Near infrared calibration transfer for undried whole maize plant between laboratory and on-site spectrometers

The analysis of the maize plant immediately after harvest is essential in order to check the composition and maturity of the plant to optimise the quality of silage. NIRS calibrations were carried out on chopped maize using three spectrophotometers: a laboratory instrument (FOSS NIRSystems 5000 scanning monochromator, FOSS, Silver Spring, MD) and two versions of newgeneration portable instruments (poliSPECNIR, PL1 and PL2). The aim was to verify the quality of the transfer of the calibration curves between FOSS, PL1 and PL2 and between PL1 and PL2, obtained by three methods of spectra processing: pre-processing, piecewise direct standardisation (PDS) and direct standardisation (DS). Seventy-six samples of chopped whole maize plant were scanned with the three instruments and were analysed by wet chemistry for dry matter (DM), ash, crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF), starch and total sugars, to develop calibration equations. Two more datasets of 15 samples each were used for the standardisation of equations and validation. The calibration transfer obtained, according to the values of R2, standard error of prediction and bias, can be considered satisfactory (0.72>R2<0.97) for DM, ash and NDF for both poliSPECNIR, while CP and ADF have shown a good accuracy of prediction (0.78>R2<0.82) with PL2. Using FOSS as a master instrument, the choice of method of standardisation varies depending on the slave instrument even though the best results are obtained using PDS with PL2. The most accurate predictions are reached using PDS even when PL1 is the master

Prediction performances of portable near infrared instruments for at farm forage analysis

The objective of this study was to evaluate the use of Near Infrared Spectroscopy (NIRS) to analyze maize silage with a portable instrument. The instrument was a Zeiss Corona 45 working between 960 and 1700 nm which was used in Italy, Czech Republic and Poland. Best prediction performances were obtained using the Italian data set. Prediction error were 1.0, 0.16 and 0.4 respectively for DM, CP and NDF on a as is basis. With the instrument from Poland and Czech Republic there were lower accuracy of prediction compared to the Italian dataset, probably for their limited (less than 100 samples) calibration data set. Merging all the data set improved prediction accuracy for CP but not DM. It would appear that some form of instrument standardization is needed before merging data set

Use of near infrared spectroscopy for assessment of beef quality traits

Chemical and physical traits and fatty acid composition of meat samples from 148 Piemontese beef samples were predicted by near infrared spectroscopy. Coefficients of determination in calibration (R2) ranged between 0.44 and 0.99 for chemical composition and between 0.02 and 0.98 for fatty acid (FA) profile, being in general more accurate for the major FA. The calibration results gave inaccurate prediction for cholesterol and collagen content and for most physical traits, such as Warner-Bratzler shear force, cooking loss, drip loss, colour (L, a, b) and pH

Hepatocellular Carcinoma in a non-Cirrhotic Liver of a HCV-Positive Woman with Sustained Viral Response

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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

Hepatitis C Virus Infection Among non-IDU HIV-Infected and Uninfected Men who Have Sex with Men

In the Mediterranean countries, hepatitis C virus infection affect nearly 45% of HIV-1 infected individuals, consistently to the high proportion of patients with a history of intravenous drug use and exposed to the two viruses by parenteral route. Even in association with HIV-infection, HCV infection is rarely transmitted through sexual intercourse due to the lower efficiency of mucosal exposure to virus than that blood-borne. Thus, the incidence and prevalence of HCV infection are far lower among the non-intravenous drug users (IDU) at risk of sexually transmitted infections (STI). Two hypotheses may be taken in account to explain the lower prevalence rates observed in our seroprevalence study. The MSMs participating to our study could have less sexual contacts with IDU-MSMs than other gay community residents in other western countries. The non-IDU MSMs recruited in this study could have a lower frequency of at-risk sexual practices for HCV then the non-IDU MSMs enrolled in other studies

Proposal and validation of new indexes to evaluate maize silage fermentative quality in lab-scale ensiling conditions through the use of a receiver operating characteristic analysis

