I. González-Martín

Determination of fatty acids in the subcutaneous fat of Iberian breed swine by near infrared spectroscopy (NIRS) with a fibre-optic probe.

A near infrared spectrometer equipped with a standard 1210/210 bundle remote reflectance fibre-optic probe, with a 5×5 cm quartz window, was used for the determination of fatty acids in the subcutaneous fat of Iberian pigs. A comparative study was made of the determination of fatty acids (C14:0, C16:0, C18:0, C18:1, C18:2, C18:3, C20: 1, Σpolyunsaturated, Σmonounsaturated and Σsaturated) in samples of subcutaneous fat from Iberian pigs by direct application of the fibre-optic probe on samples of whole subcutaneous fat and with cam-lock cups, assessing extracts of total lipids with diethyl ether. The regression method employed was modified partial least squares (MPLS). Calibration of 157 samples, using the fibre optic probe, allowed determination of fatty acids in the following ranges: C14:0 (0.78-1.77), C16:0 (15.87-29.74), C18:0 (4.61-15.90), C18:1 (43.50-61.27), C18:2 (2.03-13.94), C18:3 (0.13-1.14), C20:1 (0.45-2.32), Σpolyunsaturated (2.31-14.82), Σmonounsaturated (47.37-65.62), Σsaturated (22.09-47.31), with corrected standard errors of prediction SEP(C) of 0.093, 0.56, 0.67, 0.94, 0.42, 0.10, 0.20, 0.46, 0.94, 0.83, respectively. The robustness of the method using the fibre-optic probe was tested in a slaughterhouse using 23 samples for external validation, giving multiple correlation coefficients (RSQ) for C14:0, C16:0, C18:0, C18:1, C18:2, C18:3 C20:1, Σpolyunsaturated, Σmonounsaturated, Σsaturated acids of 0.72, 0.94, 0.72, 0.79, 0.88, 0.55, 0.17, 0.88, 0.74, and 0.90, respectively, and a corrected standard error of prediction [SEP(C)] for these acids (%) of 0.11, 0.60, 0.84, 1.20, 0.77, 0.11, 0.30, 0.76, 1.21, and 1.18, respectively.

Mineral analysis (Fe, Zn, Ca, Na, K) of fresh Iberian pork loin by near infrared reflectance spectrometry: Determination of Fe, Na and K with a remote fibre-optic reflectance probe

Abstract Near infrared spectrometry (NIRS) was used for the determination of the mineral concentrations of the elements iron, calcium, zinc, sodium and potassium in fresh samples of ground Iberian pork loin and for the determination of Fe, Na and K using a remote fibre-optic reflectance probe by direct application of the probe on intact loin. The regression method employed was the modified partial least squares (MPLS). The calibration results using 42 samples of ground pork loin had a corrected standard error of prediction (SEPC) and a correlation coefficient (RSQ) for Fe of 0.085 and 0.842; for Zn, 0.0097 and 0.695; for Ca, 0.101 and 0.761; for Na, 0.710 and 0.639 and for K, 4.414 and 0.781, respectively. The calibration results using NIR interactance with direct application to the same loin samples of a remote fibre-optic reflectance probe allowed the determination of the concentrations of Fe, Na and K, with SEPC and RSQ values of 0.084 and 0.898 for Fe; 0.698 and 0.757 for Na, and 6.760 and 0.775 for K. The robustness of the method was confirmed by applying it to eight samples of loin (ground and intact) for external validation.

Differentiation of products derived from Iberian breed swine by electronic olfactometry (electronic nose)

Abstract The aim of the present work was to differentiate products derived from Iberian breed swine, using chemometric analysis of the data obtained from an array of gas sensors. A commercial Electronic Nose (FOX 2000) comprising six metal oxide semiconductor sensors was used to generate a pattern of volatile compounds present in the samples. Linear discriminant analysis (LDA) and independent class modelling, i.e. soft independent modelling of class analogy (SIMCA) were applied to the patterns generated to achieve several classification tasks. The procedure for obtaining the signals and the chemometric treatment are rapid and simple, allowing the classification of products derived from Iberian swine according to the type of feeding regimen they have been subject to (feed, feed+acorn, acorns alone) using samples of subcutaneous adipose tissue.

Use of NIRS technology with a remote reflectance fibre-optic probe for predicting major components in bee pollen.

