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The adoption of sustainable agricultural practices (SAPs) has been very helpful to attain agricultural sustainability. However, practices are localized and site specific and, thus, less understood in Kentucky. A research was conducted throughout the Kentucky using double stratified survey method to understand farmer’s perception about their farm and farming practices sustainability, adoption of sustainable agriculture practices (SAPs) and adoption barriers of sustainable agriculture practices. The research found that farmers generally perceive that their farm and farming activities are sustainable. The results of negative binomial regression analysis suggest that row crop growers, farmers in favor of diversification, and formal education level increase probability of SAPs adoption. Vegetable growers, and farmers with irrigation facilities also increase probability of the adoption. Income from agro-tourism, land operated, age are significant variables of the adoption of SAPs in Kentucky. Inadequate knowledge, perceived difficulty of implementation, lack of (adequate) market, negative attitude about technologies, and lack of (appropriate) technologies were major adoption barriers of SAPs in Kentucky.
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This document summarizes a study analyzing key productivity indicators in the U.S. pork industry from 2007 to 2012 using data from a large record keeping organization. It finds that finishing mortality has declined while market weight has increased. Nursery performance has changed little and sow productivity has improved with pigs per mated sow and litter size increasing. The document provides averages and standard deviations for various metrics across different production phases and graphs trends over time to benchmark performance.
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This document contains data from the 2012 USDA Agricultural Census on farms and farmers in Kentucky and neighboring states. It includes charts showing the total number of farms, average farm size, and age distribution of farm operators in Kentucky compared to other states from 1982 to 2012. It also provides tables with demographic information about Kentucky farmers such as their education levels, years of experience, acreage operated, and income levels. Regression analyses are presented with the number of sustainable agriculture practices adopted as the dependent variable and various farmer and farm characteristics as independent variables.
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More presentations at http://www.swinecast.com/2016-leman-swine-conference-material
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More presentations at http://www.swinecast.com/2013-world-pork-expo
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This document summarizes a study on the relationship between cow ownership and child nutrition in rural Ethiopia. The study finds that owning cows is strongly associated with higher milk consumption and better nutrition outcomes for children ages 6-24 months, including higher HAZ scores and lower stunting rates. These effects are larger than for other variables and robust across different model specifications and datasets. While causality cannot be proven, the results suggest policies to promote the dairy sector in Ethiopia could significantly improve child nutrition, for example by supporting improved cattle breeds, dairy processing, and supplements targeting young children. Markets can partially substitute for own production, but in subsistence settings cow ownership at the household level remains important for nutrition.
Cows, missing milk markets and nutrition in rural ethiopiaessp2
1) The study examines whether cow ownership in rural Ethiopia affects child nutrition outcomes by increasing access to milk consumption. It finds that households that own cows have higher milk consumption and better anthropometric measures like reduced stunting for children ages 6-24 months.
2) The impact is larger when there are missing milk markets, as cow ownership allows for direct consumption rather than relying on markets. Additional controls and robustness checks support the findings.
3) The results suggest policy investments could significantly improve child nutrition by developing Ethiopia's dairy sector to increase cow ownership and milk yields, as well as modernizing dairy processing and markets.
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The document summarizes sow farm and nursery, finishing, and wean-to-finish closeout performance data from 2014. Key metrics like pigs weaned per sow, feed conversion ratio, and mortality rates are presented for different percentiles of performance. Benchmarking metrics allow comparison of individual operation performance to averages and top-performing farms. The data can be used to identify areas of strength and weakness to guide improvement efforts.
This is the second presentation from a six part webinar series on the National Sheep Improvement Program (NSIP). The presenter is Dr. Ken Andries from Kentucky State University. The date of the presentation was May 8, 2014.
Dr. George Foxcroft - Risk Factors For Sow CullingJohn Blue
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More presentations at http://www.swinecast.com/2015-leman-swine-conference-material
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Determinants of profit efficiency among smallholder beef producers in BotswanaILRI
Presented by Sirak Bahta and Derek Baker at the International Food and Agribusiness Management Association (IFAMA) annual meeting, Cape Town, South Africa, 16-17 June 2014.
