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

Abstract

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

Graduate Student Literature Review: Considerations for nutritional grouping in dairy farms

“…With this method, the group sizes are equal over time and allow the farm manager to use one or multiple nutritional requirements as grouping variables (McGilliard et al, 1983). Barrientos-Blanco et al (2020) used the same ranking-cluster method in a NG simulation study. However, the cows were first grouped according to their parity, stage of lactation (postpartum, early, peak, and late lactation), respective farm commercial conditions, and then grouped according to the NE L and MP requirements and milk yield.…”

“…When diets are formulated every week, returns over costs may increase by $25,000/yr for a 300-cow operation (White and Capper, 2014). Maltz et al (2013) Improvement in nutritional accuracy of diets can also be accomplished through cow grouping management (Kalantari et al, 2016;Bach et al, 2020;Barrientos-Blanco et al, 2020). This concept is known as nutritional grouping (NG) and consists of grouping cows with similar nutritional requirements and providing an adjusted diet to each group (Cabrera et al, 2012).…”

“…This concept is known as nutritional grouping (NG) and consists of grouping cows with similar nutritional requirements and providing an adjusted diet to each group (Cabrera et al, 2012). Nutritional grouping strategy facilitates improved allocation of nutrients due to decreased variance of nutritional requirements within each group (Cabrera et al, 2012;Kalantari et al, 2016;Wu et al, 2019;Barrientos-Blanco et al, 2020). As a result, dietary nutritional accuracy increases due to improving the match of diet to cow's nutritional requirements (Grant and Albright, 2001;Barrientos-Blanco et al, 2020).…”

“…Nutritional grouping strategy facilitates improved allocation of nutrients due to decreased variance of nutritional requirements within each group (Cabrera et al, 2012;Kalantari et al, 2016;Wu et al, 2019;Barrientos-Blanco et al, 2020). As a result, dietary nutritional accuracy increases due to improving the match of diet to cow's nutritional requirements (Grant and Albright, 2001;Barrientos-Blanco et al, 2020). The objective of this literature review was to better understand the mathematical tools used to simulate NG and the benefits of implementing NG in dairy farms.…”

Symposium review: Real-time continuous decision making using big data on dairy farms

“…An illustration that contrasts the NE L and MP requirements, DIM, milk yield, and diet costs, either using current FG strategy or our proposed NG strategy, is shown in Table 2. For example, the NG for peak-lactation animals shows more hierarchical distribution of DIM, NE L , and MP requirements and milk yield within groups than does the FG for peak-lactation animals (Table 2), which results in better nutrient allocation and therefore higher nutritional accuracy of the diets Barrientos et al, 2018;Bach, 2019). Better nutritional accuracy decreases the incidence of over-or underconditioned cows and increases milk productivity (Allen, 2009;Maltz et al, 2013;Kalantari et al, 2016).…”