Near infrared spectroscopy (NIRS) as a tool to predict meat chemical composition and fatty acid profile in different rabbit genotypes

Two hundreds rabbits were obtained from 3 different maternal lines and 5 pa- ternal lines, for a total of 11 combinations. After slaughtering the fresh hind legs (HL) and Longis- simus dorsi muscles (LD) were scanned in the near infrared region by using a Foss NIRSystem 5000 (λ=1100-2498 nm). The WINISI software (v 1.50) was used for the spectra analysis and samples selection (49 HL and 11 LD). Selected samples were analyzed chemically for dry matter (DM), protein, lipid, ash and fatty acid profile (FA). The obtained results were used to expand and improve the existing calibration equations for fresh rabbit's meat. Afterwards these equations were used to predict meat composition of the unselected samples. Discriminant analysis didn't segregate genetic lines. The calibration results for the 400 meat samples were accurate in predicting DM, protein, lipid and some FA (R2>0.80). Poor results were obtained for ash and for physical properties of meat. It was demonstrated that NIRS is a reliable and af- fordable technology to predict fresh rabbit meat composition, but because of the small differences between genotypes, NIRS wasn't able to discriminate samples according to their genetic belonging

Near infrared spectroscopy in food analysis: qualitative and quantitative approaches

“Food quality” is a very wide issue and sometimes it is also difficult to define. Food is generally a complex mixture of chemical compounds and physical properties which make up its characteristics. The determination of quality of such complicated systems is usually very difficult considering that the available analytical techniques can evaluate one constituent at a time and they cannot provide a response useful to define the general concept of “quality”. Furthermore, these techniques are often very expensive. They need sophisticated instrumentations and trained analysts. Near infrared spectroscopy (NIRS) seems to be able to solve the major part of these problems. The spectra obtained by scanning samples are like a fingerprint of the organic matter and they reveal much information about the composition and the chemical-physical properties of the scanned compounds. The real benefit of NIRS is its speed in providing responses, which is an essential feature especially for highly perishable food. NIRS has also the important advantage to be perfectly adaptable to modern food production systems where all the different steps of the supply chain are often automated and where the quality of the products has to be checked directly on the production line in order to obtain standardised products with specific characteristics. Even if NIRS is nowadays largely used by industries and laboratories, there is still space for further research in this field; through my PhD thesis I have tried to increase the applications of NIRS to solve specific problems of the food sector. The present thesis has been divided into 7 different chapters: The first one regards the fundamental aspects of NIRS. It provides a brief description of its foundation, the equipment it uses and the mathematical tools needed to extract the whole information contained in NIR spectra. Furthermore a selected number of NIRS applications have been described after conducting a bibliographic research. The chemometrics section is intended as a sort of introduction for beginners who approach this discipline for the first time. In fact it offers an overview about chemometrics without giving to many details of this large subject. The number of formulas in this thesis were kept to a minimum reporting just some calculations necessary to understand how to obtain a good calibration and how to evaluate its performances. The 6 other chapters of this thesis report the 6 different trials I carried out during my 3 years of PhD: - in the first study NIRS was used to evaluate meat quality of different rabbits’ genetic lines (using fresh instead of freeze-dried meat samples) and to discriminate rabbits according to their genetic belonging. It was demonstrated that NIRS may be a useful tool to monitor meat quality during the development of rabbit selection programs especially for the prediction of the main chemical constituents and the fatty acid profile; - the main aims of the second study were to test the potential of NIR spectroscopy to predict important composition parameters of Pecorino Siciliano cheese and to classify samples according to their aging period. Pecorino Siciliano cheese has to respect some prerequisites to be commercialized with the P.D.O. (Protected Designation of Origin) denomination: it must have a minimum amount of fat of 40% on dry matter bases and it has to be aged for at least 4 months. NIRS