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Impact factor 1.683
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Silva Fennica 1926-1997
1990-1997
1980-1989
1970-1979
1960-1969
Acta Forestalia Fennica
1953-1968
1933-1952
1913-1932

Articles containing the keyword 'acid-detergent fiber'.

Category: Research article

article id 7822, category Research article
Mulualem Tigabu, Annika M. Felton. (2018). Multivariate calibration of near infrared spectra for predicting nutrient concentrations of solid moose rumen contents. Silva Fennica vol. 52 no. 1 article id 7822. https://doi.org/10.14214/sf.7822
Highlights: Multivariate calibrations were established for predicting nutrient concentrations of solid moose rumen contents by near infrared spectroscopy (NIRS); Crude protein, available protein and ash contents were accurately predicted; Prediction of microbial nitrogen, ash, acid-detergent fiber, neutral detergent fiber and lignin were satisfactory; The results demonstrate that NIRS offers quick and inexpensive procedure to quantify nutrient concentrations of solid rumen contents.

This study aimed at establishing calibrations to predict nutrient concentrations of solid moose (Alces alces L.) rumen content using near infrared spectroscopy (NIRS), as an alternative to expensive chemical analyses. NIR reflectance spectra of 148 dry pulverized samples were recorded. The scanned samples were then analyzed for crude protein, available protein, microbial nitrogen (N), ash, acid-detergent fiber (ADF), neutral detergent fiber (NDF) and lignin contents following standard chemical analysis procedures. The calibration models were derived by Orthogonal Projection to Latent Structure (OPLS) and validated using external prediction sets. The calibration models accurately predicted crude protein, available protein and ash contents (R2 = 0.99, 0.96, and 0.92, prediction error = 0.39, 0.72 and 0.53% dry matter, respectively) while NDF (R2 = 0.92; prediction error = 2.23% dry matter) and ADF (R2 = 0.89; prediction error = 1.94% dry matter) were predicted with sufficient accuracy and that of microbial-N (R2 = 0.81; prediction error = 1.25 mg yeast-RNA g–1 dry matter) and lignin (R2 = 0.84; prediction error = 1.05% dry matter) were acceptable. The ratio of performance to deviation values were > 3.0 for crude protein and available protein, between 3.0 and 2.5 for ADF, NDF and lignin, and 2.32 for microbial-N; attesting the robustness of the calibration models. It can be concluded that NIR spectroscopy offers a quick and inexpensive procedure for prediction of nutrient concentrations of solid rumen contents in wild herbivores.

  • Tigabu, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Box 49, SE-230 53 Alnarp, Sweden ORCID ID: http://orcid.org/0000-0003-2471-1168 E-mail: mulualem.tigabu@slu.se (email)
  • Felton, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Box 49, SE-230 53 Alnarp, Sweden ORCID ID:E-mail: annika.felton@slu.se

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