91 research outputs found
SPECTROSCOPY, IMAGE ANALYSIS AND HYPERSPECTRAL IMAGING FOR FOOD SAFETY AND QUALITY: A CHEMOMETRIC APPROACH
Questo progetto di dottorato studia le differenti applicazioni delle tecniche ottiche non distruttive per la valutazione della qualit\ue0 e della shelf-life di prodotti vegetali cos\uec come l\u2019identificazione precoce di sviluppi microbici su superfici industriali. La spettroscopia, l\u2019analisi dell\u2019immagine e l\u2019analisi dell\u2019immagine iperspettrale possono giocare un ruolo importante nella valutazione sia della qualit\ue0 che della sicurezza degli alimenti grazie alla rapidit\ue0 e sensibilit\ue0 della tecnica, specialmente quando si utilizzano strumenti semplificati portatili. Un approccio statistico multivariato (chemiometria) \ue8 richiesto al fine di estrarre informazioni dal segnale acquisito, riducendo la dimensionalit\ue0 dei dati e mantenendo le informazioni spettrali pi\uf9 utili.
Lo scopo del primo studio presentato \u2013 Testing of a Vis-NIR system for the monitoring of long-term apple storage \u2013 \ue8 la valutazione dell\u2019applicabilit\ue0 della spettroscopia nel visibile e vicino infrarosso (Vis-NIR) per il monitoraggio e la gestione delle mele durante lo stoccaggio a basse temperature. Per sette mesi \ue8 stata seguita l\u2019evoluzione in termini di grado zuccherino e consistenza delle mele suddivise in classi di maturazione. I risultati hanno indicato che la spettroscopia \ue8 una tecnica non-distruttiva che consente una stima accurata dei parametri chimico-fisici per la classificazione delle mele in lotti omogenei.
Il lavoro descritto nel secondo paragrafo - Wavelength selection with a view to a simplified handheld optical system to estimate grape ripeness \u2013 \ue8 finalizzato all\u2019identificazione delle tre lunghezze d\u2019onda pi\uf9 importanti per il riconoscimento, direttamente in campo, dell\u2019uva pronta per essere raccolta al fine della messa a punto di un sistema semplificato e a basso costo. I coefficienti di regressione standardizzati del modello PLS (Partial Least Square) sono stati utilizzati per selezionare le variabili pi\uf9 importanti, che racchiudono l\u2019informazione pi\uf9 utile lungo l\u2019intero spettro. La stessa procedura \ue8 stata condotta per determinare la freschezza delle foglie di Valerianella durante la shelf-life - Selection of optimal wavelengths for decay detection in fresh-cut Valerianella Locusta laterr (terzo paragrafo).
Lo scopo del lavoro presentato nel quarto paragrafo del primo capitolo - Comparison between FT-NIR and Micro-NIR in the evaluation of Acerola fruit quality, using PLS and SVM regression algorithms \u2013 \ue8 stimare l\u2019acidit\ue0 titolabile e il contenuto di acido ascorbico all\u2019interno del frutto acerola, utilizzando uno strumento compatto e a basso costo denominato Micro-NIR, che lavora nell\u2019intervallo spettrale 950-1650 nm. I dati spettrali sono stati modellati mediante l\u2019applicazione di due algoritmi PLS e SVM (Support Vector Machine). La capacit\ue0 predittiva dello strumento semplificato \ue8 risultata interessante per applicazioni di monitoraggio in campo, soprattutto modellizzando i dati in modo non lineare.
Nel secondo capitolo, \ue8 presentata l\u2019applicazione di immagini RGB per la valutazione delle superfici - Image texture analysis, a non-conventional technique for early detection of biofilm. La texture dell\u2019immagine \ue8 definita come una differenza nella distribuzione spaziale, nella frequenza e nell\u2019intensit\ue0 dei livelli di grigio in ogni pixel dell\u2019immagine. Questo metodo \ue8 stato determinante per l\u2019identificazione precoce dello sviluppo microbico su superfici normalmente impiegate nell\u2019industria alimentare.
