Application of near infrared spectroscopy to predict chemical composition and energy value of compound feeds for ruminants (original) (raw)
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Animal Feed Science and Technology, 1996
Near infrared reflectance spectroscopy (NIRS) was compared with analytical methods for predicting chemical composition, digestibility and energy content of compound feeds for swine and ruminants. The study investigated numerous widely diversified feeds with known in vivo measurements (87 swine and 80 ruminant feeds). Accuracy of prediction of the energy values of swine and ruminant feeds using NIRS was slightly better than using empirical models from chemical composition or enzymatic methods. The two populations had to be modelled individually. Despite the need of a large number of samples for calibration, NIRS measurements are non-destructive, non-polluting and can be carried out during a short period of time. The most significant wavelengths selected by the step-up model for in vivo digestibility of swine and ruminant feeds lay in the range 1600-1700 nm and 2200 nm, respectively.
Journal of Istanbul Veterinary Sciences
This study aims to determine the crude protein and metabolizable energy values in ruminant mixed feeds based on the measurements obtained from Near Infrared Reflectance Spectroscopy (NIRS) device. The mixed feeds used in the study were produced in Balıkesir. Reference analyses were determined by making chemical analyses of mixed feed samples used in the study. Metabolic energy value of mixed feed samples was calculated by using the determined nutrient values in equations. Portable NIRS device was used in the study. The relationship between estimates obtained from NIRS device and reference values was statistically evaluated. In regression analysis, R2 value was found as 0.0064 for crude protein while it was 0.9397 for metabolizable energy. It has been demonstrated that the NIRS method is a fast, reliable and good estimation method for quantitatively determining the metabolic energy value in ruminant mixed feeds.
Animal Feed Science and Technology, 2009
The objective of this study was to evaluate the potential of near infrared reflectance spectroscopy (NIRS), applied to forage and/or faeces, to estimate the in vivo organic matter digestibility (OMD) and the organic matter voluntary intake (OMVI, g/kg metabolic weight [BW 0.75 ]) for a wide range of Abbreviations: BW, body weight; CEL, cellulose; CP, crude protein; DM, dry matter; H, standardized distance; ADL, acid detergent lignin; NIRS, near infrared reflectance spectroscopy; OM, organic matter; OMDcel, in vitro organic matter digestibility coefficient; OMD, in vivo organic matter digestibility coefficient; OMVI, organic matter voluntary intake; PCA, principal components analysis; R, reflexion; R 2 , coefficient of determination; RPD, standard error of reference database/standard error of cross validation; S.D., standard error of reference database; S.E., standard error of regression; SEC, standard error of calibration; SECV, standard error of cross validation.
Faecal near infrared spectroscopy to measure the diet selected and productivity of grazing ruminants
2013
In ruminants near infrared spectroscopy of faeces (F.NIRS) can measure the concentrations of faecal constituents such as N and fibre. It can also directly estimate many diet attributes, including total N, fibre, digestibility and the major plant groups (e.g. monocots versus dicots, and some plant species). In some situations F.NIRS can be used to estimate voluntary intake and liveweight change, but it is difficult to encompass animal effects (e.g. lactation, maturity), pasture availability or mineral deficiencies. Application of F.NIRS, especially in conjunction with other measurements (e.g. metabolizable energy intake calculated from liveweight change, 13C/12C ratio in faeces, microbial protein synthesis and phosphorus concentrations in faeces) can provide valuable and reliable information about the nutritional status of grazing ruminants. Examples where F.NIRS has been used to measure the nutritional status of grazing cattle and sheep are described for extensive and intensive trop...
Journal of Near Infrared Spectroscopy, 2012
This study compared the performance of single-point near infrared spectroscopy (NIR) and near infrared chemical imaging (NIR-CI) for the detection and quantification of ruminant meat meal in processed animal proteins (PAPs). A set of 126 fish-meal samples adulterated with controlled amounts (0.25% to 16%) of ruminant meal were analysed using the two techniques. Comparison of results showed that spectra obtained by NIR-CI provided better qualitative information, whereas more accurate quantitative predictions were obtained using NIR spectroscopy. NIR-CI thus offers greater potential for species discrimination/identification, whilst NIR spectroscopy is better suited for the quantification of meal derived from a given species in PAPs. These findings represent a first step in the analysis of mixed-species processed animal proteins and suggest that NIR-CI, by providing valuable information on species origin, is a promising tool that could be used as part of the EU feed control programme a...
Rapid and Simultaneous Determination of Feed Nutritive Values by Means of Near Infrared Spectroscopy
Tropical Animal Science Journal, 2018
Feed plays a significant role in livestock production worldwide. Digestibility of feed such as in vitro dry matter digestibility (IVDMD) and in vitro organic matter digestibility (IVOMD) as well as the fractions of crude fiber such as neutral detergent fiber (NDF) and acid detergent fiber (ADF) can be used as indicators of feed quality. To determine these nutritive parameters, several methods based on solvent extraction and other laboratory analyses are widely employed which are normally time consuming and may cause pollution since this analysis involves chemical materials. Near infrared spectroscopy (NIRS) is one of rapid alternative methods that can be considered to be applied due to its advantages. Therefore, the main objective of this present study is to apply NIRS in determining IVDMD, IVOMD, NDF, and ADF of animal feed samples simultaneously. Reflectance spectra were acquired for animal feed samples in wavelength range from 1000 to 2500 nm. Actual quality and nutritive values were measured by standard laboratory method. Spectra data were corrected by baseline shift correction (BSC), standard normal variate (SNV), and de-trending (DT). Prediction models were developed using principal component regression. Superior results for IVDMD, IVOMD, and NDF predictions were achieved using SNV with correlation coefficient (r) and RPD index of 0.93 and 2.78 for IVDMD, 0.90 and 2.35 for IVOMD, and 0.89 and 2.31 for NDF, respectively. ADF nutritive value was predicted accurately using DT spectrum with r and RPD index of 0.94 and 3.00, respectively. It may be concluded that NIRS can be used and applied as a rapid and simultaneous method in determining nutritive values of feed samples.
