Fecal NIRS prediction of dietary protein percentage and in vitro dry matter digestibility in diets ingested by goats in Mediterranean scrubland

The Application of NIRS to Determine Animal Physiological Traits for Wildlife Management and Conservation

The ability to measure and monitor wildlife populations is important for species management and conservation. The use of near-infrared spectroscopy (NIRS) to rapidly detect physiological traits from wildlife scat and other body materials could play an important role in the conservation of species. Previous research has demonstrated the potential for NIRS to detect diseases such as the novel COVID-19 from saliva, parasites from feces, and numerous other traits from animal skin, hair, and scat, such as cortisol metabolites, diet quality, sex, and reproductive status, that may be useful for population monitoring. Models developed from NIRS data use light reflected from a sample to relate the variation in the sample’s spectra to variation in a trait, which can then be used to predict that trait in unknown samples based on their spectra. The modelling process involves calibration, validation, and evaluation. Data sampling, pre-treatments, and the selection of training and testing datasets can impact model performance. We review the use of NIRS for measuring physiological traits in animals that may be useful for wildlife management and conservation and suggest future research to advance the application of NIRS for this purpose.

Faecal near-IR spectroscopy to determine the nutritional value of diets consumed by beef cattle in east Mediterranean rangelands

Rapid assessment of the nutritional quality of diets ingested by grazing animals is pivotal for successful cow-calf management in east Mediterranean rangelands, which receive unpredictable rainfall and are subject to hot-spells. Clipped vegetation samples are seldom representative of diets consumed, as cows locate and graze selectively. In contrast, faeces are easily sampled and their near-IR spectra contain information about nutrients and their utilization. However, a pre-requisite for successful faecal near-infrared reflectance spectroscopy (FNIRS) is that the calibration database encompass the spectral variability of samples to be analyzed. Using confined beef cows in Northern and Southern Israel, we calibrated prediction equations based on individual pairs of known dietary attributes and the NIR spectra of associated faeces (n=125). Diets were composed of fresh-cut green fodder of monocots (wheat and barley), dicots (safflower and garden pea) and natural pasture collected at various phenological states over 2 consecutive years, and, optionally, supplements of barley grain and dried poultry litter. A total of 48 additional pairs of faeces and diets sourced from cows fed six complete mixed rations covering a wide range of energy and CP concentrations. Precision (linearity of calibration, R2cal, and of cross-validation, R2cv) and accuracy (standard error of cross-validation, SEcv) were criteria for calibration quality. The calibrations for dietary ash, CP, NDF and in vitro dry matter digestibility yielded R2cal values >0.87, R2cv of 0.81 to 0.89 and SEcv values of 16, 13, 39 and 31 g/kg dry matter, respectively. Equations for nutrient intake were of low quality, with the exception of CP. Evaluation of FNIRS predictions was carried out with grazing animals supplemented or not with poultry litter, and implementation of the method in one herd over 2 years is presented. The potential usefulness of equations was also established by calculating the Mahalanobis (H) distance to the spectral centroid of a calibration population of 796 faecal samples collected throughout 2 years in four herds. Seasonal trends in pasture quality and responses to management practices were identified adequately and H<3.0 for 98% of faecal samples collected. We conclude that the development of FNIRS equations with confined animals is not only unexpensive and ethically acceptable, but their predictions are also sufficiently accurate to monitor dietary composition (but not intake) of beef cattle in east Mediterranean rangelands.

Prediction of diet quality for sheep from faecal characteristics: comparison of near-infrared spectroscopy and conventional chemistry predictive models

This study evaluated the ability of equations developed from the analysis of faecal material by conventional chemistry (F.CHEM), and by near-infrared spectroscopy (F.NIRS), to predict intake and digestibility of forages fed with or without supplements. In vivo datasets were obtained using 30 sheep and 25 diets to provide 124 diet–faecal pairs, with each sheep fed four or five of the diets. The diets were five forages fed alone or with urea, molasses, cottonseed meal or sorghum grain supplements. Ninety-nine diet–faecal pairs were selected at random, but ensuring that all diets were represented and both the F.CHEM and F.NIRS prediction equations were developed from this dataset. The remaining 25 diet–faecal pairs were used as a validation dataset. Regressions for F.CHEM were developed by stepwise regression, and F.NIRS prediction equations were developed by partial least-squares regression. Prediction equations based solely on faecal analyte concentrations (F.CHEMc) had poor predictive ability, and models incorporating faecal constituent excretion rates (F.CHEMe) were the best at predicting feed constituent intakes. These models had slightly lower standard errors of prediction (SEP) for organic matter (OM) intake and digestible OM intake compared with the F.NIRS models that did not include faecal excretion rates. However, F.NIRS models had lower SEP for protein intake and OM digestibility. Good agreement between the F.CHEMe and F.NIRS methods was evident (according to the 95% limits-of-agreement test), and both predicted the reference values precisely and with small bias. Equations derived from a dataset that included representatives of all diets used in the experiment gave much better prediction of diet characteristics than those developed from a dataset constructed entirely at random. Equations for F.NIRS developed in this way successfully predicted the characteristics of diets that included forages fed alone and with the type of supplements used in tropical Australia.

