Imputation of missing milk Fourier transform mid-infrared spectra using existing milk spectral databases: A strategy to improve the reliability of breeding values and predictive models

The use of milk Fourier transform mid-infrared (FT-MIR) spectrometry to develop management and breeding tools for dairy farmers and industry is growing and supported by the availability of numerous new predicted phenotypes to assess the nutritional quality of milk and its technological properties, but also the animal health and welfare status and its environmental fingerprint. For genetic evaluations, having a long-term and representative spectral dairy herd improvement (DHI) database improves the reliabilities of estimated breeding values (EBV) from these phenotypes. Unfortunately, most of the time, the raw spectral data used to generate these estimations are not stored. Moreover, many reference measurements of those phenotypes, needed during the FT-MIR calibration step, are available from past research activities but lack spectra records. So, it is impossible to use them to improve the FT-MIR models. Consequently, there is a strong interest in imputing those missing spectra. The innovative objective of this study was to use the existing large spectral DHI database to estimate missing spectra by selecting probable spectra using, as the match criteria, common dairy traits recorded for a long time by DHI organizations. We tested 4 match criteria combinations. Combination 1 required to have equal fat and protein contents between the sample for which a spectrum was to be estimated and the reference samples in the DHI database. Combination 2 also required an equal urea content. Combination 3 requested equal fat, protein, and lactose contents. Finally, combination 4 included all criteria. When more than one spectrum was found during the search, their average was the estimated spectrum for the query sample. Concretely, this study estimated missing spectra for 1,700 samples using 2,000,000 spectral DHI records. For assessing the effect of this spectral estimation on the prediction quality, FT-MIR equations were used to predict 11 phenotypes, selected as their quantification used different FT-MIR regions. They were related to the milk fat and mineral composition, lactoferrin content, quantity of eructed methane, body weight (BW), and dry matter intake. The accuracy between predictions obtained from actual and estimated spectra was evaluated by calculating the mean absolute error (MAE). The criteria in the fourth and second combinations were too strict to estimate a spectrum for most samples. Indeed, for many samples, no spectra with the same values for those matching criteria was found. The third match criteria combination had a poorer prediction performance for all studied traits and spectral absorptions than the first combination due to fewer matched samples available to compute the missing spectrum. By allowing a range for matching lactose content (±0.1 g/dL milk), we showed that this new combination increased the number of selected samples to compute missing spectra and predict better the infrared absorption at different wavenumbers, especially those related to the lactose quantification. The prediction performance was further improved by performing queries on the entire Walloon DHI spectral database (6,625,570 spectra), and it varied among the studied phenotypes. Without considering the traits used for the matching, the best predictions were obtained for the content of saturated fatty acids (MAE = 0.15 g/dL milk) and BW (MAE = 12.80 kg). Yet, the predictions for the unsaturated fatty acids were less accurate (MAE = 0.13 and 0.018 g/dL milk for monounsaturated and polyunsaturated fatty acids), likely because of the poorer predictions of spectral regions related to long-chain fatty acids. Similarly, poorer predictions were observed for the amount of methane eructed by dairy cows (MAE = 47.02 g/d), likely because it is not directly related to fat content or composition. Prediction accuracies for the remaining traits were also low. In conclusion, we observed that increasing the number of relevant matching criteria helps improve the quality of FT-MIR predicted phenotypes and the number of spectra used during the search. So, it would be of great interest to test in the future the suitability of the developed methodology with large-scale international spectral databases to improve the reliability of EBV from these FT-MIR-based phenotypes and the robustness of FT-MIR predictive models.

Usefulness of mid-infrared spectroscopy as a tool to estimate body condition score change from milk samples in intensively fed dairy cows

Directly measuring individual cow energy balance is not trivial. Other traits such as body condition score (BCS) and BCS change (ΔBCS) can, however, be used as an indicator of cow energy status. Body condition score is a metric used worldwide to estimate cow body reserves, but the estimation of ΔBCS was, until now, conditional on the availability of multiple BCS assessments. The aim of the present study was to estimate ΔBCS from milk mid-infrared (MIR) spectra and days in milk (DIM) in intensively fed dairy cows using statistical prediction methods. Daily BCS was interpolated from cubic splines fitted through the BCS records and daily ΔBCS was calculated from these splines. The ΔBCS records were merged with milk MIR spectra recorded on the same week. The dataset comprised 37,077 ΔBCS phenotypes across 9,403 lactations from 6,988 cows in 151 herds based in Quebec, Canada. Partial least squares regression (PLSR) and a neural network (NN) were then used to estimate ΔBCS from (1) MIR spectra only, (2) DIM only, or (3) MIR spectra and DIM together. The ΔBCS data in both the first 120 and 305 DIM of lactation were used to develop the estimates. Daily ΔBCS had a standard deviation of 4.40 × 10-3 BCS units in the 120-d dataset and of 3.63 × 10-3 BCS units in the 305-d dataset. A 4-fold cross-validation was used to calibrate and test the prediction equations. External validation was also conducted using more recent years of data. Irrespective of whether based on the first 120 or 305 DIM, or when MIR spectra only, DIM only or MIR spectra and DIM were jointly used as prediction variables, NN produced the lowest root mean square error (RMSE) of cross-validation (1.81 × 10-3 BCS units and 1.51 × 10-3 BCS units, respectively, using the 120-d and 305-d dataset). Relative to predictions for the entire 305 DIM, the RMSE of cross-validation was 15.4% and 1.5% lower in the first 120 DIM when using PLSR and NN, respectively. Predictions from DIM only were more accurate than those using just MIR spectra data but, irrespective of the dataset and of the prediction model used, combining DIM information with MIR spectral data as prediction variables reduced the RMSE compared with the inclusion of DIM alone, albeit the benefit was small (the RMSE from cross-validation reduced by up to 5.5% when DIM and spectral data were jointly used as model features instead of DIM only). However, when predicting extreme ΔBCS records, the MIR spectral data were more informative than DIM. Model performance when predicting ΔBCS records in future years was similar to that from cross-validation demonstrating the ability of MIR spectra of milk and DIM combined to estimate ΔBCS, particularly in early lactation. This can be used to routinely generate estimates of ΔBCS to aid in day-to-day individual cow management.

