CASE STUDY: Effect of pen change on milk yield by dairy cows in 2 commercial herds

Self Cite

This study introduces a new nutritional grouping method, OptiGroup, which maximizes milk income over feed cost (IOFC) using a mixed-integer nonlinear programming optimization algorithm. Analyses compared the OptiGroup with the cluster method, the current state-of-the-art nutritional grouping technique. Analyses were performed using cow-level data from 7 Wisconsin dairy farms. Consistently, the OptiGroup and the cluster were constrained to group cows simultaneously into 2 (low and high nutrient requirements) and 3 (low, medium, and high nutrient requirements) samesize groups. Each diet satisfied the net energy (NE L ) and crude protein (CP) requirements of approximately 83% of the cows in each group by using lead factors based on nutrient density. A control treatment (1-group scenario) was used as a baseline for comparisons. The IOFC, dietary nutrient densities (NE L and CP), and dry matter intake with both methods were computed and compared. The percentage of cows grouped differently and the percentages of primiparous cows and late-lactation (>200 d in milk) cows in each group were also analyzed. Results were as follows: (1) average extra IOFC of $8/cow per yr (2-group) and $12/cow per yr (3-group) by switching from cluster to OptiGroup method; (2) difference between dietary nutrient densities of the groups were reduced under OptiGroup method compared with cluster (i.e., NE L differences in 2 groups were 0.20 Mcal/kg for the cluster vs. 0.11 Mcal/kg for OptiGroup); (3) dry matter intake decreased with increasing group numbers within a grouping method, and decreased from cluster to OptiGroup method with constant group numbers; (4) percentage of primiparous cows was greater in the low group of cluster and in the high group of OptiGroup; and (5) proportion of late-lactation cows tended to be greater in the low group in both grouping strategies. Results indicated that the OptiGroup performed economically better than the cluster because of nutrient savings, even with high feed cost conditions. This study offers a new nutritional grouping paradigm, which could improve herd management on dairy farms. However, animal trials are needed to validate this new nutritional grouping method under farm conditions.

Section: Limitations Of Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

An income over feed cost nutritional grouping strategy

Liang

Shaver

et al. 2019

Self Cite

“…This suggests that feed intake and milk produc-tion might not decrease as groups become larger. In a recent study, Zwald and Shaver (2012) compared daily milk yield per cow in 2 commercial dairy farms when providing the same diet to midlactation cows that were moved to a new group and cows that were not moved to a new group. Moving cows to a different group did not affect milk yield in either farm and no negative social effect of moving cows was observed between groups.…”

Section: Constraints To Feeding More Diets To Lactating Cowsmentioning

confidence: 99%

“…Managing multiple-diet groups across lactation has the potential to improve productivity, efficiency, and feed cost savings to dairy producers (Williams and Oltenacu, 1992;Allen, 2009;Zwald and Shaver, 2012). Based on the cluster method (McGilliard et al, 1983), Cabrera et al (2012) developed and tested an online tool, "Grouping strategies for feeding lactating dairy cows" (http://dairymgt.uwex.edu/tools.php), to group cows based on nutrient requirements and income over feed cost.…”

Section: Introductionmentioning

confidence: 99%

Constraints for nutritional grouping in Wisconsin and Michigan dairy farms

Contreras‐Govea

Cabrera

Armentano

et al. 2015

Self Cite

A survey was conducted in Wisconsin (WI) and Michigan (MI) to quantify the proportion of farms that use a single diet for all lactating cows and to better understand the reasons for current grouping strategies and the limitations to grouping for better nutritional management. A questionnaire was mailed to all WI dairy farmers with ≥200 lactating cows (971 farms) and to a random sample of grade-A MI dairy farmers (800 farms) of varying herd sizes. The survey return rate was 20% in WI (196 farms) and 26% in MI (211 farms; 59 of them had ≥200 lactating cows). Feeding 2 or more different diets to lactating cows was predominant: 63% in WI (124 farms, all ≥200 lactating cows), 76% in MI farms with ≥200 lactating cows (45 farms), and 28% in MI farms with <200 lactating cows (43 farms). Farmers feeding more than 1 diet used 1 or more of the following criteria for grouping lactating cows: stage of lactation, milk production, or body condition score. Overall for both states, 52% of the farms (211 from 407 farms) feeding more than 1 diet grouped cows according to their nutritional needs. However, a notable population of farms fed the same diet to all lactating cows: 37% in WI (72 farms), 24% in MI (14 farms) for herds of ≥200 lactating cows, and 72% in MI for herds of <200 lactating cows (109 MI farms). "Desire to keep it simple" and "milk drops when cows are moved to a different group" were identified as main constraints to having more groups within a farm for nutritional purposes. Farm facilities and labor were also limiting factors to grouping in farms with herd sizes of <200 lactating cows.

“…One concern of dairy farmers with increasing the movement of cows across groups is the potential decrease in milk yield after moving (Contreras-Govea et al, 2015). Nevertheless, Zwald and Shaver (2012) reported that increasing the number of cows' movements among groups does not decrease significantly milk yield if group sizes are larger than 100 cows.…”

Section: Grouping Cowsmentioning

confidence: 99%

Improving nutritional accuracy and economics through a multiple ration-grouping strategy

Barrientos-Blanco

White

Shaver

et al. 2020

The objective of this study was to develop a model application to systematize nutritional grouping (NG) management in commercial dairy farms. The model has 4 sub-sections: (1) real-time data stream integration, (2) calculation of nutritional parameters, (3) grouping algorithm, and (4) output reports. A simulation study on a commercial Wisconsin dairy farm was used to evaluate our NG model. On this dairy farm, lactating cows (n = 2,374 ± 185) are regrouped weekly in 14 pens according to their parity and lactation stage, for which 9 diets are provided. Diets are seldom reformulated and nutritional requirements are not factored to allocate cows to pens. The same 14 pens were used to simulate the implementation of NG using our model, closely following the current farm criteria but also including predicted nutritional requirements (net energy for lactation and metabolizable protein; NE L and MP) and milk yield in an attempt to generate more homogeneous groups of cows for improved diet accuracy. The goal of the simulation study was to implement a continuous weekly system for cows' pen allocation and diet formulation. The predicted MP and NE L requirements from the NG were used to formulate the diets using commercial diet formulation software and the same feed ingredients, feed prices, and other criteria as the current farm diets. Diet MP and NE L densities were adjusted to the nutritional group requirements. Results from the simulation study indicated that the NG model facilitates the implementation of an NG strategy and improves diet accuracy. The theoretical diet cost and predicted nitrogen supply with NG decreased for lownutritional-requirement groups and increased for highnutritional-requirement groups compared with current farm groups. The overall average N supply in diets for NG management was 15.14 g/cow per day less than the current farm grouping management. The average diet