L\u2019approccio chemiometrico \ue8 stato cruciale in ogni fase del progetto di dottorato ed \ue8 definito come un approccio statistico multivariato che si applica ai dati chimici per estrarre informazione utile, ridurre il rumore di fondo e l\u2019informazione ridondante. Il lavoro presentato all\u2019inizio del terzo capitolo - Hyperspectral image analysis: a tutorial - propone una procedura standard per l\u2019elaborazione di dati tridimensionali, presentando un esempio relativo alla predizione del raffermamento del pane in cassetta.
Il secondo paragrafo del terzo capitolo, presenta una applicazione dell\u2019immagine iperspettrale su acerola, focalizzata sul contenuto di vitamina C - HSI for quality evaluation of vitamin C content in Acerola fruit. In questo lavoro, \ue8 stata acquisita l\u2019immagine di dieci acerola, raccolte in funzione del livello di maturazione, definito in base al colore della buccia (cinque acerola verdi e cinque rosse). Lo spettro della polvere di vitamina C pura \ue8 stato utilizzato come riferimento per l\u2019applicazione di due algoritmi di correlazione (spectral angle mapping e correlation coefficient), consentendo la costruzione di mappe qualitative di distribuzione dell\u2019acido ascorbico all\u2019interno del frutto.
Lo scopo dell\u2019ultimo lavoro presentato \ue8 la valutazione della qualit\ue0 post raccolta dell\u2019acerola - Selection of NIR wavelengths from hyperspectral imaging data for the quality evaluation of Acerola fruit. Le immagini iperspettrali di venti acerola sono state acquisite per cinque giorni consecutivi. La valutazione delle modificazioni spettrali durante il tempo ha consentito la selezione delle tre lunghezze d\u2019onda caratterizzanti il processo di maturazione/degradazione del frutto. L\u2019immagine in falsi colori, derivante dalla composizioni delle immagini alle tre lunghezze d\u2019onda di interesse, consente l\u2019identificazione precoce del processo degradativo in maniera rapida e non distruttiva.
Le tre tecniche non distruttive impiegate in questo progetto di dottorato hanno dimostrato efficienza e applicabilit\ue0 per la valutazione della qualit\ue0 e della sicurezza degli alimenti, rispondendo alla necessit\ue0 dell\u2019industria alimentare di tecniche accurate, veloci e obiettive per assicurare produzioni ottimali lungo l\u2019intero processo produttivo.This PhD project regards different applications of non-destructive optical techniques to evaluate quality and shelf life of agro-food product as well as the early detection of biofilm on food plants. Spectroscopy, image analysis and hyperspectral imaging could play an important role in the assessment of both quality and safety of foods due to their rapidity and sensitivity especially when using simplified portable devices. Due to the huge amount of collected data, chemometric, a multivariate statistical approach, is required, in order to extract information from the acquired signals, reducing dimensionality of the data while retaining the most useful spectral information.
The thesis is organized in four chapters, one for each technique and a final chapter including the overall conclusion. Each chapter is divided in case studies according to the matrix analysed and the data acquisition and elaboration carried out.
The first chapter is about spectroscopy. The aim of the first study - Testing of a Vis-NIR system for the monitoring of long-term apple storage - is to evaluate the applicability of visible and near-infrared (Vis-NIR) spectroscopy to monitor and manage apples during long-term storage in a cold room. The evolution of the apple classes, originally created, was analysed during 7 months of storage by monitoring TSS and firmness. Vis-NIR allows an accurate estimation of chemical-physical parameters of apples allowing a non-destructive classification of apples in homogeneous lots and a better storage management.
The work reported in the second paragraph - Wavelength selection with a view to a simplified handheld optical system to estimate grape ripeness - is aimed to identify the three most significant wavelengths able to discriminate grapes ready to be harvested directly in the field. Wavelengths selection was carried out with a view to construct a simplified handheld and low-cost optical device. Standardized regression coefficients of the PLS model were used to select the relevant variables, representing the most useful information of the full spectral region. The same approach was followed to discriminate freshness levels during shelf-life of fresh-cut Valerianella leaves - Selection of optimal wavelengths for decay detection in fresh-cut Valerianella Locusta Laterr. (third paragraph).