Mid-infrared spectroscopy for large-scale phenotyping of bovine colostrum gross composition and immunoglobulin concentration

Immunoglobulin G is the fundamental antibody for acquisition of passive transfer of immunity in ruminant newborns. Colostrum, in fact, must be administered as soon as possible after birth to ensure a successful transfer of IgG from the dam to the calf. Assessment of colostrum Ig concentration and gross composition via gold standards is expensive, time consuming, and hardly implementable for large-scale investigations. Therefore, in the present study we evaluated the predictive ability of mid-infrared spectroscopy (MIRS) as an indirect determination method. A total of 714 colostrum samples collected within 6 h from parturition from Italian Holstein cows, 30% primiparous and 70% pluriparous, were scanned using a benchtop spectrometer after dilution in pure water. The prediction models were developed by correlating spectral information with the reference measurements: IgG concentration (93.54 ± 33.87 g/L), total Ig concentrations (102.82 ± 35.04 g/L), and content of protein (14.71 ± 3.51%), fat (4.61 ± 3.04%), and lactose (2.36 ± 0.51 mg/100 mg). We found a good to excellent performance in prediction of colostrum IgG concentration and traditional composition traits in cross-validation (R2CV ≥ 0.92) and a promising and good predictive ability in external validation with R2V equal to 0.84, 0.89, and 0.74 for IgG, protein, and fat, respectively. In the case of IgG and protein content, for example, the coefficient of determination in external validation was greater than 0.84. The other Ig fractions, A and M, presented insufficient prediction accuracy likely due to their extremely low concentration compared with IgG (4.56 and 5.06 g/L vs. 93.54 g/L). The discriminant ability of MIRS-predicted IgG and protein content was outstanding when trying to classify samples according to the quality level (i.e., low vs. high concentration of IgG). In particular, the cut-off that better discriminate low- from high-quality colostrum was 75.40 g/L in the case of the MIRS-predicted IgG and 13.32% for the MIRS-predicted protein content. Therefore, MIRS is proposed as a rapid and cheap tool for large-scale punctual IgG, protein, and lactose quantification and for the screening of low-quality samples. From a practical perspective, there is the possibility to install colostrum models in the MIRS benchtop machineries already present in laboratories in charge of official milk testing. Colostrum phenotypes collected on an individual basis will be useful to breeders for the definition of specific selection strategies and to farmers for management scopes. Finally, our findings may be relevant for other stakeholders, given the fact that colostrum is an emerging ingredient for the animal and human food and pharmaceutical industry.

Estimates of diet selection in cattle grazing cornstalk residues by measurement of chemical composition and near infrared reflectance spectroscopy of diet samples collected by ruminal evacuation