Dr. Tom Stein - Benchmark Analysis of Production and Financial Measures Acros...John Blue
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More presentations at http://www.swinecast.com/2014-minnesota-pork-congress
Our Food Future: How to Create Value from Commodities case studyCreatovate Pty Ltd
Looking out to 2050 what are some of the mega-trends that will impact on our food and beverage landscape as growers, processors, manufacturers and marketers of consumer packaged goods.
Global population growth past 9b by 2050 combined with increased urbanisation, changing diet patterns in the developing world and water shortages and climate change will impact detrimentally on food supply and exacerbate demand for protein and sugar and other soft commodities.
Food manufacturers will continue to consolidate as they attempt to extract efficiency from farm to shelf and retailers will grow globally, albeit with greater changes due to localisation challenges in global retail.
Fonterra case study on how an integrated supply chain from farm to shelf has increased returns to shareholder returns from cow to shelf using highly segmented nutritional products marketed to life stage needs segments.
Dr. Joel DeRouchey - Feed Price Update and Daily Feed Efficiency Drivers John Blue
Feed Price Update and Daily Feed Efficiency Drivers - Dr. Joel DeRouchey, Kansas State University, from the 2013 World Pork Expo, June 5 - 7, 2013, Des Moines, IA, USA.
More presentations at http://www.swinecast.com/2013-world-pork-expo
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Effects of Birth Weight and Colostrum Intake on Piglet Survival and Quality - Jeffrey Wiegert, from the 2017 Allen D. Leman Swine Conference, September 16-19, 2017, St. Paul, Minnesota, USA.
More presentations at http://www.swinecast.com/2017-leman-swine-conference-material
Richard Pearson NFU Profiting from Sustainability Conference York Dec 2014Stevencann1
The document discusses the agricultural industry in the UK and Yorkshire region. It notes that while the industry has seen growth in economic contribution and food exports, farmgate prices have fallen across commodities in 2014 due to global supply and demand factors. The region of Yorkshire represents a significant portion of UK agriculture, with many farms and related employment. The conclusion emphasizes that despite current challenges, the future potential for agriculture remains strong through innovation and growing global demand.
Agricultural transformation in Cambodia has had mixed effects on food and nutrition security according to a study analyzing survey data. While per capita expenditure and commercialization indicators like the share of food purchases were positively associated with dietary diversity, some farm households saw worse nutrition outcomes. Subsistence farmers in particular experienced lower child weight-for-age z-scores compared to commercializing farmers, suggesting current agricultural policy may not benefit the most vulnerable. The results indicate Cambodia needs policies that ensure agricultural growth improves nutrition for all households, especially the poorest.
Vietnam’s food processing and beverage industry continued to grow in 2014, expanding 5.1 percent in the food processing sector, versus a 6 percent growth rate in 2013; and 10 percent in the beverage sector, from 8.8 percent in 2013, according to data provided by Vietnam’s General Statistics Office (GSO) (at 2010 prices). At current prices, Vietnam’s food and beverage industry is growing fast at almost 21 percent in 2013, with food production growing at 20 percent, and beverage production growing by almost 27 percent.
This document discusses trends in high-value agriculture in India. It notes a shift from grains to higher-value commodities like fruits, vegetables, dairy and meat due to rising incomes, urbanization, and trade policies. Exports of high-value products like fruits and vegetables have grown significantly. Contract farming has allowed small farmers to access high-value domestic and export markets. Overall high-value agriculture provides opportunities for commercialization and income growth for smallholders through arrangements like contract farming. The document analyzes crop area and production data and makes recommendations to promote diversification and infrastructure to support high-value agriculture.
Cows, missing milk markets and nutrition in rural ethiopiaessp2
This document summarizes a study on the relationship between cow ownership and child nutrition in rural Ethiopia. The study finds that owning cows is strongly associated with higher milk consumption and better nutrition outcomes for children ages 6-24 months, including higher HAZ scores and lower stunting rates. These effects are larger than for other variables and robust across different model specifications and datasets. While causality cannot be proven, the results suggest agricultural and dairy sector investments could significantly improve child nutrition. Future work aims to further explore the causal mechanisms through instrumentation strategies.
