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Digestibility and intake are parameters difficult and expensive to estimate under grazing conditions; therefore, the aim of this study was to develop near-infrared reflectance spectroscopy (NIRS) calibrations applied to feces (F-NIRS) and evaluate their accuracy to predict dry matter digestibility (DMD) and dry matter intake (DMI) of Colombian creole cattle. Five digestibility trials using creole steers were conducted; indigestible neutral detergent fiber (iNDF) was used as internal marker and Cr2O3 and TiO2 as external markers. A total of 249 forage and 396 fecal samples from individual animals were collected, dried, and grinded for conventional chemical analysis. For spectral analysis, fecal samples were pooled across collection periods (77 samples). Chemometric analysis was performed using WinISI V4.10 software applying the modified partial least squares method. Cross-validation was performed to avoid overfitting the models. The goodness-of-fit statistics considered were the coefficient of determination in cross-validation and prediction sets (R2cv and r2, respectively) and the ratio performance deviation (RPD). Fecal NIRS calibrations developed for forage and supplement DMD showed a satisfactory fit (R2cv =0.87 and RPD=2.77 and R2cv=0.92 and RPD=3.50, respectively). The accuracy of fecal output equations using chromium (Cr) and titanium (Ti) was similar in terms of R2cv (0.92) and RPD (3.63 vs. 3.57). Total DMI equations using Ti performed better compared to Cr (R2cv = 0.82 vs. 0.78; RPD=2.41 vs. 2.17, respectively). The F-NIRS models were validated using a completely independent set of fecal samples showing a moderate fit (r2>0.8 and RPD>2.0). This study showed that F-NIRS is a feasible tool to predict DMD and DMI of creole steers under grazing conditions. However, previous to socialization, this requires an improvement in accuracy of the calibrated equations related to grazing animals in different production contexts.

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This study aimed to predict fat and fatty acids (FA) contents in beef using near-infrared spectroscopy and prediction models based on partial least squares (PLS) and support vector machine regression in radial kernel (R-SVR). Fat and FA were assessed in 200 longissimus thoracis samples, and spectra were collected in reflectance mode from ground meat. The analyses were performed for PLS and R-SVR with and without wavelength selection based on genetic algorithms (GAs). The GA application improved the error prediction by 15% and 68% for PLS and R-SVR, respectively. Models based on GA plus R-SMV showed a prediction ability for fat and FA with an average coefficient of determination of 0.92 and ratio performance deviation of 4.8.

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O objetivo deste trabalho foi desenvolver um modelo preditivo através de técnica multivariada para diferenciar meios de cultivo de células-tronco cultivadas in vitro e criopreservadas de acordo com os perfis de absorbância obtidas por NIR. Para tanto, foram coletados meios de cultivo de células-tronco oriundo do fluido amniótico de fetos caprinos, antes e após o processo de criopreservação por vitrificarão, e submetidos à análise pelo NIR. Foi possível estimar com alta acurácia o tratamento empregado nas amostras, gerando uma impressão digital dos meios de cultivo in vitro de células criopreservadas ou não.(AU)

The objective of this work was to develop a predictive model through a multivariate technique to differentiate culture media from stem cells cultured in vitro and cryopreserved according to the absorbance profiles obtained by NIR. For this purpose, culture media were collected from stem cells from the amniotic fluid of goat fetuses, before and after cryopreservation by vitrification, and submitted to NIR analysis. It was possible to estimate with high accuracy the treatment used in the samples, generating a fingerprint of in vitro culture media of cryopreserved cells or not.(AU)

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O objetivo deste trabalho foi desenvolver um modelo preditivo através de técnica multivariada para diferenciar meios de cultivo de células-tronco cultivadas in vitro e criopreservadas de acordo com os perfis de absorbância obtidas por NIR. Para tanto, foram coletados meios de cultivo de células-tronco oriundo do fluido amniótico de fetos caprinos, antes e após o processo de criopreservação por vitrificarão, e submetidos à análise pelo NIR. Foi possível estimar com alta acurácia o tratamento empregado nas amostras, gerando uma impressão digital dos meios de cultivo in vitro de células criopreservadas ou não.

