The ability of a handheld near-infrared spectrometer for a rapid quality assessment of bovine colostrum including the Ig G concentration.

Portable infrared-based instruments have made significant contributions in different research fields. Within the dairy supply chain, for example, most of portable devices are based on near-infrared spectroscopy (NIRS) and are nowadays an important support for farmers and operators of the dairy sector, allowing fast decision-making, particularly for feed and milk quality evaluation and animal health and welfare monitoring. The affordability, portability, and ease of use of these innovative devices have been pivotal factors for the implementation in dairy farms. In fact, pocket-sized devices enable non-expert users to perform quick, low cost and non-destructive analysis on various samples without complex preparation. As bovine colostrum (BC) quality is mostly given by the Ig G (IgG) level, evaluating the ability of portable NIRS tools to measure antibodies concentration is advisable. In this study we used the wireless device SCiO manufactured by Consumer Physics Inc. (Tel Aviv, Israel) to collect BC spectra and then attempt to predict IgG concentration and gross and fine composition in individual samples collected as soon as possible after calving (<6 h) in primiparous and pluriparous Holstein cows farmed in 9 Italian farms. Chemometric analyses revealed that SCiO has promising predictive performance for colostral IgG concentration, total Ig concentration, fat, and AA (R2CV ≥ 0.75). Excellent accuracy was observed for dry matter, protein, and S prediction in cross-validation and good prediction ability in external validation (R2CV ≥ 0.93; R2V ≥ 0.82). Nonetheless, SCiO's ability to discriminate between good- and low-quality samples was satisfactory. The affordable cost, the accurate predictions, and the user-friendly design coupled with the increased interest in colostrum quality within the dairy sector may boost the collection of extensive BC data for management and genetic purposes in the near future.

Across countries implementation of handheld near-infrared spectrometer for the on-line prediction of beef marbling in slaughterhouse.

Only few studies have used Near-Infrared (NIR) spectroscopy to assess meat quality traits directly in the chiller. The aim of this study was therefore to investigate the ability of a handheld NIR spectrometer to predict marbling scores on intact meat muscles in the chiller. A total of 829 animals from 2 slaughterhouses in France and Italy were involved. Marbling was assessed according to the 3G (Global Grading Guaranteed) protocol using 2 different scores. NIR measurements were collected by performing 5 scans at different points of the Longissimus thoracis. An average MSA marbling score of 330-340 was obtained in the two countries. The prediction models provided a R2 in external validation between 0.46 and 0.59 and a standard error of prediction between 83.1 and 105.5. Results did provide a moderate prediction of the marbling scores but can be useful in the European industry context to predict classes of MSA marbling.

Genetic characteristics of colostrum refractive index and its use as a proxy for the concentration of immunoglobulins in Holstein cattle.

BACKGROUND: Colostral concentration of immunoglobulins (Ig) is crucial for the passive transfer of antibodies from the cow to the new-born calf. Direct determination of Ig by the gold standard radial immunodiffusion method is demanding in terms of time and costs. For this reason, a refractometer is commonly used at the farm level for an indirect estimation of colostrum quality, which is given as the Ig concentration. In this study, colostrum samples were collected from 548 Italian Holstein cows within 6 h of calving. The refractive index (BRIX, %) of these samples was assessed using a portable optical refractometer, as well as the concentration of total protein, IgG, IgA, and IgM by radial immunodiffusion. A four-trait animal model was used to estimate genetic parameters for BRIX and the different immunoglobulin isotypes. A receiver operating characteristic analysis was carried out to evaluate the BRIX diagnostic accuracy. RESULTS: Colostral BRIX was moderately heritable (0.26) and its genetic and phenotypic correlations with IgG (0.91, 0.78), IgA (0.57, 0.57), and IgM (0.71, 0.61) were all positive and of similar order, although the genetic correlations were generally higher than the phenotypic correlations. Low-quality colostrum samples, defined as those with an IgG concentration lower than 50 g/L, were accurately identified by the refractive index on the BRIX scale, with an area under the curve of 0.90. CONCLUSIONS: The use of a refractometer is recommended on dairy farms to produce a proxy for colostral Ig concentration. BRIX is a useful phenotyping tool that can be used in cattle to improve the quality of colostrum for first feeding of calves through both traditional genetic and genomic strategies. Improving colostrum quality will reduce the incidence of failure of passive transfer of immunity in young stock.

Long-term administration of a commercial supplement enriched with bioactive compounds does not affect feed intake, health status, and growth performances in beef cattle.