Cows, missing milk markets and nutrition in rural ethiopiaessp2
This document summarizes a study on the relationship between cow ownership and child nutrition in rural Ethiopia. The study finds that owning cows is strongly associated with higher milk consumption and better nutrition outcomes for children ages 6-24 months, including higher HAZ scores and lower stunting rates. These effects are larger than for other variables and robust across different model specifications and datasets. While causality cannot be proven, the results suggest policies to promote the dairy sector in Ethiopia could significantly improve child nutrition, for example by supporting improved cattle breeds, dairy processing, and supplements targeting young children. Markets can partially substitute for own production, but in subsistence settings cow ownership at the household level remains important for nutrition.
Cows, missing milk markets and nutrition in rural ethiopiaessp2
1) The study examines whether cow ownership in rural Ethiopia affects child nutrition outcomes by increasing access to milk consumption. It finds that households that own cows have higher milk consumption and better anthropometric measures like reduced stunting for children ages 6-24 months.
2) The impact is larger when there are missing milk markets, as cow ownership allows for direct consumption rather than relying on markets. Additional controls and robustness checks support the findings.
3) The results suggest policy investments could significantly improve child nutrition by developing Ethiopia's dairy sector to increase cow ownership and milk yields, as well as modernizing dairy processing and markets.
Dr. Brian Richert - Alternative Feed Ingredients: Real Options or Just a Nice...John Blue
Alternative Feed Ingredients: Real Options or Just a Nice Idea? - Dr. Brian Richert, Associate Professor of Animal Sciences, Department of Animal Sciences, Purdue University, from the 2012 Minnesota Pork Congress, January 18-19, Minneapolis, MN, USA.
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1. IOWA STATE UNIVERSITY
Department of Animal Science
U.S. 2008 – 2013 Pork Industry
Productivity Analysis
J. Stock1, C. E. Abell1, C. Hostetler2, and K. J.
Stalder1
1Iowa State University, Ames, IA 50011-3150 and
National Pork Board, Des Moines, IA 50325
2014 Pork Academy
Des Moines, IA
June 4, 2014
2. IOWA STATE UNIVERSITY
Department of Animal Science
Data Description
Production data obtained from a large U.S.
data record keeping organization
Agreement with the National Pork Board to share limited
information.
Uses:
1. Quantify the annual production levels and variation
associated for several key productivity indicators
2. Establish industry benchmarks for all swine production
phases
Breeding herd
Nursery
Wean – to – finish
Conventional finishing
3. IOWA STATE UNIVERSITY
Department of Animal Science
Data Description
Production data obtained from a large U.S.
data record keeping organization
Agreement with the National Pork Board to share limited
information.
Uses:
3. Quantify seasonal affects associated with the key productivity
indicators
4. Identify research opportunities that would improve the U.S.
pork industry production efficiency
4. IOWA STATE UNIVERSITY
Department of Animal Science
Data description
Statistical process
Industry Trends
Raw means and standard deviations were used
Seasonality evaluation
Linear model was used
Fixed effects
Company
Month
Year
Covariates – for nursery, grow-finish, and wean-to-finish
Start age
Start days
Days in facility
Covariates – Sow farm
Weaning age
5. IOWA STATE UNIVERSITY
Department of Animal Science
Data description cont’
Data (records) reported monthly for each
production phase
Nursery and finishing data –
Monthly averages are based on animals exiting the facility that
month
Sow farm data –
Monthly averages are based on litters weaned in that month
6. IOWA STATE UNIVERSITY
Department of Animal Science
Table 1. Number of companies and farms used in analysis for each facility type by year.a
Year Conventional
Finisher
Wean-to-
Finish
Nursery Sow
2008 Companies 46 23 41 39
Farms 1339 385 719 708
2009 Companies 49 20 41 40
Farms 1376 334 679 683
2010 Companies 43 19 36 33
Farms 1350 527 571 526
2011 Companies 44 21 35 33
Farms 1382 775 594 564
2012 Companies 50 28 45 40
Farms 1744 830 796 766
2013 Companies 44 26 41 45
Farms 1561 886 616 774
aMore than one farm can be managed by the same company. A farm represents a single production site.
