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Webinar summary: Practical examples – Using milk data to drive production and repro – Part 2

Part 2 continues the focus on using milk component data to guide feeding decisions on pasture-based New Zealand farms. It revisits how to read fat, protein, lactose and milk urea in context, then moves into farm case studies showing how changes in pasture quality, in-shed feeding and heat load show up in both milk data and wearable sensor data, and what to do next.

In this webinar:

1. What was covered in Part 1 and what this session adds

• Component percentages need to be read alongside kg of milk solids per cow, so you do not get fooled by dilution when volume shifts.
• Protein percentage remains the main ‘centre point’ for recommendations, with fat, lactose and milk urea used to confirm what is going on.
• Lactose is coming into view more for farmers, and the session explains how to use it once available.

2. Rumen and liver: two levers, one outcome

• Fat percentage is used as a read on rumen stability and fibre breakdown.
• Protein is influenced by what the rumen releases and what the liver can process, so it captures more than one “bottleneck”.

3. Practical tools to lift milk fat

• When pasture quality drops and energy density falls away, fat can drop at the same time as volume drops, pointing to a rumen population that has lost capacity.
• Pasture control (mowing, topping, bringing pre-graze down) was shown as a practical lever to steady the system.

4. Practical tools to lift milk protein and lactose

• A Canterbury example showed protein limitation when canola meal was used early, with improvement after switching to soy and adding a small methionine inclusion.
• The session reinforces watching totals (kg) and comparisons, not only percentages, as days in milk change and volumes shift.

5. Milk urea: read the cause, not the number

• High milk urea (mid-30s up to 40) can come from more than “too much protein”: nitrogen supply, microbial capture, high non-protein nitrogen, metabolic shifts and heat load were all covered.
• A herbage test was recommended to separate crude protein from non-protein nitrogen before deciding on the response.
• In some situations, balancing peptides and amino acids (including targeted methionine) may be part of the fix.

6. Research links to reproduction (light touch)

• The session referenced research linking appetite post-calving, lower negative energy balance and reproductive outcomes.

7. Farm case studies: spring quality loss and clawing it back

• A Southland example showed the rapid shift from short grass to pasture “going to seed”, with production tailing off as quality was lost.
• Control measures (mowing, topping, lowering pre-graze) were linked with recovery in the data.
• Wearable data (Halter) was used alongside milk data, showing changes in rumination and grazing as residuals rose.

8. In-shed feeding failures, lactose drops and heat stress signals

• In-shed feeding failures were shown to crash protein, with lactose dropping alongside volume.
• One example tracked lactose moving from 5.85 to 4.99 after an in-shed failure, with a measurable production hit even when percentage shifts looked “small”.
• Heat stress examples showed milk urea rising and collar “heavy breathing” lifting, with the breathing response lagging heat by 24–48 hours (THI above 70 in the example shown).

For more details, watch the webinar or download the slide deck.