| |
| Web URL(s): | https://scisoc.confex.com/scisoc/2022am/meetingapp.cgi/Paper/142150
Last checked: 01/24/2023
Requires: JavaScript; HTML5 |
|---|
| Publication Type:
| Report |
|---|
| Content Type: | Abstract or Summary only |
|---|
| Author(s): | Linde, Douglas;
Hannah, Brendan;
Mitchell, Andrew |
|---|
| Author Affiliation: | Linde: Presenting Author and Delaware Valley University; Hannan and Mitchell: New Zealand Sports Turf Institute |
|---|
| Title: | Lessons learned from conducting golf course benchmarking studies |
|---|
| Section: | Golf turf management oral: cultural practices, physiology, and water (includes student competition)
Other records with the "Golf turf management oral: cultural practices, physiology, and water (includes student competition)" Section
C05 turfgrass science
Other records with the "C05 turfgrass science" Section
|
|---|
| Meeting Info.: | Baltimore, Maryland: November 6-9, 2022 |
|---|
| Source: | ASA, CSSA, SSSA International Annual Meeting. 2022, p. 142150. |
|---|
| Publishing Information: | [Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America] |
|---|
| # of Pages: | 1 |
|---|
| Abstract/Contents: | "Benchmarking golf course conditions and agronomic practices across multiple golf courses has various benefits along with challenges. Understanding the nature of a benchmarking study can help scientists in conducting their own study along with interpreting the results. Three golf course benchmarking studies were conducted between 2004 and 2021. Two were conducted across 50 courses in New Zealand and one across 74 courses in Eastern Pennsylvania. Each study involved the same scientist visiting a cross section of courses to collect performance, agronomic, and quality data such as green firmness, speed, trueness, % organic matter, soil moisture, grass species, topdressing rate, N rate, turf uniformity and tee levelness. Data from these one-time course visits were compiled for each study to find trends based on budget, grass species, and soil type. Superintendents and consultants can use the data to help assess how a course compares to those with similar budgets. Common challenges included high variability, quality control in sampling and data collection, scheduling, time, travel, and lack of a statistical design. Sources of variability included time of year and time of day, rainfall or irrigation before the visit, recent usage, recent cultural practices (topdressing, coring, mowing, rolling), sampling and testing errors, age of area, grass species, and soil type and condition. The high variability often led to lower correlations and R2 values than expected, especially for variables that can widely vary during the season such as firmness, soil moisture, trueness, and uniformity. Therefore, when interpreting data for a benchmarking study, its important to focus on general trends and obvious patterns. Benefits of these benchmarking studies were that they provided a more scientific and objective approach to assess industry trends, provided better quality information to help make decisions, and gave direct interaction between scientists and superintendents." |
|---|
| Language: | English |
|---|
| References: | 0 |
|---|
| Note: | "44-2"
This item is an abstract only! |
|---|
| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Linde, D., B. Hannan, and A. Mitchell. 2022. Lessons learned from conducting golf course benchmarking studies. Agron. Abr. p. 142150. |
| Fastlink to access this record outside TGIF: https://tic.msu.edu/tgif/flink?recno=324863 |
| If there are problems with this record, send us feedback about record 324863. |
| Choices for finding the above item: |
|---|
| Web URL(s):
https://scisoc.confex.com/scisoc/2022am/meetingapp.cgi/Paper/142150
Last checked: 01/24/2023
Requires: JavaScript; HTML5 |
| Request through your local library's inter-library loan service (bring or send a copy of this TGIF record) |