7. IOWA STATE UNIVERSITY
Department of Animal Science
Company / farm summary
Increase in the number of companies and
farms represented
Tremendous increase in the data volume evaluated
Results in improved information and interpretations that
can be made
Companies becoming much more data driven
in their decision making process
8. IOWA STATE UNIVERSITY
Department of Animal Science
Company / farm summary
Grow-finish and wean-to-finish becoming farms
becoming more like their sow farm counterparts
Farm level decisions much more data driven
Continue greater use of data when guiding
company decision process regarding:
Employee
Financial
Health
Nutritional
Genetic
Some combination
9. IOWA STATE UNIVERSITY
Department of Animal Science
Benchmarking - Why do it?
Compare with other businesses
Within species
Across species
Compare herd performance
Within company
Within country
Etc.
Set goals for improving herd
For a specific trait or several traits
11. IOWA STATE UNIVERSITY
Department of Animal Science
Key Productivity Indicator Averages
Means and standard deviations across all
farms and operations.
Sow, nursery, wean-to-finish, and conventional grow-
finish data
Developed to examine yearly trends across the
U.S. Swine industry.
Operations can compare one or a number of
KPIs to see if they are above or below average
12. IOWA STATE UNIVERSITY
Department of Animal Science
Table 2. Conventional finisher average (±standard deviation) productivity from 2008 to 2013a
2008 2009 2010 2011 2012 2013
Percent
Mortality 6.29 (±4.60) 5.12 (±3.44) 4.70 (±3.05) 4.48 (±2.49) 5.03 (±3.30) 5.04 (±3.07)
Finishing
Weight (lbs) 261.2 (±16.1) 265.0 (±14.9) 268.7 (±13.4) 271.5 (±12.8) 269.2 (±14.1) 272.1 (±17.2)
Days in Finisher 125.7 (±11.0) 124.3 (±11.4) 124.6 (±10.3) 122.7 (±9.7) 121.5 (±10.8) 122.8 (±13.0)
Average Daily
Gain (lbs) 1.69 (±0.16) 1.75 (±0.15) 1.76 (±0.14) 1.81 (±0.14) 1.81 (±0.15) 1.81 (±0.16)
Feed
Conversionb
2.82 (0.32) 2.76 (±0.27) 2.77 (±0.25) 2.71 (±0.24) 2.68 (±0.23) 2.66 (±0.23)
a
All farms were given equal weighting.
b
Feed conversion is defined as feed to gain.
13. IOWA STATE UNIVERSITY
Department of Animal Science
Table 3. Wean-to-finish average (±standard deviation) productivity from 2008 to 2013a
2008 2009 2010 2011 2012 2013
Percent
Mortality 7.92 (±4.91) 7.61 (±4.79) 6.30 (±3.55) 6.33 (±3.96) 6.39 (±4.79) 6.88 (±4.66)
Finishing
Weight (lbs) 261.7 (±12.5) 264.2 (±11.0) 270.5 (±13.5) 273.6 (±12.8) 270.1 (±12.9) 274.0 (±14.5)
Days in Finisher 162.5 (±11.4) 164.2 (±10.7) 167.9 (±10.3) 166.4 (±9.0) 164.3 (±9.9) 165.3 (±10.4)
Average Daily
Gain (lbs) 1.54 (±0.13) 1.54 (±0.11) 1.54 (±0.11) 1.57 (±0.10) 1.57 (±0.11) 1.58 (±0.11)
Feed
Conversionb
2.51 (±0.17) 2.54 (±0.18) 2.52 (±0.20) 2.50 (±0.20) 2.50 (±0.18) 2.50 (±0.18)
a
All farms were given equal weighting.
b
Feed conversion is defined as feed to gain.