In the present work the potential of near infra-red spectroscopy technology (NIRS) together with the use of a remote reflectance fibre-optic probe for the analysis of fat, moisture, protein and chlorides contents of commercial cheeses elaborated with mixtures of cows, ewes and goats milk and with different curing times was examined. The probe was applied directly, with no previous sample treatment. The regression method employed was modified partial least squares (MPLS). The equations developed for the cheese samples afforded fat, moisture, protein, and chloride contents in the range 13-52%, 10-62%, 20-30%, and 0.7-2.9%, respectively. The multiple correlation coefficients (RSQ) and prediction corrected standard errors (SEP (C)) obtained were respectively 0.97 and 0.995% for fat; 0.96% and 1.640% for moisture; 0.78% and 0.760% for protein, and 0.89% and 0.112% for chlorides.

On-line non-destructive determination of proteins and infiltrated fat in Iberian pork loin by near infrared spectrometry with a remote reflectance fibre optic probe

A near infrared (NIR) spectrometer equipped with a standard 210/210 bundle remote reflectance fibre optic probe, with a 5c m× 5 cm quartz window, was used for the determination of protein and infiltrated fat in the pork loin muscle of Iberian swine (Longissimus dorsi). The content in infiltrated fat was found to vary from 3 to 19% and that of protein from 21 to 31%. The regression method employed was modified partial least squares (MPLSs). The calibration results using the fibre optic probe for 56 samples had corrected standard error of prediction of 0.74% for the fat (multiple correlation coefficient, RSQ = 0.94) and of 0.80% for the protein (RSQ = 0.881). A comparative study was carried out on the determination of fat and protein in the same pork loin samples using the fibre optic probe without destruction of the sample and with conventional measuring cells using ground samples. The method was applied in the dissecting hall of a slaughterhouse. The results show that NIR interaction, with direct application of a fibre optic probe on pork loin samples, permits the determination of protein and infiltrated fat without destruction the sample, with good results.

Determination of fatty acids in the subcutaneous fat of Iberian breed swine by near infrared spectroscopy. A comparative study of the methods for obtaining total lipids: solvents and melting with microwaves

Near infrared (NIR) spectroscopy has been used to predict the composition of the fatty acids of samples of subcutateous fat from Iberian breed swine, comparing the two methods employed for collecting total lipids—extraction with solvents and microwave melting—using gas chromatography as a reference method. The regression method used was modified partial least squares. The calibration results for 115 samples of subcutaneous fat extracted with solvents and the calibration measured with NIR permitted the determination of 12 fatty acids: C12:0, C14:0, C16:0, C16:1, C17:0, C17:1, C18:0, C18:1, C18:2, C18:3, C20;0 and C20:1, total polyunsaturated, total monosaturated and total saturated acid with squared multiple correlation coefficients of 0.84, 0.70, 0.89, 0.75, 0.62, 0.66, 0.85, 0.91, 0.88, 0.77, 0.85, 0.66, 0.90, 0.89 and 0.92, respectively, and a standard error of calibration (SEC) for these acids (%) of 0.007, 0.091, 0.48, 0.14, 0.03, 0.03, 0.42, 0.72. 0.31, 0.09, 0.02, 0.15, 0.31, 0.70 and 0.68, respectively. Extraction of total lipids by microwave melting for the same samples and using NIR calibration allowed the determination of six fatty acids: C16:0, C16:1, C18:0, C18:1, C18:2, C18:3, total polyunsaturated, total monounsaturated and total saturated acid, with a squared multiple correlation coefficients (RSQ) of 0.93, 0.70, 0.88, 0.90, 0.83, 0.63, 0.82, 0.92 and 0.95, respectively, and an SEC for these acids (%) of 0.36, 0.14, 0.44, 0.77, 0.33, 0.08, 0.39, 0.69 and 0.56, respectively. The robustness of the two extraction methods and of the determination was checked by applying them to 20 samples for external validation.