seems to be a strategic tool to monitor the production supply chain of traditional products so that improve and standardize their overall quality; - the objective of the 3rd and 4th studies was to compare different spectral regions, NIR (Near Infrared Reflectance) and visible-NIR (Vis-NIR), to assess their ability to discriminate between fresh and frozen-thawed fish products: sea bream fillets and swordfish cutlets. The substitution of thawed products labelled as fresh is a common commercial fraud. Consumers and honest traders must be protected from this fraudulent behaviour. Spectroscopy seems to be a really useful analytical technique able to discriminate samples which have undergone different storage treatments and it is especially useful for fish which has lost its original wholeness; - the 5th study highlights a very important topic about NIR spectroscopy: the calibration transfer amongst different instruments. A large and robust calibration for pork fat composition was available in our lab using a Foss NIRSystem 5000 as spectrophotometer. We tried to transfer this calibration to use it on two other instruments (Unity Scientific 2500x and Zeiss MMS1 sensor) so that all the information acquired during many years of lab analysis are kept. To avoid full recalibration of the new NIR instruments, a certain number of chemometrics tools are available; they permit the calibration transfer and spectra correction from instrumental and environmental differences. Several standardisation approaches have been proposed in literature and the aim of our study was to evaluate which of them provide the best performances for this purpose; - the aim of the last study was to discriminate Shiraz wines (vintage 2006) produced in 5 Australian regions (Barossa Valley, Coonawarra, McLaren Vale, Clare Valley, Western Australia) using UV-Visible (UV-Vis), Near Infrared (NIR) and Mid Infrared (MIR) spectroscopy, combined with chemometrics. Knowing the origin of food is extremely important to safeguard traditional products from illegal imitations and to guarantee “food traceability” which is nowadays an important concept worldwide. NIRS has found a strategic role in this field for its classification ability starting from the information embedded into the spectra. As many spectroscopy users would say, “NIRS and chemometrics are not a magic box where all the questions are answered and all problems find resolution” but we tried to underline the concept of versatility of this technique which can be applied to solve different problems in the whole food supply chain. On the other hand we have not hidden the limits that sometimes this secondary analytical technique can present.La qualità degli alimenti è un concetto molto ampio e talvolta difficile da definire. Il cibo è un miscuglio di composti chimici e proprietà fisiche che insieme definiscono le caratteristiche dell’alimento stesso. Determinare la qualità di un sistema così complesso è spesso molto difficile, soprattutto considerate le tecniche analitiche disponibili, che generalmente riescono a valutare un costituente o una proprietà alla volta senza essere in grado di esprimere un giudizio generale sulla qualità del prodotto. Queste tecniche analitiche, inoltre, sono solitamente costose in quanto richiedono strumentazioni elaborate e personale addetto qualificato. La spettroscopia nel vicino infrarosso (NIRS) sembra essere in grado di risolvere buona parte di queste problematiche. Gli spettri ottenuti attraverso lo scansionamento dei campioni possono essere considerati una sorta di “impronta digitale” della sostanza organica e possono contenere molte informazioni riguardanti la composizione e le proprietà chimico-fisiche degli alimenti. Il vero vantaggio della tecnologia NIR resta comunque la sua velocità nel fornire i risultati. Questa caratteristica è estremamente importante nel settore alimentare, dove i prodotti sono altamente deperibili e devono essere commercializzati nel più breve tempo possibile. La spettroscopia NIR si adatta perfettamente alle moderne esigenze delle industrie alimentari dove le catene di produzione sono principalmente automatizzate e la qualità degli alimenti deve essere monitorata costantemente in modo tale da standardizzare la qualità del prodotto finito. Nonostante la spettroscopia NIR venga utilizzata da laboratori ed industrie alimentari da parecchi anni, c’è ancora spazio per ulteriore ricerca in questo campo. Attraverso la mia tesi di dottorato ho cercato di ampliare le possibili applicazioni della tecnologia NIR per risolvere delle problematiche concrete del settore “produzione e commercializzazione” degli alimenti. Il lavoro è stato suddiviso in 7 capitoli. Il primo riguarda alcuni aspetti generali della spettroscopia NIR e fornisce una breve descrizione dei fondamenti, delle