Six ruminally cannulated cows (570 ± 73 kg) fed corn residues were placed in a 6 × 6 Latin square to evaluate predictions of diet composition from ruminally collected diet samples. After complete ruminal evacuation, cows were fed 1-kg meals (dry matter [DM]-basis) containing different combinations of cornstalk and leaf and husk (LH) residues in ratios of 0:100, 20:80, 40:60, 60:40, 80:20, and 100:0. Diet samples from each meal were collected by removal of ruminal contents after 1-h and were either unrinsed, hand-rinsed or machine-rinsed to evaluate effects of endogenous compounds on predictions of diet composition. Diet samples were analyzed for neutral (NDF) and acid (ADF) detergent fiber, acid detergent insoluble ash (ADIA), acid detergent lignin (ADL), crude protein (CP), and near infrared reflectance spectroscopy (NIRS) to calculate diet composition. Rinsing type increased NDF and ADF content and decreased ADIA and CP content of diet samples (P < 0.01). Rinsing tended to increase (P < 0.06) ADL content of diet samples. Differences in concentration between cornstalk and LH residues within each chemical component were standardized by calculating a coefficient of variation (CV). Accuracy and precision of estimates of diet composition were analyzed by regressing predicted diet composition and known diet composition. Predictions of diet composition were improved by increasing differences in concentration of chemical components between cornstalk and LH residues up to a CV of 22.6 ± 5.4%. Predictions of diet composition from unrinsed ADIA and machine-rinsed NIRS had the greatest accuracy (slope = 0.98 and 0.95, respectively) and large coefficients of determination (r2 = 0.86 and 0.74, respectively). Subsequently, a field study (Exp. 2) was performed to evaluate predictions of diet composition in cattle (646 ± 89 kg) grazing corn residue. Five cows were placed in 1 of 10 paddocks and allowed to graze continuously or to strip-graze corn residues. Predictions of diet composition from ADIA, ADL, and NIRS did not differ (P = 0.99), and estimates of cornstalk intake tended to be greater (P = 0.09) in strip-grazed compared to continuously grazed cows. These data indicate that diet composition can be predicted by chemical components or NIRS by ruminal collection of diet samples among cattle grazing corn residues.

Application of transmission infrared spectroscopy and partial least squares regression to predict immunoglobulin G concentration in dairy and beef cow colostrum

The objective of this study was to explore the potential of transmission infrared (TIR) spectroscopy in combination with partial least squares regression (PLSR) for quantification of dairy and beef cow colostral immunoglobulin G (IgG) concentration and assessment of colostrum quality. A total of 430 colostrum samples were collected from dairy (n = 235) and beef (n = 195) cows and tested by a radial immunodiffusion (RID) assay and TIR spectroscopy. Colostral IgG concentrations obtained by the RID assay were linked to the preprocessed spectra and divided into combined and prediction data sets. Three PLSR calibration models were built: one for the dairy cow colostrum only, the second for beef cow colostrum only, and the third for the merged dairy and beef cow colostrum. The predictive performance of each model was evaluated separately using the independent prediction data set. The Pearson correlation coefficients between IgG concentrations as determined by the TIR-based assay and the RID assay were 0.84 for dairy cow colostrum, 0.88 for beef cow colostrum, and 0.92 for the merged set of dairy and beef cow colostrum. The average of the differences between colostral IgG concentrations obtained by the RID- and TIR-based assays were -3.5, 2.7, and 1.4 g/L for dairy, beef, and merged colostrum samples, respectively. Further, the average relative error of the colostral IgG predicted by the TIR spectroscopy from the RID assay was 5% for dairy cow, 1.2% for beef cow, and 0.8% for the merged data set. The average intra-assay CV% of the IgG concentration predicted by the TIR-based method were 3.2%, 2.5%, and 6.9% for dairy cow, beef cow, and merged data set, respectively.The utility of TIR method for assessment of colostrum quality was evaluated using the entire data set and showed that TIR spectroscopy accurately identified the quality status of 91% of dairy cow colostrum, 95% of beef cow colostrum, and 89% and 93% of the merged dairy and beef cow colostrum samples, respectively. The results showed that TIR spectroscopy demonstrates potential as a simple, rapid, and cost-efficient method for use as an estimate of IgG concentration in dairy and beef cow colostrum samples and assessment of colostrum quality. The results also showed that merging the dairy and beef cow colostrum sample data sets improved the predictive ability of the TIR spectroscopy.

Prediction of methane emission from lactating dairy cows using milk fatty acids and mid-infrared spectroscopy

Enteric methane (CH4 ) production is among the main targets of greenhouse gas mitigation practices for the dairy industry. A simple, robust and inexpensive measurement technique applicable on a large scale to estimate CH4 emission from dairy cattle would therefore be valuable. Milk fatty acids (MFA) are related to CH4 production because of the common biochemical pathway between CH4 and fatty acids in the rumen. A summary of studies that investigated the predictive power of MFA composition for CH4 emission indicated good potential, with predictive power ranging between 47% and 95%. Until recently, gas chromatography (GC) was the principal method used to determine the MFA profile, but GC is unsuitable for routine analysis. This has led to the application of mid-infrared (MIR) spectroscopy. The major advantages of using MIR spectroscopy to predict CH4 emission include its simplicity and potential practical application at large scale. Disadvantages include the inability to predict important MFA for CH4 prediction, and the moderate predictive power for CH4 emission. It may not be sufficient to predict CH4 emission based on MIR alone. Integration with other factors, like feed intake, nutrient composition of the feed, parity, and lactation stage may improve the prediction of CH4 emission using MIR spectra. © 2016 Society of Chemical Industry.

