-IR) combined with chemometric modelling offers a rapid means for the determination of a range of analytes in powdered or ground samples. ATR-FT-IR offers significant advantages over combustion or enzymatic analysis of samples due to the simplicity of instrument operation, reproducibility and speed of data collection. In the present investigation, 1880 root and wood samples were collected from Shiraz, Semillon and Riesling vineyards in Australia and Germany. Nitrogen and starch concentrations were determined using standard analytical methods, and ATR-FT- IR spectra collected for each sample using a Bruker Alpha instrument. Samples were randomly assigned to either calibration or test data sets representing two thirds and one third of the samples respectively. Signal preprocessing included extended multiplicative scatter correction for water and carbon dioxide vapour, standard normal variate scaling with second derivative and variable selection prior to regression. Excellent predictive models for percent dry weight (DW) of nitrogen (range 0.10'2.65{\%}DW, median 0.45{\%}DW) and starch (range 0.25'42.82{\%}DW, median 7.77{\%}DW) using partial least squares (PLS) or support vector machine (SVM) analysis for linear and nonlinear regression respectively, were constructed and cross validated with low root mean square errors of prediction (RMSEP).",
keywords = "Open access version available, Fourier transform infrared spectroscopy, Nitrogen, Starch, Vine reserves, Vitis vinifera",
author = "Leigh Schmidtke and Jason Smith and Markus Muller and Bruno Holzapfel",
note = "Imported on 12 Apr 2017 - DigiTool details were: Journal title (773t) = Analytica Chimica Acta. ISSNs: 0003-2670;",
year = "2012",
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journal = "Analytica Chimica Acta",
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Rapid monitoring of grapevine reserves using ATR'FT-IR and chemometrics. / Schmidtke, Leigh; Smith, Jason; Muller, Markus; Holzapfel, Bruno.

In: Analytica Chimica Acta, Vol. 732, 2012, p. 16-25.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Rapid monitoring of grapevine reserves using ATR'FT-IR and chemometrics

AU - Schmidtke, Leigh

AU - Smith, Jason

AU - Muller, Markus

AU - Holzapfel, Bruno

N1 - Imported on 12 Apr 2017 - DigiTool details were: Journal title (773t) = Analytica Chimica Acta. ISSNs: 0003-2670;

PY - 2012

Y1 - 2012

N2 - Calibrations employing SVM-regression provided the optimum predictive models for nitrogen (R2 = 0.98 and RMSEP = 0.07%DW) compared to PLS regression (R2 = 0.97 and RMSEP = 0.08%DW). The best predictive models for starch was obtained using PLS regression (R2 = 0.95 and RSMEP = 1.43%DW) compared to SVR (R2 = 0.95; RMSEP = 1.56%DW). The RMSEP for both nitrogen and starch is below the reported seasonal flux for these analytes in Vitis vinifera. Nitrogen and starch concentrations in grapevine tissues can thus be accurately determined using ATR-FT-IR, providing a rapid method for monitoring vine reserve status under commercial grape production.Predictions of grapevine yield and the management of sugar accumulation and secondary metabolite production during berry ripening may be improved by monitoring nitrogen and starch reserves in the perennial parts of the vine. The standard method for determining nitrogen concentration in plant tissue is by combustion analysis, while enzymatic hydrolysis followed by glucose quantification is commonly used for starch. Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FT-IR) combined with chemometric modelling offers a rapid means for the determination of a range of analytes in powdered or ground samples. ATR-FT-IR offers significant advantages over combustion or enzymatic analysis of samples due to the simplicity of instrument operation, reproducibility and speed of data collection. In the present investigation, 1880 root and wood samples were collected from Shiraz, Semillon and Riesling vineyards in Australia and Germany. Nitrogen and starch concentrations were determined using standard analytical methods, and ATR-FT- IR spectra collected for each sample using a Bruker Alpha instrument. Samples were randomly assigned to either calibration or test data sets representing two thirds and one third of the samples respectively. Signal preprocessing included extended multiplicative scatter correction for water and carbon dioxide vapour, standard normal variate scaling with second derivative and variable selection prior to regression. Excellent predictive models for percent dry weight (DW) of nitrogen (range 0.10'2.65%DW, median 0.45%DW) and starch (range 0.25'42.82%DW, median 7.77%DW) using partial least squares (PLS) or support vector machine (SVM) analysis for linear and nonlinear regression respectively, were constructed and cross validated with low root mean square errors of prediction (RMSEP).

AB - Calibrations employing SVM-regression provided the optimum predictive models for nitrogen (R2 = 0.98 and RMSEP = 0.07%DW) compared to PLS regression (R2 = 0.97 and RMSEP = 0.08%DW). The best predictive models for starch was obtained using PLS regression (R2 = 0.95 and RSMEP = 1.43%DW) compared to SVR (R2 = 0.95; RMSEP = 1.56%DW). The RMSEP for both nitrogen and starch is below the reported seasonal flux for these analytes in Vitis vinifera. Nitrogen and starch concentrations in grapevine tissues can thus be accurately determined using ATR-FT-IR, providing a rapid method for monitoring vine reserve status under commercial grape production.Predictions of grapevine yield and the management of sugar accumulation and secondary metabolite production during berry ripening may be improved by monitoring nitrogen and starch reserves in the perennial parts of the vine. The standard method for determining nitrogen concentration in plant tissue is by combustion analysis, while enzymatic hydrolysis followed by glucose quantification is commonly used for starch. Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FT-IR) combined with chemometric modelling offers a rapid means for the determination of a range of analytes in powdered or ground samples. ATR-FT-IR offers significant advantages over combustion or enzymatic analysis of samples due to the simplicity of instrument operation, reproducibility and speed of data collection. In the present investigation, 1880 root and wood samples were collected from Shiraz, Semillon and Riesling vineyards in Australia and Germany. Nitrogen and starch concentrations were determined using standard analytical methods, and ATR-FT- IR spectra collected for each sample using a Bruker Alpha instrument. Samples were randomly assigned to either calibration or test data sets representing two thirds and one third of the samples respectively. Signal preprocessing included extended multiplicative scatter correction for water and carbon dioxide vapour, standard normal variate scaling with second derivative and variable selection prior to regression. Excellent predictive models for percent dry weight (DW) of nitrogen (range 0.10'2.65%DW, median 0.45%DW) and starch (range 0.25'42.82%DW, median 7.77%DW) using partial least squares (PLS) or support vector machine (SVM) analysis for linear and nonlinear regression respectively, were constructed and cross validated with low root mean square errors of prediction (RMSEP).

KW - Open access version available

KW - Fourier transform infrared spectroscopy

KW - Nitrogen

KW - Starch

KW - Vine reserves

KW - Vitis vinifera

U2 - 10.1016/j.aca.2011.10.055

DO - 10.1016/j.aca.2011.10.055

M3 - Article

VL - 732

SP - 16

EP - 25

JO - Analytica Chimica Acta

JF - Analytica Chimica Acta

SN - 0003-2670

ER -