14. IOWA STATE UNIVERSITY
Department of Animal Science
Table 4. Nursery average (±standard deviation) productivity from 2008 to 2013a
2008 2009 2010 2011 2012 2013
Percent
Mortality 5.82 (±5.71) 4.68 (±4.41) 4.12 (±3.62) 4.32 (±4.32) 3.80 (±3.01) 3.87 (±3.38)
Exit
Weight 49.0 (±9.2) 49.4 (±8.4) 50.7 (±9.1) 50.3 (±9.3) 50.7 (±8.4) 50.9 (±8.7)
Days in Nursery 47.4 (±6.8) 46.2 (±5.4) 46.2 (±5.5) 46.0 (±6.1) 46.0 (±5.1) 45.4 (±5.7)
Average Daily
Gain (lbs) 0.78 (±0.14) 0.80 (±0.13) 0.82 (±0.14) 0.81 (±0.14) 0.82 (±0.13) 0.83 (±0.13)
Feed
Conversionb
1.54 (±0.30) 1.53 (±0.29) 1.52 (±0.28) 1.53 (±0.25) 1.48 (±0.19) 1.48 (±0.18)
a
All farms were given equal weighting.
b
Feed conversion is defined as feed to gain.
15. IOWA STATE UNIVERSITY
Department of Animal Science
Table 5. Sow farm average (±standard deviation) productivity from 2008 to 2013a
2008 2009 2010 2011 2012 2013
Pigs/Mated
Sow/Year 22.8 (±2.9) 23.2 (±3.0) 23.5 (±2.7) 24.1 (±3.1) 23.9 (±2.9) 23.7 (±4.3)
Litters/Mated
Sow/Year 2.35 (±0.23) 2.34 (±0.21) 2.33 (±0.20) 2.33 (±0.22) 2.31 (±0.22) 2.30 (±0.26)
Total Born 12.5 (±0.9) 12.8 (±0.9) 13.0 (±1.0) 13.4 (±1.1) 13.4 (±1.0) 13.6 (±1.1)
Stillborn and
Mummies 1.23 (±0.49) 1.20 (±0.46) 1.22 (±0.48) 1.24 (±0.49) 1.17 (±0.46) 1.14 (±0.42)
Number Born
Alive 11.3 (±0.8) 11.6 (±0.9) 11.8 (±0.9) 12.1 (±1.0) 12.3 (±0.9) 12.4 (±1.0)
Number Weaned 9.7 (±0.7) 9.9 (±0.8) 10.0 (±0.7) 10.2 (±0.7) 10.3 (±0.7) 10.2 (±1.3)
Pre-weaning
Mortality % 14.2 (±5.5) 14.5 (±5.6) 14.6 (±5.8) 15.5 (±5.9) 15.5 (±5.7) 17.3 (±10.9)
Weaning Weight
(lbs) 12.4 (±1.3) 12.8 (±1.5) 13.0 (±1.4) 13.1 (±1.4) 13.2 (±1.6) 13.4 (±1.7)
Weaning Age
(d) 19.7 (±1.8) 20.5 (±2.0) 20.8 (±2.1) 20.9 (±2.5) 21.5 (±2.8) 21.9 (±2.9)
a
All farms were given equal weighting.
16. IOWA STATE UNIVERSITY
Department of Animal Science
Overall data summary
Finishing mortality has declined over time
Across all data conventional finishing mortality was
similar in 2012 and 2013
Wean –to- finish mortality increased slightly in the
same time period - initial effects of PED??
Market weight continues to increase
Increased by 4 pounds in both conventional finishing
269.2 lbs. (2012) and 272.1 (2013) and wean – to -
finish summaries 270.1 lbs. (2012) to 274.0 lbs. (2013).
Days in the finisher has remained relatively
constant over last 3 to 4 years
17. IOWA STATE UNIVERSITY
Department of Animal Science
Overall data summary cont’
Nursery performance has change little across
the reporting time period
Pigs/mated sow/ year has increased by almost
2 pigs from 2008 to 2013.
Pigs/mated sow/ year was essentially the same
between 2012 and 2013.
No improvement since 2011
Why ?? First signs of PED??
Again, litters/mated sow/year has changed
little during the time period
18. IOWA STATE UNIVERSITY
Department of Animal Science
Overall data summary cont’
Percent pre-weaning mortality has increased.
Increased in 2013 to 17.3% from 15.5% in 2012
Early signs of PED??
Represents lost opportunity
Easy to improve??
Weaning age has increased by 2 days from
2008 to 2013.