Combining near infrared spectra of feces and geostatistics to generate forage nutritional quality maps across landscapes

An important asset for the management of wild ungulates is recognizing the spatial distribution of forage quality across heterogeneous landscapes. To do so typically requires knowledge of which plant species are eaten, in what abundance they are eaten, and what their nutritional quality might be. Acquiring such data, however, may be difficult and time consuming. Here, we are proposing a rapid and cost-effective forage quality monitoring tool that combines near infrared (NIR) spectra of fecal samples and easily obtained data on plant community composition. Our approach rests on the premise that NIR spectra of fecal samples collected within low population density exclosures reflect the optimal forage quality of a given landscape. Forage quality can thus be based on the Mahalanobis distance of fecal spectral scans across the landscape relative to fecal spectral scans inside exclosures (referred to as DISTEX). The Gi* spatial autocorrelation statistic can then be applied among neighboring DISTEX values to detect and map "hot spots" and "cold spots" of nutritional quality over the landscape. We tested our approach in a heterogeneous boreal landscape on Anticosti Island (Québec, Canada), where white-tailed deer (Odocoileus virginianus) populations over the landscape have ranged from 20 to 50 individuals/km2 for at least 80 years, resulting in a loss of most palatable and nutritious plant species. Our results suggest that hot spots of forage quality occur when old-growth balsam fir stands comprise >39.8% of 300 ha neighborhoods, whereas cold spots occur in laggs (i.e., transition zones from forest to peatland). In terms of ground-level indicator plant species, the presence of Canada bunchberry (Cornus canadensis) was highly correlated with hot spots, whereas tamarack (Larix laricina) was highly correlated with cold spots. Mean DISTEX values were positively and significantly correlated with the neutral detergent fiber and acid detergent lignin contents of feces. While our approach would need more independent field trials before it is fully validated, its low cost and ease of execution should make it a valuable tool for advancing both the basic and applied ecology of large herbivores.

[Epidemiological data of urinary stones in cats between 1981 and 2008]

OBJECTIVE

Evaluation of urinary stones analysed between 1981 and 2008 in cats and comparison with data submitted, such as breed, age, sex and body weight.

MATERIAL AND METHODS

Over the given years 5173 feline uroliths from cats in Germany and some neighbouring countries were analysed. From the forms submitted the following data was obtained for most cats: breed, age, sex, body weight, obesity status and location of the urinary stone(s). All uroliths were analysed by infrared spectroscopy. Uroliths containing at least 70% of a single mineral were classified as being of that type.

RESULTS

The cats with urolithiasis belonged to 25 different breeds. The most common breed was the European shorthair (64.3%) followed by Persian (15.2%), British shorthair (3.9%), Chartreux (1.7%), Maine Coon (1.5%) and Siamese (1.1%). Most animals were neutered or castrated (81.8%). Tom cats were significantly more frequently affected than female cats. The mean age (7 years) was virtually identical between both sexes, but varied between different stone types. Cats with struvite stones were significantly younger than cats with calcium oxalate stones (6.6 versus 7.6 years). Most urinary stones were retrieved from the bladder and/or urethra (93%). Over the entire time period (1981-2008) struvite (51.2%) and calcium oxalate (38.7%) stones were the two most common urolith types. Percent calcium oxalate stones increased significantly over time and were seen more often in 2008 than struvite stones (48.6% versus 43.4%). Amongst other urinary stones, ammonium urate (1.7%), carbonate apatite (1.7%), cystine (0.5%) and xanthine (0.3%) uroliths were analysed.

CONCLUSION AND CLINICAL RELEVANCE

While struvite and calcium oxalate stones are presently found at approximately equal frequency in cats, various different urinary stones types can also occur in this species. Epidemiological knowledge of urinary stones is crucial as a basis for adequate therapy and prevention.

Estimating fatty acid content in cow milk using mid-infrared spectrometry

Interest in the fatty acid composition of dairy products is increasing; however, the measurement of fatty acids requires using gas-liquid chromatography. Although this method is suitable, it involves a time-consuming procedure, expensive reagents, and qualified staff. By comparison, the mid-infrared (MIR) spectrometry method could be a good alternative for assessing the fatty acid profile of dairy products. The objective of this study was to explore the calibration of MIR spectrometry for estimating fatty acid concentrations in milk and milk fat. Estimated concentrations in milk fat were less reliable than those for the same fatty acids in milk. Results also showed that when the fatty acid concentrations in milk increased, the efficiency of the infrared analysis method in predicting these values simultaneously increased. Selected prediction equations must have a high cross-validation coefficient of determination, a high ratio of standard error of cross-validation to standard deviation, and good repeatability of chromatographic data. Results from this study showed that the calibration equations predicting 12:0, 14:0, 16:0, 16:1cis-9, 18:1, and saturated and monounsaturated fatty acids in milk could be used. Thus, with its potential for use in regular milk recording, this infrared analysis method offers the possibility of assessing and improving the quality of milk produced. Indeed, it enables the fatty acid composition in milk to be estimated for each cow and the estimates to be used as indicator traits to determine the genetic values of underlying fatty acid concentrations. The knowledge of these genetic values would open up opportunities for animal selection aimed at improving the nutritional quality of cow milk.

