Coupling near infrared spectroscopy and chemometrics for food and drug authentication

Coupling near infrared spectroscopy and chemometrics for food and drug authentication

Federico Marini

Or better….

Marini - WSC8

Outline

• Nutritional quality of cereals• Food contamination by mycotoxins• Traceability of foodstuff• Quantification of nutrients in baby powdered milk• Determination of ee in drugs

Marini - WSC8

Nutritional quality of cereals

• Oat (Avena sativa) is considered one of the most important grain cereals for human consumption.

• Indeed, oat products are important sources of dietary fiber, β-glucan, good nutritional value proteins, vitamins and other components,which are demonstrated to be beneficial for human health.

• With the aim to assess the nutritive potential value in new naked oat genotypes during breeding work, this study focuses on the possibility of developing a rapid, accurate and precise alternative method for the simultaneous quantification of β-glucan and protein content in naked oat samples.

Marini - WSC8

The data set

• The whole data set comprises 168 naked oat samples from 12 varieties, originally coming from Italy and other European countries and being representative of a large genetic range.

• 166 samples analysed as flour by NIR spectroscopy• 54 samples analyzed as flour by NIT spectroscopy• 168 samples analyzed as whole grain by NIT spectroscopy

• Robust calibration models built by Partial Robust M-Regression

Marini - WSC8

Data set split

Marini - WSC8

NIR on flour -glucan

Marini - WSC8

Protein content

Did we need robust methods?

• The significant amount of weights <1 both for horizontal and vertical outlyingness is an indication that the choice of using robust calibration

Marini - WSC8

Results

• Reflectance measurements on flour seem to be the best experimental setup.

• However, a different test set was used in the three experiments.

• Model building repeated on a common data set.

Marini - WSC8

Comparison of the three spectroscopic setups

• Analysis was carried out only on the 54 samples analyzed by the three different spectroscopic approaches

• Clearer evidence of NIR on flour being the better setup

Marini - WSC8

Outline


Marini - WSC8

Micotoxin

• Micotoxins are products of secondary metabolism of pathogenic fungi

• They are among the highest impact contaminants for cereal cultures.

• Attention was focused on DON (a micotoxin produced by fungi of the species Fusarium)

• EU limit of 1750 ppb for wheat to be considered contaminated.

• NIR-based approach for quantification and/or assessment of the contamination status.

Marini - WSC8

Data set

• More than 150 samples analyzed at least in replicate by NIR and NIT.

• 45 samples left aside as independent test set.

Marini - WSC8

Calibration • Best pretreatment: MSC + 2nd derivative• RMSEC=17.63; RMSEP=17.82

Marini - WSC8

Classification • Best pretreatment: MSC + 2nd derivative• Classification accuracies:

– 96.4% Cont.; 92.5% non cont. (calibr)– 80% cont.; 100% non cont. (test)

Marini - WSC8

Outline


Marini - WSC8

Marini - WSC8

Traceability: introductionTraceability: introduction

• Labelling issues are of increasing concern.

• Growth and promotion of “added value” regional foods such as those produced under “Organic” and “Designated Origin” labels.

• Many labelling claims that relate to perceived added value are rarely supported by analytical data, leaving regulators to rely solely on paper auditing procedures to monitor compliance.

• Need for analytical specifications for labelling issues relating to food origin:– geographical origin,

– production origin

– species origin.

Marini - WSC8

Tracing the origin of foodstuffTracing the origin of foodstuff

• The assessment of the typicalness of a product and its traceability should imply an analytical method to determine the origin of the sample.

• Unfortunately, even if a great host of instrumental analytical techniques are at present under investigation, no one of those can be listed whose results can be directly related to the origin of the samples.

An alternative way to cope with this problem is to use mathematical and statistical methods (chemometrics) to process the results of a set of determination performed on the samples in order to obtain the desired classification.

