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Monitoring and assessment of ingestive chewing sounds for prediction of herbage intake rate in grazing cattle

Published online by Cambridge University Press:  10 October 2017

J. R. Galli ,
C. A. Cangiano ,
M. A. Pece ,
M. J. Larripa ,
D. H. Milone ,
S. A. Utsumi  and
E. A. Laca
J. R. Galli*
Affiliation:
Facultad de Ciencias Agrarias, Universidad Nacional de Rosario, C.C. 14, S 2125 ZAA, Zavalla, Santa Fe, Argentina
C. A. Cangiano
Affiliation:
Instituto Nacional de Tecnología Agropecuaria, C.C. 276, 7620 Balcarce, Buenos Aires, Argentina
M. A. Pece
Affiliation:
Facultad de Ciencias Agrarias, Universidad Nacional de Rosario, C.C. 14, S 2125 ZAA, Zavalla, Santa Fe, Argentina
M. J. Larripa
Affiliation:
Facultad de Ciencias Agrarias, Universidad Nacional de Rosario, C.C. 14, S 2125 ZAA, Zavalla, Santa Fe, Argentina
D. H. Milone
Affiliation:
Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional, sinc(i), CONICET-UNL, 4to piso FICH, Ciudad Universitaria UNL, 3000 Santa Fe, Argentina
S. A. Utsumi
Affiliation:
W.K. Kellogg Biological Station and Department of Animal Science, Michigan State University, 3700 E Gull Lake dr., Hickory Corners, MI 49060, USA
E. A. Laca
Affiliation:
Department of Plant Sciences, University of California, One Shields av., Davis, CA 95616, USA
*
†E-mail: jgalli@lidernet.com.ar
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Abstract

Accurate measurement of herbage intake rate is critical to advance knowledge of the ecology of grazing ruminants. This experiment tested the integration of behavioral and acoustic measurements of chewing and biting to estimate herbage dry matter intake (DMI) in dairy cows offered micro-swards of contrasting plant structure. Micro-swards constructed with plastic pots were offered to three lactating Holstein cows (608±24.9 kg of BW) in individual grazing sessions (n=48). Treatments were a factorial combination of two forage species (alfalfa and fescue) and two plant heights (tall=25±3.8 cm and short=12±1.9 cm) and were offered on a gradient of increasing herbage mass (10 to 30 pots) and number of bites (~10 to 40 bites). During each grazing session, sounds of biting and chewing were recorded with a wireless microphone placed on the cows’ foreheads and a digital video camera to allow synchronized audio and video recordings. Dry matter intake rate was higher in tall alfalfa than in the other three treatments (32±1.6 v. 19±1.2 g/min). A high proportion of jaw movements in every grazing session (23 to 36%) were compound jaw movements (chew-bites) that appeared to be a key component of chewing and biting efficiency and of the ability of cows to regulate intake rate. Dry matter intake was accurately predicted based on easily observable behavioral and acoustic variables. Chewing sound energy measured as energy flux density (EFD) was linearly related to DMI, with 74% of EFD variation explained by DMI. Total chewing EFD, number of chew-bites and plant height (tall v. short) were the most important predictors of DMI. The best model explained 91% of the variation in DMI with a coefficient of variation of 17%. Ingestive sounds integrate valuable information to remotely monitor feeding behavior and predict DMI in grazing cows.

Keywords

acoustic analysisingestive behaviorchewingchew-biteruminants
Type
Research Article
Information
animal , Volume 12 , Issue 5 , May 2018 , pp. 973 - 982
Copyright
© The Animal Consortium 2017 

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Footnotes

*

Retired.