Journal of Dairy Science, 2013
Currently, rapid methods are needed for feed analysis. This study examined the potential of Fouriertransform infrared (FTIR) spectroscopy to predict the nutritional value of a wide range of feeds for ruminants, as an alternative to the in situ technique. Moreover, we investigated whether universal equations could be developed that would allow the low-cost determination of crude protein (CP) concentrations and their kinetics of degradation into the rumen. Protein nutritional values of 663 samples comprising 80 different feed types were determined in terms of concentrations of CP, watersoluble CP (CP WS ), total-tract mobile bag CP digestibility (CP TTD ), and in situ CP degradability, including the rumen soluble fraction (CP A ), the degradable but not soluble fraction (CP B ), rate of CP B degradation (CP C ), effective degradability (CP ED ), and potential degradability (CP PD ). Infrared spectra of dry samples were collected by attenuated total reflectance from 4000 to 600 cm −1 . Models were developed by partial least squares (PLS) regression in a randomly selected subset of samples, and the precision of the equations was confirmed by using an external validation set. Analysis by FTIR spectroscopy was sufficiently sensitive to allow the accurate prediction of sample CP concentration (R 2 = 0.92) and to classify feeds according to their CP WS concentrations using universal models (R 2 = 0.78) that included all sample types. Moreover, substantial improvements in predictions were observed when samples were subdivided in groups. Models for forages led to accurate predictions of CP WS and fractions CP A and CP B (R 2 > 0.83), whereas models for CP TTD and CP ED could be used for screening purposes (R 2 > 0.67). This study showed that models for protein-rich concentrates alone could also be used for screening according to the feed concentrations of CP WS , CP TTD , CP ED , CP A , and CP B , but models for energy-rich concentrates gave relatively poor predictions. The general difficulty ob-served in predicting CP C is because of a low correlation between FTIR spectra and the kinetics of CP degradation, which may be the result of large variation in the reference method (i.e., in situ degradation studies) and perhaps also because of the presence of compounds that can modify the CP degradation pattern in the rumen.
Journal of Istanbul Veterinary Sciences, 2020
This study aims to determine the levels of dry matter, crude protein, and starch widely used in ruminant feeding, in dairy and beef cattle mixed feeds based on the measurements taken from two different Near-Infrared Reflectance (NIR) devices. The chemical analyses of the mixed feed samples used in the study were performed and the reference values (REF) were determined. In the research, two different NIR devices, a Benchtop-NIR and a Portable-NIR, were used and the nutrient values of mixed feeds were analyzed with these devices. It was determined that there were statistically significant differences between the reference method and NIR results for protein and starch content. Although the differences between the mean values were significant, the reference analyses results and NIR measurements were similar in some ways. According to the correlation coefficients calculated between the reference analyses with Benchtop-NIR and Portable-NIR devices, there was a weak correlation in the dry matter content, while a strong positive correlation existed in the protein (r = 0.72 for Portable, r = 0.93 for Benchtop NIR) and starch content. In the study, 30 different mixed feed (dairy cattle feed, beef cattle feed) values that are commonly used in ruminant feeding were measured.
The Professional Animal Scientist, 2004
In livestock nutrition, summative models (SM) are displacing empirical models as a preferred method to predict energy content of forages. The objective of this study was to determine the effect of using near infrared reflectance spectroscopy (NIRS) to determine nutrient subcomponents required of SM on overall ability to predict energy content of corn and legume-grass silages. Corn (n = 90) and legume-grass (n = 70) silages were collected and analyzed for CP, ADF CP, NDF, NDF CP, in vitro (IV) digestible (d) NDF, ash, and fat by standard laboratory techniques. Samples were scanned on a Model 6500 NIRS, and calibration equations were developed for each nutrient. The TDN contents of corn and legume-grass silages were then estimated using a SM, where the model nutrients were determined by laboratory or NIRS methods. The predicted TDN content of corn and legume-grass silages was compared to IV d OM to assess overall utility. The NIRS calibrations were adequate (R 2 > 0.90) for CP and NDF for both corn and legume-grass silages with standard errors of calibration (SEC) <0.55
Animal Production Science, 2016
An important constraint of in situ degradability studies is the need to analyse a high number of samples and often with insufficient amount of residue, especially after the longer incubations of high-quality forages, that impede the study of more than one nutritional component. Near-infrared spectroscopy (NIRS) has been established as a reliable method for predicting composition of many entities, including forages and other animal feedstuffs. The objective of this work was to evaluate the potential of NIRS for predicting the crude protein (CP) and neutral detergent fibre (NDF) concentration in rumen incubation residues of permanent and sown temperate pastures in a vegetative stage. In situ residues (n = 236) from four swards were scanned for their visible-NIR spectra and analysed for CP and NDF. Selected equations developed by partial least-squares multivariate regression presented high coefficients of determination (CP = 0.99, NDF = 0.95) and low standard errors (CP = 4.17 g/kg, ND...