Evaluation of Chemical Parameters in Soft Mold-Ripened Cheese During Ripening by Mid-Infrared Spectroscopy

The suitability of mid-infrared spectroscopy (MIR) to follow the evolution throughout ripening of specific physicochemical parameters in Camembert-type cheeses was evaluated. The infrared spectra were obtained directly from raw cheese samples deposited on an attenuated total reflectance crystal. Significant correlations were observed between physicochemical data, pH, acid-soluble nitrogen, nonprotein nitrogen, ammonia (NH4+), lactose, and lactic acid. Dry matter showed significant correlation only with lactose and nonprotein nitrogen. Principal components analysis factorial maps of physicochemical data showed a ripening evolution in 2 steps, from d 1 to d 7 and from d 8 to d 27, similar to that observed previously from infrared spectral data. Partial least squares regressions made it possible to obtain good prediction models for dry matter, acid-soluble nitrogen, nonprotein nitrogen, lactose, lactic acid, and NH4+ values from spectral data of raw cheese. The values of 3 statistical parameters (coefficient of determination, root mean square error of cross validation, and ratio prediction deviation) are satisfactory. Less precise models were obtained for pH.

Variation in Fatty Acid Contents of Milk and Milk Fat Within and Across Breeds

The aim of this research was to study the potential for selection of cows with a higher nutritional quality of milk fat by studying the differences in fatty acid profiles within and across the following breeds: Dual Purpose Belgian Blue, Holstein-Friesian, Jersey, Montbeliarde, and non-Holstein Meuse-Rhine-Yssel type Red and White. Six hundred milk samples from 275 animals were taken from 7 herds. Several types of fatty acids in milk and milk fat were quantified using mid-infrared spectrometry and previously obtained calibration equations. Statistical analyses were made using a mixed linear model with a random animal effect. The variance components were estimated by using REML. Results showed breed differences for the fatty acid profile. The repeatability estimate obtained in the present study may suggest the existence of moderate additive genetic variance for the fatty acid profile within each breed. Results also indicated variation for each analyzed milk component in the whole cow population studied. Genetic improvement of the nutritional quality of milk fat based on fatty acid profiles might be possible, and further research and development are warranted.

Use of infrared spectroscopy for diagnosis of traumatic arthritis in horses

OBJECTIVE

To evaluate use of infrared spectroscopy for diagnosis of traumatic arthritis in horses.

ANIMALS

48 horses with traumatic arthritis and 5 clinically and radiographically normal horses.

PROCEDURES

Synovial fluid samples were collected from 77 joints in 48 horses with traumatic arthritis. Paired samples (affected and control joints) from 29 horses and independent samples from an affected (n = 12) or control (7) joint from 19 horses were collected for model calibration. A second set of 20 normal validation samples was collected from 5 clinically and radiographically normal horses. Fourier transform infrared spectra of synovial fluids were acquired and manipulated, and data from affected joints were compared with controls to identify spectroscopic features that differed significantly between groups. A classification model that used linear discriminant analysis was developed. Performance of the model was determined by use of the 2 validation datasets.

RESULTS

A classification model based on 3 infrared regions classified spectra from the calibration dataset with overall accuracy of 97% (sensitivity, 93%; specificity, 100%). The model, with cost-adjusted prior probabilities of 0.60:0.40, yielded overall accuracy of 89% (sensitivity, 83%; specificity, 100%) for the first validation sample dataset and 100% correct classification of the second set of independent normal control joints.

CONCLUSIONS AND CLINICAL RELEVANCE

The infrared spectroscopic patterns of fluid from joints with traumatic arthritis differed significantly from the corresponding patterns for controls. These alterations in absorption patterns may be used via an appropriate classification algorithm to differentiate the spectra of affected joints from those of controls.

Structure and composition of the septal nacreous layer of Nautilus macromphalus L. (Mollusca, Cephalopoda)

The nacreous layer of Mollusca is the best-known aragonitic structure and is the usual model for biomineralization. However, data are based on less than 10 species. In situ observations of the septal nacreous layer of the cephalopod Nautilus shell has revealed that the tablets are composed of acicular laths. These laths are composed of round nanograins surrounded by an organic sheet. No hole has been observed in the decalcified interlamellar membranes. A set of combined analytical data shows that the organic matrices extracted from the nacreous layer are glycoproteins. In both soluble and insoluble matrices, S amino acids are rare and the soluble organic matrices have a higher sulfated sugar content than the insoluble matrices. It is possible that the observed differences in the structure and composition of the nacreous layers of the outer wall and septa of the Nautilus shell have a dual origin: evolution and functional adaptation. However, we have no appropriate data as yet to answer this question.

Isoflurane measurement error using short wavelength infrared techniques in horses: influence of fresh gas flow and pre-anaesthetic food deprivation

OBJECTIVE

To quantify the isoflurane measurement error arising from the use of short wavelength infrared (IR) anaesthetic gas analysis during low flow anaesthesia in horses.

STUDY DESIGN

Prospective clinical study.

ANIMAL POPULATION

Sixty-four client-owned horses referred for elective or emergency surgery (age 1-16 years, body mass 400-650 kg).

