1 / 51

CHARACTERISTICS OF NORTH AMERICAN SURI ALPACAS

CHARACTERISTICS OF NORTH AMERICAN SURI ALPACAS. A study sponsored by the Suri Network Summarized and analyzed by: Chris Lupton Texas AgriLife Research The Texas A&M System San Angelo July, 2009. Project design.

gertrudeking
Download Presentation

CHARACTERISTICS OF NORTH AMERICAN SURI ALPACAS

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. CHARACTERISTICS OF NORTH AMERICAN SURI ALPACAS A study sponsored by the Suri Network Summarized and analyzed by: Chris Lupton Texas AgriLife Research The Texas A&M System San Angelo July, 2009

  2. Project design • The project was designed by the Education and Research Committee of the Suri Network with input from the members: Tony Cotton, Board Liaison; Andy Tillman, Ann Hayes, Bill Vonderhaar, Bruce Van Natta, Carolyn Geise, Claudia Raessler, Jacqueline Cristini, Kay Ryschon, Laurel Shouvlin, and Mary Lou Clingan.

  3. Cooperating breeders • Alpaca Jack’s Suri Farm, East Findlay, Ohio • Ameripaca Alpaca Breeding Company, Galesville, Maryland • Latah Creek Alpacas, Mica, Washington • Leraso Farm Alpacas, Long Grove, Illinois • Pucara International, McMinnville, Oregon • Super Suris, Mead, Washington • Sur-real Alpacas, Westfield, Indiana

  4. Objectives of study • . Establish means, extreme values, and variability for objectively measured BW, height to withers, and numerous fleece, fiber, skin, and blood characteristics of 100 2-yr-old male and female, white and colored, Suri alpacas from several North American breeders representing diverse genetics and environments.

  5. Objectives of study • . Record subjective assessments of several traits (e.g., color, lock consistency, and luster), compare with objective data when available, and calculate correlations with measured traits.

  6. Objectives of study • . Calculate correlations between all traits measured and assessed in the study.

  7. Who did what ? • Breeders • Provided the following information and samples: • Farm location, age of animal, color, ARI number, sex (and pregnancy status for females, intact or castrated for males), BW after shearing, BCS, height to withers, weight of fleece components (blanket, neck, seconds, and total), dates of first and second shearings (permitted adjustment of weights and staple lengths of 2nd fleece to 365 days), mid-blanket fleece sample and skin biopsy, photographs of alpaca’s head, left and right profiles, and close-up of fiber.

  8. Who did what ? • Breeders • Insert pictures of some of the animals

  9. Who did what ? • Mr. Ian Watt, Morro Bay, CA • Measured mid-side samples using an OFDA2000 instrument on 9-6-06. • This resulted in measurement of 14 fiber-related traits, 7 of which were used in the analysis.

  10. Who did what ? • OFDA2000 instrument and report

  11. Who did what ? • OFDA2000 instrument and report

  12. Who did what ? • Dr. Jim E. Watts, Bowral, NSW, Australia: • Measured follicle and fiber traits on the skin biopsies and staple samples that resulted in 23 traits used in the analysis. • A sub-set of skin samples (n=10) was also measured by Dr. Norm Evans.

  13. Who did what ? • Horizontal sections of stained alpaca skin

  14. Who did what ? • Bossa Nova Technologies, Venice, CA • Measured specular and diffuse polarized reflected light from washed, aligned, alpaca staple samples (N = 33) using their SAMBA instrument. • Calculated several estimates of luster and measured luminance for each sample.

  15. Who did what ? • The Samba Hair System

  16. Who did what ? • Using a Scanning Electron Microscope, Dr. Chris Davitt, Washington State University, measured: • Scale length (N=873) on fibers (N=102) of known diameter from individual animals (N=29). • Scale thickness (N=1000) on fibers of known diameter (N=20, range 15 to 40 microns) from individual animals (N=20).

  17. Who did what ? • Fiber diameter and scale lengths

  18. Who did what ? • Fiber diameter and scale thickness (40,000 X)

  19. Who did what ? Blood samples were analyzed for: • Mineral levels at Michigan State University’s Diagnostic Center for Population and Animal Health • Metabolic profiles and cell blood counts with differentials at Oregon State University’s Veterinary Diagnostic Lab.

  20. Who did what ? • The blood analyses gave rise to 51 variables that were included in the overall analysis.

  21. Who did what ? • The data were sent to Chris Lupton, an animal fiber researcher with Texas AgriLife Research, Texas A&M System, who organized the data into a single spreadsheet and used the SAS statistical package to calculate means, variability, and extreme values for each measured and assessed trait and also calculated correlation coefficients between the traits. • The results are summarized in a 168-page report to the Suri Network and, in much less detail, in this presentation.

