• Application of class-modelling techniques to near infrared data for food authentication purposes

      Oliveri, P.; Di Egidio, V.; Woodcock, T.; Downey, Gerard; European Union (Elsevier, 2011)
      Following the introduction of legal identifiers of geographic origin within Europe, methods for confirming any such claims are required. Spectroscopic techniques provide a method for rapid and non-destructive data collection and a variety of chemometric approaches have been deployed for their interrogation. In this present study, class-modelling techniques (SIMCA, UNEQ and POTFUN) have been deployed after data compression by principal component analysis for the development of class-models for a set of olive oil and honey. The number of principal components, the confidence level and spectral pre-treatments (1st and 2nd derivative, standard normal variate) were varied, and a strategy for variable selection was tried. Models were evaluated on a separate validation sample set. The outcomes are reported and criteria for selection of the most appropriate models for any given application are discussed.
    • Assessment of physico-chemical traits related to eating quality of young dairy bull beef at different ageing times using Raman spectroscopy and chemometrics

      Nian, Yingqun; Zhao, Ming; O'Donnell, Colm P.; Downey, Gerard; Kerry, Joseph P.; Allen, Paul; Teagasc Walsh Fellowship Programme (Elsevier, 2017-06-27)
      Raman spectroscopy and chemometrics were investigated for the prediction of eating quality related physico-chemical traits of Holstein-Friesian bull beef. Raman spectra were collected on the 3rd, 7th and 14th days post-mortem. A frequency range of 1300–2800 cm− 1 was used for partial least squares (PLS) modelling. PLS regression (PLSR) models for the prediction of WBSF and cook loss achieved an R2CV of 0.75 with RMSECV of 6.82 N and an R2CV of 0.77 with RMSECV of 0.97%w/w respectively. For the prediction of intramuscular fat, moisture and crude protein content, R2CV values were 0.85, 0.91 and 0.70 with RMSECV of 0.52%w/w, 0.39%w/w and 0.38%w/w respectively. An R2CV of 0.79 was achieved for the prediction of both total collagen and hydroxyproline content, while for collagen solubility the R2CV was 0.88. All samples (100%) from 15- and 19-month old bulls were correctly classified using PLS discriminant analysis (PLS-DA), while 86.7% of samples from different muscles (longissimus thoracis, semitendinosus and gluteus medius) were correctly classified. In general, PLSR models using Raman spectra on the 3rd day post-mortem had better prediction performance than those on the 7th and 14th days. Raman spectroscopy and chemometrics have potential to assess several beef physical and chemical quality traits.
    • Confirmation of brand identity of a Trappist beer by mid-infrared spectroscopy coupled with multivariate data analysis

      Engel, J.; Blanchet, L.; Buydens, L.M.C.; Downey, Gerard; European Union (Elsevier, 2012)
      Authentication of foods is of importance both to consumers and producers for e.g. confidence in label descriptions and brand protection respectively. The authentication of beers has received limited attention and in most cases only small data sets were analysed. In this study, Fourier-transform infrared attenuated total reflectance (FT-IR ATR) spectroscopy was applied to a set of 267 beers (53 different brands) to confirm claimed identity for samples of a single beer brand based on their spectral profiles. Skewness-adjusted robust principal component analysis (ROBPCA) was deployed to detect outliers in the data. Subsequently, extended canonical variates analysis (ECVA) was used to reduce the dimensionality of the data while simultaneously achieving maximum class separation. Finally, the reduced data were used as inputs to various linear and non-linear classifiers. Work focused on the specific identification of Rochefort 8º (a Trappist beer) and both direct and indirect (using an hierarchical approach) identification strategies were studied. For the classification problems Rochefort versus non-Rochefort, Rochefort 8º versus non-Rochefort 8º and Rochefort 8º versus Rochefort 6º and 10º, correct prediction abilities of 93.8%, 93.3% and 97.3% respectively were achieved.
    • Detection and quantification of apple adulteration in diluted and sulphited strawberry and raspberry purées using visible and near infrared spectroscopy

