Data mining old digestibility trials for nutritional monitoring in confined goats with aids of fecal near infra-red spectrometry

There is currently no economically viable method to monitor the nutrition of individual goats reared in confinement. Fecal near-infrared reflectance spectroscopy (“fecal NIRS”) enables to predict dietary attributes, based on the analysis of the reflectance of feces in the Near Infrared. Fecal NIRS calibration datasets comprise fecal NIR spectra paired with their associated dietary information. Dedicated trials to generate such datasets are costly, but such datasets are also the outcome of digestibility trials conducted by the hundreds throughout the world. We asked whether data-mining past digestibility trials in which fecal samples were retained could be used to construct fecal NIRS calibrations. This depends on the stability of fecal NIR spectra over years. Using fecal samples that were NIR-scanned in 2003, kept in dry storage at room temperature for 3 years and then scanned again in 2006, we found that the spectra changed, in particular in NIR regions related with CP and digestibility, but the five principal component scores, explaining almost all the spectral variability, were not modified. Fecal NIRS calibration equations based on 375 fecal samples collected in three countries from dairy goats between 1978 and 2001 were less precise and accurate than those based on a subset of 134 samples collected after 1988, which predicted the dietary percentages of hay, silage, corn stover, and beet pulp with high Rcal2>0.97 and accuracy values – estimated by the standard error of cross-validation (SECV) – of 4.1%, 3.2%, 6.0%, and 2.2% of DM, respectively. The Rcal2 and SECV for dietary percentage of concentrate was 0.89 and 6.4%, respectively. All dietary chemical percentages were predicted with Rcal2 values above 0.93. The SECV values for dietary percentages of CP, NDF, ADF, and ADL were 0.9%, 2.9%, 1.7%, and 0.60% of DM. External validations of NDF and ADF were satisfactory. The digestibility of OM and NDF featured Rcal2 values of 0.88 and 0.94, with SECV values of 2.7% and 4.1%. The intakes of DM and CP were predicted with Rcal2>0.91 and SECV values of 264 and 45gd−1, respectively. These results suggest that monitoring the feeding efficiency and nutritional traceability of individual goats by fecal NIRS is potentially feasible. Recent fecal samples should be used, but moderately aged samples (<18 years) may be generally used and older samples can contribute to some calibrations. The challenge for the goat industry would be to organize cooperatively the collection and calibration of fecal NIRS data-sets and exploiting them cooperatively.