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Balchem — Technical Presentation (November 2024)

22 slides from Balchem's technical presentation, November 2024

  1. Slide 1: In a tier pricing system: Managing for both milk fat and protein

    10/4/22 In a tier pricing system: Managing for both milk fat and protein Kevin Harvatine, Ph.D. Professor of Nutritional Physiology Penn State University kjh182@psu.edu 1 Thoughts on adapting in ”Historic” times - Most quotas/limits and trucking are based on pounds of milk - There is extra value to

  2. Slide 2: Milk fat and protein yield are the main drivers of cash flow on dairy farms

    10/4/22 Milk fat and protein yield are the main drivers of cash flow on dairy farms ($/hd/d @85 lb of 3.9 fat & 3.1 protein) Fat $16 Does not 5 year average: Protein $14 include PPD! Fat = $2.25/lb Milk Value, $/hd/d Other solids $12 Prot = $2.48/lb Other Solids = $0.22/lb $10 $8 $6 $4 $2 Harvatine

  3. Slide 3: The mammary gland is a milk synthesis factory with three assembly lines

    10/4/22 The mammary gland is a milk synthesis “factory” with three assembly lines: Fat, Protein, and Lactose - There is coordinated regulation of these three assembly lines …….. and also some differential regulation - You are paid for pounds of each component, but a change in percent can give you an

  4. Slide 4: How are the Assembly Lines regulated?

    10/4/22 How are the “Assembly Lines” regulated? - We have to make the “machines” (Enzymes) for the assembly line - Turn-up expression of the genes - Translate the mRNA into protein - We have to turn all the “machines” on high - Make sure the “machines” have enough substrate to keep them going The “f

  5. Slide 5: Large variation between herds in milk components

    10/4/22 There is large variation between herds in both milk components, but more in fat than protein Milk Fat, % Milk Protein, % 7 4 6 3.5 5 3 4 2.5 3 2 2 1.5 Stdev = 0.34 10th = 3.5 Stdev = 0.15 10th = 2.9 90th = 4.3 90th = 3.3 (64,895 test days from 5926 herds) Harvatine unpublished from DRMS Data

  6. Slide 6: Even larger variation in milk fat between cows within a herd

    18EA1-5 database cleaned HO onl - Distribution of Fat%, FatPEBV Page 1 of 10 10/4/22 Distributions There is even larger variation in milk fat between Fat% cows within a herd 6.5 6 5.5 Milk fat, % 5 4.5 90th = 4.8% 4 10th = 2.7% 3.5 3 2.5 2 1.5 1720 cows from 5 herds - Differences between cows likely

  7. Slide 7: Milk yield has little effect on protein and fat concentration at herd level

    10/4/22 DRMS_2018Aug_PTAs - Fit Y by X of AVGFP, AVGPP by Milk Yield, lb DRMS_2018Aug_PTAs Page - Fit Y by X of AVGFP, 1 of 2 by Milk Yield, lb AVGPP Page 2 of 2 But, milk yield has little effect on protein and Fit Groupfat concentration Fit at the herd level Bivariate Group Fit of AVGFP By Milk Yie

  8. Slide 8: Do not forget about milk flow

    10/4/22 Take home: “Do not forget about milk flow” You can’t give up much yield when seeking to increase milk fat or protein 3.8 3.6-3.8 Fat Yield, lb 3.6 3.4-3.6 3.4 3.2-3.4 3.2 3 3-3.2 2.8 2.8-3 2.6 2.6-2.8 2.4 4 2.4-2.6 2.2 3.75 70 72 74 ,% 76 78 80 3.5 2.2-2.4 82 84 86 Protein+Fat Yield Fat 88 9

  9. Slide 9: What can we do to increase milk yield and fat and protein yield?

    10/4/22 What can we do to increase milk yield and fat and protein yield? All the things good farms do right! - Cow Comfort/barn design - Optimal calving intervals (herd DIM) - Genetics - Herd health - Transition cow program - Photoperiod management - Forage quality and energy intake - Good silage ma

  10. Slide 10: Sire genetic potential and milk fat and protein percent

    anging from !0.02 to 0.07. in the highest quartile of PROPCT PTA had an overall rized into quartiles to facilitate data analysis and inter- average FATPCT of milk during the first 10 months of tage of sires in different FATPCT or PROPCT average of 3.13% milk protein and cows in the lowest pretation.