      Downey, Gerard; Kelly, J. Daniel; Department of Agriculture, Food and the Marine (American Chemical Society, 2003)
      Adulteration of sulphited strawberry and raspberry purées by apple is a commercial problem. Strawberry (n=31) and raspberry (n=30) purées were prepared from Irish-grown fruit and adulterated at levels of 10-75% w/w using cooking apples. Visible and near infrared transflectance spectra were recorded using a 0.1 mm sample thickness. Classification and quantification models were developed using raw and scatter-corrected and/or derivatised spectral data. Classification as pure strawberry or raspberry was attempted using soft independent modelling of class analogy (SIMCA). The best models used spectral data in the wavelength ranges 400-1098 nm (strawberry) and 750-1098 nm (raspberry) and produced total correct classification rates of 75% (strawberry) and 95% (raspberry). Quantification of apple content was performed using partial least squares (PLS) regression. Lowest predictive errors obtained were 11.3% (raspberry) and 9.0% (strawberry). These results were obtained using spectral data in the wavelength ranges 400-1880 and 1100-1880 nm respectively. These results suggest minimum detection levels of apple in soft fruit purées of approximately 25% and 20% w/w for raspberry and strawberry respectively.
    • Detection of adulteration in fresh and frozen beefburger products by beef offal using mid-infrared ATR spectroscopy and multivariate data analysis

      Zhao, Ming; Downey, Gerard; O'Donnell, Colm P.; Teagasc Walsh Fellowship Programme; Food Safety Authority of Ireland (Elsevier, 17/10/2013)
      A series of authentic and offal-adulterated beefburger samples was produced. Authentic product (36 samples) comprised either only lean meat and fat (higher quality beefburgers) or lean meat, fat, rusk and water (lower quality product). Offal adulterants comprised heart, liver, kidney and lung. Adulterated formulations (46 samples) were produced using a D-optimal experimental design. Fresh and frozen-then-thawed samples were modelled, separately and in combination, by a classification (partial least squares discriminant analysis) and class-modelling (soft independent modelling of class analogy) approach. With the former, 100% correct classification accuracies were obtained separately for fresh and frozen-then-thawed material. Separate class-models for fresh and frozen-then-thawed samples exhibited high sensitivities (0.94 to 1.0) but lower specificities (0.33 – 0.80 for fresh samples and 0.41 – 0.87 for frozen-then-thawed samples). When fresh and frozen-then-thawed samples were modelled together, sensitivity remained 1.0 but specificity ranged from 0.29 to 0.91. Results indicate a role for this technique in monitoring beefburger compliance to label.
    • Detection of offal adulteration in beefburgers using near infrared reflectance spectroscopy and multivariate modelling

      Zhao, Ming; O'Donnell, Colm P.; Downey, Gerard; Food Safety Authority of Ireland; Teagasc Walsh Fellowship Programme (IM Publications, 2013)
      The main aim of this study was to develop a rapid and reliable tool using near infrared (NIR) reflectance spectroscopy to confirm beefburger authenticity in the context of offal (kidney, liver, heart and lung) adulteration. An experimental design was used to develop beefburger formulations to simultaneously maximise the variable space describing offal-adulterated samples and minimise the number of experiments required. Authentic (n = 36) and adulterated (n = 46) beefburger samples were produced using these formulations. Classification models (partial least squares discriminant analysis, PLS1-DA) and class-modelling tools (soft independent modelling of class analogy, SIMCA) were developed using raw and pre-treated NIR reflectance spectra (850-1098 nm wavelength range) to detect authentic and adulterated beefburgers in (1) fresh, (2) frozen-then-thawed and (3) fresh or frozen-then-thawed states. In the case of authentic samples, the best PLS1-DA models achieved 100% correct classification for fresh, frozen-then-thawed and fresh or frozen-then-thawed samples. SIMCA models correctly identified all the fresh samples but not all the frozen-then-thawed and fresh or frozen-then-thawed samples. For the adulterated samples, PLS1-DA models correctly classified 95.5% of fresh, 91.3% of frozen-then-thawed and 88.9% of fresh or frozen-then-thawed beefburgers. SIMCA models exhibited specificity values of 1 for both fresh and frozen-then-thawed samples, 0.99 for fresh or frozen-then-thawed samples; sensitivity values of 1, 0.88 and 0.97 were obtained for fresh, frozen-then-thawed and fresh or frozen-then-thawed products respectively. Quantitative models (PLS1 regression) using both 850-1098 nm and 1100-2498 nm wavelength ranges were developed to quantify (1) offal adulteration and (2) added fat in adulterated beefburgers, both fresh and frozen-then-thawed. Models predicted added fat in fresh samples with acceptable accuracy (RMSECV = 2.0; RPD = 5.9); usefully-accurate predictions of added fat in frozen-then-thawed samples were not obtained nor was prediction of total offal possible in either sample form.
    • Feasibility Study on the Use of Visible–Near-Infrared Spectroscopy for the Screening of Individual and Total Glucosinolate Contents in Broccoli