The aim of the work presented in the fourth paragraph of the first chapter - Comparison between FT-NIR and Micro-NIR in the evaluation of Acerola fruit quality, using PLS and SVM regression algorithms - is to estimate titratable acidity and ascorbic acid content in acerola fruit, using a MicroNIR, an ultra-compact and low-cost device working between 950 \u2013 1650 nm. The spectral data were modelled using two different regression algorithms, PLS (partial least square) and SVM (support vector machine). The prediction ability of Micro-NIR appears to be suitable for on field monitoring using non-linear regression modelling (i.e. SVM).
In the second chapter, image analysis was performed. The traditional RGB imaging for the evaluation of image texture, a specific surface characteristic, is presented. The texture of an image is given by differences in the spatial distribution, in the frequency and in the intensity of the values of the grey levels of each pixel of the image. This technique was applied for the early detection of biofilm in its early stages of development, when it is still difficult to observe it by the naked eye, was evaluated (Image texture analysis, a non-conventional technique for early detection of biofilm).
In the third paragraph, image and spectroscopy were combined in hyperspectral imaging applications. Data analysis by chemometric was crucial in any stage of my PhD project. Chemometric is a multivariate statistical approach that is applied on chemical data to extract the useful information avoiding noise and redundant data. At the beginning of the third chapter - Hyperspectral image analysis: a tutorial - proposes an original approach, developed as a flow sheet for three-dimensional data elaboration. The method was applied, as an example, to the prediction of bread staling during storage.
The first application about hyperspectral on acerola is focused on the vitamin C content - HIS for quality evaluation of vitamin C content in Acerola fruit. Ten different acerola fruits picked up according to two different stages of maturity, based on the colour of the peel (5 green and 5 red acerola), were analysed. The spectra of pure vitamin C powder was used as references for computing models with two different correlation techniques: spectral angle mapping and correlation coefficient allowing the construction of a qualitative distribution map of ascorbic acid inside the fruit.
The aim of the last one work presented is to evaluate acerola post-harvest quality - Selection of NIR wavelengths from hyperspectral imaging data for the quality evaluation of Acerola fruit. Hyperspectral images of 20 acerolas were acquired for five consecutive days and an investigation of time trends was carried out to highlight the most important three wavelengths that characterized the ripeness/degradation process of the Acerola fruit. The false-colour RGB images, derived from the composition of the three interesting wavelengths selected, data enable early detection of the senescence process in a rapid and non-destructive manner.
In conclusion, the three non-destructive optical techniques applied in this PhD project have proved to be one of the most efficient and advanced tools for safety and quality evaluation in food industry answering the need for accurate, fast and objective food inspection methods to ensure safe production throughout the entire production process
A NANOSPHERICAL DENDRIMERIC GALLATE ESTER FOR LONG TERM PRESERVATION OF ESSENTIAL OILS: AN INTEGRATED CHEMOMETRIC ASSISTED FT-IR STUDY
Essential oils (EOs) are hydrophobic concentrated liquids from plants made of volatile chemical compounds. EOs are very popular in the food, cosmetic and pharmaceutical industry as aromas, fragrances and alternative therapeutic devices [1, 2]. EOs are susceptible to degradation reactions, especially of oxidative type, triggered by temperature, light and oxygen availability. A loss of quality and alterations of sensory and pharmacological properties may occur, causing the production of smelly or even harmful compounds, responsible for allergic reactions and skin irritation [3-5]. For preventing and delaying EOs\u2019 spoilage, synthetic preservatives as 2,6-bis(1,1-dimetiletil)-4-metilphenol (BHT) or t-butil-4-hydrohyanisole (BHA) are commonly adopted; but, in addition to a limited efficiency due mainly to poor solubility in oils, they may cause health diseases [6]. Natural polyphenols as gallic acid (GA) are nowadays proposed as safer alternatives, but their efficiency is limited by their low compatibility with hydrophobic material again, or by the occurrence of probable side reactions with oils constituents. Recently, a hydrophobic and biodegradable GA-enriched dendrimer (GAD) (Fig. 1.a) characterised by a nanospherical morphology (Fig. 1.b) and endowed with a remarkable antioxidant activity was synthetized [7]. Further studies currently being completed, have shown that GAD, with respect to free GA, possesses also more efficient antibacterial properties against several antibiotics-resistant G+ strains, inhibits platelet aggregation and ROS accumulation thus representing an excellent alternative to conventional drugs to combat infections and thrombus formation [8]. In this study, based on integrated results obtained from the due investigations, GAD is advised also as an innovative and semi-synthetic preservative additive.
a)
b)
Figure 1. Intuitive representation of GA-enriched dendrimer (GAD) structure (a); SEM images of GAD spherical nanoparticles (b). Scale bars represent 300 nm.
