Observation of ingestive and rumination behaviors of dairy cows may assist in detecting diseases, controlling reproductive status, and estimating intake. However, direct observation of cows on pasture is time consuming and can be difficult to realize. Consequently, different systems have been developed to automatically record behavioral characteristics; among them is the RumiWatch System (RWS; Itin and Hoch GmbH, Liestal, Switzerland). Until now, the RWS has not been thoroughly validated under grazing conditions. The aim of the current study was to validate the RWS, against direct observation, in measuring ingestive and rumination behaviors of dairy cows during grazing and supplementation in the barn. A further objective was to examine whether it is possible to refine the algorithm used by the evaluation software RumiWatch Converter 0.7.3.2 to improve the accuracy of the RWS. The data were collected from an experiment carried out with 18 lactating Holstein cows in a crossover block design including 3 treatments and 3 measuring periods. All cows grazed night and day, 19 h/d, and were either unsupplemented or supplemented, with chopped whole-plant corn silage, or chopped whole-plant corn silage mixed with a protein concentrate. During the measuring periods, cows were equipped with the RumiWatch Halter, and their ingestive and rumination behaviors were recorded concurrently by the RumiWatch Halter and by direct observation (690 × 10 min). Comparison of concurrently measured data shows that the RWS detected jaw movements reliably, but classification errors occurred. A low relative prediction error of ≤0.10 for the number of rumination boluses, rumination chews, and total eating chews was found. A high relative prediction error of >0.10 was found for the number of prehension bites and time spent in prehension and eating. Both converter versions performed equally well in differentiating ingestive and rumination behaviors when cows were supplemented in the barn or when grazing and supplementation activities were combined. For grazing cows, with no supplementation, more reliable results for the total number of eating chews, rumination chews, prehension bites, and time spent in these activities were obtained, by using the RumiWatch Converter 0.7.3.11. In light of these findings, further research is warranted to improve the accuracy of the RWS and to allow a differentiation between mastication chews and prehension bites while eating.
Information about the individual herbage DMI (HDMI) of grazing dairy cows is important for an efficient use of pasture herbage as an animal feed with a range of benefits. Estimating HDMI, with its multifaceted influencing variables, is difficult but may be attempted using animal, performance, behavior, and feed variables. In our study, 2 types of approaches were explored: 1 for HDMI estimation under a global approach (GA), where all variables measured in the 4 underlying experiments were used for model development, and 1 for HDMI estimation in an approach without information about the amount of supplements fed in the barn (WSB). The accuracy of these models was assessed. The underlying data set was developed from 4 experiments with 52 GA and 50 WSB variables and one hundred thirty 7-d measurements. The experiments differed in pasture size, herbage allowance, pregrazing herbage mass, supplements fed in the barn, and sward composition. In all the experiments, cow behavioral characteristics were recorded using the RumiWatch system (Itin and Hoch GmbH, Liestal, Switzerland). Herbage intake was estimated by applying the n-alkane method. Finally, HDMI estimation models with a minimal relative prediction error of 11.1% for use under GA and 13.2% for use under WSB were developed. The variables retained for the GA model with the highest accuracy, determined through various selection steps, were herbage crude protein, chopped whole-plant corn silage intake in the barn, protein supplement or concentrate intake in the barn, body weight, milk yield, milk protein, milk lactose, lactation number, postgrazing herbage mass, and bite rate performed at pasture. Instead of the omitted amounts of feed intake in the barn and, due to the statistical procedure for model reduction, the unconsidered variables postgrazing herbage mass and bite rate performed at pasture, the WSB model with the highest accuracy retained additional variables. The additional variables were total eating chews performed at pasture and in the barn, total eating time performed at pasture, number of total prehension bites, number of prehension bites performed at pasture, and herbage ash concentration. Even though behavioral characteristics alone did not allow a sufficiently accurate individual HDMI estimation, their inclusion under WSB improved estimation accuracy and represented the most valid variables for the HDMI estimation under WSB. Under GA, the inclusion of behavioral characteristics in the HDMI estimation models did not reduce the root mean squared prediction error. Finally, further adaptation, as well as validation on a more comprehensive data set and the inclusion of variables excluded in this study such as body condition score or gestation, should be considered in the development of HDMI estimation models.
Knowledge about individual daily herbage dry matter (DM) intake (DMI) helps identifying efficient dairy cows and adapting supplementation better to herbage intake and nutrient requirements of grazing dairy cows. With the aid of behavioural characteristics, raw data recorded with the RumiWatch (RW) system and processed with the RW converter 0.7.3.31 (C31), estimation of herbage DMI may be possible. First, C31, which allows differentiation of prehension bites and mastication chews, was validated through direct observation of behavioural characteristics and compared to the previous RW converter 0.7.3.11 (C11). Further, the influence of a low and high pre‐grazing herbage mass (HM), with the same target herbage allowance (HA), on bite mass, DMI, number of prehension bites, and milk production was investigated. In total, 24 lactating Holstein cows were pairwise allotted to one of two HM treatments. The cows received a new pasture paddock twice per day with a daily target HA of 22 kg DM per cow/day. On average, low HM (LHM) and high HM (HHM) paddocks had an HM of 589 and 2288 kg DM/ha, respectively, above 6.7 click units (1 CU = 0.5 cm). Overall, LHM cows produced 2.7 kg/day more milk and 2.5 kg/day more energy‐corrected milk, had the same herbage DMI and a similar prehension bite mass. The averaged bite mass per week was 0.49 g DM/bite (LHM) or 0.47 g DM/bite (HHM), respectively. A longer eating time (617 vs. 559 min/day) and a shorter rumination time (297 vs. 365 min/day) were observed for the LHM cows compared with the HHM cows. The validation of the RW showed similar results for C11 and C31 apart from prehension bites, where C31 showed a mean absolute deviation of 12.4%. Pre‐grazing HM had no effect on relevant behavioural characteristics for prospective intake estimation, namely, bite mass and number of prehension bites.
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