19.7 days in 2008 to 21.9 days in 2013
Weaning weight has increased by 2 lb.
19. IOWA STATE UNIVERSITY
Department of Animal Science
Table descriptions
Tables 6-9 and 14-17 have the average and
standard deviation for each key productivity
indicator by top 10% and bottom 25% of farms
in each production stage, respectively.
Farms in each percentile were determined for
each KPI
Farms in each percentile were not the same for each
production indicator
The top and bottom were defined as desirable or
undesirable for each trait (rather than higher or
lower)
21. IOWA STATE UNIVERSITY
Department of Animal Science
Top 10% summary
Separate out to understand performance levels
attained by the very best operations for each
KPI.
Demonstrates at least what potential is
Top 10% farms pigs/mated sow/ year was 28.5
Where are the 30 PSY herds
Demonstrates how difficult it is to achieve and sustain
the outstanding performance for any of the KPIs
Recognize that top performance can contribute
to reduced trait variation
22. IOWA STATE UNIVERSITY
Department of Animal Science
Top 10% summary
Performance is what sets producers / operations
apart
Reduced variation can also be important
Caution – by definition variation (standard deviation) should be
smaller when the overall group is divided into
subgroups.
– variation or standard deviation more comparable when
comparing two subclasses with each other.
23. IOWA STATE UNIVERSITY
Department of Animal Science
Table 6. Conventional finisher average (±standard deviation) productivity from 2008 to 2013 for farms in
the top 10% for each production indicatora
2008 2009 2010 2011 2012 2013
Percent
Mortality 1.90 (±0.56) 1.50 (±0.46) 1.44 (±0.42) 1.37 (±0.41) 1.62 (±0.44) 1.62 (±0.50)
Finishing
Weight (lbs) 291.3 (±10.2) 292.8 (±8.8) 291.3 (±6.9) 293.9 (±7.8) 292.7 (±11.4) 300.1 (±15.4)
Days in Finisher 106.0 (±5.5) 105.0 (±5.5) 106.8 (±5.0) 105.0 (±5.2) 103.5 (±5.7) 103.0 (±6.2)
Average Daily
Gain (lbs) 1.95 (±0.08) 2.00 (±0.09) 2.00 (±0.07) 2.05 (±0.09) 2.05 (±0.07) 2.10 (±0.11)
Feed
Conversionb
2.34 (±0.14) 2.35 (±0.13) 2.39 (±0.10) 2.38 (±0.08) 2.35 (±0.08) 2.34 (±0.09)
a
All farms were given equal weighting.
b
Feed conversion is defined as feed to gain.
24. IOWA STATE UNIVERSITY
Department of Animal Science
Table 7. Wean-to-finish average (±standard deviation) productivity from 2008 to 2013 for farms in the
top 10% for each production indicatora
2008 2009 2010 2011 2012 2013
Percent
Mortality 2.80 (±0.67) 2.54 (±0.65) 2.28 (±0.58) 2.34 (±0.44) 1.94 (±0.51) 2.19 (±0.61)
Finishing
Weight (lbs) 282.2 (±6.7) 282.2 (±4.7) 294.1 (±4.8) 295.5 (±3.5) 293.3 (±4.5) 297.2 (±5.5)
Days in Finisher 144.6 (±6.1) 146.8 (±6.6) 149.0 (±5.8) 152.1 (±2.9) 147.5 (±5.4) 148.7 (±8.1)
Average Daily
Gain (lbs) 1.75 (±0.05) 1.73 (±0.08) 1.74 (±0.06) 1.74 (±0.04) 1.76 (±0.06) 1.77 (±0.07)
Feed
Conversionb
2.23 (±0.12) 2.24 (±0.09) 2.23 (±0.05) 2.19 (±0.05) 2.21 (±0.04) 2.22 (±0.08)
a
All farms were given equal weighting.
b
Feed conversion is defined as feed to gain.