attrezzature e degli strumenti necessari per l‘interpretazione degli spettri. La parte riguardante la chemiometria vuole essere una sorta di introduzione per coloro che si avvicinano per la prima volta a questa disciplina molto ampia. Il numero di formule inserito in questa tesi è stato mantenuto il più basso possibile, riportando solo quelle necessarie per ottenere delle buone calibrazioni e per poter poi testare le loro performance. Gli altri sei capitoli della tesi trattano i diversi contributi sperimentali che ho condotto durante i miei tre anni di dottorato di ricerca: - nel primo studio la spettroscopia NIR è stata utilizzata per valutare la qualità della carne di coniglio basando l’analisi sul prodotto fresco. È stata inoltre testata la capacità discriminante di questa tecnologia per classificare i campioni sulla base della loro linea genetica di appartenenza. È stato dimostrato che la tecnologia NIR potrebbe diventare una tecnica analitica di supporto nei piani di selezione genetica dei conigli per monitorare la qualità della loro carne soprattutto per quel che riguarda la predizione dei principali costituenti chimici e del profilo acidico di questo prodotto; - gli obiettivi del secondo contributo sperimentale sono stati la predizione della composizione centesimale del formaggio Pecorino Siciliano DOP e la classificazione di questo prodotto sulla base del suo grado di stagionatura. Per essere commercializzato con la denominazione DOP, questo formaggio deve rispettare alcuni prerequisiti minimi quali un contenuto di grasso pari al 40% sulla sostanza secca e un livello di stagionatura minima di 4 mesi. NIRS sembra una tecnica analitica molto utile per poter standardizzare la qualità e le tecniche di produzione dei prodotti tradizionali italiani che per essere commercializzati su mercati nazionali ed internazionali devono presentare caratteristiche ben definite; - l’obiettivo del terzo e quarto contributo sperimentale è stato il confronto di diverse regioni spettrali quali il NIR (vicino infrarosso) e il visibile-vicino infrarosso (Vis-NIR) per la discriminazione di pesce fresco da quello decongelato. I due contributi avevano come oggetto di studi due prodotti ittici di qualità quali i filetti di orata e i tranci di pesce spada. La vendita di prodotto decongelato spacciato per fresco è una comune frode commerciale da cui i consumatori e i commercianti devono essere protetti. La spettroscopia si è dimostrata una tecnica analitica utile per discriminare campioni che hanno subito trattamenti di conservazione diversi, in particolare per quei prodotti ittici che hanno perso la loro integrità anatomica (quali filetti e tranci); - il quinto studio ha trattato un argomento particolarmente importante nell’ambito della spettroscopia NIR: il trasferimento di calibrazioni tra diversi strumenti. Il nostro laboratorio aveva a disposizione una calibrazione ampia e robusta costruita sul grasso suino per la predizione del numero di iodio e del profilo acidico. Le equazioni erano state ottenute usando uno spettrofotometro FOSS NIRSystem 5000. Il nostro obiettivo era quello di trasferire questa calibrazione su altri due strumenti (Unity Scientific 2500x e un sensore Zeiss MMS1 portatile) per poter quindi mantenere e sfruttare l’informazione acquisita durante molti anni di analisi chimiche di laboratorio su questa matrice. Per evitare la ricalibrazione degli strumenti secondari, la chemiometria mette a disposizione diverse tecniche definite “modelli di standardizzazione” che nel nostro studio sono state poste a confronto; - l’obiettivo dell’ultimo contributo introdotto in questa tesi è stata la discriminazione di vino Shiraz prodotto in 5 diverse regioni australiane particolarmente vocate per il settore vitivinicolo (Barossa Valley, McLaren Vale, Clare Valley, Coonawarra, Western Australia). Diverse regioni spettrali sono state confrontate a tale scopo (Visibile, vicino infrarosso e medio infrarosso), sfruttando inoltre diverse tecniche di classificazione che la chemiometria mette a disposizione. Conoscere l’origine degli alimenti è di particolare importanza soprattutto per salvaguardare i prodotti tradizionali. Questi, infatti, rischiano di essere sostituiti con prodotti simili ma di qualità inferiore. La spettroscopia NIR, impiegando le informazioni contenute nello spettro di un alimento, si è rivelata in grado di discriminare i prodotti sulla base della loro origine. Sicuramente la spettroscopia NIR non è una “scatola magica” dove tutte le domande trovano risposta e i problemi vengono risolti, ma possiede una versatilità tale da consentirne l’impiego in molteplici realtà industriali e commerciali. Attraverso la mia tesi ho cercato di mettere in luce le potenzialità di questa tecnologia senza però nascondere i limiti che ho riscontrato nel corso del suo utilizzo

