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Innehåll tillhandahållet av PIPESTONE. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av PIPESTONE eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.
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Episode #58: Using Research and Production Data to Drive Genetics

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Manage episode 406132518 series 3143451
Innehåll tillhandahållet av PIPESTONE. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av PIPESTONE eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

Join Dr. Spencer Wayne on the latest episode of SwineTime, where he dives deep into swine genetics with experts Erin Little, Pipestone Research, and Carrie Pollard, Pipestone Business.

In this engaging discussion, Erin and Carrie discuss how PIPESTONE is unlocking valuable insights into swine genetics for producers using both research and production data.

With over 4 million pigs' worth of production data at their fingertips through the FarmStats program, Carrie reveals the power of records analysis in driving informed decision-making for pork producers. From mortality rates to feed conversions, learn how this wealth of information transforms how we understand and optimize genetic lines in the swine industry.

Erin shares the journey from data to action, where findings from cutting-edge research initiatives are transformed into actionable insights for pork producers. By simulating real-world conditions within commercial barns, they can observe how different genetic lines perform in various environments and management practices. This level of scrutiny allows researchers to identify patterns, trends, and areas of improvement, ultimately driving advancements in swine genetics and production practices.

The trio underscores PIPESTONE's dedication to research and data collection, aiming to equip producers with the knowledge and tools needed to navigate the dynamic landscape of pork production.

  continue reading

62 episoder

Artwork
iconDela
 
Manage episode 406132518 series 3143451
Innehåll tillhandahållet av PIPESTONE. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av PIPESTONE eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

Join Dr. Spencer Wayne on the latest episode of SwineTime, where he dives deep into swine genetics with experts Erin Little, Pipestone Research, and Carrie Pollard, Pipestone Business.

In this engaging discussion, Erin and Carrie discuss how PIPESTONE is unlocking valuable insights into swine genetics for producers using both research and production data.

With over 4 million pigs' worth of production data at their fingertips through the FarmStats program, Carrie reveals the power of records analysis in driving informed decision-making for pork producers. From mortality rates to feed conversions, learn how this wealth of information transforms how we understand and optimize genetic lines in the swine industry.

Erin shares the journey from data to action, where findings from cutting-edge research initiatives are transformed into actionable insights for pork producers. By simulating real-world conditions within commercial barns, they can observe how different genetic lines perform in various environments and management practices. This level of scrutiny allows researchers to identify patterns, trends, and areas of improvement, ultimately driving advancements in swine genetics and production practices.

The trio underscores PIPESTONE's dedication to research and data collection, aiming to equip producers with the knowledge and tools needed to navigate the dynamic landscape of pork production.

  continue reading

62 episoder

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