Marini - WSC8

An example: olive oilAn example: olive oil

• Authentication of the origin of olive oil samples• 57 extra virgin olive oil samples

– 20 from Sabina, Lazio (13 harvested 2009, 7 harvested 2010)– 37 samples of different origin (22 from 2009, 15 from 2010

• MIR and NIR spectra recorded on each sample

Training/test set selection• Duplex algorithm repeated class-wise on each pretreatment separately

(Split ratio: 2/1)• Data selected more than 10 times (out of 15) in test set

Marini - WSC8

PLS-DA on MIR data

• Best results with MSC + quadratic bl.• %cc on test set: 85.7% (sabina); 86.7% (other origins)

Marini - WSC8

PLS-DA on NIR data

• Best results in CV with 4 pretreatments.• %cc on test set (d1): 100% (sabina); 100% (other origins) • %cc on test set (other 3): 100% (sabina); 93.3% (other origins)

Marini - WSC8

Spectral interpretation

• All the spectral regions identified as relevant correspond to significant NIR features: – the bands at around 4450-5000 cm-1, which may be attributed to

combination bands of C=C and C-H stretching vibration of cis unsaturated fatty acids,

– the bands between 5650 and 6000 cm-1, due to the combination bands and first overtone of C-H of methylene of aliphatic groups of oil,

– and those between 7074 and 7180 cm-1, corresponding to C-H combination band of methylene.

Marini - WSC8

SIMCA on MIR data

Marini - WSC8

• Sensitivity decreases in CV.• Best model with d1 (based on geometric average of sens & spec)• Test set: 71.43% (sens.); 73.33% (spec.)

SIMCA on NIR data

Marini - WSC8

• Best model with det & MSC+d1 (based on geometric avg. of sens & spec)• Test set (det): 100% (sens.); 93.33% (spec.)• Test set (MSC+d1): 71.43% (sens.); 86.67% (spec.)

Effect of year (SIMCA NIR)

Marini - WSC8

• Best model with det, d1 & MSC+det• Models highly sensitive and specific in cal. &CV• Test set (2010 samples): high specificity, no sensitivity

Effect of year (Coomans)

Marini - WSC8

• If discriminant classification is sought, still a good classification ability could be obtained, notwithstanding the diversity

A second example: pistachio nuts

• The major pistachio-producing countries of the world are, in order, Iran, USA (California), Turkey, Syria, but to lesser extent, other countries cultivate pistachios as well, between these Italy and India.

• In Italy, only one variety (Bianca) is cultivated mainly in Bronte. • Italian production is very low in comparison to that of Asia and the

USA; however, it is compensated by the very high quality.• Each producing country’s applied tariff rates and national laws on

commodities vary dramatically. Therefore, pistachio variation in quality, food safety (e.g., contamination by aflatoxins), import/export fees, legal implications, and financial concerns makes determining the country of origin for pistachios important to protect the consumers against potential fraud, and there is a need to develop analytical methods to determine their geographical origin.

Marini - WSC8

Samples

• 483 pistachio samples from the 4 main producing countries + Italy and India were analyzed (NIR spectra recorded on both halves of nut and averaged)

Marini - WSC8

Country Nr. of samples

Italy (Bronte) 41

Iran 121

India 41

Syria 40

Turkey 120

USA 120

Training/test splitting

Marini - WSC8

Country Nr. of samples

Italy (Bronte) 22+19

Iran 83+38

India 23+18

Syria 25+15

Turkey 86+34

USA 81+39

PLS-DA modeling

Best model:

MSC+detrending

Marini - WSC8

Bronte India Iran Syria Turkey USA

Calibration 97.48% 96.82% 90.54% 96.47% 95.17% 99.79%

CV 97.32% 95.30% 89.48% 93.97% 93.15% 99.17%

Prediction 95.14% 91.29% 83.59% 93.63% 91.71% 99.19%

Bronte: red

India: blue

Iran: black

Syria: green

Turkey: cyan

USA: purple

Training set: empty

Test set: filled

Predictions

Marini - WSC8

VIP

Marini - WSC8

SIMCA

• Optimal complexity evaluated as those resulting in the best geometric average between sensitivity and specificity in CV

