Rapid and Simultaneous Determination of Feed Nutritive Values by Means of Near Infrared Spectroscopy
Abstract
Feed plays a significant role in livestock production worldwide. Digestibility of feed such as in vitro dry matter digestibility (IVDMD) and in vitro organic matter digestibility (IVOMD) as well as the fractions of crude fiber such as neutral detergent fiber (NDF) and acid detergent fiber (ADF) can be used as indicators of feed quality. To determine these nutritive parameters, several methods based on solvent extraction and other laboratory analyses are widely employed which are normally time consuming and may cause pollution since this analysis involves chemical materials. Near infrared spectroscopy (NIRS) is one of rapid alternative methods that can be considered to be applied due to its advantages. Therefore, the main objective of this present study is to apply NIRS in determining IVDMD, IVOMD, NDF, and ADF of animal feed samples simultaneously. Reflectance spectra were acquired for animal feed samples in wavelength range from 1000 to 2500 nm. Actual quality and nutritive values were measured by standard laboratory method. Spectra data were corrected by baseline shift correction (BSC), standard normal variate (SNV), and de-trending (DT). Prediction models were developed using principal component regression. Superior results for IVDMD, IVOMD, and NDF predictions were achieved using SNV with correlation coefficient (r) and RPD index of 0.93 and 2.78 for IVDMD, 0.90 and 2.35 for IVOMD, and 0.89 and 2.31 for NDF, respectively. ADF nutritive value was predicted accurately using DT spectrum with r and RPD index of 0.94 and 3.00, respectively. It may be concluded that NIRS can be used and applied as a rapid and simultaneous method in determining nutritive values of feed samples.
References
AOAC. 2012. Officials Methods of Analysis. 15th ed. Association of Official Analytic Chemists, Arlington, VA.
Azzouz, T., A. Puigdomenech, M. Aragay, & R. Tauler. 2003. Comparison between different pre-treatment methods in the analysis of forage samples using near-infrared diffuse reflectance spectroscopy and partial least-squares multivariate calibration method. Analytica Chimica Acta 484:121-134. https://doi.org/10.1016/S0003-2670(03)00308-8
Balabin, R. M. & E. I. Lomakina. 2011. Support vector machine regression as an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data. Analyst 136:1703-1712. https://doi.org/10.1039/c0an00387e
Balabin, R. M. & S. V. Smirnov. 2011. Melamine detection by mid and near infrared (MIR/NIR) spectroscopy: a quick and sensitive method for dairy products analysis including liquid milk, infant formula, and milk powder. Talanta 85: 562-568. https://doi.org/10.1016/j.talanta.2011.04.026
Cen, H. & Y. He. 2007. Theory and application of near infrared reflectance spectroscopy in determination of food quality. Trends in Food Science & Technology 18: 72-83. https://doi.org/10.1016/j.tifs.2006.09.003
Cozzolino, D., W. U. Cynkar, N. Shah, & P. Smith. 2011. Multivariate data analysis applied to spectroscopy: Potential application to juice and fruit quality. Food Research International 44:1888-1896. https://doi.org/10.1016/j.foodres.2011.01.041
Fearn, T. 2002. Assessing calibrations: SEP, RPD, RER and R2. NIR News, 13, 12−14. https://doi.org/10.1255/nirn.689
Huang, H., H. Yu, H. Xu, & Y. Ying. 2008. Near infrared spectroscopy for on/in-line monitoring of quality in foods and beverages: a review. Journal of Food Engineering 87: 303-313. https://doi.org/10.1016/j.jfoodeng.2007.12.022
Mouazen, A. M., B. Kuang, J. De Baerdemaeker, & H. Ramon. 2010. Comparison among principal component, partial least squares and back propagation neural network analyses for accuracy of measurement of selected soil properties with visible and near infrared spectroscopy. Geoderma 158: 23–31. https://doi.org/10.1016/j.geoderma.2010.03.001
Munawar, A.A., D.V. Hoersten, E. Pawelzik, J. K. Wegener, & D. Moerlein. 2016. Rapid and non-destructive prediction of inner quality attributes of intact mango using Fourier-transform infrared and chemometrics. J. Engineering in Agriculture, Environment and Food 9: 208–215.