Near infrared spectroscopy in animal science production:principles and applications

Near infrared (NIR) is one of the techniques belonging to vibrational spectroscopy. Its radiation (750 to 2500nm) interacts with organic matter, and the absorption spectrum is rich in chemical and physical information of organic molecules. In order to extract valuable information on the chemical properties of samples, it is necessary to mathematically process spectral data by chemometric tools. The most important part in the development of an NIR method is building the predicting model generally called calibration. NIR spectroscopy has several advantages over other analytical techniques: rapidity of analysis, no use of chemicals, minimal or no samples preparation, easily applicable in different work environments (on/in/at line applications). On the other hand, NIR spectroscopy has some disadvantages: low ability to predict compounds at low concentration (<0.1%), necessity of accurate analysis as reference, development of calibration models required high trained personnel, need of a large and up-to-date calibration data set (often difficult to obtain), difficulties to transfer calibration among instruments, initial high financial investments. In the feed industry, NIR spectroscopy is used for: feed composition, digestibility (in vivo, in vitro, in situ), traceability assessment (to avoid possible frauds). As far as animal products are concerned, NIR spectroscopy has been used to determine the main composition of meat, milk, fish, cheese, eggs. Furthermore, it was also used to predict some physical properties (tenderness, WHC (Water Holding Capacity), drip loss, colour and pH in meat; coagulation ability in milk; freshness, flavour and other sensorial parameters in cheese). Interesting applications of NIR spectroscopy regard issues like: determination of animal products&rsquo; authenticity and the detection of adulteration (in order to prevent frauds), discrimination PDO (Protected Designation of Origin) and PGI (Protected Geographical Indication) from other non traditional products, detect handling aspects (freezing, thawing or fresh). There is a growing interest in the evaluation of animal products&rsquo; quality directly on-line to have a continuous control of the production process. Furthermore, new portable instruments are becoming now available, which will allow to easily monitor some processes at the factory (i.e. ripening and ageing of sausages and cheeses)

Discrimination between Shiraz Wines from Different Australian Regions:The Role of Spectroscopy and Chemometrics

This study reports the use of UV-visible (UV-vis), near-infrared (NIR), and midinfrared (MIR) spectroscopy combined with chemometrics to discriminate among Shiraz wines produced in five Australian regions. In total, 98 commercial Shiraz samples (vintage 2006) were analyzed using UV-vis, NIR, and MIR wavelength regions. Spectral data were interpreted using principal component analysis (PCA), linear discriminant analysis (LDA), and soft independent model of class analogy (SIMCA) to classify the wine samples according to region. The results indicated that wine. samples from Western Australia and Coonawarra can be separated from the other wines based on their MIR spectra. Classification results based on MIR spectra also indicated that LDA achieved 73% overall correct classification, while SIMCA 95.3%. This study demonstrated that IR spectroscopy combined with chemometric methods can be a useful tool for wine region discrimination

Near infrared spectroscopy (NIRS) as a tool to predict meat chemical composition and fatty acid profile in different rabbit genotypes

Two hundreds rabbits were obtained from 3 different maternal lines and 5 paternal lines, for a total of 11 combinations. After slaughtering the fresh hind legs (HL) and Longissimus dorsi muscles (LD) were scanned in the near infrared region by using a Foss NIRSystem 5000 (gimel=1100-2498 nm). The WINISI software (v 1.50) was used for the spectra analysis and samples selection (49 HL and 11 LD). Selected samples were analyzed chemically for dry matter (DM), protein, lipid, ash and fatty acid profile (FA). The obtained results were used to expand and improve the existing calibration equations for fresh rabbit's meat. Afterwards these equations were used to predict meat composition of the unselected samples. Discriminant analysis didn't segregate genetic lines. The calibration results for the 400 meat samples were accurate in predicting DM, protein, lipid and some FA (R(2)>0.80). Poor results were obtained for ash and for physical properties of meat. It was demonstrated that NIRS is a reliable and affordable technology to predict fresh rabbit meat composition, but because of the small differences between genotypes, NIRS wasn't able to discriminate samples according to their genetic belonging

Impiego della spettroscopia NIR per la stima della composizione chimica ed acidica della carne di coniglio e per discriminare l'allevamento outdoor da quello indoor

Trentotto conigli di popolazione locale \u201cGrigio Rustica\u201d sono stati sottoposti a 2 tipi di allevamento in gabbia multipla: all\u2019interno del capannone (Indoor) e all\u2019esterno (Outdoor). La carne fresca dell\u2019arto posteriore \ue8 stata analizzata al NIRS in riflettanza con lunghezze d\u2019onda comprese tra 1100 e 2498 nm, utilizzando uno strumento monocromatore 5000 (FOSS Italia), un software WINISI v.1.50. Dieci campioni selezionati sulla base della distanza globale di Mahalanobis sono stati analizzati per la determinazione della composizione chimica e del profilo acidico. I dati analitici sono stati trattati con il software WINISI per migliorare il set di calibrazione precedente e per stimare la composizione chimica ed acidica dei campioni non analizzati. La spettroscopia NIR \ue8 stata altres\uec utilizzata per discriminare la carne appartenente a conigli allevati Indoor e Outdoor. La predizione della composizione chimica \ue8 risultata eccellente per lipidi e sostanza secca, molto buona per proteina grezza, con valori R2 di 0.98, 0.96 e 0.92, SECV di 0.25, 0.35 e 0.31 e 1-VR di 0.95, 0.91 e 0.80, rispettivamente. La predizione del profilo acidico della carne \ue8 stata meno accurata. Gli acidi grassi saturi, monoinsaturi e poliinsaturi hanno presentato R2 di 0.98, 0.78 e 0.77, SECV di 2.01, 1.39 e 2.0 e 1-VR di 0.55, 0.74 e 0.57, rispettivamente. La migliore predizione \ue8 stata ottenuta con l\u2019acido palmitico (R2=0.99; SECV=1.21; 1-VR=0.79), il pi\uf9 rappresentato (28%). La spettroscopia NIR ha discriminato in modo soddisfacente le carni di coniglio derivate da sistemi di allevamento diversi. L\u201984% dei conigli allevati Indoor e il 79% di quelli allevati Outdoor sono stati correttamente classificati. La spettroscopia NIR risulta quindi una tecnica sufficientemente sensibile per l\u2019identificazione dell\u2019origine dei campioni considerati e la stima della composizione chimica ed acidica su carne di coniglio fresca permette di ridurre in misura significativa i costi di analisi