  11. Slide 11: Little difference in genetic potential for milk protein between herds

    10/4/22 There is also little difference in genetic potential for milk protein between herds 3.15 PTA Milk Protein, % PTA Milk Protein, lb 0 3.1 3.05 -50 3 -100 2.95 90th = 12 lb 90th = 3.077% 75th = 7 lb 75th = 3.069% 25th = -8 lb 25th = 3.052% 10th = -18 lb 10th = 3.044% 18EA1-5=database [(PTAF +cl

  12. Slide 12: Milk fat concentration linearly increasing in all milk markets but FL

    10/4/22 Milk fat concentration linearly increasing in all milk markets but FL 4.10 12 Month Running Average Milk Fat Northeast FL 4.00 Percent of MIlk 3.90 3.80 3.70 3.60 3.50 12/2002 10/2003 12/2007 10/2008 12/2012 10/2013 12/2017 10/2018 6/2000 4/2001 2/2002 8/2004 6/2005 4/2006 2/2007 8/2009 6/20

  13. Slide 13: Is diet-induced milk fat depression not a problem anymore?

    10/4/22 I have been told “diet-induced MFD is not a problem anymore”! Is this true? - Risk factors have decreased? - Maybe we all listened to Dr. Jenkins and it is solved? - We have selected for cows more resistant to MFD? - We are missing diet-induced MFD because we have not adequately adjusted to

  14. Slide 14: Genetic potential for milk protein has been increasing in Holsteins

    10/4/22 Genetic potential for milk protein % and yield has also been increasing in Holsteins 3.30% 3.25% 3.20% From Center for Dairy Milk Protein, % 3.15% Cattle Breeding 3.10% 3.05% 3.00% 2.95% 1000 2.90% 900 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 2014 2018 Milk Protein Yield, lb 80

  15. Slide 15: How do we feed for more milk protein?

    10/4/22 How do we feed for more milk protein? 1. Make sure adequate AA are being absorbed (essential AA!!) - Healthy rumen - Amino acid balancing 2. Turn on milk protein synthesis in the mammary gland - “Energy signals” - Hormones…….Insulin/IGF1 mechanism - Number of potential mechanisms (mTOR) - In

  16. Slide 16: Maximizing rumen microbial protein yield should always be the first goal

    10/4/22 Maximizing rumen microbial protein yield should always be the first goal! We get: - Optimal amino acid supply - Normal biohydrogenation (no milk fat depression) - Optimal acetate yield for milk fat synthesis - Optimal energy intake - Drives milk flow - Drives milk protein synthesis - Probabl

  17. Slide 17: Interaction of casein and insulin on milk protein was replicated

    10/4/22 The interaction of casein and insulin on milk protein was replicated INSULIN, AMINO ACIDS, AND MILK PROTEIN 1517 +Insulin Casein 10% m or e la ct ose (+0.13 kg/d; P < 0 .0 1 ) t h a n t h e Wa t er t r ea t m en t (Ta ble 3 ). F or bot h in su lin cla m p t r ea t m en t s, t h e en h a n ce

  18. Slide 18: Long-acting insulin also increased milk protein in high producing cows

    10/4/22 Long-acting insulin also increased milk protein in high producing cows P-Values CON INS-A INS-B Trt INS-A INS-B Prot % 3.00 3.20 3.29 0.04 0.001 <0.001 0.2 Prot yield, kg 1.46 1.40 1.54 0.08 0.08 0.06 0.22 Winkelman et al. 2013 35 What is going to impact the “energy” signals important to mil

  19. Slide 19: Nutrition and Management is an Experiment in Progress

    10/4/22 Nutrition and Management is often best practiced as an “Experiment in Progress”!! First- - Accurately and precisely set your goals! • Account for seasonal effects • Is the sample a daily average? • What is the genetic potential of the herd? • Is the problem across all cows or just the high g

  20. Slide 20: Maximizing milk fat yield and milk protein yield

    10/4/22 Maximizing milk fat yield Cont. 2. Good acetate yield – Fiber digestibility – Rumen function 3. Optimal fat supply – Total fat – Fatty acid profile 39 Maximizing milk protein yield - Are we meeting AA requirements? - Microbial protein - AA balancing - Are we optimizing energy? – Careful sinc

  21. Slide 21: Monitor milk yield and milk fat and protein percent over time

    10/4/22 Monitor milk yield and milk fat and protein percent over time!!! 41 Let’s review Rumen environment is critical to milk fat and protein yield and involves interactions of numerous dietary, cow, and environmental factors - Focus on fat and protein pounds! - Smaller genetic differences between

  22. Slide 22: Thank You

    10/4/22 Lab Members: Cesar Matamoros, Beckie Bomberger, Alanna Staffin, Abiel Berhane, Sarah Bennett, Yusuf Adeniji, Muhammad Husnain, Muhammad Arif Previous Lab Members: Dr. Ahmed Elzennary. Reilly Pierce, Dr. Rachel Walker, Dr. Chengmin Li, Elle Andreen, Dr. Isaac Salfer, Dr. Daniel Rico, Dr. Mich

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