33 research outputs found
Emerging trends of advanced sensor based instruments for meat, poultry and fish quality – a review
Aquaphotomics: an innovative application of near-infrared spectroscopy focusing on water
In the field of food science, indirect methods which can be used to determine a certain property of the sample by correlating the measured physico-chemical characteristics are widely applied for the detection of food counterfeiting. Near infrared spectroscopy (NIR), complemented by multivariate statistical analyses, is a quick, non-destructive method that does not require sample preparation in most cases. The interactions that can be observed between aqueous systems or aqueous solutions and electromagnetic radiation (light), i.e., the effects of different perturbations on the structural and functional properties of water, are investigated by a new and dynamically evolving area of science called aquaphotomics. It has been proven by a number of research results that by applying the so-called “water-mirror approach”, the detection limits that can be obtained using the conventional approach can be overcome in aqueous systems, and in certain cases components that are present in concentrations that are a few orders of magnitude lower than usual can be detected. The technique of aquaphotomics has been tested in diverse areas of science such as medicine, microbiology, plant physiology or food analysis. In our series of experiments, the detectability of the counterfeiting of ground paprika samples using 0 to 40% corn flour has been investigated by applying the method of aquaphotomics to their solutions. During the evaluation of the results, the first harmonic range of water (1,300-1,600 nm) was used. Spectral patterns were represented on an aquagram, and then a model for estimating the corn flour content was constructed using the Partial Least Squares Regression (PLSR) method. PLSR results showed a strong correlation between the added amount of corn flour and the amount estimated by NIR (near-infrared) spectroscopy. Samples with a lower corn flour content (0-3%) showed a greater absorbance around 1,450 nm, while samples with a higher corn flour content (15-40%) exhibited a greater absorbance between 1,364 and 1,412 nm. These differences are explained by the spectral absorption of water bound with hydrogen bonds to varying degrees. Research results from recent years show that aquaphotomics is a promising technique in many areas of science, including food science
Aquaphotomics : a közeli infravörös spektroszkĂłpia innovatĂv, vĂzközpontĂş alkalmazása
Az Ă©lelmiszertudomány terĂĽletĂ©n sokfelĂ© alkalmaznak olyan indirekt mĂłdszereket az Ă©lelmiszerhamisĂtás detektálására, amelyekkel a mĂ©rt fizikai-kĂ©miai jellemzĹ‘k korreláltatása alapján meghatározhatĂł a vizsgált minta valamely tulajdonsága. Gyors, mintaelĹ‘kĂ©szĂtĂ©st általában nem igĂ©nylĹ‘, roncsolásmentes mĂłdszernek bizonyul a többváltozĂłs statisztikai elemzĂ©sekkel kiegĂ©szĂtett közeli infravörös spektroszkĂłpia (NIR). A vizes - vagy vizes oldatba vitt - rendszerek Ă©s az elektromágneses sugárzás (fĂ©ny) következtĂ©ben megfigyelhetĹ‘ kölcsönhatásokat, tehát a kĂĽlönbözĹ‘ perturbáciĂłk a vĂz szerkezeti Ă©s funkcionális tulajdonságaira gyakorolt hatását egy Ăşj, dinamikusan fejlĹ‘dĹ‘ tudományterĂĽlet, az aquaphotomics vizsgálja. Több kutatási eredmĂ©ny is bizonyĂtja, hogy az Ăşn. „vĂztĂĽkör-megközelĂtĂ©s” alkalmazásával a vizes rendszerekben a konvencionális megközelĂtĂ©ssel elĂ©rhetĹ‘ detektáciĂłs határ átlĂ©phetĹ‘, esetenkĂ©nt akár nĂ©hány nagyságrenddel kisebb mennyisĂ©gben jelen lĂ©vĹ‘ komponensek kimutatása is megvalĂłsĂthatĂł. Az aquaphotomics technikát a tudomány olyan terĂĽletein teszteltĂ©k, mint pĂ©ldául a gyĂłgyászat, a mikrobiolĂłgia, a növĂ©nyĂ©lettan vagy az Ă©lelmiszervizsgálat. KĂsĂ©rletsorozatunkban fűszerpaprika-Ĺ‘rlemĂ©nyek kukoricaliszttel 0-40%-ban törtĂ©nĹ‘ hamisĂtásának detektálhatĂłságát vizsgáltuk az aquaphotomics metodika alkalmazásával azok oldatainak felhasználásával. Az eredmĂ©nyek Ă©rtĂ©kelĂ©se során a vĂz elsĹ‘ felharmonikus