Replaced with revised version of poster 07/19/11.Production Economics, Productivity Analysis, Research and Development/Tech Change/Emerging Technologies,

Naseem, Anwar

Singla, Rohit

English

Research Papers in Economics

Economic Analysis of Marker-Assisted Selection in Canola 
 
 
 
 
Rohit Singla 
(ROHIT.SINGLA@MCGILL.CA) 
 
Anwar Naseem 
 
 
(ANWAR.NASEEM@MCGILL.CA) 
Agricultural Economics, Department of Natural Resource Sciences 
McGill University, Ste-Anne-de-Bellevue, QC 
 
 
 
 
 
 
Poster prepared for presentation at the Agricultural & Applied Economics 
Association’s 2011 AAEA & NAREA Joint Annual Meeting, Pittsburgh, 
Pennsylvania, July 24-26, 2011 
 
 
 
 
 
Copyright 2011 by Rohit Singla and Anwar Naseem. All rights reserved. Readers may 
make verbatim copies of this document for non-commercial purposes by any means, 
provided that this copyright notice appears on all such copies. Economic Analysis of Marker Assisted Selection in Canola 
Rohit Singla and Anwar Naseem 
Agricultural Economics, McGill University, Montreal  
INTRODUCTION 
 A  significant  amount  of  investments  have  been  made  on  agricultural  genomics 
research worldwide targeting biotic, abiotic and other useful traits in different crop 
species. In particular genomics research has been used to identify suitable genetic 
markers  that  could  be  used  in  crop  breeding  through  marker  assisted  selection 
(MAS). This study estimates the potential economic impact of genomics based MAS 
in canola. The assessment of the economic impact of the MAS technique can help 
provide useful guidance to research managers. 
 The specific objectives of this study is to provide an ex-ante economic assessment of 
MAS  breeding  in  comparison  to  (1)  no  variety  development,  and  (2)  variety 
development through conventional breeding (CB) for five abiotic traits in Canola in 
Canada.  The  five  traits  are  Cold  Tolerance,  Drought  Tolerance,  Pod  shattering 
resistance, Heat blast resistance and Soil salinity tolerance. 
 Recent studies by Rudi et. al. (2010) and Alpuerto et. al. (2009) evaluating economic 
impact of MAS in Rice and Cassava give only point estimates of  various economic 
impacts  at  aggregate  level  without  considering  a  possible  correlation  between 
important model parameters. This case study provides a detailed economic analysis 
by estimating a range of various economic impacts at regional level in Canada after 
assuming a possible correlation between major model parameters. 
 
METHODS 
 We are using a partial-equilibrium, economic surplus approach with price spillovers 
(and no technology spillovers) described by Alston, Norton and Pardey (1995) which 
allows  for  the  exploration  of  the  influence  of  a  broad  range  of  policy,  market, 
technology  and  adoption  factors  on  the  timing,  magnitude,  and  distribution  of  the 
economic benefits of R&D.  
 In order to account for uncertainty in the model parameters, stochastic simulations 
were conducted in order to evaluate the distributions of economic benefits. Repeated 
samples were drawn from a joint distribution of the parameters of yield change and 
maximum  adoption  rate  .  Sensitivity  analysis  were  conducted  on  other  important 
model parameters  i.e. Probability of success and R&D lags 
 
 
 
 
RESULTS 
 
 
 
 
 
 
 
 
 
 
                
 
 
 
 
 
 
 
 
 
 
Sensitivity Analysis 
 
 
 
 
 
 
 
                                 
 
 
 
 
 
 
 
 
 
REFERENCES 
 Alston, J.M., G.W. Norton, and P.G. Pardey. 
Science under Scarcity: Principles and Practice for 
Agricultural Research Evaluation and Priority 
Setting. Ithaca, NY: Cornell University Press, 
1995. 
 Alpureto, V.E.B., G.W. Norton, J. Alwang, and A.M. 
Ismael. ‘Economic Impact Analysis of Marker-
Assisted Breeding for Tolerance to Salinity and 
Phosphorous Deficiency in Rice.’ Review of 
Agricultural Economics 31 (2009): 779-92.  
 Canola Council of Canada, Saskatoon, SK  
 U.S. Canola Digest. Vol. 3, No. 2,  2008 
 Rudi, N., G.W. Norton, J. Alwang, and  G. 
Asumugha (2010). ‘Economic impact analysis of 
marker-assisted breeding for resistance to pests 
and postharvest deterioration in cassava.’ AfJARE 
4 (2010): 110-22 
 
 
 
 
 
 
 
  
 
