Masters Theses

Date of Award

8-2023

Degree Type

Thesis

Degree Name

Master of Science

Major

Animal Science

Major Professor

Elizabeth A. Eckelkamp

Committee Members

Elizabeth A. Eckelkamp, Yang Zhao, Charles Martinez

Abstract

Fetch cows, dairy cattle that do not voluntarily enter automated milking systems (AMS), increase labor costs, and decrease efficiency. The objective of this study was to describe fetch cows based on fetch lists and herd-management software data. This study was conducted on a commercial dairy farm (n = 510 cows) using 8 AMS from October 1, 2021, to May 10, 2022. Data were collected via PCDART, DairyComp, and a proprietary interface. Two fetch categories by cow, EverFetch (EF) and NeverFetch (NF), and three status groups by cow by day, True Fetch (on fetch list and fetched; TF), False Fetch (on fetch list and not fetched; FF), and No Fetch Required (not on list; NFR), were created. The impact of health events (no event, reproduction, general health, and scheduled events), parity (1, 2, 3, and 4+ lactations) and AMS variables (milk visit outcome, production, and components; feed intake, etc.) on fetch category and status were analyzed using the GLIMMIX procedure of SAS 9.4 (P ≤ 0.05). The sections were evenly divided by fresh or in-training (≤ 25 days in milk (DIM)) and lactation (> 25 DIM). The lactating group was divided into three sections (early, mid, and late lactation) based on total cow-day observation quartiles. The sections were ≤ 25 DIM (fresh), > 25 and ≤ 86 DIM (early lactation), > 86 and < 214 DIM (mid-lactation), and ≥ 214 DIM (late-lactation).

Decision support tools have provided end-users with options for decision-making under different scenarios. The objective of this decision tool was for Southeastern USA producers considering an automatic milking system to input their information and determine AMS investment impact. Data were sourced from sixty-two farm observations across Tennessee, Kentucky, and North Carolina through the University of Tennessee Dairy Gauge Program (2021 and 2022). Median data across years included farm incomes and expenses. Investment in AMS was modeled to determine net present value (NPV), internal rate of return (IRR), and payback period (PP). Across all scenarios, retrofitting was the most profitable construction style. Future research is needed to test the models and find benchmarks for determining fetch cow status and economic.

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