References

Bailey, D, Gross, J, Laca, E, Rittenhouse, L, Coughenour, M, Swift, D and Sims, P 1996. Mechanisms that result in large herbivore grazing distribution patterns. Journal of Range Management 49, 386–400.CrossRefGoogle Scholar
Benvenutti, M, Gordon, I and Poppi, D 2006. The effect of the density and physical properties of grass stems on the foraging behaviour and instantaneous intake rate by cattle grazing an artificial reproductive tropical sward. Grass and Forage Science 61, 272–281.CrossRefGoogle Scholar
Black, J and Kenney, P 1984. Factors affecting diet selection by cow. II. Height and density of pasture. Australian Journal of Agricultural Research 35, 565–578.CrossRefGoogle Scholar
Charif, R, Mitchell, S and Clark, C 1995. Canary 1.2 user’s manual. Cornell Laboratory of Ornithology, Ithaca, NY, USA.Google Scholar
Galli, J, Cangiano, C, Demment, M and Laca, E 2006. Acoustic monitoring of chewing and intake of fresh and dry forages in steers. Animal Feed Science and Technology 128, 14–30.CrossRefGoogle Scholar
Galli, J, Cangiano, C, Milone, D and Laca, E 2011. Acoustic monitoring of short-term ingestive behaviour and intake in grazing sheep. Livestock Science 140, 32–41.CrossRefGoogle Scholar
Ginnett, T and Demment, M 1995. The functional response of herbivores – analysis and test of a simple mechanistic model. Functional Ecology 9, 376–384.CrossRefGoogle Scholar
Inoué, T, Brookes, I, John, A, Kolver, E and Barry, T 1994. Effects of leaf shear breaking load on the feeding value of perennial ryegrass (Lolium perenne) for cow. 2. Feed intake, particle breakdown, rumen digesta outflow and animal performance. Journal of Agricultural Science 123, 137–147.CrossRefGoogle Scholar
Kalu, B and Fick, G 1981. Quantifying morphological development of alfalfa for studies of hebage quality. Crop Science 21, 267–271.CrossRefGoogle Scholar
Klein, L, Baker, S, Purser, D, Zaknich, A and Bray, A 1994. Telemetry to monitor sounds of chews during eating and rumination by grazing sheep. Proceedings of the Australian Society of Animal Production 20, p. 423.Google Scholar
Laca, EA 2008. Foraging in a heterogeneous environment: intake and diet choice. In Resource ecology: spatial and temporal dynamics of foraging (ed. H Prins H and F Van Lagevelde), pp. 81–100. Springer, Dordrecht, the Netherlands.CrossRefGoogle Scholar
Laca, E and Demment, M 1991. Herbivory: the dilemma of foraging in a spatially heterogeneous food environment. In Plant defenses against mammalian herbivory (ed. RT Palo and CT Robbins), pp. 29–44. Boca Raton, FL, USA.Google Scholar
Laca, E, Ungar, E and Demment, M 1994. Mechanisms of handling time and intake rate of a large mammalian grazer. Applied Animal Behavior Science 39, 3–19.CrossRefGoogle Scholar
Laca, E and WallisDeVries, M 2000. Acoustic measurement of intake and grazing behaviour of cattle. Grass and Forage Science 55, 97–104.CrossRefGoogle Scholar
Li, C 1975. Path analysis. A primer. Boxwood Press, Pacific Grove, CA, USA.Google Scholar
Mcleod, M, Kennedy, P and Minson, D 1990. Resistance of leaf and stem fractions of tropical forage to chewing and passage in cattle. British Journal of Nutrition 63, 105–119.CrossRefGoogle ScholarPubMed
Milone, D, Galli, J, Cangiano, C, Rufiner, H and Laca, E 2012. Automatic recognition of ingestive sound of cattle based on hidden Markov models. Computers and Electronics in Agriculture 67, 51–65.CrossRefGoogle Scholar
Moore, K, Moser, L, Vogel, K, Waller, S, Johnson, B and Pedersen, J 1991. Describing and quantifying growth stages of perennial forage grasses. Agronomy Journal 83, 1073–1077.CrossRefGoogle Scholar
Robertson, J and Van Soest, P 1980. The detergent system of analysis and its application to human foods. In The analysis of dietary fiber in foods (ed. WPT James and O Theander), pp. 123–158. Marcel Dekker Inc, NY, USA.Google Scholar
SAS Institute Inc. 2015. JMP® version 12. User’s guide statistics. SAS Institute Inc, Cary, NC, USA.Google Scholar
Schirmann, K, von Keyserlingk, MAG, Weary, D, Veira, D and Heuweieser, W 2009. Technical note: validation of a system for monitoring rumination in dairy cows. Journal of Dairy Science 92, 6052–6055.CrossRefGoogle ScholarPubMed
Syntrillium Software Corporation 2002. Cool edit pro version 2. User’s manual. Syntrillium Software Corporation, Phoenix, AZ, USA.Google Scholar
Ungar, E, Ravid, N, Zada, T, Ben-Moshe, E, Yonatan, R, Baram, H and Genizi, A 2006. The implications of compound chew-bite movements for bite rate in grazing cattle. Applied Animal Behaviour Science 98, 183–195.CrossRefGoogle Scholar
Ungar, E and Rutter, S 2006. Classifying cattle jaw movements: comparing IGER behaviour recorder and acoustic techniques. Applied Animal Behaviour Science 98, 11–27.CrossRefGoogle Scholar
WallisDeVries, M and Laca, E 1998. From feeding station to patch: scaling up food intake measurements in grazing cattle. Applied Animal Behaviour Science 60, 301–315.CrossRefGoogle Scholar
Watt, LJ, Clark, CEF, Krebs, GL, Petzel, CE, Nielsen, S and Utsumi, SA 2015. Differential rumination, intake, and enteric methane production of dairy cows in a pasture-based, automatic milking system. Journal of Dairy Science 98, 7248–7263.CrossRefGoogle Scholar
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