      Hernandez-Hierro, Jose Miguel; Valverde, Juan; Villacreces, Salvador; Reilly, Kim; Gaffney, Michael; Gonzalez-Miret, Maria Lourdes; Heredia, Francisco J.; Downey, Gerard; Spanish MICINN; Junta de Andalucia; et al. (American Chemical Society, 11/07/2012)
      The potential of visible–near-infrared spectroscopy to determine selected individual and total glucosinolates in broccoli has been evaluated. Modified partial least-squares regression was used to develop quantitative models to predict glucosinolate contents. Both the whole spectrum and different spectral regions were separately evaluated to develop the quantitative models; in all cases the best results were obtained using the near-infrared zone between 2000 and 2498 nm. These models have been externally validated for the screening of glucoraphanin, glucobrassicin, 4-methoxyglucobrassicin, neoglucobrassicin, and total glucosinolates contents. In addition, discriminant partial least-squares was used to distinguish between two possible broccoli cultivars and showed a high degree of accuracy. In the case of the qualitative analysis, best results were obtained using the whole spectrum (i.e., 400–2498 nm) with a correct classification rate of 100% in external validation being obtained.
    • Image Processing of Outer-Product matrices - a new way to classify samples: Examples using visible/NIR/MIR spectral data.

      Jaillais, B.; Morrin, V.; Downey, Gerard (Elsevier, 2007)
      A chemometric analysis has been developed to emphasise the discrimination power of spectroscopic techniques such as near infrared, mid-infrared and visible spectroscopy. The combination of two spectral domains using outer product analysis (OPA) leads to the calculation of an outer product (OP) matrix. The representation of this matrix is called the "analytical fingerprint" of the samples and their classification is performed in the following steps. First, two different techniques are tested by subtracting the images one-by-one and the sum of all the elements of the resulting difference matrix gives a scalar, characteristic of the distance between the two images. Combining chemical analysis with image processing techniques provides an original approach to study butters and margarines in relation to their fat content. Best results were obtained with the OP matrix built from NIR and visible signals following the use of city block distance and average linkage. Samples were arranged in four groups: 100 %, 82-75 %, 70-59 % and 38-25 % w/w fat. The cophenetic correlation coefficient (validity of the cluster information generated by the linkage function) associated with these spectral data has a value of 0.973. Similar results were obtained using Ward's algorithm which generated four groups and a cophenetic correlation coefficient equal to 0.959.
    • Investigating the use of visible and near infrared spectroscopy to predict sensory and texture attributes of beef M. longissimus thoracis et lumborum

      Cafferky, Jamie; Sweeney, Torres; Allen, Paul; Sahar, Amna; Downey, Gerard; Cromie, A. R.; Hamill, Ruth; Department of Agriculture, Food and the Marine; 11/SF/311 (Elsevier, 2019-08-16)
      The aim of this study was to calibrate chemometric models to predict beef M. longissimus thoracis et lumborum (LTL) sensory and textural values using visible-near infrared (VISNIR) spectroscopy. Spectra were collected on the cut surface of LTL steaks both on-line and off-line. Cooked LTL steaks were analysed by a trained beef sensory panel as well as undergoing WBSF analysis. The best coefficients of determination of cross validation (R2CV) in the current study were for textural traits (WBSF = 0.22; stringiness = 0.22; crumbly texture = 0.41: all 3 models calibrated using 48 h post-mortem spectra), and some sensory flavour traits (fatty mouthfeel = 0.23; fatty after-effect = 0.28: both calibrated using 49 h post-mortem spectra). The results of this experiment indicate that VISNIR spectroscopy has potential to predict a range of sensory traits (particularly textural traits) with an acceptable level of accuracy at specific post-mortem times.
    • Near infra-red spectroscopy in the food industry: a tool for quality management

      Downey, Gerard (Teagasc, 1999-03)
      Near infrared (NIR) spectroscopy is a rapid, non-destructive analytical technique which has been used in the food and agriculture industries for almost 20 years. Ireland was one of the first countries in the world to adopt this method for national trading purposes and the grain trade has used it for off-farm and in-process analysis since 1981. However, other sectors have been slower to realise its potential and as part of a process of demonstrating the role which it may play in monitoring quality in a range of food industry applications, a programme of research and development has been on-going within Teagasc and its predecessor An Foras Talúntais.
    • Near Infrared Spectroscopy in the Food Industry: A Tool of Quality Management.

