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Using faecal near-infrared spectroscopy (FNIRS) to estimate nutrient digestibility and chemical composition of diets and faeces of growing pigs

机译:使用粪便近红外光谱法(FNIRS)估算生长猪日粮和粪便的养分消化率和化学成分

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摘要

Near-infrared spectroscopy has been successfully used in predicting nutrient digestibility and other parameters, e.g. diet composition from the spectra of faeces samples in herbivores (FNIRS). The objective of the present study was to investigate if the chemical composition of diets and faeces, as well as the apparent digestibility of organic matter (OM), crude protein (CP), neutral-detergent and acid-detergent fibre (aNDFom, ADFom) and crude fibre (CF) can be predicted with sufficient accuracy from spectra of pigs' faeces. Faecal samples (n = 202), together with detailed information about the chemical composition of these samples and the diets supplied, were provided from five very different digestibility trials with growing pigs. Faecal spectra were obtained by NIRS and calibrations were developed using the complete dataset. Accuracy of calibration equations was assessed by means of standard error of cross-validation (SECV) and the RPD value (standard deviation of lab results/SECV). The prediction of the chemical composition of the diet was considered successful, as all calibration equations had RPD values well above 2, the value that indicates sufficient accuracy. The chemical composition of faeces was predicted with good to sufficient accuracy. Calibrations developed to estimate the apparent nutrient digestibility from faecal spectra worked well for OM and CP, with a SECV of 0.024 for both and RPD values of 2.1 and 2.4. This very promising result merits further investigation. The prediction of the apparent digestibility of fibre fractions was less successful. We conclude that the FNIRS approach is feasible for use in pig nutrition research for predicting the chemical composition of diet and faeces, as well as to determine the apparent digestibility of OM and CP in situations where controlled digestibility trials are not possible. (C) 2015 Elsevier B.V. All rights reserved.
机译:近红外光谱已成功用于预测营养物质的消化率和其他参数,例如食草动物粪便样本光谱中的饮食组成(FNIRS)。本研究的目的是调查饮食和粪便的化学成分,以及有机物(OM),粗蛋白(CP),中性洗涤剂和酸洗涤剂纤维(aNDFom,ADFom)的表观消化率。从猪粪便的光谱可以足够准确地预测粗纤维(CF)。粪便样品(n = 202),以及有关这些样品的化学成分和所提供日粮的详细信息,是从五个生长猪的消化率非常不同的试验中获得的。通过NIRS获得粪便光谱,并使用完整的数据集进行校准。通过交叉验证的标准误差(SECV)和RPD值(实验室结果/ SECV的标准偏差)评估校准方程式的准确性。饮食中化学成分的预测被认为是成功的,因为所有校准方程的RPD值均远高于2,该值表明足够的准确性。预测粪便的化学成分具有良好到足够的准确性。用来估计粪便光谱中表观营养物质消化率的标定对于OM和CP效果很好,两者的SECV为0.024,RPD值为2.1和2.4。这个非常有希望的结果值得进一步研究。纤维级分表观消化率的预测不太成功。我们得出结论,FNIRS方法可用于猪营养研究,以预测日粮和粪便的化学组成,以及在不可能进行可控制消化试验的情况下确定OM和CP的表观消化率。 (C)2015 Elsevier B.V.保留所有权利。

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