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ARS Home » Plains Area » Mandan, North Dakota » Northern Great Plains Research Laboratory » Research » Publications at this Location » Publication #409254

Research Project: Sustainable Agricultural Systems for the Northern Great Plains

Location: Northern Great Plains Research Laboratory

Title: Evaluating fecal DNA metabarcoding to estimate the dietary botanical composition for goats

Author
item MALIK, ROBIN - North Dakota State University
item Kronberg, Scott
item Hendrickson, John
item Scott, Drew
item DEKEYSER, SHAWN - North Dakota State University
item SEDIVEC, KEVIN - North Dakota State University

Submitted to: Rangeland Ecology and Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/6/2024
Publication Date: 5/1/2024
Citation: Malik, R., Kronberg, S.L., Hendrickson, J.R., Scott, D.A., Dekeyser, S., Sedivec, K. 2024. Evaluating fecal DNA metabarcoding to estimate the dietary botanical composition for goats. Rangeland Ecology and Management. 94:163-167. https://doi.org/10.1016/j.rama.2024.03.005.
DOI: https://doi.org/10.1016/j.rama.2024.03.005

Interpretive Summary: Improved techniques are needed to estimate dietary species composition, the amounts of each plant species consumed by grazing animals. The fecal DNA-based technique has been proposed as a non-invasive method to determine dietary species composition. However, studies suggest that it is more effective to qualitatively estimate the plant species eaten by wild and domestic animals than for accurately quantifying amounts of each species eaten. Therefore, we tested the technique with goats, which were fed known amounts of different types of plant materials. Broadleaf plant materials fed were leaves from the trees Russian olive, silver buffaloberry, the shrub western snowberry and the invasive weed wormwood sage plus a mixture of predominantly smooth bromegrass, which also included very small amounts of other grasses such as Kentucky bluegrass and forbs such as leafy spurge. DNA-based estimates of the dietary composition of the goats were generally different from those of their known dietary composition. An exception was for wormwood sage when expressed on a crude protein basis. Therefore, we conclude that the fecal DNA-based technique for estimating the dietary composition of goat diets may be useful qualitatively for livestock producers and rangeland managers, but needs further development to be a better quantitative technique.

Technical Abstract: Improved techniques are needed to estimate the dietary species composition of grazing animals. The fecal DNA metabarcoding technique has been proposed as a non-invasive method to determine dietary species composition. However, studies suggest that it is more effective to qualitatively estimate species composition of wild and domestic animals than for accurately quantifying diet composition. The technique, using the trnL barcode, was evaluated with ten individually-penned goats, which were fed hand-harvested plant materials that were collected fresh each morning. Known amounts of each type of plant material were fed and completely consumed by the goats. Goats were fed at 3% of their body weight on a DM basis. Broadleaf plant materials fed were Russian olive (Elaeagnus angustifolia), silver buffaloberry (Shepherdia argentea), western snowberry (Symphoricarpos occidentalis) and wormwood sage (Artemisia absinthium) plus a mixture of predominantly smooth bromegrass (Bromus inermis), which also included very small amounts of other grasses such as Kentucky bluegrass (Poa pratensis) and forbs such as leafy spurge (Euphorbia esula). Estimates of the dietary composition of the goats were different (P = 0.04) from those of their known dietary composition, except for wormwood sage when expressed on a crude protein basis (P = 0.98), regardless of whether known composition was expressed on a dry matter or crude protein basis. Therefore, we conclude that the fecal DNA metabarcoding technique for estimating the dietary composition of goat diets is useful qualitatively but needs further development to be a better quantitative technique.