Effect of adult weight and CT-based selection on carcass traits of growing rabbits

The aim of this study was to compare the carcass traits of different genotypes. Maternal line (M; n=31; adult weight/AW/4.0-4.5kg) (selected for number of kits born alive), Pannon White (P; n=32; AW: 4.3-4.8kg), and Large type line (L, n=32; AW: 4.8-5.4kg) (P and L were selected for carcass traits based on CT/Computer tomography/data) rabbits were analysed. Rabbits were slaughtered at 11 wk of age. P rabbits showed the highest dressing out percentage (M=60.2, P=61.3 and L=61.1%, with a significant difference between groups M and P, P<0.05), the lowest ratio of fore part (M=26.0, P=25.7 and L=26.9%, differences were significant between groups M-P and L, P<0.05), and the largest ratio of the hind part (M=37.3, P=38.2 and L=37.2%, differences were significant between groups M-L and P, P<0.05) to the reference carcass. It can be concluded that carcass traits were influenced by CT-based selection

Comparison of Visible and Near-Infrared Reflectance Spectroscopy to Authenticate Fresh and Frozen-thawed Swordfish (Xiphias gladius L)

This study evaluated near-infrared (NIR) and visible-NIR (Vis-NIR) spectroscopy as a way to distinguish fresh (F) from frozen-thawed (T) swordfish cutlets (Xiphias gladius). A total of 90 F and 60 T samples were used. The T samples were stored at a high and low frozen temperature (HT: -10\ub0C; LT: -18\ub0C). Spectra were collected using a Vis-NIR portable spectrophotometer (380\u20131080 nm) and a NIR monochromator (1100\u20132500 nm). The percentage of correctly classified samples obtained with Vis-NIR spectroscopy was 6596.7%, whereas that for NIR was 6590.0%. The best classification was observed comparing F and HT samples using Vis-NIR (100% vs. 96.7%, respectively). The more descriptive principal component scores (PCS) of NIR and Vis-NIR were used with a multivariate binary logistic regression. The model with the PCS of the first two Vis-NIR principal components accounted for 81.1% of the classification. Vis-NIR could be a strategic tool to screen the cold treatment of swordfish

Comparison of productive and carcass traits of different genotypes

different adult weight. The maternal line is selected for litter size (M; n=31) (adult weight /AW/ 4.0-4.5 kg); the Pannon White (P; n=42; AW: 4.3-4.8 kg) and a large sized (paternal) line are selected for weight gain and for carcass traits (using CT-data). The average daily gain (between the ages of 5 and 11 weeks) of the L rabbits exceeded that of the P and M rabbits by 4.3 and 8.8 g, respectively (P<0.001). 272 and 491 g differences were found for 11 week old body weight. The daily feed intake of the L rabbits was 17 and 23 g higher that that of the P and L group (P<0.001). The feed conversion ratio and the mortality rate of the 3 genotypes did not differ. The highest dressing out percentage (61.3%) was observed by the P rabbits exceeding by 1.1% the M group (P<0.05). The dressing out percentage of the L groups was also favourable (61.1%). Compared to the reference carcass the ratio of the fore part was the highest (26.9%) and the lowest (25.7%) for the L and P groups, respectively. An opposite order was recorded for the ratio of the hind part (L: 37.2%, P: 38.2%). The ratio of the perirenal fat was similar for every genotype. Based on the results it can be concluded that feed intake and final weight are determined by the adult body weight (of the genotypes) (the large sized line showed the most favourable performances), dressing out percentage and ratio of the fore and hind parts are determined by the CT aided selection (P rabbits achieved the best results)