MATERIALS AND METHODS

Horses were divided into four groups based on duration of pre-anaesthetic food deprivation period (FDP) and fresh gas flow during anaesthesia: a high flow group with normal FDP (n = 16) and three groups with low flow and normal (n = 29), long (n = 5) or no (n = 14) FDP, respectively. Circuit isoflurane concentrations were measured simultaneously using a short wavelength (methane-sensitive) analyser (Datex Capnomac Ultima) and a long wavelength (methane-insensitive) analyser (Hewlett Packard M 1025 B) for at least 60 minutes. The difference between the readings of both analysers gave the isoflurane measurement error of short wavelength IR analysis, from which the circuit methane concentration was calculated.

RESULTS

In the low flow groups, isoflurane measurement error increased over time, whereas in the high flow group, error remained constant after an initial rise in the first 15 minutes. The isoflurane measurement error was significantly lower (p < 0.005) in the high flow group compared with the low flow-normal FDP group from 15 to 60 minutes. Compared to the low flow - normal FDP group, isoflurane measurement error was significantly smaller (p < 0.001, from 15 to 60 minutes) in the low flow-long FDP group and significantly larger (p = 0.016, at 60 minutes) in the low flow-no FDP group. Within the low flow-no FDP group, values in colic cases did not differ from those in noncolic cases (p > 0.7).

CONCLUSIONS

Isoflurane measurement using short wavelength IR absorption is inaccurate. The fresh gas flow and duration of pre-anaesthetic food deprivation influence the isoflurane measurement error during anaesthesia in horses.

CLINICAL RELEVANCE

Short wavelength IR analysers are not reliable for isoflurane measurement during (low flow) anaesthesia in horses.

Technical note: Comparison of Raman, mid, and near infrared spectroscopy for predicting the amino acid content in animal meals12

The objective of this study was to compare three infrared spectroscopy techniques for routine evaluation of AA in animal meals. Animal meals (n = 54) with known AA contents were scanned with a near (NIRS), mid (FTIR), and Raman infrared spectrometer. For NIRS and Raman, samples were scanned "as is", whereas for FTIR, samples had to be finely ground before scanning to obtain reasonable spectra. Both FTIR and Raman data suffered from noise; for Raman, this prevented the development of calibrations. Using derivatized spectral data and a standardized outlier removal procedure, calibrations for nutritionally relevant AA could be developed that were equivalent for both NIRS and FTIR. The variation across AA tested explained (r2) by these calibrations was 70% for NIRS and 68 + 3% for FTIR. Removing spectral data between 4,000 and 2,000 cm(-1) from the FTIR data improved calibrations (P = 0.09) and explained an average of 77% of the variation with prediction errors lower than obtained with NIRS (P < 0.01). However, FTIR calibrations based on the entire or the shortened spectrum contained fewer samples than did NIRS calibrations (41 and 39 vs. 48, respectively; P < 0.01) because more samples were removed as outliers. In conclusion, Raman did not yield acceptable spectra for animal meals. For FTIR, sample preparation was more time-consuming because the samples required grinding before analysis. Using the entire mid-infrared range, FTIR calibrations were comparable to NIRS calibrations. Calibrations for FTIR were improved by eliminating wave numbers that exhibited more noise, resulting in prediction errors better than those for NIRS. Thus, FTIR has the potential to yield better calibrations for AA in animal meals than NIRS, but it requires greater care in sample preparation and scanning.

Evaluation of the reliability and repeatability of automated milk urea nitrogen testing

The purpose of this study was to evaluate the reliability (precision and accuracy), and repeatability of an infrared method of determining milk urea nitrogen. The reference method used for the reliability assessment was a wet-chemistry, enzymatic determination of milk urea nitrogen. Reliability and repeatability, as measured by concordance correlation coefficients, were 0.97 and 0.99, respectively.

Near- versus mid-infrared diffuse reflectance spectroscopy for determination of minerals in dried poultry manure

The objective of this study was to determine if accurate calibrations for mineral content in dried poultry manures could be developed using near- or mid-infrared spectra. Samples (n = 124) were obtained from a commercial testing laboratory along with conventionally determined values for Ca, Cu, K, Mg, Mn, P, S, and Zn. Samples were blended in a food blender, dried at 60 C, ground to 20 mesh, and scanned in the near-infrared (rotating sample cup) on a scanning monochromator. Samples were also scanned in the mid-infrared on a Fourier transform spectrometer using a custom-made sample transport. Results showed that calibrations based on nearor mid-infrared spectra were not satisfactory for the accurate determination of Ca, Cu, K, Mg, Mn, P, S, or Zn in dried poultry manures. At best, most of the calibrations would be suitable for only gross estimates, although the mid-infrared calibration for P might be suitable for some needs in which only a limited degree of accuracy was needed. Either spectral range could be used to separate dried poultry manure samples into those containing less than 3% and greater than 8% Ca but not to accurately differentiate samples within those two groupings. Finally, although the mid-infrared calibrations were the more accurate for five of the eight minerals studied, the differences between the two sets of calibrations were so varied that it would be difficult to say that one region is better for mineral content measurement.