      Downey, Gerard (Teagasc, 01/03/1999)
      Near infrared (NIR) spectroscopy is a rapid, non-destructive analytical technique which has been used in the food and agriculture industries for almost 20 years. Ireland was one of the first countries in the world to adopt this method for national trading purposes and the grain trade has used it for off-farm and in-process analysis since 1981. However, other sectors have been slower to realise its potential and as part of a process of demonstrating the role which it may play in monitoring quality in a range of food industry applications, a programme of research and development has been on-going within Teagasc and its predecessor An Foras Talúntais. NIR spectroscopy provides the food processor with information. This information may describe how much of a given substance is present in a mixture or how the overall quality of the substance compares to a reference material e.g. a previous batch of raw material, finished goods or a competitor’s product. This report provides some examples of precompetitive R&D on representative qualitative and quantitative problems in a range of foods and food ingredients. The use of NIR spectra collected within 24 hours of slaughter to predict beef tenderness 14 days later shows considerable promise. Non-destructive monitoring of flesh composition in farmed salmon has paved the way for the efficient use of expensive feed materials while the content of each species in binary mixtures of minced beef and lamb has been accurate enough to suggest the use of NIR spectroscopy as a rapid screening tool by regulatory agencies, food processors and retailers. Classification of a range of food ingredients (including skim milk powder and flour) into one of a number of functionally-discrete categories has been successfully achieved with levels of accuracy high enough to warrant immediate industry utilisation i.e. greater than 90% for skim milk powders and 97% in the case of flour. Species confirmation in a number of raw minced meats (chicken, turkey, pork, beef and lamb) has been achieved with over 90% accuracy in feasibility studies. Calibrations transferred from one NIR instrument to another lose accuracy because of differences in instrument construction, sample presentation and other factors. A research effort has recently been applied to this problem of transferability and results are available for both scanning and fixed filter instruments. The success achieved opens the way for using NIR results obtained in different companies or countries as an uncontested basis for trade.
    • Observations on the water distribution and extractable sugar content in carrot slices after pulsed electric field treatment

      Aguilo-Aguayo, Ingrid; Downey, Gerard; Keenan, Derek F.; Lyng, James G.; Brunton, Nigel; Rai, Dilip K.; Department of Agriculture, Food and the Marine; Generalitat of Catalonia; Lifelong Learning Programme; FIRM 06/TNI/AFRC6; et al. (Elsevier, 13/06/2014)
      The impact of pulsed electric field (PEF) processing conditions on the distribution of water in carrot tissue and extractability of soluble sugars from carrot slices was studied. Time domain NMR relaxometry was used to investigate the water proton mobility in PEF-treated carrot samples. Three distinct transverse relaxation peaks were observed in untreated carrots. After PEF treatment only two slightly-overlapping peaks were found; these were attributed to water present in the cytoplasm and vacuole of carrot xylem and phloem tissues. This post-treatment observation indicated an increase in water permeability of tissues and/or a loss of integrity in the tonoplast. In general, the stronger the electric field applied, the lower the area representing transverse relaxation (T2) values irrespective of treatment duration. Moreover an increase in sucrose, β- and α-glucose and fructose concentrations of carrot slice extracts after PEF treatment suggested increases in both cell wall and vacuole permeability as a result of exposure to pulsed electric fields.
    • Performances of full cross-validation partial least squares regression models developed using Raman spectral data for the prediction of bull beef sensory attributes

      Zhao, Ming; Nian, Yingqun; Allen, Paul; Downey, Gerard; Kerry, Joseph P.; O’Donnell, Colm P.; Teagasc Walsh Fellowship Programme (Elsevier BV, 2018-04-23)
      The data presented in this article are related to the research article entitled “Application of Raman spectroscopy and chemometric techniques to assess sensory characteristics of young dairy bull beef” [1]. Partial least squares regression (PLSR) models were developed on Raman spectral data pre-treated using Savitzky Golay (S.G.) derivation (with 2nd or 5th order polynomial baseline correction) and results of sensory analysis on bull beef samples (n = 72). Models developed using selected Raman shift ranges (i.e. 250–3380 cm−1, 900–1800 cm−1 and 1300–2800 cm−1) were explored. The best model performance for each sensory attributes prediction was obtained using models developed on Raman spectral data of 1300–2800 cm−1.
    • Preliminary study on the use of near infrared hyperspectral imaging for quantitation and localisation of total glucosinolates in freeze-dried broccoli

