Field testing a rapid method for estimating alfalfa quality

R. Mark Sulc, Kenneth A. Albrecht, Jerome H. Cherney, Marvin H. Hall, Shannon C. Mueller, Steve B. Orloff

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


Predictive equations for alfalfa quality (PEAQ) based on height of the tallest stem and maturity stage of the most mature stem in a sample were developed to estimate neutral-detergent fiber (NDF) and acid-detergent fiber (ADF) concentrations in alfalfa (Medicago sativa L.). Field testing of these equations is limited outside the state of Wisconsin where they were developed. Our objectives were to test these equations for estimating alfalfa NDF and ADF across a wide geographic area and to evaluate the performance of PEAQ on a whole-field basis by using within-field subsampling. Alfalfa samples varying in height and maturity were collected throughout the growing season from fields in New York (n = 28), Pennsylvania (n = 23), Ohio (n = 48), California (n = 45), and Wisconsin (n = 48) in 1994 to 1996. Additional samples were collected in Ohio and Wisconsin from producer-managed fields in which 5 to 10 subsamples per field were taken on each sampling date (n = 296 subsamples from 51 fields). Observed NDF and ADF values were regressed on estimated values. The accuracy of PEAQ in other states was at least equal to that observed in Wisconsin. Across all states, regression equations for NDF and ADF were slightly biased (b ≠ 1.0 and/or γ-intercept ≠ 0 at P < 0.01); however, prediction errors were sufficiently low to allow use of PEAQ as a preharvest management tool. Root mean square error values ranged from 19.1 to 23.9 g kg-1 for NDF and 15.0 to 19.0 g kg-1 for ADF. Prediction errors were 16.2 g kg-1 for NDF and 13.2 g kg-1 for ADF across Ohio and Wisconsin when regressing observed means on estimated means of five subsamples per field-sampling date combination. We conclude that predictive equations for alfalfa quality based on a combination of stem height and maturity were robust across a wide range of environments.

Original languageEnglish (US)
Pages (from-to)952-957
Number of pages6
JournalAgronomy Journal
Issue number6
StatePublished - 1997

All Science Journal Classification (ASJC) codes

  • Agronomy and Crop Science


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