Nawi, N. M., G. Chen, T. Jensen, & S. A. Mehdizadeh. 2013. Prediction and classification of sugar content of sugarcane based on skin scanning using visible and shortwave near infrared. Biosystems Engineering, 115: 154-161. https://doi.org/10.1016/j.biosystemseng.2013.03.005
Nicolai, B. M., K. Beullens, E. Bobelyn, A. Peirs, W. Saeys, K. I. Theron, & J. Lamertyn. 2007. Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: a review. Postharvest Biology and Technology, 46: 99-118. https://doi.org/10.1016/j.postharvbio.2007.06.024
Porep, J. U., D. R. Kammerer, & R. Carle. 2015. On-line application of near infrared (NIR) spectroscopy in food. Trends in Food Science & Technology, 46: 211-230. https://doi.org/10.1016/j.tifs.2015.10.002
Samadi & P. Yu. 2011. Dry and moist heating-induced changes in protein molecular structure, protein subfraction, and nutrient profiles in soybeans. J. Dairy Sci. 94:6092–6102. https://doi.org/10.3168/jds.2011-4619
Samadi, K. Theodoridou, & P. Yu. 2013. Detect the sensitivity and response of protein molecular structure of whole canola seed (yellow and brown) to different heat processing methods and relation to protein utilization and availability using ATR-FT/IR molecular spectroscopy with chemometrics. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 105 :304–313. https://doi.org/10.1016/j.saa.2012.11.096
Samadi, S. Wajizah, & Sabda. 2015. Peningkatan kualitas ampas tebu sebagai pakan ternak melalui fermentasi dengan penambahan level tepung sagu yang berbeda. Agripet. 15:104-111. https://doi.org/10.17969/agripet.v15i2.2849
Samadi, S. Wajizah, Y. Usman, D. Riyatsyah, & Z. Al Firdausya. 2016. Improving sugarcane bagasse as animal feed by aminiation and followed by fermentationwith Trichoderma harzianum (in vitro study). Animal Production 18: 14-21. https://doi.org/10.20884/1.anprod.2016.18.1.516
Samadi, S.Wajizah & A. A. Munawar. 2018. Fast and simultaneous prediction of animal feed nutritive values using near infrared reflectance spectroscopy. In C. T. Bull, I. T. Riley, E. Munir, A. R. Alimon, P. Hariyadi, A. Kabutey, D. B. Weaver, R. Llewelyn, C. Sumantri, E. Purba, R. Sigalingging & Onrizal (Eds). International Conference on Agriculture, Environment, and Food Security 7–8 November 2017, Medan. https://doi.org/10.1088/1755-1315/122/1/012112
Santoso, B., B. Tj Hariadi, V.Sabariah, & T. Sraun. 2014. Fermentation quality in vitro nutrient digestibility of fresh rice straw-based silage treated with lactic acid bacteria. Med. Pet. 37:115-120. http://dx.doi.org/10.5398/medpet.2014 .37.2.115
Shepherd, K.D., B. Vanlauwe, C. N. Gachengo, & C. A. Palm. 2005. Decomposition and mineralization of organic residues using near infrared spectroscopy. Plant and Soil 277: 315-333. https://doi.org/10.1007/s11104-005-7929-y
Suryapratama, W & F. M. Suhartati. 2012. Fermentasi jeramai padi dengan menggunakan white rot fungi dan suplementasi Saccharomyces cerevisiae pengaruhnya terhadap kecernaan nutrient secara in vitro. Agripet 12:1-6. https://doi.org/10.17969/agripet.v12i2.195
Tilley, J.M.A. & R. A. Terry. 1963. A two stage technique for the in vitro digestion of forage crops. J. Br. Grass: 18: 104-112. https://doi.org/10.1111/j.1365-2494.1963.tb00335.x
Tsenkova, R., S. Atanassova, K. Itoh, Y. Ozaki, & K. Toyoda. 2011. Near infrared spectroscopy for biomonitoring: cow milk composition measurement in a spectral region from 1,100 to 2,400 nanometers. J. Anim. Sci. 78: 515-522. https://doi.org/10.2527/2000.783515x
Wanapat, M., S. Polyrach, K. Boonnop, C. Mapato, & A. Cherdthong. 2009. Effect of treating rice straw with urea and calcium hydroxide upon intake, digestibility, rumen fermentation and milk yield of dairy cows. Livest. Sci. 125:238-243. https://doi.org/10.1016/j.livsci.2009.05.001
Wajizah, S, Samadi, Y. Usman, & E. Mariana. 2015. Evaluasi nilai nutrisi dan kecernaan in vitro pelepah kelapa sawit (oil palm fronds) yang difermentasi menggunakan Aspergillus niger dengan penambahan sumber karbohidrat yang berbeda. Agripet. 15: 13-19. https://doi.org/10.17969/agripet.v15i1.2286
Williams, P. C. 2001. Implementation of Near-Infrared Technology. In P. C. Williams, & K. H. Norris (Eds.), Near Infrared Technology in the Agricultural and Food Industries. American Association of Cereal Chemist., St. Paul, Minnesota, USA. Pp. 145-169.