In the context of dairy cow feeding, it is increasingly important to know the quality of the maize silage used in the ration and therefore, it appears to be crucial optimizing the techniques necessary to assess it. The aim of this study was to evaluate whether some reference indexes, like the Flieg-Zimmer's (FZS), the German agricultural society's (DLG) and Vanbelle's scores, could properly estimate the quality of fermentations of maize silage made in a lab-scale ensiling system, and to calculate and validate new quality indexes suitable for lab-scale fermentations. The experimental dataset was obtained by analysing through near-infrared spectroscopy 522 samples of whole maize crop ensiled immediately after the harvest, using the vacuum-packing technique. The six (I1 \u2013 I6) new indexes were calculated on the basis of chemical and physical parameters as: pH, organic acids, ethanol, etc. All the indexes were tested for normality with the Shapiro\u2013Wilk test. In order to define the accuracy with which the new indexes ranked the maize silage on the basis of its fermentation quality, a receiver operating characteristic (ROC) analysis was performed, using the FZS as gold standard test and dichotomizing the FZS in two levels according to a cut-off (FZS 360 g/kg) dry matter (DM). In the lab-scale silages the new indexes were normally distributed, whereas the reference indexes were not. The new indexes showed values of AUC ranging between 0.76 and 0.89, with the I5 index showing the best combination of sensitivity (0.87) and specificity (0.77) in discriminating between good and poor quality silage. The cut-off of the new indexes ranged between 45.0 and 57.4 points. The lab-scale silages were all excellent, no matter the category of DM. However, while FZS and DLG did not differ among the 3 categories, I1 \u2013 I6 were significantly higher in silages with low DM (P < 0.001). Silages with low DM had the highest concentrations of lactic acid (56.4 g/kg DM, P < 0.001), ammonia (61.4 g/kg DM, P < 0.001) and butyric acid (0.62 g/kg DM, P < 0.001) as well. Data confirmed that the new proposed indexes are promising in describing the fermentation quality of maize silage in lab-scale conditions

Prediction performances of portable near infrared instruments for at farm forage analysis

The objective of this study was to evaluate the use of Near Infrared Spectroscopy (NIRS) to analyze maize silage with a portable instrument. The instrument was a Zeiss Corona 45 working between 960 and 1700 nm which was used in Italy, Czech Republic and Poland. Best prediction performances were obtained using the Italian data set. Prediction error were 1.0, 0.16 and 0.4 respectively for DM, CP and NDF on a as is basis. With the instrument from Poland and Czech Republic there were lower accuracy of prediction compared to the Italian dataset, probably for their limited (less than 100 samples) calibration data set. Merging all the data set improved prediction accuracy for CP but not DM. It would appear that some form of instrument standardization is needed before merging data set

METODO ED APPARECCHIATURA PER L’ANALISI DI UN PRODOTTO ALIMENTARE PER ANIMALI DA ALLEVAMENTO

La presente invenzione concerne un metodo per l’analisi di un prodotto alimentare per animali da allevamento, il quale comprende: una fase di 5 distribuzione del prodotto alimentare in una mangiatoia; una fase di campionamento del prodotto alimentare; una fase di rilevamento, per ciascun campione, di valori di più parametri; una prima fase di calcolo, per ciascun parametro, della media complessiva (MC) e della deviazione standard complessiva (SDC) dei valori di tale parametro; una seconda fase di calcolo, per 10 ciascun parametro, di un corrispondente indice di rapporto (IR) ricavato dal rapporto tra la corrispondente deviazione standard complessiva (SDC) e la corrispondente media complessiva (MC); una terza fase di calcolo, per ciascun parametro, di un indice di parametro (IP) ricavato dal prodotto del corrispondente indice di rapporto (IR) con un corrispondente coefficiente di peso 15 (CP); una quarta fase di calcolo di un indice numerico di omogeneità complessiva (IO) ottenuto dal rapporto tra la somma degli indici di parametro (IP) e la somma di valori teorici di indici massimi accettabili di parametro (TMA); una prima fase di confronto dell’indice numerico di omogeneità complessiva (IO) con almeno un valore di soglia; una prima fase di associazione 20 dell’indice numerico di omogeneità complessiva (IO) con un indice descrittivo di stato (IDS)

Authenticating Production Origin of Wild and Farmed Sea Bass (Dicentrarchuslabrax) by Infrared Spectroscopy NIRS (Near Infrared ReflectanceSpectroscopy)

Near Infrared Reflectance Spectroscopy (NIRS) technique is a secondary analytical technique based on the ability of every chemical compound and complex matrix of absorbing, transmitting and reflecting the infrared radiations. Over the last decade NIRS system has been used in many tests for fish and other food products due to its versatility and rapidity of analysis. The aim of this study was to evaluate NIRS performances in the prediction of Farmed vs. Wild production method of European sea bass. Wild (n=19) and Farmed (n=20) subjects were submitted to analysis in order to assess proximate composition and fatty acids profile of the whole fillet. Aliquots of wet and ground freeze-dried minced fillet were scanned in duplicates (1100 to 2498 nm; 2 nm intervals) in reflectance mode using a monochromator NIRsystem 5000. NIRS technique evidenced a satisfactory accurateness in predicting Protein, Lipids and Fatty acids profile in raw tissues. Repetition of measures on freeze-dried tissue increased some predicting values (r2: coefficient of determination on cross-validation range from 0.671 to 0.992; SECV: standard error of cross-validation range from 0.864 to 2.981). Results showed that NIRS technique was able to discriminate between Wild (94.7% samples recognized) and Farmed (100% samples recognized) using wet muscles, and 100% for both classes on ground freeze-dried fillet