Feed additives including natural bioactive compounds (BCs) in combination with vitamin E (VitE) and organic Se could mitigate animal stress associated with intensive livestock farming due to their anti-inflammatory and antioxidant properties. Yeast and yeast derivate are included in feed additives as probiotic products and digestion promoters. Scutellaria baicalensis is a source of bioactive compounds and has been tested in monogastrics, exhibiting many immunostimulating and hepato-protective activities. However, the literature lacks information regarding S. baicalensis effects on beef cattle performance and health status. The aim of the present study was to evaluate the impact on beef cattle's feed intake, health and oxidative status, and growth performances of the inclusion of a commercial supplement (CS) containing VitE, organic Se, yeast derivate, and S. baicalensis extract during the fattening and finishing period. A total of 143 Charolaise male cattle were allotted into 12 pens of 11-12 animals each and assigned to a control ( 463.9 ± 21.48 body weight - BW) or a treated ( 469.8 ± 17.91  BW) group. Each group included two replicates of three pens. The treated groups were supplemented with 20  g CS animal - 1 d - 1 . Feed intake was measured monthly on a pen base during two consecutive days. Total mixed ration and fecal samples were collected at three time points (monthly, from November to February) and pooled by replicate for the analyses to monitor digestibility. Blood samples were individually collected at the beginning and at the end of the trial for oxidative status and metabolic profile determination. Final BW and carcass weight were individually recorded to calculate average daily gain, feed conversion ratio, and carcass yield. Similar feed digestibility between groups were observed during the whole experiment. Feed intake, growth performances, final body weight, average daily gain, feed conversion rate, oxidative status, and metabolic profile were not affected by the dietary inclusion of the tested CS indicating no detrimental effect of the treatment. Different doses of this product should be tested in the future in order to provide a more complete report on the product efficacy.

Handheld near-infrared spectrometer allows on-line prediction of beef quality traits.

The aim of this study was to evaluate the ability of a miniaturized near-infrared spectrometer to predict chemical parameters, technological and quality traits, fatty acids and minerals in intact Longissimus thoracis and Trapezius obtained from the ribs of 40 Charolais cattle. Modified partial least squares regression analysis to correlate spectra information to reference values, and several scatter correction and mathematical treatments have been tested. Leave-one-out cross-validation results showed that the handheld instrument could be used to obtain a good prediction of moisture and an approximate quantitative prediction of fat or protein contents, a*, b*, shear force and purge loss with coefficients of determination above 0.66. Moreover, prediction models were satisfactory for proportions of MUFA, PUFA, oleic and palmitic acids, for Fe and Cu contents. Overall, results exhibited the usefulness of the on-line miniaturized tool to predict some beef quality traits and the possibility to use it with commercial cuts without sampling, carcass deterioration nor grinding and consequent meat products' loss.

The concentrations of immunoglobulins in bovine colostrum determined by the gold standard method are genetically correlated with their near-infrared prediction.

BACKGROUND: The quality of colostrum administered to calves is based on its concentration in immunoglobulins G (IgG, g/L). Immunoglobulins A (IgA) and M (IgM) are also present but at a lower level. The gold standard reference analysis for these traits, radial immunodiffusion, is time-consuming and expensive. In order to define breeding strategies that are aimed at improving colostrum quality in dairy cattle, a large amount of data is needed, and the use of indicator traits would be beneficial. In the study presented here, we explored the heritabilities of reference (radial immunodiffusion) and near infrared-predicted IgG, IgA, and IgM concentrations and estimated their genetic correlations. First, the colostrum of 765 Holstein cows from nine herds was sampled to perform a reference analysis and the near-infrared spectra (400-2500 nm) were stored. We used a calibration set (28% of the initial samples) that was representative of the herds and cow parity orders to develop prediction equations for IgG, IgA, and IgM concentrations. Finally, these traits were predicted in the validation set (72% of the initial samples) to estimate genetic parameters for the predictions. Genetic correlations between reference and predicted values of each trait were estimated through bivariate linear animal models. RESULTS: The three near-infrared-predicted immunoglobulin fractions were genetically correlated with their reference value. In particular, the reference and predicted IgG concentrations were strongly correlated at both the genetic (0.854 ± 0.314) and phenotypic level (0.767 ± 0.019). Weaker associations were observed for IgA and IgM concentrations, which were predicted with lower accuracy compared to IgG. Simulation analyses suggested that improving colostrum quality by selective breeding in Holstein cattle based on near-infrared predicted colostrum immunoglobulins concentrations is feasible. In addition, less than 10 mL of colostrum are needed for spectra acquisition and thus implementation of such analyses is possible in the near future. CONCLUSIONS: The concentrations of colostrum immunoglobulins can be predicted from near-infrared spectra and the genetic correlation between the reference and the predicted traits is positive and favourable, in spite of the large standard errors of the estimates. Near-infrared spectroscopy can be exploited in selective breeding of dairy cattle to improve colostral immunoglobulins concentration.

Detailed characterization of plant-based burgers.

