Tropical Animal Science Journal
Vol. 43 No. 3 (2020): Tropical Animal Science Journal

Prediction Accuracy Improvement of Indonesian Dairy Cattle Fiber Feed Compositions Using Near-Infrared Reflectance Spectroscopy Local Database

Despal Despal (Department of Nutrition and Feed Technology, Faculty of Animal Science, IPB University)
L. A. Sari (Study Program Nutrition and Feed Technology, Department of Nutrition and Feed Technology, Faculty of Animal Science, IPB University)
R. Chandra (Study Program Nutrition and Feed Technology, Department of Nutrition and Feed Technology, Faculty of Animal Science, IPB University)
R. Zahera (Department of Nutrition and Feed Technology, Faculty of Animal Science, IPB University)
I. G. Permana (Department of Nutrition and Feed Technology, Faculty of Animal Science, IPB University)
L. Abdullah (Department of Nutrition and Feed Technology, Faculty of Animal Science, IPB University)



Article Info

Publish Date
03 Sep 2020

Abstract

The accuracy of near infrared reflectance spectroscopy (NIRS) depends on the database generated from the conventional wet chemistry (CWC). Currently, the local database of fiber-source feeds for tropical dairy cattle are still limited. The study aimed to compare CWC and NIRS initial database (NIRSID) results, to predict CWC from NIRSID, and to improve the accuracy of NIRS prediction using local database (NIRSLD). Five feeds as sources of fiber (Napier grass, natural grass, corn leaves, corn husk, and rice straw) from 4 areas of dairy cattle farming were used (4 farms from each area). For external calibration, 20 independent Napier grass samples were tested. Samples were analyzed using NIRS and CWC to measure dry matter (DM), ash, crude protein (CP), ether extract (EE), crude fiber (CF), neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), and silica (Si) to calculate hemicellulose, cellulose, and lignin contents. The results obtained by NIRSID were compared to those obtained by CWC using T-test. Predictions of CWC from the results obtained by NIRSID were attempted using regressions. The NIRSLD was developed by inputting the CWC value to NIRS spectrums. Internal calibration and validation as well as external calibration, were run. The results showed that NIRSID has low capacity in determining CWC (R2<0.683). Calibration using local database (NIRSLD) improved CWC prediction accuracy (residual predictive deviation (RPD) > 2 except for DM, EE, CF, ADL, and lignin). External validation showed that CWC and NIRSLD were similar in all parameters (p<0.05). The ratios of the standard error of prediction (SEP) to the standard error of laboratory (SEL) were > 2 for CP, CF, and ADF. It is concluded that the local database of NIRS of fiber-source feeds is necessary to improve the prediction accuracy of local dairy fiber-source feeds values using NIRS.

Copyrights © 2020






Journal Info

Abbrev

tasj

Publisher

Subject

Agriculture, Biological Sciences & Forestry Energy

Description

ropical Animal Science Journal (Trop. Anim. Sci. J.) previously Media Peternakan is a scientific journal covering broad aspects of tropical animal sciences. Started from 2018, the title is changed from Media Peternakan in order to develop and expand the distribution as well as increase the ...