References of "Dardenne, Pierre"
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See detail4. Qualité des froments en 2014: une récolte prometteuse et puis la douche froide
Sinnaeve, Georges; Gofflot, Sébastien; Chandelier, Anne et al

in Bodson, Bernard; Destain, Jean-Pierre (Eds.) Livre Blanc Céréales (2014, September 11)

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See detailInnovative lactation stage specific prediction of CH4 from milk MIR spectra
Vanlierde, Amélie; Vanrobays, Marie-Laure ULg; Dehareng, Frédéric et al

Conference (2014, August 28)

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See detailUsing milk spectral data for large-scale phenotypes linked to mitigation and efficiency
Soyeurt, Hélène ULg; Vanlierde, Amélie; Vanrobays, Marie-Laure ULg et al

Conference (2014, August 26)

Even if producing milk efficiently has always been a major concern for producers, the direct environmental impact of their cows is becoming a novel one. Traits linked to this issue were identified as ... [more ▼]

Even if producing milk efficiently has always been a major concern for producers, the direct environmental impact of their cows is becoming a novel one. Traits linked to this issue were identified as methane emission (CH4), dry matter intake (DMI) and feed efficiency (FE); however they are available on a small scale. Researches showed that CH4 could be predicted from milk mid-infrared (MIR) spectra, allowing large-scale recording at low cost. The main objective of this study was to show, using a modelling approach, that DMI and FE could be derived from milk MIR spectra. For that, knowledge of body weight (BW) is required; however it was unknown in this study. Derived procedure was based on milk yield and composition, MIR CH4, and modelled standard animal requirements, allowing the prediction of expected BW. An external validation was conducted based on 91 actual records. 95% confidence limit for the difference ranged between -0.66 and 18.84 kg for BW, from -0.02 to 0.26 kg/day for DMI, and from -0.02 to 0.002 kg of fat corrected milk/kg DM for FE. Root mean square errors were 39.66 kg, 0.56 kg/d, and 0.03 kg/DM for the 3 studied traits. P-value for the t-test was not significant for BW and DMI. This suggests the possibility to obtain expected BW and therefore DMI from MIR spectra. Single trait animal test-day models used 1,291,850 records to assess the variability of studied traits. Significant variations were observed for the lactation stage, parity, genetics, and age. These findings were in agreement with the literature except for early lactation. This suggests in conclusion that the MIR information gave similar results for DMI and CH4 for the major part of lactation. The use of this novel method to predict expected BW offers new possibilities interesting for the development of genomic and genetic tools. [less ▲]

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See detailCreation of universal MIR calibration by standardization of milk spectra: example of fatty acids
Grelet, Clément; Fernandez Pierna, Juan; Soyeurt, Hélène ULg et al

Poster (2014, August 25)

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See detailUsing milk spectral data for large-scale phenotypes linked to mitigation and efficiency
Soyeurt, Hélène ULg; Vanlierde, Amélie; Vanrobays, Marie-Laure ULg et al

in Book of abstracts of the 65th annual meeting of the European Federation of Animal Science (2014, August)

Even if producing milk efficiently has always been a major concern for producers, the direct environmental impact of their cows is becoming a novel one. Traits linked to this issue were identified as ... [more ▼]

Even if producing milk efficiently has always been a major concern for producers, the direct environmental impact of their cows is becoming a novel one. Traits linked to this issue were identified as methane emission (CH4), dry matter intake (DMI) and feed efficiency (FE); however they are available on a small scale. Researches showed that CH4 could be predicted from milk mid-infrared (MIR) spectra, allowing large-scale recording at low cost. The main objective of this study was to show, using a modelling approach, that DMI and FE could be derived from milk MIR spectra. For that, knowledge of body weight (BW) is required; however it was unknown in this study. Derived procedure was based on milk yield and composition, MIR CH4, and modelled standard animal requirements, allowing the prediction of expected BW. An external validation was conducted based on 91 actual records. 95% confidence limit for the difference ranged between -0.66 and 18.84 kg for BW, from -0.02 to 0.26 kg/day for DMI, and from -0.02 to 0.002 kg of fat corrected milk/kg DM for FE. Root mean square errors were 39.66 kg, 0.56 kg/d, and 0.03 kg/DM for the 3 studied traits. P-value for the t-test was not significant for BW and DMI. This suggests the possibility to obtain expected BW and therefore DMI from MIR spectra. Single trait animal test-day models used 1,291,850 records to assess the variability of studied traits. Significant variations were observed for the lactation stage, parity, genetics, and age. These findings were in agreement with the literature except for early lactation. This suggests in conclusion that the MIR information gave similar results for DMI and CH4 for the major part of lactation. The use of this novel method to predict expected BW offers new possibilities interesting for the development of genomic and genetic tools. [less ▲]

