Determining Ripeness in White Sturgeon Females to Maximize Yield and Quality

of Caviar

Molly Webb, Montana State University, USFWS

Principal Investigators and Institutions

Serge Doroshov, University of California, Davis

Barbara Rasco, Washington State University

Anna Cavinato, Eastern Oregon University

Wendy Sealey, Montana State University, USFWS

Outreach: Gary Fornshell, University of Idaho Extension

Principal Investigators and Institutions

Industry Advisor: Peter Struffenegger Sterling Caviar, LLC

Technical Advisor: Fred Conte, UC Davis

Industry Participants: Leo Ray, Fish Breeders of Idaho Linda Lemmon, Blind Canyon Aquaranch Inc.

Long-Term Project Goal Develop a less invasive, faster, and better

predictor of maturity to optimize caviar yield and quality from white sturgeon at harvest

B

A

PI=A/B

Replace Oocyte Polarization Index (PI)

Proposed Tools

Short Wavelength Near Infrared Spectroscopy

Fourier Transform Infrared Spectroscopy

Radioimmunoassay

Ideal Approach to Sorting Step 1

Fall

Low PI (< 0.18) Early

High PI (> 0.26)

Late

Medium PI (0.19-0.26)

Middle

Harvest

Ideal Approach to Sorting Step 2

Harvest Low PI (< 0.13)

Harvest

Medium High PI (> 0.13)

Don’t Harvest

Atretic

Don’t Harvest

Caviar 2009 Study California

November (n=160)

Low PI (0.162 + 0.034)

January

Medium PI (0.242 + 0.008)

March

High PI (0.301 + 0.016)

May

Caviar 2009: Oocyte PI at Harvest �

0.00

0.05

0.10

0.15

0.20

0.25

0.30

Low PI Medium PI High PI

PI Groups

Polar

izatio

n In

dex

*

*

SortedControl

�

Caviar 2009: Caviar Yield (% Body Wt) �

0

5

10

15

Low PI Medium PI High PI

PI Groups

Cavia

r Yiel

d (%

Bod

y Weig

ht)

*

SortedControl

�

Ovarian Adiposity

0.0

5.0

10.0

15.0

Low Fat Medium Fat High Fat

Fat Categories

8 year olds

7 year olds

Cavia

r Yiel

d (%

Body

Weig

ht)

aa

b b

c

c

�

Model Development for Prediction of Oocyte PI

SW-NIR FT-IR

SW-NIR Model for Fall Sorting by Abdominal Scan

Classified PI Actual Low PI (%)

PI Medium and High PI (%)

Low PI (< 0.18)

73 (947)

34 (198)

Medium (0.19-0.26) High PI (> 0.26)

27 (343)

66 (391)

SW-NIR Model for Fall Sorting by Egg Scan

Classified PI Actual Low PI (%)

PI Medium and High PI (%)

Low PI (< 0.18)

84 (938)

31 (185)

Medium (0.19-0.26) High PI (> 0.26)

16 (184)

69 (418)

SW-NIR Model for Harvest by Abdominal Scan

Classified PI Actual Low PI (%)

PI Medium and High PI (%)

Low PI (< 0.13)

76 (710)

32 (301)

High PI (> 0.13)

24 (227)

68 (641)

SW-NIR Model for Harvest by Egg Scan

Classified PI Actual Low PI (%)

PI Medium and High PI (%)

Low PI (< 0.13)

81 (605)

30 (295)

High PI (> 0.13)

19 (140)

70 (685)

Classification No. Correctly Classified Spectra

% Correctly Classified Spectra

0.05 < PI < 0.10 278 92.67

0.10 < PI < 0.15 281 93.67

0.15 < PI < 0.20 269 89.67

0.20 < PI < 0.25

271 90.33

PI > 0.25 292 97.33

FT-IR Model using Plasma

Fall 2009 - Spring 2010

Segregated females using FT-IR at both California and Idaho farms

Regression Analysis Using Model Developed from 2008-2009 Data

0.10

0.15

0.20

0.25

0.30

Pred

icte

d PI

(200

8-20

09 D

ata)

0.10 0.15 0.20 0.25 0.30

Actual PI

R2=0.235

Regression Analysis Using Model Developed from 2008-2009 Data Plus 2010 Fish

0.10

0.15

0.20

0.25

0.30

Pred

icte

d PI

(200

8-20

09 D

ata

Plus

201

0 Su

bset

)

0.10 0.15 0.20 0.25 0.30

Actual PI

R2=0.718

Actual PI Predicted PI using 2008-2009

model

Predicted PI using 2008-2009 model plus 2010

0.133 ± 0.021 0.245 ± 0.006 0.150 ± 0.007

0.155 ± 0.035 0.230 ± 0.019 0.172 ± 0.017

0.182 ± 0.019 0.201 ± 0.011 0.175 ± 0.007

0.225 ± 0.020 0.180 ± 0.013 0.242 ± 0.011

0.248 ± 0.018 0.256 ± 0.017 0.251 ± 0.012

PI Comparisons

Fall 2010-Spring 2011 Segregate females using FT-IR with multiple year classes

Refine/optimize both FT-IR and SW-NIR models

Explore SW-NIR probe design

Accomplishments to Date Plasma sex steroids, SW-NIR, and FT-IR can

be used to predict early atresia with 70-95% accuracy

Oocyte PI may be predicted from SW-NIR and

FT-IR spectra; model development continues Highly variable caviar yield appears to be caused

by ovarian adiposity

Outreach Activities to Date

11 Presentations at national meetings 1 Manuscript published (J. Agric. Food Chem.) 3 Manuscripts accepted (Aquaculture) 5 Manuscripts in prep 2 Extension publications in prep