25. IOWA STATE UNIVERSITY
Department of Animal Science
Table 8. Nursery average (±standard deviation) productivity from 2008 to 2013 for farms in the top 10%
for each production indicatora
2008 2009 2010 2011 2012 2013
Percent
Mortality 1.06 (±0.36) 0.93 (±0.31) 0.95 (±0.34) 0.91 (±0.31) 0.94 (±0.28) 0.84 (±0.29)
Exit
Weight 68.7 (±8.5) 66.1 (±7.4) 68.5 (±9.1) 69.0 (±9.4) 65.8 (±4.2) 66.1 (±5.9)
Days in Nursery 36.6 (±3.9) 37.3 (±3.4) 38.3 (±3.9) 35.8 (±4.2) 36.3 (±3.3) 34.8 (±3.9)
Average Daily
Gain (lbs) 1.05 (±0.11) 1.05 (±0.08) 1.09 (±0.09) 1.08 (±0.11) 1.04 (±0.06) 1.07 (±0.09)
Feed
Conversionb
1.07 (±0.19) 1.11 (±0.18) 1.08 (±0.21) 1.16 (±0.15) 1.16 (±0.16) 1.18 (±0.16)
a
All farms were given equal weighting.
b
Feed conversion is defined as feed to gain.
26. IOWA STATE UNIVERSITY
Department of Animal Science
Table 9. Sow farm average (±standard deviation) productivity from 2008 to 2013 for farms in the top
10% for each production indicatora
2008 2009 2010 2011 2012 2013
Pigs/Mated
Sow/Year 27.5 (±1.4) 27.6 (±1.2) 27.7 (±1.2) 29.2 (±3.1) 28.5 (±2.0) 29.5 (±3.9)
Litters/Sow/Year 2.71 (±0.14) 2.67 (±0.13) 2.64 (±0.14) 2.69 (±0.17) 2.65 (±0.11) 2.74 (±0.24)
Total Born 14.1 (±0.7) 14.2 (±0.4) 14.7 (±0.5) 15.3 (±0.6) 15.1 (±0.4) 15.3 (±0.9)
Stillborn and
Mummies 0.59 (±0.14) 0.60 (±0.12) 0.62 (±0.10) 0.61 (±0.11) 0.55 (±0.13) 0.50 (±0.14)
Number Born
Alive 12.6 (±0.3) 12.9 (±0.4) 13.3 (±0.5) 13.9 (±0.6) 13.8 (±0.4) 14.0 (±0.8)
Number Weaned 10.9 (±0.3) 11.0 (±0.3) 11.2 (±0.4) 11.4 (±0.3) 11.5 (±0.3) 11.7 (±0.3)
Pre-weaning
Mortality % 5.2 (±3.4) 5.8 (±2.9) 4.6 (±4.3) 5.8 (±2.2) 5.6 (±3.5) 5.4 (±2.9)
Weaning Weight
(lbs) 14.9 (±1.5) 15.7 (±0.9) 15.5 (±1.1) 15.5 (±0.7) 16.2 (±0.8) 16.7 (±0.9)
Weaning Age
(d) 22.9 (±1.3) 24.7 (±1.3) 24.9 (±1.1) 25.4 (±1.4) 27.0 (±1.6) 27.8 (±1.8)
a
All farms were given equal weighting.
27. IOWA STATE UNIVERSITY
Department of Animal Science
Top 10% summary
Separate out to understand performance levels
attained by the very best operations for each
KPI.
Demonstrates at least what potential is
Recognize that top performance can contribute
to reduced trait variation
28. IOWA STATE UNIVERSITY
Department of Animal Science
Top 10% summary
Represents above average performance for
each KPI.
Does not describe the relationship with other
KPIs and ability to maintain all at top 10%.
Can use this to establish goals for certain KPIs
Be sure that when setting goals they are attainable and
are achievable in a reasonable time frame.