Isolation of steroidal sapogenins implicated in experimentally induced cholangiopathy of sheep grazing Brachiaria decumbens in Brazil

As part of an experimental study, crystal-associated cholangiopathy was induced in 9 sheep by grazing pure pastures of Brachiaria decumbens in Brazil. One of these sheep showed characteristic lesions of photosensitization. The analysis of the B decumbens samples by acidic hydrolysis followed by TLC and infrared spectrum revealed diosgenin as the principal sapogenin present in the plant. In the rumen contents samples from the B decumbens-grazing group were identified by TLC, 1H and 13C NMR and EIMS as epismilagenin, episarsasapogenin, and a mixture of smilagenin and sarsasapogenin. In the bile samples from the B decumbens-grazing group, TLC analysis demonstrated 2 compounds similar to epismilagenin and episarsasapogenin. However, by this same method, those compounds were not observed in the rumen contents and bile from 2 sheep which served as control animals. The P chartarum spore counts remained very low during the experimental period.

Near infrared spectroscopy for biomonitoring: cow milk composition measurement in a spectral region from 1,100 to 2,400 nanometers

The potential of near infrared spectroscopy (NIRS; 1,100 to 2,400 nm) to measure fat, total protein, and lactose content of nonhomogenized milk during milking and the influence of individual characteristics of each cow's milk on the accuracy of determination were studied. Milk fractions were taken during milking, twice per month, for 6 mo. Samples were taken every 2nd and 4th wk at the morning and the evening milkings. Teatcups were removed at each 3 L of milk yield as determined with a fractional sampling milk meter. A total of 260 milk samples were collected and analyzed with an NIRSystem 6500 spectrophotometer with 1-mm sample thickness. Partial least squares (PLS) regression was used to develop calibration models for the examined milk components. The comparison with the reference method was based on standard error of cross validation (SECV). The obtained SECV varied from .107 to .138% for fat content, from .092 to .125% for total protein, and from .066 to .096% for lactose content, and the accuracy of the reference method (AOAC, 1990, method No 972.16) was .05% for all measured milk components. The obtained models had lower SECV when an individual cow's spectral data were used for calibration. The reduction of SECV for each cow's individual calibration, when compared with SECV for the set of all samples, differed with the different constituents. For fat content determination, the reduction reached 22.46%, for protein 26.40%, and for lactose 31.25%. This phenomena was investigated and explained by principle component analysis (PCA) and by comparing loading of PLS factors that account for the most spectral variations for each cow and the measured milk components, respectively. The results of this study indicated that NIRS (1,100 to 2,500 nm, 1-mm sample thickness) was satisfactory for nonhomogenized milk compositional analysis of milk fractions taken in the process of milking.

In situ and laboratory assessment of heart rate in a Mediterranean limpet using a noninvasive technique

Heart rate of the Mediterranean limpet Patella caerulea L. was investigated on the natural shore and in the laboratory by using a technique based on infrared phototransducers. Field recording occurred in the Gulf of Trieste (northern Adriatic) during March and June 1997. A consistent dependence of heart rate on temperature was observed in limpets both when submerged and when exposed to air in the two periods, but thermal acclimation was evident. During spontaneous activity at high tide, heart rate increased 1.5-1.7 times the values observed during resting in water at corresponding temperatures. The dependence of heart rate on temperature (10 degrees, 16 degrees, and 22 degrees C) and size (wet weight <1.25 and >1.30 g) in submerged limpets from different populations (northern Adriatic and Tyrrhenian) was tested in the laboratory by adopting a factorial design. The results showed a marked effect of temperature, body weight, and their interaction, independent from the site of origin. Smaller limpets showed a linear increase of heart rate in the whole range of temperature tests, while in the larger ones the increase between 10 degrees and 16 degrees C was greater than between 16 degrees and 22 degrees C. Heart rate decreased with increasing body size at control (16 degrees C) and high (22 degrees C) temperature, while at lower temperature (10 degrees C) no effect of body size was evident. When removed from their home scar, limpets increased heart rate to about 1.5 times the reference value. Finally, correlation of oxygen consumption with heart rate of submerged limpets maintained at a different temperature (10 degrees -22 degrees C) was statistically significant.