tartományát használtuk (1300-1600 nm). A spektrális mintázatokat aquagramon szemlĂ©ltettĂĽk, majd parciális legkisebb nĂ©gyzetek regressziĂłja (Partial Least Squares Regression - PLSR) -mĂłdszerrel modellt Ă©pĂtettĂĽnk a kukoricaliszt-tartalom becslĂ©sĂ©re. A PLSR-eredmĂ©nyek szoros korreláciĂłt mutattak a hozzáadott Ă©s a NIR-spektroszkĂłpiával (Near Infra Red spectroscopy) becsĂĽlt kukoricaliszt mennyisĂ©ge között. A kisebb kukoricaliszt tartalmĂş minták (0-3%) 1450 nm körĂĽl mutattak nagyobb elnyelĂ©st, mĂg a nagyobb kukoricaliszt tartalmĂş minták (15-40%) 1364-1412 nm között. Ezeket a kĂĽlönbsĂ©geket a hidrogĂ©nkötĂ©sekkel eltĂ©rĹ‘ mĂ©rtĂ©kben kötött vĂz spektrális elnyelĂ©se magyarázza. Az elmĂşlt Ă©vekben vĂ©gzett kutatások eredmĂ©nyei azt mutatják, hogy az aquaphotomics-technika több tudományterĂĽlet mellett az Ă©lelmiszertudományban is ĂgĂ©retesnek bizonyul
Standard Analytical Methods, Sensory Evaluation, NIRS and Electronic Tongue for Sensing Taste Attributes of Different Melon Varieties
Grafting by vegetables is a practice with many benefits, but also with some unknown influences on the chemical composition of the fruits. Our goal was to assess the effects of grafting and storage on the extracted juice of four orange-fleshed Cantaloupe type (Celestial, Donatello, Centro, Jannet) melons and two green-fleshed Galia types (Aikido, London), using sensory profile analysis and analytical instruments: An electronic tongue (E-tongue) and near-infrared spectroscopy (NIRS). Both instruments are known for rapid qualitative and quantitative food analysis. Linear discriminant analysis (LDA) was used to classify melons according to their varieties and storage conditions. Partial least square regression (PLSR) was used to predict sensory and standard analytical parameters. Celestial variety had the highest intensity for sensory attributes in Cantaloupe variety. Both green and orange-fleshed melons were discriminated and predicted in LDA with high accuracies (100%) using the E-tongue and NIRS. Galia and Cantaloupe inter-varietal classification with the E-tongue was 89.9% and 82.33%, respectively. NIRS inter-varietal classification was 100% with Celestial variety being the most discriminated as with the sensory results. Both instruments, classified different storage conditions of melons (grafted and self-rooted) with high accuracies. PLSR showed high accuracy for some standard analytical parameters, where significant differences were found comparing different varieties in ANOVA
Detecting Low Concentrations of Nitrogen-Based Adulterants in Whey Protein Powder Using Benchtop and Handheld NIR Spectrometers and the Feasibility of Scanning through Plastic Bag
Nitrogen-rich adulterants in protein powders present sensitivity challenges to conventional combustion methods of protein determination which can be overcome by near Infrared spectroscopy (NIRS). NIRS is a rapid analytical method with high sensitivity and non-invasive advantages. This study developed robust models using benchtop and handheld spectrometers to predict low concentrations of urea, glycine, taurine, and melamine in whey protein powder (WPP). Effectiveness of scanning samples through optical glass and polyethylene bags was also tested for the handheld NIRS. WPP was adulterated up to six concentration levels from 0.5% to 3% w/w. The two spectrometers were used to obtain three datasets of 819 diffuse reflectance spectra each that were pretreated before linear discriminant analysis (LDA) and regression (PLSR). Pretreatment was effective and revealed important absorption bands that could be correlated with the chemical properties of the mixtures. Benchtop NIR spectrometer showed the best results in LDA and PLSR but handheld NIR spectrometers showed comparatively good results. There were high prediction accuracies and low errors attesting to the robustness of the developed PLSR models using independent test set validation. Both the plastic bag and optical glass gave good results with accuracies depending on the adulterant of interest and can be used for field applications