Determination of inorganic elements in animal feeds by NIRS technology and a fibre-optic probe

In the present work we study the use of near infra-red spectroscopy (NIRS) technology together with a remote reflectance fibre-optic probe for the analysis of the mineral composition of animal feeds. The method allows immediate control of the feeds without prior sample treatment or destruction through direct application of the fibre-optic probe on the sample. The regression method employed was modified partial least squares (MPLS). The calibration results obtained using forty samples of animal feeds allowed the determination of Fe, Mn, Ca, Na, K, P, Zn and Cu, with a standard error of prediction (SEP(C)) and a correlation coefficient (RSQ) of 0.129 and 0.859 for Fe; 0.175 and 0.816 for Mn; 5.470 and 0.927 for Ca; 2.717 and 0.862 for Na; 4.397 and 0.891 for K; 2.226 and 0.881 for P; 0.153 and 0.764 for Zn, and 0.095 and 0.918 for Cu, respectively. The robustness of the method was checked by applying it to 10 animal feeds samples of unknown mineral composition in the external validation.

NIR Spectroscopy: An Alternative for Soil Analysis

Advances in laboratory instrumentation and chemometrics provide alternatives to traditional methods of conducting soil chemical analysis. One of these is infrared diffuse reflectance spectroscopy in the near-infrared spectral range (NIRS). Herein we report the results of a multinational study to develop useful calibrations associating NIRS spectra with laboratory-measured results for total soil carbon (C), total soil nitrogen (N), δ13C, and δ15N from a single soil site in Mexico subjected to zero- and conventional-tillage regimens with and without crop residues and crop rotations of maize and wheat across 16 years. Modified partial least squares regression (MPLS) was used to obtain useful NIR predictions for total soil C and N, with ratio performance deviation (RPD) values of 6.8 and 2.6, respectively. Corresponding multiple correlation coefficients (RSQs) for C and N were 0.98 and 0.85, with standard errors of prediction (SEPs) of ±0.45 g C kg–1 and ±0.09g Nkg–1, respectively. The generation of δ15N and δ13C models produced different NIR recordings in soils with and without crop residues. Application of discriminant partial least squares (DPLS) statistics to the NIR spectral data allowed us to discriminate soils with and without residues. The prediction confidence for stable isotopes was 90% (internal validation) and 94% (external validation). Modified partial least squares regression was used to estimate δ15N and δ13C. Ratio performance deviation, RSQ, and SEP values obtained for δ13C and δ15N were 2.44 and 3.57, 0.83 and 0.81, ±0.5‰ (parts per thousand) and ±0.45‰ in soils with residues and 2.5 and 3.8, 0.93 and 0.92, and ±0.2‰ and ±0.23‰ in soils without residues, respectively. Overall, results obtained with NIRS were comparable to those obtained using conventional analytical methods, a finding that has wide relevance to agricultural soils and environmental studies in tropical locations. However, further testing is necessary to confirm that the calibration models are neither site nor instrument specific.

Discrimination of seasonality in cheeses by near-infrared technology

BACKGROUND Owing to the importance of the season of collection of milk for cheese quality, a study was made of the usefulness of near-infrared spectroscopy (NIRS) for discriminating the seasonal origin (winter or summer) of milk and quantifying the fat content of cheeses, since fat is one of the components most affected by the season of collection of milk for the elaboration of cheeses. RESULTS In the internal validation, 96% of samples from winter milk and 97% of samples from summer milk were correctly classified, while in the external validation the prediction rate of samples correctly classified was 92%. Moreover, quantitative models allowed the determination of fat in winter, summer and winter + summer cheeses. CONCLUSION Rapid prediction of the fat content of cheeses and the seasonal origin (winter or summer) of milk was achieved using NIRS without previous destruction or treatment of samples.

Near-infrared spectroscopy (NIRS) with a fibre-optic probe for the prediction of the amino acid composition in animal feeds

The amino acids alanine, aspartic acid, glutamic acid, glycine, phenylalanine, valine, lysine, proline, and tyrosine present in feeds with different textures (blocks, tablets, granules and flour (meal) and used in different stages of animal feeding regimes (lactation, growth, maintenance, etc.) were analysed using near-infrared reflectance spectroscopy (NIRS) technology together with a remote reflectance fibre-optic probe. The method allows immediate control of the animal feeds without prior sample treatment or destruction through direct application of the fibre-optic probe on the sample. The regression method used was Modified Partial Least Squares (MPLS). The equations developed to determine the amino acid contents of the feeds afforded high values for the RSQ coefficient (0.814-0.963) in all the amino acids with the exception of lysine (0.687). The statistical prediction descriptors SEP, SEP(C) (with values between 0.134 for valine and 0.015 for aspartic acid) and bias indicated that the amino acid values in feeds predicted with NIRS with a fibre optic probe are comparable to those obtained with the chemical ion-exchange HPLC method.