Demographics, farm and reproductive management strategies used in Australian automatic milking systems compared with regionally proximal conventional milking systems. Issue 9 (September 2017)

• Record Type: Journal Article
• Authors: Keeper, DM; Kerrisk, KL; House, JK; Garcia, SC; Thomson, P
• Is Part Of: Australian veterinary journal. Volume 95:Issue 9(2017)
• Page Start: 325
• Page End: 332
• Publication Date: 2017-09
• Subjects: dairy innovation -- reproduction -- robotic milking; Veterinary medicine -- Australia -- Periodicals; Veterinary medicine -- Periodicals; Veterinary Medicine -- Periodicals; 636.089
• DOI: 10.1111/avj.12618
• Languages: English
• ISSNs: 0005-0423

Abstract

Abstract : Objective: To determine the management practices utilised in automatic milking systems (AMS) that affect reproductive management and performance and how these compare with the management practices used in regionally proximal conventional milking systems (CMS). Methods: This study examined demographic and management data from AMS and CMS dairy farms through a survey, with a specific focus on reproductive management procedures. Results: Overall, responses from AMS and CMS dairy farms showed little difference in terms of respondent demographics, farm size, herd structure and most farm management strategies. AMS dairies were more likely to use activity meters or other electronic oestrus detection aids than CMS dairies (P < 0.001) and were also more likely to have changed to electronic recording systems (P = 0.007). Although many respondents indicated that they used key monitoring parameters to assess reproductive performance (e.g. days in milk, conception vs pregnancy rate etc.), the format of responses varied significantly, indicating a relatively widespread (among the respondents) lack of knowledge regarding the meaning and usage of some of these common parameters/terminology. Conclusions: Ultimately, reproductive management practices of AMS dairies were largely similar to those of CMS dairies, indicating that such practices can be implemented in a practical sense, even though the resultant reproductive performance is not yet understood. Understanding that the key reproductive management strategies do not need to change vastly is important to ensure that new adoptees are well informed. Further work is needed to objectively measure AMS performance to increase the knowledge base and generate the confidence that will facilitate further adoption of this innovation.