Prediction of the chemical composition of poultry excreta by near infrared spectroscopy

被引:26
|
作者
Bastianelli, Denis [1 ]
Bonnal, Laurent [1 ]
Juin, Herve [2 ]
Mignon-Grasteau, Sandrine [3 ]
Davrieux, Fabrice [4 ]
Carre, Bernard [3 ]
机构
[1] CIRAD, Lab Alimentat Anim, F-34398 Montpellier 05, France
[2] INRA, EASM, F-17700 Surgeres, France
[3] INRA, Unite Rech Avicoles, F-37380 Nouzilly, France
[4] CIRAD, Qualisud, F-34398 Montpellier 05, France
关键词
poultry; broiler; faeces; gross energy; nitrogen; uric acid; starch; crude fat; digestibility; NIR spectroscopy; REFLECTANCE SPECTROSCOPY; MANURE COMPOST; URIC-ACID; WHEAT; NITROGEN; ENERGY; DIGESTIBILITIES; TECHNOLOGY; COMPONENTS; PROTEIN;
D O I
10.1255/jnirs.864
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
The potential of near infrared (NIR) spectroscopy for the determination of the chemical composition of poultry excreta was investigated, within the framework of studies on heritability of digestive efficiency in broilers. Samples in the calibration and validation databases (DB1 and DB2) corresponded to animals fed with a similar wheat-based diet. A second validation study was performed on excreta samples from animals fed more variable diets, including peas and maize (DB3). Excreta samples were freeze-dried and ground. Near infrared reflectance spectra were taken on a monochromator spectrometer between 400nm and 2500nm. Samples were analysed for mineral matter (MM), gross energy (GE), starch, crude fat (CFAT), total nitrogen (NTOT), uric acid nitrogen (NUA) and protein nitrogen estimated directly (PNTERP) or by difference between NTOT and NUA (PNUA). Depending on the parameters studied, 250 to 700 samples were analysed by reference methods. The standard error of cross-validation (SECO and R-2 of calibrations were: 0.60% and 0.96 for MM, 166 kJkg(-1) and 0.99 for GE, 0.59% and 1.00 for starch, 0.44% and 0.99 for CFAT, 0.25% and 0.89 for NTOT and 0.22% and 0.97 for NUA, respectively. Calibration for PNTERP (SECV=0.07 A; R-2=0.98) was much more precise than PNUA (SECV=0.21%, R-2=0.85). Validation carried out on databases DB2 and DB3 resulted in standard errors of prediction (on DB2) and extrapolation (on DB3) generally higher than SECV, while remaining relatively precise with prediction r(2) values from 0.83 to 0.99 and extrapolation r(2) from 0.86 to 0.98, with the exception of PNUA for which r(2) was 0.22 and 0.64, respectively. For some parameters, the lower validation performance was due to biases, particularly in the case CFAT and NUA for prediction and MM, GE and NUA for extrapolation. Global calibrations made with DB1+DB2+DB3 were more precise (GE, NTOT) or equally precise (all other parameters) than with DB1 alone. These results confirmed the potential precision of calibrations for the major organic compounds in poultry excreta and suggested that their use could be extended to excreta issued from a wider range of diets without losing precision.
引用
收藏
页码:69 / 77
页数:9
相关论文
共 50 条
  • [1] Use of visible-near infrared spectroscopy to predict nutrient composition of poultry excreta
    Cruz-Conesa, Andres
    Ferre, Joan
    Perez-Vendrell, Anna M.
    Callao, M. Pilar
    Ruisanchez, Itziar
    ANIMAL FEED SCIENCE AND TECHNOLOGY, 2022, 283
  • [2] Prediction of sorghum chemical composition by near infrared spectroscopy technique
    Saliba, EOS
    Neto, SMMG
    Rodriguez, NM
    Miranda, LF
    Obeid, JA
    Teixeira, GL
    Oliveira, MA
    ARQUIVO BRASILEIRO DE MEDICINA VETERINARIA E ZOOTECNIA, 2003, 55 (03) : 357 - 360
  • [3] Prediction of the chemical composition of mutton with near infrared reflectance spectroscopy
    Viljoen, M.
    Hoffman, L. C.
    Brand, T. S.
    SMALL RUMINANT RESEARCH, 2007, 69 (1-3) : 88 - 94
  • [4] Research on Prediction Chemical Composition of Beef by Near Infrared Reflectance Spectroscopy
    Sun Xiao-ming
    Lu Ling
    Zhang Jia-cheng
    Zhang Song-shan
    Sun Bao-zhong
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2011, 31 (02) : 379 - 383
  • [5] Prediction of chemical composition of sugar beet pulp by near infrared reflectance spectroscopy
    Fernandez, B.
    Andres, S.
    Prieto, N.
    Mantecon, A. R.
    Giraldez, F. J.
    JOURNAL OF NEAR INFRARED SPECTROSCOPY, 2008, 16 (02) : 105 - 110
  • [6] Prediction of the chemical composition of white clover by near-infrared reflectance spectroscopy
    Berardo, N
    GRASS AND FORAGE SCIENCE, 1997, 52 (01) : 27 - 32
  • [7] Near-infrared reflectance spectroscopy for the prediction of chemical composition in walnut kernel
    Yi, Jianhua
    Sun, Yifei
    Zhu, Zhenbao
    Liu, Ning
    Lu, Jiali
    INTERNATIONAL JOURNAL OF FOOD PROPERTIES, 2017, 20 (07) : 1633 - 1642
  • [8] Near Infrared Spectroscopy technology for prediction of chemical composition of natural fresh pastures
    Parrini, Silvia
    Acciaioli, Anna
    Franci, Oreste
    Pugliese, Carolina
    Bozzi, Riccardo
    JOURNAL OF APPLIED ANIMAL RESEARCH, 2019, 47 (01) : 514 - 520
  • [9] Prediction of chemical composition of Cynodon spp. by near infrared reflectance spectroscopy
    Fonteneli, RS
    Scheffer-Basso, SM
    Dürr, JW
    Appelt, JV
    Bortolini, F
    Haubert, FA
    REVISTA BRASILEIRA DE ZOOTECNIA-BRAZILIAN JOURNAL OF ANIMAL SCIENCE, 2004, 33 (04): : 838 - 842
  • [10] A dataset of the chemical composition and near-infrared spectroscopy measurements of raw cattle, poultry and pig manure
    Morvan, Thierry
    Goge, Fabien
    Oboyet, Thierry
    Carel, Odile
    Fouad, Youssef
    DATA IN BRIEF, 2021, 39