 
Traits  Parameters  Alberta  Saskatchewan  Manitoba  
Cold Tolerance  Yield loss due to cold (%)  23  10.5  10.5 
Annual acreage expansion (%)   3  1  0 
Affected acreage (%)  50  50  0 
Drought 
Tolerance 
Yield loss due to drought (%)  25  12  10 
Annual acreage expansion (%)   3.5  2  1 
Affected acreage (%)  40  22.5  15 
Heat Blast 
Resistance 
Yield loss due to Heat Blast (%)  12.5  11  5 
Affected area (%)  60  30  10 
Pod Shattering 
Resistance 
Yield loss due to pod shattering (%)  3.5  11  5 
Affected area (%)  11  40  5 
Soil 
Salinity 
Tolerance 
Yield loss in salt-affected soils (%)  11  2.5  2.5 
Annual Acreage Expansion (%)   1  0.5  0 
Affected area (%)  25  10  5 
 Common Parameters  Values 
R&D lags for MAS (Years)  10 
R&D lags for CB (Years)  13 
Demand elasticity Canada  -0.20 
Supply elasticity Canada  0.26 
Demand elasticity ROW  -0.15 
Supply elasticity ROW  0.26 
Canola price/tonne ($)  450 
Domestic demand (million tonnes)  4.5 
ROW demand (million tonnes)  33 
Probability of success  0.5 
Total costs ($ per acre)  206.43 
Time Horizon  including R&D (Yrs)  20  
Discount Rate  1.25 
Expected change in costs (%)  9.5 
DATA/PARAMETERS 
 Majority of the parameters  presented 
here were obtained through an online 
survey  of  canola  agronomists, 
breeders and scientists in Canada.  
 Other  parameters  were  obtained 
from the website of ‘Canola Council 
of Canada’. 
 Average  canola  yields  for  Alberta, 
Saskatchewan,  Manitoba,  and  other 
provinces  are  0.769,  0.698,  0.779 
and 0.721 tonnes/acre, respectively 
 Average canola acreages in Alberta, 
Saskatchewan,  Manitoba,  and  other 
provinces are 5117.5, 7518.8, 3096.3 
and  51.25  thousand  acres, 
respectively. 
 Maximum  %  adoption  rates  ranges 
for  abiotic  traits  were  70-80,  60-70, 
50-60,  60-70  for  Alberta, 
Saskatchewan,  Manitoba  and  other 
provinces. 
CONCLUSIONS 
 Aggregate  mean  benefits  from  MAS  in 
comparison to no breeding are expected to be 
~3.9 billion dollars in Canada and  ~1 billion $ 
in ROW for the five abiotic traits, under baseline 
parameter values. 
 Global  incremental  benefits  from  MAS  in 
comparison  to  CB  are  expected  to  be  ~2.85 
billion $  for the five abiotic traits. 
 Among  the  five  abiotic  traits,  80%  of  the 
benefits  are  expected  to  be  realized  with 
improvements  in  cold  and  drought  tolerance 
traits. 
 Majority of the benefits in Canada are expected 
to  be  realized  in  Alberta,  followed  by 
Saskatchewan and Manitoba 
 The benefits from MAS were highly sensitive to 
probability  of  successfully  incorporating  a  trait 
in canola 
 The incremental benefits of MAB in comparison 
to  CB  were  sensitive  to  a  difference  in  R&D 
lags for MAB and CB. 
 
 
0.00 500.00 1000.00 1500.00 2000.00
Soil Salinity Tolerance
Pod Shatter Resistance
Heat Blast Resistance
Drought Tolerance
Cold Tolerance
Fig1. Average Benefits from five traits (million $) 
Canada
ROW
-500 0 500 1000 1500 2000
Soil Salinity Tolerance
Pod Shatter Resistance
Heat Blast Resistance
Drought Tolerance
Cold Tolerance
Fig2. Distribution of benefits in Canada ( M $) 
Alberta
Saskatchewan
Manitoba
0 200 400 600 800 1000 1200
Soil Salinity Tolerance
Pod Shatter Resistance
Heat Blast Resistance
Drought Tolerance
Cold Tolerance
Fig3. Average incremental Benefits  from MAB in 
comparison to CB 
Canada
ROW
-500 0 500 1000
Soil Salinity Resistance
Pod Shatter Resistance
Heat Blast Resistance
Drought Tolerance
Cold Tolerance
Fig4. Regional distribution of  incremental benefits 
from MAB in comparison to CB in Canada 
Alberta
Saskatchewan
Manitoba
0.00
200.00
400.00
600.00
800.00
1000.00
1200.00
1400.00
1600.00
1800.00
MAB = 10
CB=12
MAB = 10
CB=13
MAB = 10
CB=14
MAB = 10
CB=15
B
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Prob_Success 
Fig6. Difference in R&D lags and incremental 
benefits 
Soil Salinity Tolerance Pod Shatter Resistance Heat Blast Resistance
Drought Tolerance Cold Tolerance
0
500
1000
1500
2000
2500
3000
3500
0.4 0.5 0.6 0.7 0.8
B
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m
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$
 
Fig5. Probability of success and total benefits 
Soil Salinity Tolerance Pod Shatter Resistance Heat Blast Resistance
Drought Tolerance Cold Tolerance
AB  SK 
MB 

Economic Analysis of Marker-Assisted Selection in Canola

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