Search Results

You are looking at 21 - 30 of 1,189 items for :

  • "data analysis" x
Clear All
Free access

W.A. Dozier Jr., R. Rodriguez-Kabana, A.W. Caylor, D.G. Himelrick, N.R. McDaniel and J.A. McGuire

Research Data Analysis. Alabama Agricultural Experiment Station Journal Series no. 11-902552P. The cost of publishing this paper was defrayed in part by the payment of page charges. Under postal regulations, this paper therefore must be hereby

Full access

Kimberly R. Hilgers, Cynthia Haynes and William R. Graves

guarantee or warrantee of the product and does not imply its approval to the exclusion of other products or vendors that also may be suitable. We gratefully acknowledge J.A. Schrader for his assistance with data analysis.

Free access

Stanislav V. Magnitskiy, Claudio C. Pasian, Mark A. Bennett and James D. Metzger

plants, Dr. Kari Green-Church and Mrs. Nan Kleinholz at the Chemical Instrumentation Center, The Ohio State University, for help with mass spectrometry analysis of paclobutrazol residue in plant samples, and Mr. Bert Bishop for assistance in data analysis.

Free access

Wei Qiang Yang and Barbara L. Goulart

We thank Yildiz H. Akin and Marvin L. Risius, for their advice on data analysis; James F. Hancock and Pete Callow, for their generous supply of tissue-cultured clonal blue-berry shoots; and Kathleen Demchak, for her technical assistance. The

Free access

Shumin Li, Nihal C. Rajapakse and Roy E. Young

16802-1909. Technical contribution No. 4790 of the South Carolina Agricultural Experiment Station, Clemson Univ. We thank J.R. Rieck for his advice in experimental design and data analysis.

Free access

Teresa A. Cerny, James E. Faust, Desmond R. Layne and Nihal C. Rajapakse

, Inc. Tokyo, Japan are gratefully acknowledged for the financial support. We thank James Reick of the Department of Experimental Statistics at Clemson University for helping with the data analysis and Sonja Maki of Department of Horticulture for her

Free access

Sonja L. Maki, Sriyani Rajapakse, Robert E. Ballard and Nihal C. Rajapakse

design and data analysis.

Free access

Walter W. Stroup, Stacy A. Adams and Ellen T. Paparozzi

An experiment was performed to investigate the effect of various nitrogen sulfer combinations on the quality of poinsettias. After various physiological measurements were taken, commercial growers, retailers, and consumers were asked to evaluate the salability of the plants. In order to avoid evaluator fatigue, only a limited number of plants could be evaluated. This presented both experimental design and data analysis problems. In view of these constraints, and in order to obtain meaningful results, an unreplicated 7 x 8 factorial design was used. Data were analyzed using the method of half-normal plots in conjunction with a modification of the analysis of variance procedure. Rationale and alternative designs will be presented, as well as the step-by-step procedure for using this method as contrasted with the standard ANOVA technique.

Free access

J.H. van den Berg, M.W. Bonierbale, E.E. Ewing, R.L. Plaisted and S.D. Tanksley

Tuberization and stolonization of cuttings were used as a model system to assess response to photoperiod in segregating potato progenies. The progenies were from backcrosses of a diploid hybrid between Solanum tuberosum and the short day requiring S. berthaultii to both parent species. Restriction Fragment Length Polymorphism (RFLP) analyses had been performed on these progenies as a part of other investigations. The RFLP maps were used to identify the loci controlling the photoperiod responses characterized by the cuttings. In the S. berthaultii backcross population, one locus appeared to control the response of cuttings only under long photoperiods, and coincided with a locus detected for stolonization on whole plants; a second locus was effective for tuberization under short photoperiods but was not detected with certainty under long photoperiods. Data analysis for the second backcross population is currently underway.

Free access

F. D. Moore III and E. E. Roos

An index “internal slope” derived from the cumulative frequency distribution of individual seed leachate conductivities is related to seed quality; the larger the index value the less variation among individual seeds in a sample (100 seeds) and the higher the seed quality. We have recently developed data acquisition/instrurment control/data smoothing/data analysis software which accesses frequency and cumulative frequency distributions of individual seed conductivities and the derived index on an almost continuous basis from the start of the first soaking.

At present, lack of convergence with regard to curve fitting may occur necessitating multiple sampling times. A “window in time” approach is described whereby index estimates during a two-hour interval within the index stability phase are averaged. Evidence of the method's ability to assess seed vigor will be presented.