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
[21]   Evaluation of prediction models of chemical composition and gross energy of kikuyo (Pennisetum clandestinum) using near infrared spectroscopy (NIRS) [J].
Mejia, Flor ;
Yoplac, Ives ;
Bernal, Wilmer ;
Castro, Wilson .
REVISTA DE INVESTIGACIONES VETERINARIAS DEL PERU, 2019, 30 (03) :1068-1076
[22]   Prediction of chemical composition and neutral detergent fibre of Italian ryegrass (Lolium multiflorum lam) by near infrared spectroscopy (NIRS) [J].
Sandra B.Q. ;
Teresa A.F. ;
Fernando C.C. ;
Felipe S.M.H. ;
Christian L.L. ;
Jean R.E. ;
Virginia R. ;
Oscar E.F. ;
Jorge G.V. ;
Víctor V.M. .
Revista de Investigaciones Veterinarias del Peru, 2017, 28 (03) :538-548
[23]   Obtainment of calibration curves to determine the chemical composition of the species Pennisetum purpureum through Near Infrared Reflectance Spectroscopy (NIRS) [J].
Valenciaga, Dalky ;
de Oliveira Simoes, Eloisa ;
La O, O. ;
Chongo, Bertha ;
Oramas, A. ;
Cairo, J. C. .
CUBAN JOURNAL OF AGRICULTURAL SCIENCE, 2007, 41 (02) :157-160
[24]   Assessment of fecal near-infrared spectroscopy to predict feces chemical composition and apparent total-tract digestibility of nutrients in pigs [J].
Nirea, Kahsay G. ;
de Nanclares, Marta Perez ;
Skugor, Adrijana ;
Afseth, Nils K. ;
Meuwissen, Theodorus H. E. ;
Hansen, Jon O. ;
Mydland, Liv T. ;
Overland, Margareth .
JOURNAL OF ANIMAL SCIENCE, 2018, 96 (07) :2826-2837
[25]   Use of near-infrared spectroscopy for prediction of chemical composition of Tifton 85 grass [J].
Serafim, Camila Cano ;
Guerra, Geisi Loures ;
Mizubuti, Ivone Yurika ;
Boscaro de Castro, Filipe Alexandre ;
Prado-Calixto, Odimari Pricila ;
Galbeiro, Sandra ;
Poveda Parra, Angela Rocio ;
Bumbieris Junior, Valter Harry ;
Nedel Pertile, Simone Fernanda ;
de Almeida Rego, Fabiola Cristine .
SEMINA-CIENCIAS AGRARIAS, 2021, 42 (03) :1287-1302
[26]   Near-Infrared Spectroscopy and Chemometrics Methods to Predict the Chemical Composition of Cratylia argentea [J].
Abreu, Lucas Freires ;
Lana, Angela Maria Quintao ;
Climaco, Leonardo Campos ;
Matrangolo, Walter Jose Rodrigues ;
Barbosa, Elizabeth Pereira ;
da Silva, Karina Toledo ;
Rowntree, Jason E. ;
da Silva, Edilane Aparecida ;
Simeone, Maria Lucia Ferreira .
AGRONOMY-BASEL, 2023, 13 (10)
[27]   An approach to predict chemical composition of goat Longissimus thoracis et lumborum muscle by Near Infrared Reflectance spectroscopy [J].
Teixeira, Alfredo ;
Oliveira, Antonio ;
Paulos, Katia ;
Leite, Ana ;
Marcia, Anabela ;
Amorim, Andre ;
Pereira, Etelvina ;
Silva, Severiano ;
Rodrigues, Sandra .
SMALL RUMINANT RESEARCH, 2015, 126 :40-43
[28]   Use of near infrared spectroscopy to predict chemical parameters and phytotoxicity of peats and growing media [J].
Ludwig, Bernard ;
Schmilewski, Gerald ;
Terhoeven-Urselmans, Thomas .
SCIENTIA HORTICULTURAE, 2006, 109 (01) :86-91
[29]   The use of Near Infrared Reflectance Spectroscopy on dried samples to predict biological parameters of grass silage [J].
Park, RS ;
Gordon, FJ ;
Agnew, RE ;
Barnes, RJ ;
Steen, RWJ .
ANIMAL FEED SCIENCE AND TECHNOLOGY, 1997, 68 (3-4) :235-246
[30]   Near-infrared reflectance spectroscopy (NIRS) for the mandatory labelling of compound feedingstuffs:: chemical composition and open-declaration [J].
Pérez-Marín, DC ;
Garrido-Varo, A ;
Guerrero-Ginel, JE ;
Gómez-Cabrera, A .
ANIMAL FEED SCIENCE AND TECHNOLOGY, 2004, 116 (3-4) :333-349