PREDICTION OF CHEMICAL COMPOSITION AND ENERGY VALUE OF GRASS SILAGE BY NEAR-INFRARED REFLECTANCE SPECTROSCOPY
One hundred and eighteen grass silage samples with known chemical composition and in vitro determined concentration of net energy for lactation (NEL) were scanned over the wavelength range from 1100 to 2500 nm at 8 nm intervals. Calibration equations for the prediction of crude protein (CP), crude f...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | Bulgarian |
| Published: |
University of Zagreb, Faculty of Agriculture
2006-10-01
|
| Series: | Journal of Central European Agriculture |
| Subjects: | |
| Online Access: | http://jcea.agr.hr/articles/344_PREDICTION_OF_CHEMICAL_COMPOSITION_AND_ENERGY_VALUE_OF_GRASS_SILAGE_BY_NEAR_INFRARED_REFLECTANCE_SPECTROSCOPY_en.pdf |
| _version_ | 1818129956565155840 |
|---|---|
| author | TOMAŽ ŽNIDARŠIČ JOŽE VERBIČ DRAGO BABNIK |
| author_facet | TOMAŽ ŽNIDARŠIČ JOŽE VERBIČ DRAGO BABNIK |
| author_sort | TOMAŽ ŽNIDARŠIČ |
| collection | DOAJ |
| description | One hundred and eighteen grass silage samples with known chemical composition and in vitro determined concentration of net energy for lactation (NEL) were scanned over the wavelength range from 1100 to 2500 nm at 8 nm intervals. Calibration equations for the prediction of crude protein (CP), crude fi bre (CF), crude fat (F), crude ash (A), dry matter of air-dried samples (DM) and NEL were developed by the use of principal component analysis (PCA) and modifi ed partial least squares regression technique (mPLS). NIRS demonstrated high predictive ability for CP (R2 = 0.97), CF (R2 = 0.96) and A (R2 = 0.94). Moderate accuracy was characteristic for F and DM (R2 = 0.81 and 0.79). Crude protein, F and DM deviations from reference methods were comparable to those which are expected by the use of the same reference methods in different laboratories. The determination coeffi cient for in vitro assessed NEL concentration was 0.76. Seventy-seven percent of samples lied within acceptable limits of ± 0.3 MJ NEL kg-1DM. Suboptimal sample distribution, i.e. small number of samples in classes below 4.6 and above 6.0 MJ NEL kg-1DM was observed. It seems that deviations of NIRS predicted values from the reference values were related to the concentration of NEL. It was concluded that NIRS shows the potential for reliable determination of chemical composition and energy value of grass silage. |
| first_indexed | 2024-12-11T07:57:23Z |
| format | Article |
| id | doaj.art-869a2f2446e04f578ddc0c05a6aaee1e |
| institution | Directory Open Access Journal |
| issn | 1332-9049 |
| language | Bulgarian |
| last_indexed | 2024-12-11T07:57:23Z |
| publishDate | 2006-10-01 |
| publisher | University of Zagreb, Faculty of Agriculture |
| record_format | Article |
| series | Journal of Central European Agriculture |
| spelling | doaj.art-869a2f2446e04f578ddc0c05a6aaee1e2022-12-22T01:15:13ZbulUniversity of Zagreb, Faculty of AgricultureJournal of Central European Agriculture1332-90492006-10-0171127134PREDICTION OF CHEMICAL COMPOSITION AND ENERGY VALUE OF GRASS SILAGE BY NEAR-INFRARED REFLECTANCE SPECTROSCOPYTOMAŽ ŽNIDARŠIČJOŽE VERBIČDRAGO BABNIKOne hundred and eighteen grass silage samples with known chemical composition and in vitro determined concentration of net energy for lactation (NEL) were scanned over the wavelength range from 1100 to 2500 nm at 8 nm intervals. Calibration equations for the prediction of crude protein (CP), crude fi bre (CF), crude fat (F), crude ash (A), dry matter of air-dried samples (DM) and NEL were developed by the use of principal component analysis (PCA) and modifi ed partial least squares regression technique (mPLS). NIRS demonstrated high predictive ability for CP (R2 = 0.97), CF (R2 = 0.96) and A (R2 = 0.94). Moderate accuracy was characteristic for F and DM (R2 = 0.81 and 0.79). Crude protein, F and DM deviations from reference methods were comparable to those which are expected by the use of the same reference methods in different laboratories. The determination coeffi cient for in vitro assessed NEL concentration was 0.76. Seventy-seven percent of samples lied within acceptable limits of ± 0.3 MJ NEL kg-1DM. Suboptimal sample distribution, i.e. small number of samples in classes below 4.6 and above 6.0 MJ NEL kg-1DM was observed. It seems that deviations of NIRS predicted values from the reference values were related to the concentration of NEL. It was concluded that NIRS shows the potential for reliable determination of chemical composition and energy value of grass silage.http://jcea.agr.hr/articles/344_PREDICTION_OF_CHEMICAL_COMPOSITION_AND_ENERGY_VALUE_OF_GRASS_SILAGE_BY_NEAR_INFRARED_REFLECTANCE_SPECTROSCOPY_en.pdfgrass silage/ net energy for lactation/ chemical composition/ nirs |
| spellingShingle | TOMAŽ ŽNIDARŠIČ JOŽE VERBIČ DRAGO BABNIK PREDICTION OF CHEMICAL COMPOSITION AND ENERGY VALUE OF GRASS SILAGE BY NEAR-INFRARED REFLECTANCE SPECTROSCOPY Journal of Central European Agriculture grass silage/ net energy for lactation/ chemical composition/ nirs |
| title | PREDICTION OF CHEMICAL COMPOSITION AND ENERGY VALUE OF GRASS SILAGE BY NEAR-INFRARED REFLECTANCE SPECTROSCOPY |
| title_full | PREDICTION OF CHEMICAL COMPOSITION AND ENERGY VALUE OF GRASS SILAGE BY NEAR-INFRARED REFLECTANCE SPECTROSCOPY |
| title_fullStr | PREDICTION OF CHEMICAL COMPOSITION AND ENERGY VALUE OF GRASS SILAGE BY NEAR-INFRARED REFLECTANCE SPECTROSCOPY |
| title_full_unstemmed | PREDICTION OF CHEMICAL COMPOSITION AND ENERGY VALUE OF GRASS SILAGE BY NEAR-INFRARED REFLECTANCE SPECTROSCOPY |
| title_short | PREDICTION OF CHEMICAL COMPOSITION AND ENERGY VALUE OF GRASS SILAGE BY NEAR-INFRARED REFLECTANCE SPECTROSCOPY |
| title_sort | prediction of chemical composition and energy value of grass silage by near infrared reflectance spectroscopy |
| topic | grass silage/ net energy for lactation/ chemical composition/ nirs |
| url | http://jcea.agr.hr/articles/344_PREDICTION_OF_CHEMICAL_COMPOSITION_AND_ENERGY_VALUE_OF_GRASS_SILAGE_BY_NEAR_INFRARED_REFLECTANCE_SPECTROSCOPY_en.pdf |
| work_keys_str_mv | AT tomazznidarsic predictionofchemicalcompositionandenergyvalueofgrasssilagebynearinfraredreflectancespectroscopy AT jozeverbic predictionofchemicalcompositionandenergyvalueofgrasssilagebynearinfraredreflectancespectroscopy AT dragobabnik predictionofchemicalcompositionandenergyvalueofgrasssilagebynearinfraredreflectancespectroscopy |