Wiryawan, K.G., A. Saefuddin, A.M. Fuah, R. Priyanto, L. Khotijah, & S. Suharti. 2017. Fermentation characteristis and nitrogen retention of Madura cattle fed complete rations containing soybean pod and by-products. Med. Pet. 40:28-34. https://doi.org/10.5398/medpet.2017.40.1.28
Azzouz, T., A. Puigdomenech, M. Aragay, & R. Tauler. 2003. Comparison between different pre-treatment methods in the analysis of forage samples using near-infrared diffuse reflectance spectroscopy and partial least-squares multivariate calibration method. Analytica Chimica Acta 484:121-134. https://doi.org/10.1016/S0003-2670(03)00308-8
Balabin, R. M. & E. I. Lomakina. 2011. Support vector machine regression as an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data. Analyst 136:1703-1712. https://doi.org/10.1039/c0an00387e
Balabin, R. M. & S. V. Smirnov. 2011. Melamine detection by mid and near infrared (MIR/NIR) spectroscopy: a quick and sensitive method for dairy products analysis including liquid milk, infant formula, and milk powder. Talanta 85: 562-568. https://doi.org/10.1016/j.talanta.2011.04.026
Cen, H. & Y. He. 2007. Theory and application of near infrared reflectance spectroscopy in determination of food quality. Trends in Food Science & Technology 18: 72-83. https://doi.org/10.1016/j.tifs.2006.09.003
Cozzolino, D., W. U. Cynkar, N. Shah, & P. Smith. 2011. Multivariate data analysis applied to spectroscopy: Potential application to juice and fruit quality. Food Research International 44:1888-1896. https://doi.org/10.1016/j.foodres.2011.01.041
Fearn, T. 2002. Assessing calibrations: SEP, RPD, RER and R2. NIR News, 13, 12−14. https://doi.org/10.1255/nirn.689
Huang, H., H. Yu, H. Xu, & Y. Ying. 2008. Near infrared spectroscopy for on/in-line monitoring of quality in foods and beverages: a review. Journal of Food Engineering 87: 303-313. https://doi.org/10.1016/j.jfoodeng.2007.12.022
Mouazen, A. M., B. Kuang, J. De Baerdemaeker, & H. Ramon. 2010. Comparison among principal component, partial least squares and back propagation neural network analyses for accuracy of measurement of selected soil properties with visible and near infrared spectroscopy. Geoderma 158: 23–31. https://doi.org/10.1016/j.geoderma.2010.03.001
Munawar, A.A., D.V. Hoersten, E. Pawelzik, J. K. Wegener, & D. Moerlein. 2016. Rapid and non-destructive prediction of inner quality attributes of intact mango using Fourier-transform infrared and chemometrics. J. Engineering in Agriculture, Environment and Food 9: 208–215.
Nawi, N. M., G. Chen, T. Jensen, & S. A. Mehdizadeh. 2013. Prediction and classification of sugar content of sugarcane based on skin scanning using visible and shortwave near infrared. Biosystems Engineering, 115: 154-161. https://doi.org/10.1016/j.biosystemseng.2013.03.005
Nicolai, B. M., K. Beullens, E. Bobelyn, A. Peirs, W. Saeys, K. I. Theron, & J. Lamertyn. 2007. Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: a review. Postharvest Biology and Technology, 46: 99-118. https://doi.org/10.1016/j.postharvbio.2007.06.024
Porep, J. U., D. R. Kammerer, & R. Carle. 2015. On-line application of near infrared (NIR) spectroscopy in food. Trends in Food Science & Technology, 46: 211-230. https://doi.org/10.1016/j.tifs.2015.10.002
Samadi & P. Yu. 2011. Dry and moist heating-induced changes in protein molecular structure, protein subfraction, and nutrient profiles in soybeans. J. Dairy Sci. 94:6092–6102. https://doi.org/10.3168/jds.2011-4619
Samadi, K. Theodoridou, & P. Yu. 2013. Detect the sensitivity and response of protein molecular structure of whole canola seed (yellow and brown) to different heat processing methods and relation to protein utilization and availability using ATR-FT/IR molecular spectroscopy with chemometrics. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 105 :304–313. https://doi.org/10.1016/j.saa.2012.11.096
Samadi, S. Wajizah, & Sabda. 2015. Peningkatan kualitas ampas tebu sebagai pakan ternak melalui fermentasi dengan penambahan level tepung sagu yang berbeda. Agripet. 15:104-111. https://doi.org/10.17969/agripet.v15i2.2849