Near-infrared reflectance analysis for predicting beef longissimus tenderness

Near-infrared reflectance spectra (1,100 to 2,498 nm) were collected on beef longissimus thoracis steaks for the purpose of establishing the feasibility of predicting meat tenderness by spectroscopy. Partial least squares (PLS) analysis (up to 20 factors) and multiple linear regression (MLR) were used to predict cooked longissimus Warner-Bratzler shear (WBS) force values from spectra of steaks from 119 beef carcasses. Modeling used the combination of log(1/R) and its second derivative. Overall, absorption was higher for extremely tough steaks than for tender steaks. This was particularly true at wavelengths between 1,100 and 1,350 nm. For PLS regression, optimal model conditions (R2 = .67; SEC = 1.2 kg) occurred with six PLS factors. When the PLS model was tested against the validation subset, similar performance was obtained (R2 = .63; SEP = 1.3 kg) and bias was small (<.3 kg). Among the 39 samples in the validation data set, 48.7, 87.7, and 97.4% of the samples were predicted within 1.0, 2.0, and 3.0 kg, respectively, of the observed Warner-Bratzler shear force value. The optimal PLS model was able to predict whether a steak would have a Warner-Bratzler shear force value < 6 kg with 75% accuracy. The R2 of MLR model was .67, and 89% of samples were correctly classified (< 6 vs > 6 kg) for Warner-Bratzler shear force. These data indicate that NIR is capable of predicting Warner-Bratzler shear force values of longissimus steaks. Refinement of this technique may allow nondestructive measurement of beef longissimus at the processing plant level.

Glycolipid antigen for use in diagnostic assays for bovine tuberculosis

A glycolipid antigen, was isolated, purified and characterized from Mycobacterium bovis An5. Chemical analysis (thin-layer chromatography, nuclear magnetic resonance and infrared spectra) showed that this glycolipid was a 2,3-di-O-acyl trehalose (DAT), similar to the DAT of M. tuberculosis. This antigen was used to establish ELISA-based serodiagnostic tests for M. bovis-infected cattle. The sensitivity and specificity of the assay were investigated using sera of cattle from tuberculosis-free herds and from tuberculosis-infected herds. No correlation was found between DAT-ELISA and the skin test, nor between DAT-ELISA and interferon-gamma with bovine purified protein derivative. The antibody titres were not related to cell-mediated immunity. Although the antigen was highly specific (95.9%), the sensitivity of DAT-ELISA, as judged from assays in bacteriologically confirmed tuberculosis, was low (29 to 36.8%). The low sensitivity of ELISA might also be attributed to a reciprocal relationship between B-cell proliferation and T-cell protective immunity.

Bilateral xanthine nephrolithiasis in a dog

Xanthinuria is an uncommon metabolic disorder clinically manifested as urolithiasis. There are two forms of the disease, congenital and iatrogenic. The former was diagnosed in a four-year-old dachshund bitch. The patient was presented with signs of terminal chronic renal failure. Urine was bacteriologically sterile with massive amorphous crystalluria. Bilateral nephrolithiasis was diagnosed at necropsy. The kidneys were shrunken with marked atrophy of the renal cortex and medulla. Infrared spectrometry revealed that the stones comprised 100 per cent xanthine. Later, two of the patient's siblings were examined for urine xanthine content; both showed higher concentrations of xanthine than a control dog. The described case is compared with seven known published cases of congenital xanthinuria.

Infrared and atomic spectrometry analysis of the mineral composition of a series of equine sabulous material samples and urinary calculi

Atomic spectrometry has been used in 20 samples of equine urinary sabulous deposits in order to detect minor elements accompanying the predominant element, calcium, which is present in the form of calcium carbonate (calcite and/or vaterite). The elements measured have been (besides calcium) magnesium, sodium, potassium, iron, copper and manganese. Phosphates, sulphates and silica are frequently present as minor constituents of equine urinary sabulous deposits and uroliths, but their detection can be difficult by infrared (IR) spectroscopy in the original samples due to overlapping with the bands of calcium carbonate. For that reason, the calcination residues of six urinary calculi and 33 samples of sabulous material have been studied by IR spectroscopy and energy dispersive X-ray (EDX) analysis. The results confirm the presence of the above mentioned minor constituents in most samples studied.

Near infrared spectroscopy of pedal haemodynamics and oxygenation in normal and laminitic horses

The present study applies near infrared spectroscopy (NIRS) to the haemodynamics of the pedal circulation in normal and laminitic horses. NIRS is a noninvasive technique which uses changes in light absorption at 4 wavelengths to provide information on the changes in cytochrome aa3 (cyt aa3) reduction-oxidation (redox) status, and changes in the tissue concentration of oxyhaemoglobin (O2Hb), deoxyhaemoglobin (HHb) and therefore total haemoglobin (tHb). Other studies have shown NIRS to be sensitive to changes in tissue oxygenation and perfusion in human cerebral and limb circulation. In this study, the NIRS sensor was applied to the dorsal surface of horses' hooves. Normal and laminitic animals (acute and chronic) were subjected to manoeuvres (cuff tourniquet; digital vessel occlusion at the palmar surface of the pastern; lifting of contralateral limb) predicted to change pedal haemodynamics. The procedures produced changes in pedal haemodynamics and oxygenation, which were similar to those observed in the ischaemic/reperfused human forearm. Laminitic differed from normal horses: return of HHb to baseline was slower and the change in cyt aa3 more rapid than normal in cases of chronic laminitis, taken to indicate reduced O2 stores as a result of compromised basal perfusion. In acute laminitis, baseline values did not fluctuate following any of the manoeuvres, suggesting haemostasis in the diseased hoof. NIRS is a useful noninvasive method to assess pedal vascular function in normal and laminitic horses.