  22. RESULTS • The final spreadsheet contained 173 columns (representing traits) and 63 rows (representing individual animals. • All cells were not full (missing data). • A few very obvious outliers were not included in the analysis. • Plan to show histograms showing the distribution of some of the traits measured.

  23. RESULTS

  24. Medullation • Primary fibers • 1-94%, 1-98%, 47-100%

  25. General observation : • above line = high luster • on line = medium luster • below line = low luster (subjectively assessed)

  26. Bottom line on alpaca fiber luster measurement • We have an instrument and a protocol that are capable of producing highly reproducible measurements of luster and color. • The current luster measurements are NOT independent of color. • Further research is required to produce a luster measure that is independent of color (McColl and Lupton currently working on ARF/SN-sponsored project with this objective).

  27. Correlations • Statistical explanation. • Correlation coefficients (r values) were calculated between all the variables measured or estimated in this study. • An r value of 1 means the two variables are perfectly correlated and one can be accurately predicted from the other. • An r value of 0 means absolutely no correlation between the 2 variables.

  28. Correlations • Practically, most r values lie somewhere between 0 and 1 so the question arises as to the significance of the correlation. • This is a function of how well one variable predicts the other (and vice versa) and the number of data pairs included in the correlation analysis. • Significance of a correlation (or other statistical effect) is indicated by the probability or P value. P < 0.05 means there is a greater than 95% chance the correlation is real (or a less than 5% chance that the correlation is due to chance). Smaller values of P (e.g., P < 0.001) indicate greater confidence that the correlation is not due to chance.

  29. Correlations • Some predictable ones, e.g. • AFD versus Secondary:Primary follicle ratio, r = -0.50, P < 0.0001 • AFD versus follicle density, r = -0.57, P < 0.0001 • AFD versus clean luster score, r = -0.34, P = 0.01 • Fiber growth rate versus mean fiber length, r = 0.96, P < 0.0001 • Raw luster versus clean luster, r = 0.71, P < 0.0001

  30. Correlations • Some less predictable ones, e.g. • Clean luster score and variability in fiber diameter (SDFD), r = -0.42, P = 0.003 • AFD versus % medullation in secondary fibers, r = 0.56, P < 0.0001 • Clean luster score and % medullation in secondary fibers, r = -0.48, P = 0.002 • Scale length versus staple length, r = 0.66, P < 0.0001 • AFD of secondary fibers versus albumin level in blood, r = 0.45, P = 0.001

  31. Correlations • And some you thought might be significant but are not, e.g. • Clean luster score versus: • follicle density, r = 0.2046, P = 0.1585 • scale thickness, r = 0.1620, P = 0.5490 • scale length, r = 0.1367, P = 0.5440

  32. Correlations • And some you thought might be significant but are not, e.g. • Reich-Robbins luster versus: • follicle density, r = -0.2817, P = 0.1183 • scale thickness, r = -0.2709, P = 0.4204 • BUT scale length is significant, r = - 0.5135, P = 0.0503 (and worthy of further investigation).

  33. Correlations • Very many more, mainly non-significant but also numerous significant and unexpected correlations between traits. • May provide directions for further research, testing, and breeding guidelines.

  34. SUMMARY • This study was conducted with 63 2-yr-old male and female, white and colored, Suri alpacas from 7 North American breeders representing diverse genetics and environments. • The study has established means, extreme values (min and max), and variability (SD, CV) of multiple traits. • objectively measured BW, height to withers • numerous fleece, fiber, skin, and blood characteristics

  35. SUMMARY • The traits reported included: • objectively measured body weight, height to withers, and fleece weights (n = 5) • numerous fiber (n = 11), skin / fiber (n = 23), and blood (n = 49) characteristics. • subjectively assessed body condition score, luster scores (n=2) and lock consistency.

  36. SUMMARY • All the traits measured or scored were included in a correlation analysis. • A correlation coefficient (r, and an associated P value) was calculated between every possible pair of traits.

  37. SUMMARY • Differences in traits between the sexes (n = 14, table 3 in report) were identified. • Differences in traits between white and colored animals (n = 21, table 5 in report) were identified.

  38. SUMMARY • Because of their uniqueness, 3 of the fiber traits measured were presented and discussed in more detail: • Scale length • Scale thickness • Luster

More Related