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'Global' and 'local' predictions of dairy diet nutritional quality using near infrared reflectance spectroscopy

机译:使用近红外反射光谱法对乳制品饮食营养质量的“全球”和“本地”预测

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摘要

The objective of the study was to evaluate performance of classic (global) and innovative (local) calibration techniques to monitor cattle diet, based on fecal near infrared reflectance spectroscopy (NIRS). A 3-yr on-farm survey (2005-2008) was carried out in Vietnam and La Reunion Island to collect animal, feed intake, and feces excretion data. Feed and feces were scanned by a Foss NIRsystem 5000 monochromator (Foss, Hiller0d, Denmark) to estimate diet characteristics and nutrient digestibility. A data set including 1,322 diet-fecal pairs was built and used to perform global and local calibrations. Global equations gave satisfactory accuracy [coefficient of determination (R~2) >0.8, 10% ≤ relative standard error of prediction (RSEP) <20%], whereas local equations gave good accuracy (R~2 >0.8, RSEP <10%) or excellent accuracy (R2 >0.9, RSEP <10%) for the prediction of diet intake, quality, and digestibility. When validating the equations using the external individual data, both techniques were robust, with similar RSEP (8%) and R~2 (0.82) values. The predictive performance of global and local equations was improved (RSEP = 5% and R~2 = 0.90) when averaged animal data from farm, visit, and similar milk production were used. In particular, local equations reduced RSEP by 43% and increased R2 by 15%, on average, compared with those obtained from individual data. The low RSEP (4%), high R2 (0.96), and good ratio performance deviation (RPD = 5) illustrated the excellent accuracy and robustness of the local equations. Findings suggest the ability of fecal NIRS to successfully and more accurately predict diet properties (intake, quality, and digestibility) with local calibration techniques compared with classic global techniques, especially on an averaged data set. Local calibration techniques represent an alternative promising method and potentially a decision support tool torndecide whether diets meet dairy cattle requirements or need to be modified.
机译:这项研究的目的是基于粪便近红外反射光谱(NIRS)评估经典(全球)和创新(本地)校准技术的性能,以监测牛的饮食。在越南和拉留尼汪岛进行了为期3年的农场调查(2005-2008年),以收集动物,饲料摄入量和粪便排泄数据。饲料和粪便由Foss NIRsystem 5000单色仪(Foss,Hiller0d,丹麦)进行扫描,以估计日粮的特性和营养物质的消化率。建立了包括1,322对饮食-粪便对的数据集,并将其用于执行全局和局部校准。整体方程给出了令人满意的精度[测定系数(R〜2)> 0.8,10%≤相对标准预测误差(RSEP)<20%],而局部方程给出了良好的精度(R〜2> 0.8,RSEP <10% )或极好的准确性(R2> 0.9,RSEP <10%)来预测饮食摄入,质量和消化率。当使用外部个体数据验证方程时,这两种技术都非常可靠,RSEP(8%)和R〜2(0.82)值相似。当使用来自农场,探视和类似奶产量的平均动物数据时,全局方程和局部方程的预测性能得到了改善(RSEP = 5%,R〜2 = 0.90)。特别是,与从单个数据中获得的方程相比,局部方程平均使RSEP降低了43%,R2平均增加了15%。低的RSEP(4%),高的R2(0.96)和良好的比率性能偏差(RPD = 5)说明了局部方程的出色准确性和鲁棒性。研究结果表明,与传统的全球技术相比,粪便NIRS可以通过局部校准技术成功,更准确地预测饮食特性(摄入,质量和消化率),尤其是在平均数据集上。本地校准技术代表了另一种有前途的方法,并可能成为决策支持工具,以决定日粮是否满足奶牛需求或需要进行修改。

著录项

  • 来源
    《Journal of dairy science》 |2010年第10期|p.4961-4975|共15页
  • 作者单位

    Faculty of Animal Sciences and Aquaculture, Hanoi University of Agriculture, Vietnam;

    rnCIRAD, UPR Systemes d'elevage, Montpellier, F-34398 France;

    rnCIRAD, UPR Systemes d'elevage, Saint-Pierre, La Reunion, F-97410 France;

    rnCentre Wallon de Recherches Agronomiques (CRA-W), Departement Qualite des Productions Agricoles, 24 Chaussee de Namur,B-5030 Gembloux, Belgium;

    rnFaculty of Animal Sciences and Aquaculture, Hanoi University of Agriculture, Vietnam;

    rnCIRAD, UPR Systemes d'elevage, Saint-Pierre, La Reunion, F-97410 France;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    dairy diet; near infrared reflectance spec-troscopy; quality; prediction;

    机译:乳制品饮食;近红外反射光谱质量;预测;

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