Realistic if you are in the bottom 25% to expect top 10%
performance within 6 months of establish new goals
Goals that are set too high are not seen as incentives by barn
workers
29. IOWA STATE UNIVERSITY
Department of Animal Science
Top 10% Summary cont’
Highlights
Conventional market weight tops 300lbs for top 10% for
the first time in 2013
Same value for wean-to-finish was 297 in 2013
Days to market, ADG, and Feed Conversion essentially
unchanged from 2008 through 2013 in conventional and
wean-to-finishing operations
Nursery performance KPIs similar from 2012-2013
Pigs per mated female per year reached 29.5 in the top
10% in 2013
Pre-weaning mortality remains just above 5% for 2013
31. IOWA STATE UNIVERSITY
Department of Animal Science
Comparison of Top 10% vs Bottom 25%
Conventional Finishing
Huge difference in mortality Top 10% < 2% vs Bottom 25% >10%
average across 6 years
Bottom 25% moving in right direction in recent years
Below 9% 3 most recent years
Bottom 25% sell at much light weight than Top 10%
Bottom 25% 254.2 vs Top 10% 298.7
Net 46 lb. difference at 0.84$/lb. live results in 38.64 for every pig
marketed in additional gross income
Bottom 25% have more days in the finisher than the Top 10%
Bottom 25% = 140 vs. Top 10% = 103
Indicates the bottom 25% growing slower 1.56 vs. 2.00 lbs.
Top 10% has much better feed conversion when compared to the
bottom 25%.
Top 10% 2.37 vs. Bottom 25% 3.08
32. IOWA STATE UNIVERSITY
Department of Animal Science
Comparison of Top 10% vs. Bottom 25%
Wean-to-Finish Finishing
Early years data may be biased due to small sample number
Huge difference in mortality Top 10% 2.5% vs. Bottom 25% >12%
average across 6 years
Finishing weight Top 10% 288 lbs. vs. Bottom 25% 251 lbs.
Bottom 25% averaged over 3 week more days in the finisher
Top 10% 147.1 vs. Bottom 25% 177.5
Consequently ADG differed between the groups
Bottom 25% 1.62 vs. Top 10% at 2.10
Top 10% feed conversion was 2.34 while the bottom 25% was 2.98
33. IOWA STATE UNIVERSITY
Department of Animal Science
Comparison of Top 10% vs. Bottom 25%
Nursery
Again substantial mortality differences
Top 10% less than 1% (0.84) Bottom 25% 7.90 %
Top 10% nursery exit weight 66.1 lbs. while the Bottom 25%
was 39.9 lbs.
Days in the Nursery Top 10% 34.8 vs. Bottom 25% 51.7
Nursery Average Daily Gain Top 10% 1.07 lbs. /d vs. Bottom
25% 0.67 lbs./d
Feed conversion Top 10% 1.18 vs. Bottom 25% 1.69
34. IOWA STATE UNIVERSITY
Department of Animal Science
Comparison of Top 10% vs Bottom 25%
Sow Farm
Trait Top 10% Bottom 25% Diff.
Pigs/Mated Sow/ Year 29.5 18.7 10.8
Litters/Mated Sow/ Year 2.74 2.00 0.74
Total born 15.3 12.1 3.2
Still born and mummies 0.50 1.67 1.17
Number born alive 14.0 11.2 1.8
Number weaned 11.7 8.8 2.9
Pre-weaning mortality 5.4 29.1 23.7
Weaning weight 16.7 11.5 5.2
Weaning age 27.8 18.6 9.2
35. IOWA STATE UNIVERSITY
Department of Animal Science
Comparison of Top 10% vs. Bottom 25%
Important to examine variation (standard
deviations) between groups
Mortality variation always lower for better performing
herds
May be near biological minimum and have less room to improve
Other traits where variation is greater among poorer
performing herds
Nursery, Grow-Finish & Wean-to-Finish
Feed conversion
Sow farm
Still born and mummies
Number weaned
Both traits correlated with each other
36. IOWA STATE UNIVERSITY
Department of Animal Science
Comparison of Top 10% vs. Bottom 25%
Important to examine variation (standard
deviations) between groups
Other traits where variation is greater among better
performing herds
Sow farm
Weaning weight
Weaning age
Both traits correlated with each other
37. IOWA STATE UNIVERSITY
Department of Animal Science
Additional information available
Plots of averages
Top 25%
Average
Bottom 25%
Examine rate of change over time across relative
productivity levels
Seasonality estimates
Monthly averages across time using a more sophisticated
statistical model
Seasonality estimates tables – sets one month to average
0 and compares other months relative to the average
month
Seasonality summary