Foraging behaviour of beef cattle in the hilly terrain of a Mediterranean grassland

The objective of this study was to determine the role of terrain in the foraging behaviour of beef cows grazing hilly Mediterranean grasslands. The study was conducted in eastern Galilee, Israel, during 2002 and 2003 on two similar 28-ha paddocks encompassing distinct terrain types in terms of slope and rock cover. The paddocks were continuously grazed by cows from mid winter (January–February) to autumn (September) at two different stocking rates (1.1 and 0.56 cows per ha). From early June to the end of September the cows were offered poultry litter ad libitum as a supplementary feed. The location and activity of cows were monitored with GPS collars during four periods in each year: early spring (February–March), late spring (April), early summer (June) and late summer (August). Herbage mass was measured at the beginning of each of these periods. During early and late spring, when the herbage mass and nutritive value of herbage were high, the cows spent 40–50% of the day grazing, with peaks in the morning and afternoon. In the dry, late summer period (August), grazing of the herbage was 20–22% of the day, occurring only in the early morning and late afternoon with sporadic bouts of grazing until midnight. In all periods the cows tended to prefer the flattest terrain sites. As the herbage mass declined to 1000–1500 kg ha–1, the exploitation of the pasture during grazing became increasingly similar among the different terrains. Even on relatively small paddocks, where grazing pressure was close to the full potential of the site, free-ranging cows tended to prefer less sloping and rocky sites. It is concluded that the grazing strategy of beef cows is determined by the interaction between terrain, the distribution of the herbage mass and the nutritive value of the herbage. As herbage mass declines during the growing season, the distribution of grazing becomes uniform and all terrain types are exploited.

Predicting the quality of browse-containing diets fed to sheep using faecal near-infrared reflectance spectroscopy

The potential of data collected from past feeding trials to derive faecal near-infrared reflectance spectroscopy (fNIRS) calibrations for predicting the attributes of browse-containing sheep diets was examined. Reference data and faecal near-infrared spectrum pairs (n = 240) originated from five feeding trials involving 40 diets consisting of varying levels of fresh browse and oaten chaff. The fNIRS calibrations were developed to predict crude protein (CP), total phenolics (TP), total tannin (TT) and phosphorus (P) contents, protein precipitation capacity of tannin (PPC), in vivo digestibility of dry matter (DMD), organic matter (OMD) and crude protein (CPD) and in vitro OMD (IVOMD), metabolisable energy (ME) and short chain fatty acid production (eSCFA) in the diet. The precision of calibrations was evaluated by the coefficient of determination (R2c) and standard error (SEC) of calibration. The predictive ability of calibrations was evaluated by standard error of cross-validation (SECV), standard error of prediction (SEP), slope of the validation regression and the ratio of the standard deviation of the reference data to the SECV (RPD). For all fNIRS calibrations, R2c was >0.80 and SEC was close to the respective SECV. Slope of the validation regressions did not deviate from 1 for chemical attributes but deviated from 1 for functional attributes (except eSCFA). The RPD of DMD and OMD was <3, whereas the ratio was >3 for CP, TP, TT, PPC, P, CPD, IVOMD, ME and eSCFA calibrations. Data derived from the past feeding trials could be used to derive robust fNIRS calibrations to predict chemical attributes (CP, TP, TT, PPC, P) of browse-containing sheep diets. Although, fNIRS calibrations predicting dietary in vitro functional properties (digestibility and ME) were superior to those predicting in vivo functional properties, both were not so robust. Statistics of fNIRS calibrations derived using reference data originating from in vitro methods needs to be carefully interpreted.

Effects of breed, sex, and age on the variation and ability of fecal near-infrared reflectance spectra to predict the composition of goat diets

The effects of breed, sex, and age of goats on fecal near-infrared reflectance spectroscopy-predicted percentage juniper in the diet were investigated, as were spectral differences in feces from goats differing in estimated genetic merit for juniper consumption. Eleven goats from each breed, sex, and age combination, representing 2 breeds (Angora and meat-type), 3 sex classifications (female, intact male, and castrated male), and 2 age categories [adult and kid (less than 12 mo of age)] were fed complete, pelleted rations containing 0 or 14% juniper. After 7 d on the same diet, fecal samples were collected for 3 d, and the spectra from the 3 replicate samples were averaged. Fecal samples were assigned to calibration or validation data sets. In a second experiment, Angora and meat goats with high or low estimated genetic merit for juniper consumption were fed the same diet to determine the effect of consumer group on fecal spectra. Feces were scanned in the 1,100- to 2,500-nm range with a scanning reflectance monochromator. Fecal spectra were analyzed for the difference in spectral characteristics and for differences in predicted juniper in the diet using internal and independent calibration equations. Internal calibration had a high precision (R(2) = 0.94), but the precision of independent validations (r(2) = 0.56) was low. Spectral differences were affected by diet, sex, breed, and age (P < 0.04). However, diet was the largest source of variation in spectral differences. Predicted percentage of juniper in the diet also showed that diet was the largest source of variation, accounting for 95% of the variation in predictions from internal calibrations and 51% of the variation in independent validations. Predictions from independent calibrations readily detected differences (P < 0.001) in the percentage of juniper in the 2 diets, and the predicted differences were similar to the actual differences. Predicted juniper in the diet was also affected by sex. Feces from goats from different juniper consumer groups fed a common diet were spectrally different, and the difference may have resulted from a greater intake by high- compared with low-juniper-consuming goats. Fecal near-infrared reflectance spectroscopy predictions of botanical composition of diets should be considered an interval scale of measurement.