Quantification of Condensed Tannins in Sainfoin Powder (Onobrychisviciifolia) by FT-NIR Spectroscopy
PDF

Keywords

Partial least square regression, principal component analysis, factorial discriminant analysis, ISO 12099:2017.

How to Cite

1.
Cédric Camps, Werne Steffen, Mélanie Quennoz, Xavier Simonnet, Céline Gilli. Quantification of Condensed Tannins in Sainfoin Powder (Onobrychisviciifolia) by FT-NIR Spectroscopy. Glob. J. Agric. Innov. Res. Dev [Internet]. 2017 Dec. 29 [cited 2022 May 21];4(1):58-66. Available from: https://www.avantipublishers.com/index.php/gjaird/article/view/712

Abstract

 Models based on FT-NIR spectroscopy and PLS-regressions were developed over three harvest years to determine the condensed tannins contents (CT, %(w/w)) in sainfoin powders. The three data sets corresponding to the three harvest years were used as calibration and then validation sets, successively. Finally, a global model gathering all the three years data sets has been developed. The developed models predict CT in a range of 2.06 to 11.28 %(w/w). The accuracy of the models depended on the range of CT-values of the calibration and validation sets. Finally, it was possible to predict the CT with a SEP-value lower than 0.5% (w/w) and R2-value higher than 0.9. In the present study, some of the PLS-parameters such as bias, slope and SEP have been statistically evaluated using the international standard ISO 12099:2017. The final global model was very promising since bias was not significantly different from 0, the slope was not significantly different from 1, and obtained SEP was 0.49% (w/w) while the calculated SEP-limit was 0.47% (w/w). The presently developed model was robust over the three years and the global model presented very interesting values. Such approach would be very useful to develop a new quantitative, rapid and low cost method to assess the CT of sainfoin powders. This method will allow us to free ourselves from the traditional chemical method that consumes time, money and chemicals.
https://doi.org/10.15377/2409-9813.2017.04.7
PDF

References

Frame J. Forage legumes for temperate grasslands: SCIENCE PUBLISHERS INC, MAY ST, PO BOX 699, ENFIELD, NH 03748 USA; 2005. 320 p.

Werne S, Isensee A, Maurer V, Perler E and Drewek A, Heckendorn F. Integrated control of gastrointestinal nematodes in lambs using a bioactive feed×breed approach. Veterinary Parasitology 2013; 198(3): 298-304. https://doi.org/10.1016/j.vetpar.2013.09.021

Heckendorn F, Häring DA, Maurer V, Zinsstag J, Langhans W, et al. Effect of sainfoin (Onobrychis viciifolia) silage and hay on established populations of Haemonchus contortus and Cooperia curticei in lambs. Veterinary Parasitology 2006; 142(3-4): 293-300. https://doi.org/10.1016/j.vetpar.2006.07.014

Werne S, Perler E, Maurer V, Probst JK, Hoste H, et al. Effect of sainfoin (Onobrychis viciifolia) and faba bean (Vicia faba) on the periparturient rise in ewes infected with gastrointestinal nematodes. Small Ruminant Research 2013; 113(2): 454-60. https://doi.org/10.1016/j.smallrumres.2013.03.022

Theodoridou K, Aufrère J, Andueza D, Pourrat J, Le Morvan A, et al. Effects of condensed tannins in fresh sainfoin (Onobrychis viciifolia) on in vivo and in situ digestion in sheep. Animal Feed Science and Technology 2010; 160(1- 2): 23-38. https://doi.org/10.1016/j.anifeedsci.2010.06.007

Wang Y, Barbieri LR, Berg BP and McAllister TA. Effects of mixing sainfoin with alfalfa on ensiling, ruminal fermentation and total tract digestion of silage. Animal Feed Science and Technology 2007; 135(3-4): 296-314. https://doi.org/10.1016/j.anifeedsci.2006.07.002

Camps C, Gérard M, Quennoz M, Brabant C, Oberson C, et al. Prediction of essential oil content of oregano by hand‐held and Fourier transform NIR spectroscopy. Journal of the Science of Food and Agriculture 2014; 94(7): 1397-402. https://doi.org/10.1002/jsfa.6427

Camps C, Deltheil L and Gilli C. Qualitative and Quantitative Models Based on Handheld NIR Spectroscopy to Monitor the Tomato Fruit Development During Early and Full Season. Global Journal of Agricultural Innovation 2014; 1: 27-38. https://doi.org/10.15377/2409-9813.2014.01.01.4

Camps C, Toussirot M, Quennoz M and Simonnetb X. Determination of artemisinin and moisture content of Artemisia annua L. dry powder using a hand-held near infrared spectroscopy device. Journal of Near Infrared Spectroscopy 2011; 19(3): 191-8. https://doi.org/10.1255/jnirs.927

Decruyenaere V, Lecomte P, Demarquilly C, Aufrere J, Dardenne P, et al. Evaluation of green forage intake and digestibility in ruminants using near infrared reflectance spectroscopy (NIRS): Developing a global calibration. Animal Feed Science and Technology 2009; 148(2-4): 138-56. https://doi.org/10.1016/j.anifeedsci.2008.03.007

Alomar D, Fuchslocher R and de Pablo M. Effect of preparation method on composition and NIR spectra of forage samples. Animal Feed Science and Technology 2003; 107(1-4): 191-200. https://doi.org/10.1016/S0377-8401(03)00124-X

Ruisánchez I, Rius FX, Maspoch S, Coello J, Azzouz T, et al. Preliminary results of an interlaboratory study of chemometric software and methods on NIR data. Predicting the content of crude protein and water in forages. Chemometrics and Intelligent Laboratory Systems 2002; 63(2): 93-105. https://doi.org/10.1016/S0169-7439(02)00039-4

Grabber JH, Zeller WE and Mueller-Harvey I. Acetone Enhances the Direct Analysis of Procyanidin- and Prodelphinidin-Based Condensed Tannins in Lotus Species by the Butanol–HCl–Iron Assay. Journal of Agricultural and Food Chemistry 2013; 61(11): 2669-78. https://doi.org/10.1021/jf304158m

Bertrand D, Courcoux P, Autran JC and Méritan R. Stepwise canonical discriminant analysis of continuous digitalized signals: Application to chromatograms of wheat proteins. Journal of Chemometrics 1990; 4(3bis): 427-13.

Dykes L, Hoffmann L, Portillo-Rodriguez O, Rooney WL and Rooney LW. Prediction of total phenols, condensed tannins, and 3-deoxyanthocyanidins in sorghum grain using nearinfrared (NIR) spectroscopy. Journal of Cereal Science 2014; 60(1): 138-42. https://doi.org/10.1016/j.jcs.2014.02.002