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See detailInnovative lactation stage specific prediction of CH4 from milk MIR spectra
Vanlierde, Amélie; Vanrobays, Marie-Laure ULg; Dehareng, Frédéric et al

in Book of abstracts of the 65th annual meeting of the European Federation of Animal Science (2014, August)

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See detailCreation of universal MIR calibration by standardization of milk spectra: example of fatty acids
Grelet, Clément; Fernandez Pierna, Juan; Soyeurt, Hélène ULg et al

in Book of abstracts of the 65th annual meeting of the European Federation of Animal Science (2014, August)

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See detailSorting of crop residues and fossil bones from soil by NIR Hyperspectral Imaging
Vincke, Damien; Eylenbosch, Damien ULg; Baeten, Vincent et al

Poster (2014, June)

Soil is a complex matrix containing a wide variety of constituents of interest for disciplines like agronomy or archaeology; it could either be crop residues like roots and straws or bones and ceramics ... [more ▼]

Soil is a complex matrix containing a wide variety of constituents of interest for disciplines like agronomy or archaeology; it could either be crop residues like roots and straws or bones and ceramics. Current challenges comprise the detection of these constituents as well as the assessment of their qualitative parameters by means of fast and non-destructive analytical methods. The scope of this work is to present two applications using Near Infrared Hyperspectral Imaging (NIR-HSI) combined with chemometrics to sort constituents of soil and to assess their qualitative parameters. The first application concerns the feasibility study of using NIR-HSI to sort crop residues such as roots and straws in soil. The second application aim to develop a method to assess the level of collagen preservation in fossil bones. [less ▲]

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See detailSorting of crop residues and fossil bones from soil by NIR Hyperspectral Imaging
Vincke, Damien; Eylenbosch, Damien ULg; Fernández Pierna, Juan Antonio et al

Conference (2014, June)

The scope of this paper is to present two applications using Near Infrared Hyperspectral Imaging (NIR-HSI) combined with chemometrics to sort constituents of soil and assess their qualitative parameters ... [more ▼]

The scope of this paper is to present two applications using Near Infrared Hyperspectral Imaging (NIR-HSI) combined with chemometrics to sort constituents of soil and assess their qualitative parameters. In the first application, the feasibility of using NIR-HSI to sort crop residues such as roots and straws in soil has been demonstrated. In the second application the potential of such instrumentation and method to assess the level of collagen preservation in fossil bones has been proved. [less ▲]

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See detailAnalysis of collagen preservation in bones recovered in archaeological contexts using NIR Hyperspectral Imaging
Vincke, Damien; Miller, Rebecca ULg; Stassart, Edith ULg et al

in Talanta (2014), 125

The scope of this article is to propose an innovative method based on Near Infrared Hyperspectral Chemical Imaging (NIR-HCI) to rapidly and non-destructively evaluate the relative degree of collagen ... [more ▼]

The scope of this article is to propose an innovative method based on Near Infrared Hyperspectral Chemical Imaging (NIR-HCI) to rapidly and non-destructively evaluate the relative degree of collagen preservation in bones recovered from archaeological contexts. This preliminary study has allowed the evaluation of the potential of the method using bone samples from the Early Upper Palaeolithic, Mesolithic and Neolithic periods at the site of Trou Al'Wesse in Belgium. NIR-HCI, combined with chemometric tools, has identified specific spectral bands characteristic of collagen. A chemometric model has been built using Partial Least Squares Discriminant Analysis (PLS-DA) to identify bones with and without collagen. This enables the evaluation of the degree of collagen preservation and homogeneity in bones within and between different strata, which has direct implications for archaeological applications (e.g., taphonomic analyses, assemblage integrity) and sample selection for sub- sequent analyses requiring collagen. Two archaeological applications are presented: comparison between sub-layers in an Early Upper Palaeolithic unit, and evaluation of the range of variability in collagen preservation within a single Holocene stratum. [less ▲]

