The use of near infrared spectroscopy (NIRS) to predict the chemical composition of feed samples used in ostrich total mixed rations

被引:12
作者
Swart, E. [1 ,3 ]
Brand, T. S. [1 ,2 ]
Engelbrecht, J. [4 ]
机构
[1] Elsenburg Inst Anim Prod, Dept Agr Western Cape, ZA-7607 Elsenburg, South Africa
[2] Univ Stellenbosch, Dept Anim Sci, ZA-7602 Matieland, South Africa
[3] Nelson Mandela Metropolitan Univ, ZA-6530 George, South Africa
[4] Nelson Mandela Metropolitan Univ, Dept Phys, ZA-6031 Port Elizabeth, South Africa
关键词
NIRS; ostrich TMR; chemical composition; nutritive value; REFLECTANCE SPECTROSCOPY; NUTRITIVE-VALUE; COMPOUND FEEDS; ENERGY VALUE; CALIBRATION;
D O I
10.4314/sajas.v42i5.22
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
The wet chemical analysis of feed samples is time consuming and expensive. Near infrared spectroscopy (NIRS) was developed as a rapid technique to predict the chemical composition of feeds. The prediction of accuracy of NIRS relies heavily on obtaining a calibration set which represents the variation in the main population, accurate laboratory analyses and the application of the best mathematical procedures. In this study NIRS was used to determine the chemical composition of total mixed rations (TMRs) used in ostrich diets. A sample population of 479 ostrich feed samples was used in the calibration and 94 samples were used in the independent validation of dry matter (DM), ash, crude protein (CP), ether extract (EE), crude fibre (CF), acid detergent fibre (ADF), neutral detergent fibre (NDF), gross energy (GE), calcium (Ca) and phosphorus (P). Coefficient of determination in validation (r(v)(2)) and standard error of prediction (SEP) was satisfactory (r(v)(2) values higher than 0.80). Coefficient of determination and SEP values for CP, EE, CF, ADF, NDF and GE were 0.97% and 0.74%, 0.89% and 0.50%, 0.94% and 1.41%, 0.89% and 2.67%, 0.95% and 2.81% and 0.80% and 0.28 MJ/kg, respectively. Less accurate values (r(v)(2) below 0.80) were obtained for DM, ash, Ca and P being 0.57% and 0.28%, 0.67% and 1.29%, 0.43% and 0.59% and 0.49% and 0.11%, respectively. The study indicated that NIRS is a suitable tool for a rapid, non-destructive and reliable prediction of the chemical composition of ostrich TMRs.
引用
收藏
页码:550 / 554
页数:5
相关论文
共 48 条
[31]   The use of near-infrared reflectance spectroscopy (NIRS) in the prediction of chemical composition and in vitro neutral detergent fiber (NDF) digestibility of Italian alfalfa hay [J].
Brogna, Nico ;
Pacchioli, Maria Teresa ;
Immovilli, Alessandra ;
Ruozzi, Fabrizio ;
Ward, Ralph ;
Formigoni, Andrea .
ITALIAN JOURNAL OF ANIMAL SCIENCE, 2009, 8 :271-273
[32]   Assessment of the species composition of forest floor horizons in mixed spruce-beech stands by Near Infrared Reflectance Spectroscopy (NIRS) [J].
Gruselle, Marie-Cecile ;
Bauhus, Juergen .
SOIL BIOLOGY & BIOCHEMISTRY, 2010, 42 (08) :1347-1354
[33]   Potential used of near infrared reflectance spectroscopy to predict meat physico-chemical composition of guinea fowl (Numida meleagris) reared under different production systems [J].
Tejerina, D. ;
Lopez-Parra, M. M. ;
Garcia-Torres, S. .
FOOD CHEMISTRY, 2009, 113 (04) :1290-1296
[34]   Optimisation of dry matter and nutrients in feed rations through use of a near-infrared spectroscopy system mounted on a self-propelled feed mixer [J].
Mostafa, Ehab ;
Twickler, Philipp ;
Schmithausen, Alexandre ;
Maack, Christian ;
Ghaly, Abdelkader ;
Buescher, Wolfgang .
ANIMAL PRODUCTION SCIENCE, 2021, 61 (05) :540-+
[35]   Use of fecal near-infrared reflectance spectroscopy to predict residual feed intake in growing calves. [J].
Gutierrez-Banuelos, H. ;
Prince, S. ;
Tolleson, D. R. ;
Carstens, G. E. ;
Forbes, T. D. A. ;
Rouquette, F. M. ;
Randel, R. D. ;
Welsh, T. H., Jr. .
JOURNAL OF ANIMAL SCIENCE, 2007, 85 :30-31
[36]   Influence of the Physical Properties of Samples in the Use of NIRS to Predict the Chemical Composition and Gas Production Kinetic Parameters of Corn and Grass Silages [J].
Dias, Cristiana S. A. M. Maduro ;
Nunes, Helder P. B. ;
Borba, Alfredo E. S. .
FERMENTATION-BASEL, 2023, 9 (05)
[37]   Prediction of tree species composition in fine root mixed samples using near-infrared reflectance spectroscopy [J].
Tong, J. ;
Xiang, W. ;
Lei, P. ;
Liu, J. ;
Tian, D. ;
Deng, X. ;
Fang, X. ;
Peng, C. .
PLANT BIOSYSTEMS, 2016, 150 (03) :412-419
[38]   The use of near-infrared reflectance spectroscopy in the prediction of the chemical composition of goose fatty liver [J].
Molette, C ;
Berzaghi, P ;
Zotte, AD ;
Remignon, H ;
Babile, R .
POULTRY SCIENCE, 2001, 80 (11) :1625-1629
[39]   The use of near-infrared reflectance spectroscopy (NIRS) in the prediction of chemical composition of freeze-dried egg yolk and discrimination between different n-3 PUFA feeding sources [J].
Zotte, Antonella Dalle ;
Berzaghi, Paolo ;
Jansson, Lisa-Marie ;
Andrighetto, Igino .
ANIMAL FEED SCIENCE AND TECHNOLOGY, 2006, 128 (1-2) :108-121
[40]   Prediction of chemical composition and origin identification of European sea bass (Dicentrarchus labrax L.) by near infrared reflectance spectroscopy (NIRS) [J].
Xiccato, G ;
Trocino, A ;
Tulli, F ;
Tibaldi, E .
FOOD CHEMISTRY, 2004, 86 (02) :275-281