Technical note: A novel approach to estimate dry matter intake of lactating dairy cows through multiple on-cow accelerometers

Abstract

The objective of this study was to evaluate the feasibility of using multiple 3-dimensional accelerometers to estimated individual dry matter intake (DMI) of lactating dairy cows. Twenty-four Holstein cows in late lactation were assigned into 2 groups, a calibration group (n = 12) and a validation group (n = 12). All cows were fitted with 3 sensors that recorded 3-dimensional acceleration (i.e., x, y, and z) at 10-s intervals, 1 on the lateral side of the left hind leg and 2 attached directly to a halter over the nose and jaw area on the left side. Then, 3 accelerations were generated from each accelerometer (e.g., Leg-X, Leg-Y, and Leg-Z). Six new variables were created based on the change in acceleration in the nose and jaw accelerometers between 2 consecutive time points (e.g., LagJaw-X). For both groups (i.e., calibration and validation), cows were continuously video recorded while data on acceleration and intake of total mixed ration were collected for 10 consecutive days. Cows were fed once daily using an individual gate system, and individual refusals were recorded next day before morning feeding. Cows were fed a common lactating cow diet (17.9% crude protein; 1.70 Mcal/kg of dry matter). In the calibration group, individual eating bouts were obtained based on video recordings and merged with the corresponding accelerometer data. Then, a stepwise regression analysis was conducted using the REG procedure of SAS (SAS Institute, Cary, NC) to determine the ranges in acceleration that accounted for the highest variation in DMI (highest R 2 ) in each acceleration variable. All 32,767 potential acceleration combinations were tested in the validation group using the acceleration ranges predetermined in the calibration group. The CORR procedure of SAS was used to test the Pearson correlation coefficient (r) between the type of DMI [i.e., based on accelerations (DMI accel ) or actual DMI (DMI actual )]. The MIXED procedure of SAS was used to perform a repeated-measures analysis with type (DMI accel vs. DMI actual ), day, and their interaction (T × D) in the model. From this analysis, 8 candidate acceleration models were selected based on high r and similarity (P > 0.15) in terms of T and T × D between DMI accel and DMI actual . A simulated effect on DMI actual was artificially created in the validation group by dividing this group (n = 12) into high and low intake cows (n = 6/group; DMI of 24.1 vs. 18.7 kg/d), and the candidate models were tested to determine whether they were sensitive enough to detect this effect. From these candidate models, AEN (Leg-X + Jaw-Z + LagJaw-Z) showed a weak correlation (r = 0.36) between DMI accel and DMI actual , but DMI accel and DMI actual were highly similar (21.2 vs. 21.4 kg/d of DMI). In addition, this was the only model that could detect the simulated effect on DMI actual (22.1 vs. 20.3 kg/d of DMI) in the validation group. The fact that the simulated effect on DMI actual was detected based only on accelerations is highly significant, and models such as AEN could be substantial...

Predicting Daily Dry Matter Intake Using Feed Intake of First Two Hours after Feeding in Mid and Late Lactation Dairy Cows with Fed Ration Three Times Per Day

“…The REG procedure is a simple and general-purpose procedure for both unary and multiple regression analysis [16]. When only a few of independent variables are introduced in the model, and, at the same time, these independent variables are all continuous variables and have significant linear relationships with the dependent variables, REG is suitable and widely used for regression analysis [17][18][19]. Finally, the model to predict DMI was developed using the PROC REG procedure in the SAS software.…”

Evaluation of ruminal motility using an indwelling 3-axis accelerometer in the reticulum in cattle

“…In addition, attempts were also made to use a minimized bolus-type wireless sensor node with a built-in three-axis accelerometer [17]. The three-axis acceleration sensor (3XA) has been variously used in cattle for the purpose of acquiring the biological information of an individual [4,6,19,23]. It has been used in various ways, such as to measure the amount of exercise by attaching it to the ear or ankle [24], to detect lameness [18], and so on.…”

Real-Time Behavioral Recognition in Dairy Cows Based on Geomagnetism and Acceleration Information

“…The models all have the highest recognition rate of the lying behavior data collected by the accelerometer installed on the cow's leg, and the recognition rate of the SVM model is up to 99%. Carpinelli [33] collected the behavioral acceleration data of dairy cows and used SAS's REG program (SAS Institute, Cary, NC) to estimate the cow feed intake (DMI). DMIaccel and DMIactual are highly similar (21.2 vs. 21.4 kg/d DMI).…”