Flexitarians have reduced their meat consumption showing a rising interest in plant-based meat alternatives with 'meaty' characteristics, and we are witnessing an unprecedented growth of meat substitutes in the Western market. However, to our knowledge, no information regarding the 'simulated beef burgers' nutritional profile compared to similar meat products has been published yet. Here we show that, whilst both plant-based and meat-based burgers have similar protein profile and saturated fat content, the former are richer in minerals and polyunsaturated fatty acids. We found that the most abundant minerals in both categories were Na, K, P, S, Ca, and Mg; being Na and S content similar between groups. Only six amino acids differed between categories, being hydroxyproline exclusively in meat-based burgers. Plant-based burgers revealed fourfold greater content of n-6 than meat-based burgers, and greater short-chain fatty acids proportion. Our results demonstrate how 'simulated beef' products may be authenticated based on some specific nutrients and are a good source of minerals. We believe that there is a need to provide complete and unbiased nutritional information on these 'new' vegan products so that consumers can adjust their diet to nutritional needs.

Application of a Handheld Near-Infrared Spectrometer to Predict Gelatinized Starch, Fiber Fractions, and Mineral Content of Ground and Intact Extruded Dry Dog Food.

The aim of the present study was to investigate the ability of a handheld near-infrared spectrometer to predict total and gelatinized starch, insoluble fibrous fractions, and mineral content in extruded dry dog food. Intact and ground samples were compared to determine if the homogenization could improve the prediction performance of the instrument. Reference analyses were performed on 81 samples for starch and 99 for neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), and minerals, and reflectance infrared spectra (740 to 1070 nm) were recorded with a SCiO™ near-infrared (NIR) spectrometer. Prediction models were developed using modified partial least squares regression and both internal (leave-one-out cross-validation) and external validation. The best prediction models in cross-validation using ground samples were obtained for gelatinized starch (residual predictive deviation, RPD = 2.54) and total starch (RPD = 2.33), and S (RPD = 1.92), while the best using intact samples were obtained for gelatinized starch (RPD = 2.45), total starch (RPD = 2.08), and K (RPD = 1.98). Through external validation, the best statistics were obtained for gelatinized starch, with an RPD of 2.55 and 2.03 in ground and intact samples, respectively. Overall, there was no difference in prediction models accuracy using ground or intact samples. In conclusion, the miniaturized NIR instrument offers the potential for screening purposes only for total and gelatinized starch, S, and K, whereas the results do not support its applicability for the other traits.

At-line Prediction of Gelatinized Starch and Fiber Fractions in Extruded Dry Dog Food Using Different Near-Infrared Spectroscopy Technologies.

This study aimed to assess the feasibility of visible/near-infrared reflectance (Vis-NIR) and near-infrared transmittance (NIT) spectroscopy to predict total and gelatinized starch and fiber fractions in extruded dry dog food. Reference laboratory analyses were performed on 81 samples, and the spectrum of each ground sample was obtained through Vis-NIR and NIT spectrometers. Prediction equations for each instrument were developed by modified partial least squares regressions and validated by cross- (CrV) and external validation (ExV) procedures. All studied traits were better predicted by Vis-NIR than NIT spectroscopy. With Vis-NIR, excellent prediction models were obtained for total starch (residual predictive deviation; RPDCrV = 6.33; RPDExV = 4.43), gelatinized starch (RPDCrV = 4.62; RPDExV = 4.36), neutral detergent fiber (NDF; RPDCrV = 3.93; RPDExV = 4.31), and acid detergent fiber (ADF; RPDCrV = 5.80; RPDExV = 5.67). With NIT, RPDCrV ranged from 1.75 (ADF) to 2.61 (acid detergent lignin, ADL) and RPDExV from 1.71 (ADL) to 2.16 (total starch). In conclusion, results of the present study demonstrated the feasibility of at-line Vis-NIR spectroscopy in predicting total and gelatinized starch, NDF, and ADF, with lower accuracy for ADL, whereas results do not support the applicability of NIT spectroscopy to predict those traits.

Prediction of Mineral Composition in Commercial Extruded Dry Dog Food by Near-Infrared Reflectance Spectroscopy.

The pet food industry is interested in performing fast analyses to control the nutritional quality of their products. This study assessed the feasibility of near-infrared spectroscopy to predict mineral content in extruded dry dog food. Mineral content in commercial dry dog food samples (n = 119) was quantified by inductively coupled plasma optical emission spectrometry and reflectance spectra (850-2500 nm) captured with FOSS NIRS DS2500 spectrometer. Calibration models were built using modified partial least square regression and leave-one-out cross-validation. The best prediction models were obtained for S (coefficient of determination; R2 = 0.89), K (R2 = 0.85), and Li (R2 = 0.74), followed by P, B, and Sr (R2 = 0.72 each). Only prediction models for S and K were adequate for screening purposes. This study supports that minerals are difficult to determine with NIRS if they are not associated with organic molecules.