Data mining old digestibility trials for nutritional monitoring in confined goats with aids of fecal near infra-red spectrometry

Landau, S.; Giger-Reverdin, Sylvie; Rapetti, L.; Dvash, L.; Dorleans, Michelle; Ungar, Eugene D.

doi:10.1016/j.smallrumres.2008.03.010

Cited by 33 publications

(22 citation statements)

References 28 publications

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“…The chemical analysis for CP was performed by automated Kjeldahl method and for NDF according to Goering and Van Soest [1,27]. Protein content was determined by acid digestion [46].…”

Section: Chemical Referencementioning

confidence: 99%

Estimating Pasture Quality of Fresh Vegetation Based on Spectral Slope of Mixed Data of Dry and Fresh Vegetation—Method Development

et al. 2015

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Abstract:The main objective of the present study was to apply a slope-based spectral method to both dry and fresh pasture vegetation. Differences in eight spectral ranges were identified across the near infrared-shortwave infrared (NIR-SWIR) that were indicative of changes in chemical properties. Slopes across these ranges were calculated and a partial least squares (PLS) analytical model was constructed for the slopes vs. crude protein (CP) and neutral detergent fiber (NDF) contents. Different datasets with different numbers of fresh/dry samples were constructed to predict CP and NDF contents. When using a mixed-sample dataset with dry-to-fresh ratios of 85%:15% and 75%:25%, the correlations of CP (R 2 = 0.95, in both) and NDF (R 2 = 0.84 and 0.82, respectively) were almost as high as when using only dry samples (0.97 and 0.85, respectively). Furthermore, satisfactory correlations were obtained with a dry-to-fresh ratio of 50%:50% for CP (R 2 = 0.92). The OPEN ACCESSRemote Sens. 2015, 7 8046 results of our study are especially encouraging because CP and NDF contents could be predicted even though some of the selected spectral regions were directly affected by atmospheric water vapor or water in the plants.

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“…The chemical analysis for CP was performed by automated Kjeldahl method and for NDF according to Goering and Van Soest [1,27]. Protein content was determined by acid digestion [46].…”

Section: Chemical Referencementioning

confidence: 99%

Estimating Pasture Quality of Fresh Vegetation Based on Spectral Slope of Mixed Data of Dry and Fresh Vegetation—Method Development

et al. 2015

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“…The samples were oven-dried for 72 h at 60 °C and ground to pass through a 1-mm sieve [47]. Spectral measurements and chemical analysis of CP, NDF and digestibility were performed.…”

Section: In-situ Sample Collection and Spectral Measurementsmentioning

confidence: 99%

“…The chemical analysis for CP was performed by automated Kjeldahl method, for NDF according to Goering and Van Soest [4,47] and for in vitro dry matter digestibility according to Tilley and Terry [46,48]; MEC was calculated as (4.4 × digestibility × 0.82)/100 [49,50].…”

Section: Chemical Referencementioning

confidence: 99%

Spectral Slope as an Indicator of Pasture Quality

et al. 2014

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Abstract:In this study, we develop a spectral method for assessment of pasture quality based only on the spectral information obtained with a small number of wavelengths. First, differences in spectral behavior were identified across the near infrared-shortwave infrared spectral range that were indicative of changes in chemical properties. Then, slopes across different spectral ranges were calculated and correlated with the changes in crude protein (CP), neutral detergent fiber (NDF) and metabolic energy concentration (MEC). Finally, partial least squares (PLS) regression analysis was applied to identify the optimal spectral ranges for accurate assessment of CP, NDF and MEC. Six spectral domains and a set of slope criteria for real-time evaluation of pasture quality were suggested. The evaluation of three level categories (low, medium, high) for these three parameters showed a success rate of: 73%-96% for CP, 72%-87% for NDF and 60%-85% for MEC. Moreover, only one spectral range, 1748-1764 nm, was needed to provide a good estimation of CP, NDF and MEC. Importantly, five of the six selected spectral regions were not affected by water absorbance. With some OPEN ACCESSRemote Sens. 2015, 7 257 modifications, this rationale can be applied to further analyses of pasture quality from airborne sensors.

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“…Directly using fecal NIR spectra related to attributes of the diet is considered a novel and exciting application to NIR spectroscopy (Dixon and Coates 2009). Since chemical composition can be predicted from fecal spectra as accurately as from direct analysis of feeds (Landau et al 2004), near infrared reflectance has been widely applied in the agricultural industry to evaluate the nutritional quality of domestic herbivore feeds (Leite et al 1995;Walker et al 2002;Boval et al 2004;Landau et al 2005Landau et al , 2006Landau et al , 2008Fanchone et al 2009), as well as to monitor the nutritional status and ecology of grazing herbivores (Dixon and Coates 2009), including wild deer (Dryden 2003).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Fecal-FT-NIRS as a Noninvasive Tool for Assessing Diet Quality of Mediterranean Deer

Tellado¹,

Órpez²,

Muñoz-Cobo³

et al. 2015

Rangeland Ecology & Management

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Data mining old digestibility trials for nutritional monitoring in confined goats with aids of fecal near infra-red spectrometry

Cited by 33 publications

References 28 publications

Estimating Pasture Quality of Fresh Vegetation Based on Spectral Slope of Mixed Data of Dry and Fresh Vegetation—Method Development

Estimating Pasture Quality of Fresh Vegetation Based on Spectral Slope of Mixed Data of Dry and Fresh Vegetation—Method Development

Spectral Slope as an Indicator of Pasture Quality

Fecal-FT-NIRS as a Noninvasive Tool for Assessing Diet Quality of Mediterranean Deer

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