An income over feed cost nutritional grouping strategy

Abstract

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.

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

“…For example, in the peak multiparous groups, pen 8 has the lowest, pen 9 has intermediate, and pen 10 has the highest milk yield (Table 4), which results in low, medium, and high MP and NE L predicted requirements, respectively. Different nutrient allocations for 3 nutritional groups are consistent with results previously reported by Kalantari et al (2016) and Wu et al (2019).…”

“…The improvement of dietary nutrition accuracy may generate economic benefits from the potential increase in milk yield (Kalscheur et al, 1999;Maltz et al, 2013;Kalantari et al, 2016) and savings from a decrease in diet costs (Cabrera and Kalantari, 2016;Wu et al, 2019). In this research, we did not predict potential milk yield improvement from the NG strategy.…”

“…Nutritional grouping (NG) management can improve the nutritional accuracy of diets, reduce nutrient losses, and increase income over feed costs (IOFC) in dairy farms (Cabrera et al, 2012;Kalantari et al, 2016;Wu et al, 2019). Available on-farm data streams, computer and feeding systems, and existing farm grouping (FG) protocols offer an opportunity to facilitate the implementation of NG.…”

“…Better nutritional accuracy of NG would also reduce overall feed costs (Kalscheur et al, 1999;VandeHaar et al, 2016) and increase IOFC (Kalantari et al, 2016;Wu et al, 2019). Multiple NG simulation analyses have shown productive and economic benefits when lactating cows are grouped according to their nutritional requirements (St-Pierre and Thraen, 1999;Allen, 2009;Bach, 2014;Kalantari et al, 2016).…”

Performance and Usability of Smartglasses for Augmented Reality in Precision Livestock Farming Operations

“…Historical knowledge and individual productivity are fundamental for flock grouping [27], especially for feeding strategies [28,29] and genetic improvement programs [30], which consist of identifying and grouping animals with predetermined characteristics (mainly milk yield and prolificacy). Moreover, these programs require a considerable amount of human, animal and material resources [31,32].…”