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See detailL’intérêt de la spectroscopie proche infrarouge en analyse de terre (synthèse bibliographique)
Genot, Valérie ULg; Bock, Laurent ULg; Dardenne, Pierre et al

in Biotechnologie, Agronomie, Société et Environnement = Biotechnology, Agronomy, Society and Environment [=BASE] (2014), 18(2),

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See detailDiscrimination of grassland species and their classification in botanical families by laboratory scale NIR hyperspectral imaging: preliminary results
Dale, Laura ULg; Thewis, André ULg; Boudry, Christelle ULg et al

in Talanta (2013), 116

The objective of this study was to discriminate by a NIR line scan hyperspectral imaging, taxonomic plant families comprised of different grassland species. Plants were collected from semi-natural meadows ... [more ▼]

The objective of this study was to discriminate by a NIR line scan hyperspectral imaging, taxonomic plant families comprised of different grassland species. Plants were collected from semi-natural meadows of the National Apuseni Park, Apuseni Mountains, Gârda area (Romania) according to botanical families. Chemometric tools such as PLS-DA were used to discriminate distinct grassland species, and assign the different species to botanical families. Species within the Poacea family and Other Botanical Families could be distinguished (R2=0.91 and 0.90, respectively) with greater accuracy than those species in the Fabacea family (R2=0.60). A correct classification rate of 99% was obtained in the assignment of the various species to the proper family. Moreover a complete study based on wavelength selection has been performed in order to identify the chemical compound related to each botanical family and therefore to the possible toxicity of the plant. This work could be considered as a first step for the development of a complete procedure for the detection and quantification of possible toxic species in semi-natural meadows used by grazing animals. [less ▲]

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See detailNew tools for the dairy sector based on MIR and NIR spectroscopy
Grelet, Clément; Dehareng, Frédéric; Vanlierde, Amélie ULg et al

Conference (2013, November 05)

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See detailMid-infrared prediction of cheese yield from milk and its genetic variability in first-parity cows
Colinet, Frédéric ULg; Troch, Thibault ULg; Vanden, Bossche et al

Conference (2013, August 29)

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See detailHerd-test-day variability of methane emissions predicted from milk MIR spectra in Holstein cows
Vanrobays, Marie-Laure ULg; Kandel, Purna Bhadra ULg; Soyeurt, Hélène ULg et al

Poster (2013, August 26)

The aim of this study was to estimate the herd-test-day (HTD) effect on milk yield, fat and protein content, and methane (CH4) emissions of Walloon Holstein first-parity cows. A total of 412,520 test-day ... [more ▼]

The aim of this study was to estimate the herd-test-day (HTD) effect on milk yield, fat and protein content, and methane (CH4) emissions of Walloon Holstein first-parity cows. A total of 412,520 test-day records and milk mid-infrared (MIR) spectra of 69,223 cows in 1,104 herds were included in the data set. The prediction equation developed by Vanlierde et al. (Abstract submitted to EAAP 2013; R² of cross-validation=0.70) was applied on the recorded spectral data to predict CH4 emissions (g/d). Daily CH4 emissions expressed in g/kg of milk were computed by dividing CH4 emissions (g/d) by daily milk yield of cows. Several bivariate (a CH4 trait with a production trait) random regression test-day models including HTD and classes of days in milk and age at calving as fixed effects and permanent environment and genetic as random effects were used. HTD solutions of studied traits obtained from these models were studied and presented large deviations (CV=17.54%, 8.93%, 4.68%, 15.51%, and 23.18% for milk yield, fat and protein content, MIR CH4 (g/d), and MIR CH4 (g/kg of milk), respectively) indicating differences among herds, especially for milk yield and CH4 traits. HTD means per month of milk yield and fat and protein contents presented similar patterns within year. The maximum of monthly HTD means corresponded to the spring (pastern release) for milk yield and to the winter for fat and protein contents. The minimum corresponded to the month of November for milk yield and to the summer for the other traits. For MIR CH4 (g/d), monthly HTD means showed similar patterns as fat and protein content within year. MIR CH4 (g/kg of milk) presented maximum values of monthly HTD means in November and minimum values in May. Finally, results of this study showed that HTD effects on milk production traits and on MIR CH4 emissions varied through herds and seasons. [less ▲]

