The process of milk yield in highly productive cows under robotic milking conditions
Bibliographic record
Abstract
Scientific research was conducted at the Tere- zinе Agricultural Enterprise in the Bila Tserkva dis trict of the Kyiv region, where Ukraine’s first dairy farm with 500 cows and robotic milking systems was established. This farm has new spatial planning and technological solutions for the premises, in particular, a width of 36 m and a height of 10.5 m. In this prem ises, 8 robotic milking systems from De Laval are located in the center. Given that such a farm was cre ated for the first time in Ukraine, it was appropriate to study the process of milking cows that come to be milked of their own free will. The article highlights the results of research on the process of milk yield in high-yielding cows under conditions of robotic milk ing depending on age, lactation period, productivity of cows, and an assessment of the quality of milk ob tained under these conditions. It was established that the rate of milk ejection in cows of different lactations depends on their pro ductivity and the period of lactation activity. It in creases with the age of the animals and is the lowest in primiparous cows and the highest in cows of the IV lactation. A similar situation is observed with the average and maximum rate of milk ejection. Studies have also shown that both the average and maximum rate of milk ejection in cows depend on the daily pro ductivity of the animals. At any productivity in cows of the second, third and fourth lactations, the average rate of milk ejection increases compared to the first by 3.4 % and 11.38 %, respectively. It has been es tablished that robotic milking technology ensures the full manifestation of the milk ejection reflex, since regardless of productivity and stage of lactation, the maximum intensity of milk yield in all groups of cows is observed in the first minute of milking. It has been found that the lactation activity of animals under conditions of “motivational milking” is characterized by a slightly longer duration. The highest mass frac tion of fat in milk was found in cows in their second lactation (4.25%), and the lowest (4.12%) in cows in their fourth lactation. The ratio of fat to protein mass is within the physiological norms for animals at 1.24 1.28 to 1.0. Key words: motivational milking, milk yield, milk quality, spatial planning and technological solutions for premises, robotic milking systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".