Marini - WSC8

SIMCA

• Best model: MSC+detrending

Marini - WSC8

Class Sensitivity (Cal)

Specificity (Cal)

Sensitivity (CV)

Specificity (CV)

Sensitivity (Pred)

Specificity (Pred)

Bronte 95.45% 95.64% 72.73% 95.30% 89.47% 96.53%

India 100.00% 90.57% 65.22% 93.60% 83.33% 98.62%

Iran 98.80% 68.35% 93.98% 67.93% 92.11% 76.80%

Syria 88.00% 88.81% 88.00% 87.46% 73.33 82.43%

Turkey 95.35% 79.06% 84.88% 80.77% 73.53% 80.62%

USA 93.83% 100.00% 85.19% 100.00% 87.18% 99.19%

SIMCA models

Marini - WSC8

Bronte in detail

Marini - WSC8

Outline

• Nutritional quality of cereals• Food contamination by mycotoxins• Traceability of foodstuff• Quantification of nutrients in baby powdered

milk• Determination of ee in drugs

Marini - WSC8

Quantification of nutrients in powdered milk for babies

• Baby powdered milk is a product based on milk of cows or other animals and/or other ingredients which have been proven to be suitable for infant feeding.

• The nutritional safety and adequacy should be scientifically demonstrated to support normal growth and development of infants.

• In addition to the compositional requirements, other ingredients may be added to ensure that the formulation is suitable as the sole source of nutrition for the infant, or to provide other benefits that are similar to outcomes of populations of breastfed babies.

• The suitability for the particular nutritional uses of infants and the safety of additional compounds added at the chosen levels shall be scientifically demonstrated.

Marini - WSC8

Samples

Marini - WSC8

• Preliminary results only on lipid content.

BiPLS

Marini - WSC8

….

• Spectral region is divided into intervals & PLS models are computed removing one interval at a time.

• Interval whose deletion results in lowest RMSECV is removed.• Procedure is iterated up to the desired number of retained variables

8 intervals1600 variables



Marini - WSC8

..

.....

.

.....

.

..........

.....

.crom

oso

mi

a b c d e1

n

evaluation of the fitness of chromosomes

ranking of chromosomes according to fitness

cross-over

mutation

new generation P(t+1)

Population of n chromosomes with m genes P(t)

stop

gen

era

tion

GA

BiPLS-GA

Marini - WSC8

Method RMSECV

No sel 1.41

BiPLS 0.96

BiPLS-GA 0.90

Outline


Marini - WSC8

Motivation

• Quite often only one enantiomeric form of an IPA is pharmacologically active.

• After cases such that of thalidomide, FDA recommends that the enantiomeric purity of pharmaceutical formulations is checked.

• Present methods:– Polarimetry– HPLC on chiral columns– NMR

• In this study the possiblity of using NIR+chemometrics to predict the enantiomeric excess of an IPA is studied.

Marini - WSC8

Ibuprofen: phase diagram

• Phase diagram confirms that ibuprofen crystalizes as a racemic mixture.

• This suggests that R and S have the same spectrum but both have a different spectrum than the racemate

Marini - WSC8

Ibuprofen: NIR spectra

Marini - WSC8

Ibuprofen: calibration & testing

• Best pretreatment: MSC + 2nd der• 4 LVs• RMSEC=2.11• RMSECV= 2.43• RMSEP=1.71

Marini - WSC8

Interpretation - VIP

• 4000-4800 cm-1: combination of bands from methylenic C-H and overtones of the bendings

• 6000 cm-1: First overtone of the aromatic C-H stretching and of asymmetric stretching of methyls

Marini - WSC8

Marini - WSC8

Coupling near infrared spectroscopy and chemometrics for food and drug authentication

Documents

Transcript of Coupling near infrared spectroscopy and chemometrics for food and drug authentication