      Hernandez-Hierro, Jose Miguel; Esquerre, Carlos; Valverde, Juan; Villacreces, Salvador; Reilly, Kim; Gaffney, Michael; Gonzalez-Miret, Maria Lourdes; Heredia, Francisco J.; O'Donnell, Colm P.; Downey, Gerard; et al. (Elsevier, 15/11/2013)
      The use of hyperspectral imaging to (a) quantify and (b) localise total glucosinolates in florets of a single broccoli species has been examined. Two different spectral regions (vis–NIR and NIR), a number of spectral pre-treatments and different mask development strategies were studied to develop the quantitative models. These models were then applied to freeze-dried slices of broccoli to identify regions within individual florets which were rich in glucosinolates. The procedure demonstrates potential for the quantitative screening and localisation of total glucosinolates in broccoli using the 950–1650 nm wavelength range. These compounds were mainly located in the external part of florets.
    • Semi-supervised linear discriminant analysis

      Toher, Deirdre; Downey, Gerard; Murphy, Thomas Brendan; Science Foundation Ireland; Teagasc (Wiley, 02/07/2012)
      Fisher's linear discriminant analysis is one of the most commonly used and studied classification methods in chemometrics. The method finds a projection of multivariate data into a lower dimensional space so that the groups in the data are well separated. The resulting projected values are subsequently used to classify unlabeled observations into the groups. A semi-supervised version of Fisher's linear discriminant analysis is developed, so that the unlabeled observations are also used in the model fitting procedure. This approach is advantageous when few labeled and many unlabeled observations are available. The semi-supervised linear discriminant analysis method is demonstrated on a number of data sets where it is shown to yield better separation of the groups and improved classification over Fisher's linear discriminant analysis.
    • Surface decontamination of meat using thermal processes

      McCann, Máiréad; Sheridan, James J.; Downey, Gerard (Teagasc, 2007-02)
      This study investigated the effectiveness of a novel heat apparatus for decontamination of meat surfaces inoculated with important foodborne pathogens using either steam or dry air.
    • Technology transfer of research results (The 2xtra project)

      McDonagh, Ciara; Byrne, Briege; Troy, Declan J.; Mullen, Anne Maria; Downey, Gerard; European Commission; European Union (Teagasc, 2008-02)
      The 2XTRA project (Technology Transfer Research Results Atlantic Area) was carried out with the aim of promoting economic activity based on research results and technologies developed within universities, research and technology institutes and companies in the European Atlantic Area. This collaborative work was carried out by a strong partnership of 13 entities across this region and included universities, research and technology institutes, private consultants and TBC (technology-based company) incubators. The specific goals of the project were: ● The exchange of information and experiences on technology transfer (TT) with a view to assisting project partners directly and feeding into their regional innovation systems. ● The promotion of new technology-based companies by drawing on collective experiences and developing methodologies relating to - identification and evaluation of business ideas - production of business plans, and - support of early stage companies internationalising. ● The creation of an Atlantic Area Network to support and promote technology-based companies (TBCs) and the technology transfer process. These objectives were achieved through defined activities carried out in three separate stages of this project.
    • Texture of fruit and vegetable components of ready meals

      Downey, Gerard (Teagasc, 2000-12)
      Vegetable and fruit purées are important parts of prepared ready-meals. Further expansion of this food sector will depend among other things on improved and consistent product quality. Innovative organoleptic properties in ready-meal components will assist in product diversification and the growth of market share.
    • Using induced chlorophyll production to monitor the physiological state of stored potatoes (Solanum tuberosum L.)

      Garnett, Jessica; Wellner, Nikolaus; Mayes, Andrew G; Downey, Gerard; Kemsley, E.K.; Teagasc Walsh fellowship Programme; Biotechnology and Biological Sciences Research Council, U.K.; 2014028 (Elsevier, 2018-08-04)
      A Visible/Near-infrared (Vis/NIR) spectrometer equipped with a fibre-optic probe was used to stimulate and measure chlorophyll production in potato tubers, at low levels that produce no visible greening in the skin. Subtle responses to changes in the light stimulus were also tracked. When used with a static experimental setup, these measurements are precise. However, the technique is very sensitive to the exact geometry of the tuber-probe arrangement, and careful positioning of the probe is crucial. Complementary studies established that tissue under the apical buds (‘eyes’) has greater capacity to produce chlorophyll than other locations on the tuber surface. A long-term study of multiple tubers suggested that different cultivars behave differently in terms of the rate of chlorophyll production. These behavioural differences may be related to the batch dormancy status; validating this potential relationship is the focus of ongoing work.