The objective of this work was to develop a predictive model through a multivariate technique to differentiate culture media from stem cells cultured in vitro and cryopreserved according to the absorbance profiles obtained by NIR. For this purpose, culture media were collected from stem cells from the amniotic fluid of goat fetuses, before and after cryopreservation by vitrification, and submitted to NIR analysis. It was possible to estimate with high accuracy the treatment used in the samples, generating a fingerprint of in vitro culture media of cryopreserved cells or not.

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The main definition for meat quality should include factors that affect consumer appreciation of the product. Physical laboratory analyses are necessary to identify factors that affect meat quality and specific equipment is used for this purpose, which is expensive and destructive, and the analyses are usually time consuming. An alternative method to performing several beef analyses is near-infrared reflectance spectroscopy (NIRS), which permits to reduce costs and to obtain faster, simpler, and nondestructive measurements. The objective of this study was to evaluate the feasibility of NIRS to predict shear force [Warner-Bratzler shear force (WBSF)], marbling, and color (*a = redness; b* = yellowness; and L* = lightness) in meat samples of uncastrated male Nelore cattle, that were approximately 2-yr-old. Samples of longissimus thoracis (n = 644) were collected and spectra were obtained prior to meat quality analysis. Multivariate calibration was performed by partial least squares regression. Several preprocessing techniques were evaluated alone and in combination: raw data, reduction of spectral range, multiplicative scatter correction, and 1st derivative. Accuracies of the calibration models were evaluated using the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), coefficient of determination in the calibration (R2C), and prediction (R2P) groups. Among the different preprocessing techniques, the reduction of spectral range provided the best prediction accuracy for all traits. The NIRS showed a better performance to predict WBSF (RMSEP = 1.42 kg, R2P = 0.40) and b* color (RMSEP = 1.21, R2P = 0.44), while its ability to accurately predict L* (RMSEP = 1.98, R2P = 0.16) and a* (RMSEP = 1.42, R2P = 0.17) was limited. NIRS was unsuitable to predict subjective meat quality traits such as marbling in Nelore cattle.

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The objective of this study was to compare the prediction efficiency of IgG concentration in bovine colostrum by NIRS, using liquid and dried (Dry-Extract Spectroscopy for Infrared Reflectance, DESIR) samples by transflectance and reflectance modes, respectively. Colostrum samples (157), obtained from 2 commercial Holstein dairy farms, were collected within the first hour after calving and kept at -20 °C until analysis. After thawing and homogenisation, a subsample of 500 mg of liquid colostrum was placed in an aluminium mirror transflectance cell (0·1 mm path length), in duplicate, to collect the spectrum. A glass fiber filter disc was infused with another subsample of 500 mg of colostrum, in duplicate, and dried in a forced-air oven at 60 °C for 20 min. The samples were placed in cells for dry samples to collect the spectra. The spectra in the VIS-NIR region (400-2500 nm) were obtained with a NIRSystems 6500 monochromator. Mathematical treatments, scatter correction treatments and number of cross-validation groups were tested to obtain prediction equations for both techniques. Reference analysis for IgG content was performed by radial immunodiffusion. The DESIR technique showed a higher variation in the spectral regions associated with water absorption bands, compared with liquid samples. The best equation for transflectance method (liquid samples) obtained a higher coefficient of determination for calibration (0·95 vs. 0·94, respectively) and cross validation (0·94 vs. 0·91, respectively), and a lower error of cross validation (9·03 vs. 11·5, respectively) than the best equation for reflectance method (DESIR samples). In final, both methods showed excellent capacity for quantitative analysis, with residual predictive deviations above 3. It is concluded that, regarding accuracy of prediction and time for obtaining results of IgG from bovine colostrum, NIRS analysis of liquid samples (transflectance) is recommended over dried samples (DESIR technique by reflectance).