Samadi, S. Wajizah, Y. Usman, D. Riyatsyah, & Z. Al Firdausya. 2016. Improving sugarcane bagasse as animal feed by aminiation and followed by fermentationwith Trichoderma harzianum (in vitro study). Animal Production 18: 14-21. https://doi.org/10.20884/1.anprod.2016.18.1.516
Samadi, S.Wajizah & A. A. Munawar. 2018. Fast and simultaneous prediction of animal feed nutritive values using near infrared reflectance spectroscopy. In C. T. Bull, I. T. Riley, E. Munir, A. R. Alimon, P. Hariyadi, A. Kabutey, D. B. Weaver, R. Llewelyn, C. Sumantri, E. Purba, R. Sigalingging & Onrizal (Eds). International Conference on Agriculture, Environment, and Food Security 7–8 November 2017, Medan. https://doi.org/10.1088/1755-1315/122/1/012112
Santoso, B., B. Tj Hariadi, V.Sabariah, & T. Sraun. 2014. Fermentation quality in vitro nutrient digestibility of fresh rice straw-based silage treated with lactic acid bacteria. Med. Pet. 37:115-120. http://dx.doi.org/10.5398/medpet.2014 .37.2.115
Shepherd, K.D., B. Vanlauwe, C. N. Gachengo, & C. A. Palm. 2005. Decomposition and mineralization of organic residues using near infrared spectroscopy. Plant and Soil 277: 315-333. https://doi.org/10.1007/s11104-005-7929-y
Suryapratama, W & F. M. Suhartati. 2012. Fermentasi jeramai padi dengan menggunakan white rot fungi dan suplementasi Saccharomyces cerevisiae pengaruhnya terhadap kecernaan nutrient secara in vitro. Agripet 12:1-6. https://doi.org/10.17969/agripet.v12i2.195
Tilley, J.M.A. & R. A. Terry. 1963. A two stage technique for the in vitro digestion of forage crops. J. Br. Grass: 18: 104-112. https://doi.org/10.1111/j.1365-2494.1963.tb00335.x
Tsenkova, R., S. Atanassova, K. Itoh, Y. Ozaki, & K. Toyoda. 2011. Near infrared spectroscopy for biomonitoring: cow milk composition measurement in a spectral region from 1,100 to 2,400 nanometers. J. Anim. Sci. 78: 515-522. https://doi.org/10.2527/2000.783515x
Wanapat, M., S. Polyrach, K. Boonnop, C. Mapato, & A. Cherdthong. 2009. Effect of treating rice straw with urea and calcium hydroxide upon intake, digestibility, rumen fermentation and milk yield of dairy cows. Livest. Sci. 125:238-243. https://doi.org/10.1016/j.livsci.2009.05.001
Wajizah, S, Samadi, Y. Usman, & E. Mariana. 2015. Evaluasi nilai nutrisi dan kecernaan in vitro pelepah kelapa sawit (oil palm fronds) yang difermentasi menggunakan Aspergillus niger dengan penambahan sumber karbohidrat yang berbeda. Agripet. 15: 13-19. https://doi.org/10.17969/agripet.v15i1.2286
Williams, P. C. 2001. Implementation of Near-Infrared Technology. In P. C. Williams, & K. H. Norris (Eds.), Near Infrared Technology in the Agricultural and Food Industries. American Association of Cereal Chemist., St. Paul, Minnesota, USA. Pp. 145-169.
Wiryawan, K.G., A. Saefuddin, A.M. Fuah, R. Priyanto, L. Khotijah, & S. Suharti. 2017. Fermentation characteristis and nitrogen retention of Madura cattle fed complete rations containing soybean pod and by-products. Med. Pet. 40:28-34. https://doi.org/10.5398/medpet.2017.40.1.28
Authors
SamadiS., WajizahS., & MunawarA. A. (2018). Rapid and Simultaneous Determination of Feed Nutritive Values by Means of Near Infrared Spectroscopy. Tropical Animal Science Journal, 41(2), 121-127. https://doi.org/10.5398/tasj.2018.41.2.121
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors submitting manuscripts should understand and agree that copyright of manuscripts of the article shall be assigned/transferred to Tropical Animal Science Journal. The statement to release the copyright to Tropical Animal Science Journal is stated in Form A. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA) where Authors and Readers can copy and redistribute the material in any medium or format, as well as remix, transform, and build upon the material for any purpose, but they must give appropriate credit (cite to the article or content), provide a link to the license, and indicate if changes were made. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
Article Details