In this regard, GAD proved a much more efficient preservative power than free GA and, unlike GA, it never acts as a pro-oxidant. Besides classic oxidation indexes, the desired information was obtained by FT-IR spectroscopy assisted by multivariate analysis (MVA). For further confirmation of the so obtained results, interpretations of FT-IR data by considering the area of some selected informative bands and iodometric titrations to determine the hydro peroxide value (PV) were also performed [9].
References
[1] Yamamoto S., SOFW J., 2008, 134, 8.
[2] Jiang Y., Wu N., Fu Y.-J., Wang W., Luo M., Zhao C.-J., Zu Y.-G., and Liu Y.-L., Environ. Toxicol. Pharmacol., 2011, 32, 63.
[3] Hagvall L., Skold M., Brared-Christensson J., Borje A., and Karlberg A.-T., Contact Dermatitis, 2008, 59, 143.
[4] Skold M., Hagvall L., and Karlberg A.-T., Contact Dermatitis, 2008, 58, 9.
[5] Brared-Christensson J., Matura M., Gruvberger B., Bruze M., and Karlberg A.-T., Contact Dermatitis, 2010, 62, 32.
[6] Hirose M., Takesada Y., Tanaka H., Tamano S., Kato T., and Shirai T., Carcinogenesis, 1998, 19, 207.
[7] Alfei S., Catena S., and Turrini F., Drug Deliv. Trans. Res., under review.
[8] Alfei S., Signorello M. A., Schito A., Catena S., and Turrini F., results not yet published
[9] Alfei S., Oliveri P., and Malegori C., New J. Chem., under review
Identification of invisible biological traces in forensic evidences by hyperspectral NIR imaging combined with chemometrics
HIS for quality evaluation of vitamin C content in acerola fruit.
The aim of this work is to evaluate, by HIS, vitamin C distribution in acerola fruit as discriminant quality parameter so to deliver the product to the industry according to the fruit quality
Selection of NIR wavelengths from hyperspectral imaging data for the quality evaluation of acerola fruit.
The aim of this work is to evaluate Acerola post-harvest quality using NIR hyperspectral imaging
Comparison between FT-NIR and Micro-NIR in the evaluation of Acerola fruit quality, using PLS and SVM regression algorithms.
The aim of this work is to estimate in a non-destructive manner, in acerola fruit, titratable acidity and ascorbic acid content
Evaluation of safety, quality and shelf life of agro-food product using non-destructive optical and instrumental-sensory devices
Questo progetto di dottorato studier\ue0 le possibili applicazioni di tecniche ottiche non distruttive e sensoriali - strumentali per determinare sicurezza, qualit\ue0 e conservazione di prodotti agro-alimentari cos\uec come la corretta sanificazione di impianti alimentari. Spettroscopia, immagine iperspettrale e naso elettronico potrebbero giocare un ruolo importante nella valutazione sia della qualit\ue0 che della sicurezza degli alimenti grazie alla rapidit\ue0, sensibilit\ue0 e semplicit\ue0. Queste tecniche saranno utilizzate in combinazione sulla stessa matrice alimentare. \uc8 richiesto un approccio multivariato per estrarre le informazioni dai dati raccolti. Prospettiva futura di questo lavoro sar\ue0 lo sviluppo di sistemi semplificati, portatili e utilizzabili on-line.This PhD project will study the possible application of non-destructive optical and instrumental-sensory techniques to evaluate safety, quality and shelf life of agro-food product as well as the sanification of food plants. Spectroscopy, hyperspectral imaging and e-nose could play an important role in the assessment of both quality and safety of foods due to their rapidity, sensitivity and simplicity. These techniques will be used in combination on the same food matrix. A multivariate statistical approach is required, in order to extract information from the signals acquired. The development of simplified, portable devices will be the future of these research project
Advanced strategies in near infrared spectroscopy and multivariate data analysis for food safety and authentication
Hyperspectral NIR imaging for food quality and authentication: overview and applications
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