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Esta pesquisa teve como objetivo avaliar as diferenças nos padrões de desenvolvimento ponderal, composição de carcaça e qualidade de carne entre linhagens e touros representativos da raça Nelore, com aplicação de tecnologias modernas para coleta de dados e estimação de parâmetros genéticos e fenotípicos das características em estudo. Foram utilizados dados de desenvolvimento ponderal, características de carcaça e qualidade de carne de machos da raça Nelore, terminados a pasto e confinamento e pertencentes a programas de avaliação genética. Desses animais, foram coletadas informações individuais de características de carcaça avaliadas por ultrassonografia e medidas corporais para estimação do frame de cada animal. Ao abate, foram avaliadas características de carcaça e carne, diretamente na carcaça e também através de imagens digitais do músculo Longissimus para determinação de atributos relacionados à qualidade, como maciez, perdas por cozimento, gordura intramuscular e pH. Avaliações por infravermelho com comprimentos de onda na faixa do visível próximo (VIS-NIRS) foram tomadas para associação com valores de pH, força de cisalhamento e lipídios no músculo Longissimus. Foram estimados parâmetros genéticos para todas as características avaliadas neste trabalho. As características de ganho ponderal, frame, medidas de ultrassonografia e qualidade de carne foram utilizadas para comparação entre genearcas e novos genearcas da raça Nelore. Estas informações em conjunto com a validação ferramentas auxiliares para coleta de fenótipos poderão ajudar na condução de programas de melhoramento genético de características de desempenho e qualidade de nos rebanhos dessa raça, bem como a obtenção de importantes informações sobre a variabilidade e valor genético de genearcas e touros representativos da raça Nelore

The objective of this study was to evaluate the differences of growth, carcass composition and beef quality traits among lineages and representative Nellore sires, using new technologies to collect data and estimate genetic and phenotypic parameters. Data on growth, carcass and meat quality traits of Nellore bulls, raised in pastures and included in genetic evaluation programs were analyzed. Individual information on live ultrasound carcass measurements and frame were, also, collected. After slaughter, carcass, beef quality traits and video image analysis (VIA) of muscle Longissimus were obtained for estimation of beef quality attributes like tenderness, cooking losses, intramuscular fat and pH. Evaluations with Near Infrared Spectroscopy (VIS-NIRS) were made to quantify tenderness and lipid in Longissimus muscle. Genetic parameters were estimated for all traits analyzed in this study. Traits like performance, frame, ultrasound carcass evaluation and meat quality were used to compare lineages and representative Nellore sires. This research provide precious information to development of auxiliary tools for genetic improvement of growth, carcass and meat quality traits in Nellore herds, and provide important information about variability and genetic value of founders and representative sires of this breed

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The objective of this work was to assess the potential of near infrared spectroscopy to predict the immunoglobulin G (IgG) content in bovine colostrum. Liquid colostrum samples (n=157) were collected from Holstein cows from 2 dairy farms in southern Chile. Samples were obtained within 1h of parturition and scanned in folded transmission (transflectance) in the visible-near infrared range. Multivariate regression models (modified partial least squares) were developed with spectral data against IgG content measured by radial immunodiffusion. The best calibration included a mathematical treatment of the spectra by a second derivative plus standard normal variate and detrending. The best equation explained a high proportion of the variation in IgG content (R(2) of 0.95 in calibration and 0.94 in cross-validation). Average (91.5 g/L), standard deviation (37.6g/L), and range, as highest minus lowest values (171.9 g/L) of reference values were 10.1, 4.2, and 19 times the value of the root mean square error of cross-validation (9.03 g/L) respectively. Near-infrared spectroscopy, scanned in folded transmission, is an effective tool to predict the IgG content in liquid colostrum.

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