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See detailHerd-test-day variability of methane emissions predicted from milk MIR spectra in Holstein cows
Vanrobays, Marie-Laure ULg; Kandel, Purna Bhadra ULg; Soyeurt, Hélène ULg et al

in Book of Abstracts of the 64th Annual Meeting of the European Federation of Animal Science (2013, August)

The aim of this study was to estimate the herd-test-day (HTD) effect on milk yield, fat and protein content, and methane (CH4) emissions of Walloon Holstein first-parity cows. A total of 412,520 test-day ... [more ▼]

The aim of this study was to estimate the herd-test-day (HTD) effect on milk yield, fat and protein content, and methane (CH4) emissions of Walloon Holstein first-parity cows. A total of 412,520 test-day records and milk mid-infrared (MIR) spectra of 69,223 cows in 1,104 herds were included in the data set. The prediction equation developed by Vanlierde et al. (Abstract submitted to EAAP 2013; R² of cross-validation=0.70) was applied on the recorded spectral data to predict CH4 emissions (g/d). Daily CH4 emissions expressed in g/kg of milk were computed by dividing CH4 emissions (g/d) by daily milk yield of cows. Several bivariate (a CH4 trait with a production trait) random regression test-day models including HTD and classes of days in milk and age at calving as fixed effects and permanent environment and genetic as random effects were used. HTD solutions of studied traits obtained from these models were studied and presented large deviations (CV=17.54%, 8.93%, 4.68%, 15.51%, and 23.18% for milk yield, fat and protein content, MIR CH4 (g/d), and MIR CH4 (g/kg of milk), respectively) indicating differences among herds, especially for milk yield and CH4 traits. HTD means per month of milk yield and fat and protein contents presented similar patterns within year. The maximum of monthly HTD means corresponded to the spring (pastern release) for milk yield and to the winter for fat and protein contents. The minimum corresponded to the month of November for milk yield and to the summer for the other traits. For MIR CH4 (g/d), monthly HTD means showed similar patterns as fat and protein content within year. MIR CH4 (g/kg of milk) presented maximum values of monthly HTD means in November and minimum values in May. Finally, results of this study showed that HTD effects on milk production traits and on MIR CH4 emissions varied through herds and seasons. [less ▲]

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See detailUse of visible-near infrared spectroscopy to determine cheese properties
Troch, Thibault ULg; Vanden Bossche, Sandrine; De Bisschop, Céline et al

in Book of Abstracts of the 64th Annual Meeting of the European Federation of Animal Science (2013, August)

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See detailMid-infrared prediction of cheese yield from milk and its genetic variability in first-parity cows
Colinet, Frédéric ULg; Troch, Thibault ULg; Vanden Bossche, Sandrine et al

in Book of Abstracts of the 64th Annual Meeting of the European Federation of Animal Science (2013, August)

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See detailUse of visible-near infrared spectroscopy to determine cheese properties
Troch, Thibault ULg; Vanden Bossche, Sandrine; De Bisschop, Céline et al

Poster (2013, August)

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See detailHyperspectral imaging applications in agriculture and agro-food product quality and safety control: A review
Dale, Laura ULg; Thewis, André ULg; Boudry, Christelle ULg et al

in Applied Spectroscopy Reviews (2013), 48(2), 142-159

In this review, various applications of Near Infrared Hyperspectral Imaging (NIR-HSI) in agriculture and in the quality control of agro-food products are presented. NIR-HSI is an emerging technique that ... [more ▼]

In this review, various applications of Near Infrared Hyperspectral Imaging (NIR-HSI) in agriculture and in the quality control of agro-food products are presented. NIR-HSI is an emerging technique that combines classical NIR spectroscopy and imaging techniques in order to simultaneously obtain spectral and spatial information from a field or a sample. The technique is non-destructive, non-polluting, fast and relatively inexpensive per analysis. Currently, its applications in agriculture range from vegetation mapping, crop disease, stress and yield detection to component identification in plants and impurity detection. There is growing interest in HSI for the safety and quality assessment of agro-food products. The applications have been classified from the level of satellite images to the macroscopic, if not, molecular level. [less ▲]

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