On-line prediction of lamb fatty acid composition by visible near infrared spectroscopy.

This study investigated the potential of visible near infrared spectroscopy (Vis-NIRS) to quantify the fatty acid(FA) composition of lamb meat under commercial abattoir conditions. Genetic algorithm based partial least squares (PLS) were used to develop regression models for predicting individual FA and FA groups such as saturated FA (SFA), monounsaturated FA (MUFA) and polyunsaturated FA (PUFA). Overall, the majority of the FA(C14:0, C16:0, C16:1, C17:0, C18:1 c9, C18:1 c11, C18:2 n-6, C18:2 c9 t11 and C18:1 t11), intramuscular fat(IMF) and all FA groups were predicted with an R2(CV), the squared correlation between observed and cross validated predicted values,which ranged between 0.60 and 0.74 and ratio prediction to deviation (RPD) values between 1.60 and 2.24. However the results for the remaining FA (C17:1, C18:0, C18:3 n−3, C20:4, C20:5, C22:5, C22:6) were unsatisfactory (R2= 0.35-0.57, RPD= 0.76-1.49). This indicates that Vis-NIRS could be used as an on-line tool to predict a number of FA.

Pullanagari RR ，Yule IJ ，Agnew M 《-》

Genetic analysis of beef fatty acid composition predicted by near-infrared spectroscopy.

The aims of this study were 1) to investigate the potential application of near-infrared spectroscopy (NIRS) to predict intramuscular fat (IMF) and fatty acid (FA) composition of individual meat samples, 2) to estimate heritability of IMF and FA NIRS-based predictions, and 3) to assess the statistical relevance of the genetic background of such predictions by using the Bayes factor (BF) procedure. Young Piemontese bulls (n = 1,298) were raised and fattened on 124 farms, and slaughtered at the same commercial abattoir. Intramuscular fat content and FA composition were analyzed on a random subset of 148 samples of minced and homogenized longissimus thoracis muscle. Near-infrared spectroscopy spectra were collected on all samples (n = 1,298) in reflectance mode between 1,100 and 2,498 nm (every 2 nm) using fresh minced meat samples. Calibration models developed from the random subset of 148 samples were used to predict IMF and FA contents of the remaining 1,150 samples. Intramuscular fat content and FA predictions were analyzed under a Bayesian univariate animal linear models, and the statistical relevance of heritability estimates was assessed through BF; the model with polygenic additive effects was favored when BF > 1. In general, satisfactory results (R(2) > 0.60) were obtained for 6 out of the 8 major FA (C14:0, C:16:0, C16:1, C18:0, C18:1n-9 cis/trans, and C18:1n-11 trans), 6 out of the 19 minor FA (C10:0, C12:0, C17:0, C17:1, C18:2 cis-9,trans-11, and C20:2), and the total SFA, MUFA, and PUFA. Bayes factors between models with and without a genetic component provided values greater than 1 for IMF, C14:0, C16:0, C18:1n-9 cis/trans, C17:0, C17:1, C20:2, SFA, MUFA, and PUFA. The greatest BF was reached by C20:2 (BF >10), suggesting strong evidence of genetic determinism, whereas IMF, C18:1n-9 cis/trans, C17:0, C17:1, MUFA, and PUFA showed substantial evidence favoring the numerator model (3.16 < BF < 10). Point estimates of heritabilities for FA predicted by NIRS were low to moderate (0.07 to 0.21). Results support that NIRS is a useful technique to satisfactorily predict some FA of meat. The existence of an important genetic determinism affecting FA profile has been confirmed, suggesting that FA composition of meat can be genetically modified.

Cecchinato A ，De Marchi M ，Penasa M ，Casellas J ，Schiavon S ，Bittante G ... -  《-》

Application of NIRS for predicting fatty acids in intramuscular fat of rabbit.

The aim of this study was to evaluate the use of near infrared reflectance spectroscopy (NIRS) for predicting fatty acid content in intramuscular fat to be applied in rabbit selection programs. One hundred and forty three freeze-dried Longissimus muscles (LM) were scanned by NIRS (1100-2498nm). Modified Partial Least Squares models were obtained. Equations were selected according to standard error of cross validation (SECV) and coefficient of determination of cross validation (R(2)(CV)). Residual predictive deviation of cross validation (RPD(CV)) was also studied. Accurate predictions were reported for IMF (R(2)(CV)=0.98; RPD(CV)=7.57), saturated (R(2)(CV)=0.96; RPD(CV)=5.08) and monounsaturated FA content (R(2)(CV)=0.98; RPD(CV)=6.68). Lower accuracy was obtained for polyunsaturated FA content (R(2)(CV)=0.83; RPD(CV)=2.40). Several individual FA were accurately predicted such as C14:0, C15:0, C16:0, C16:1, C17:0, C18:0, C18:1 n-9, C18:2 n-6 and C18:3 n-3 (R(2)(CV)=0.91-0.97; RPD(CV)>3). Long chain polyunsaturated FA and C18:1 n-7 presented less accurate prediction equations (R(2)(CV)=0.12-0.82; RPD(CV)<3).

Zomeño C ，Juste V ，Hernández P 《-》

Determination of fatty acids in broiler breast meat by near-infrared reflectance spectroscopy.

The aim of this study was to develop near-infrared reflectance spectroscopy (NIRS) calibrations for determination of the fatty acids (FA) in broiler breast meat. A total of 144 breast meat samples were freeze-dried and divided into calibration set and validation set. Calibration models were developed for FA including C14:0, C16:0, C16:1n-7, C18:0, C18:1n-7, C18:1n-9, C18:2n-6, C18:3n-3, C18:3n-6, C20:0, C20:1n-9, C20:2n-6, C20:4n-6, C20:5n-3, C22:4n-6, C22:6n-3, C24:0 and C24:1n-9. Calibration models for FA groups were also developed. Calibrations based on the absolute FA content were more accurate than those based on the relative composition (%). The coefficients of determination of FA and FA groups (based on the absolute content) except C18:3n-6, C20:0, C20:2n-6 and C24:1n-9, were between 0.86 and 0.98 for calibration, and 0.83 and 0.97 for validation. The results indicate NIRS can be a feasible and rapid method for determination of FA with a mean concentration over 0.10g/kg.

Zhou LJ ，Wu H ，Li JT ，Wang ZY ，Zhang LY ... -  《-》

At-line prediction of fatty acid profile in chicken breast using near infrared reflectance spectroscopy.

Near infrared reflectance (NIR) spectroscopy was evaluated as at-line technique to predict FA profile of chicken breast directly at the slaughterhouse. Intact breasts of 214 chickens were scanned by applying a fiber optic probe to the Pectoralis superficialis muscle. Meat samples were analyzed by gas chromatography as the reference method for the determination of FA composition. Calibration equations were developed considering NIR wavelengths between 1100 and 1830nm, and modified partial least square (MPLS) was chosen as the chemometrics method to perform the calibrations. Different mathematical pre-treatments were tested and the best calibration equation for each FA was retained. Near infrared reflectance spectroscopy did not result in satisfactory predictions of FA. The best predictions were observed for oleic acid (C18:1n-9), monounsaturated FA (MUFA), and polyunsaturated FA (PUFA), and for a few minor FA. Results suggest that for chicken breast muscle, a lean meat, it was not possible to predict FA using NIR spectroscopy as an at-line technique in the abattoir.

De Marchi M ，Riovanto R ，Penasa M ，Cassandro M ... -  《-》