Web URL(s): http://elibrary.asabe.org/azdez.asp?JID=3&AID=28474&CID=t1993&v=36&i=5&T=2&redirType= Last checked: 10/13/2015 Requires: PDF Reader
Publication Type:
i
Report
Author(s): Churchill, D. B. ;
Bilsland, D. M. ;
Cooper, T. M.
Author Affiliation: Project Leader, USDA-Agricultural Research Service, NFSPRC, OR; Senior Faculty Research Assistant, Oregon State Univ.; Senior Research Assistant, Bioresource Engineering Dept., Oregon State University
Title: Separation of mixed lots of tall fescue and ryegrass seed using machine vision
Source: Transactions of the American Society of Agricultural Engineers . Vol. 36, No. 5, September/October 1993, p. 1383-1386.
# of Pages: 4
Publishing Information: St. Joseph, MI
Keywords: TIC Keywords: Festuca arundinacea ; Lolium perenne ; Seed mixtures ; Seed harvesting ; Seeds
Abstract/Contents: "Samples from two mixed lots of tall fescue (Festuca arundinacea ) and ryegrass (Lolium perenne ) seed were hand separated and 10 physical properties of the individual seeds of both species were measured or calculated using a machine vision system (MVS). Data from measurements were subjected to logistic regression analysis, and models were created to distinguish the two species. A model created from the combined data from both lots characterized 83.13% of the tall fescue and 79.87% of the ryegrass. The combined regression model from both lots was then incorporated into a MVS algorithim, and previously unseparated quantities from each lot were separated based on the model. Using this procedure, an average of 83.87% of the tall fescue and 72.64% of the ryegrass seed were correctly classified. This procedure demonstrates potential for future automated MVS purity analysis and separation of mixtures of tall fescue and ryegrass and other difficult-to-separate seed lots."
Language: English
References: 16
Note: Figures Tables
ASA/CSSA/SSSA Citation (Crop Science -Like - may be incomplete ): Churchill, D. B., D. M. Bilsland, and T. M. Cooper. 1993. Separation of mixed lots of tall fescue and ryegrass seed using machine vision. Trans. Proc. Am. Soc. Agric. Eng. 36(5):p. 1383-1386.
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Web URL(s): http://elibrary.asabe.org/azdez.asp?JID=3&AID=28474&CID=t1993&v=36&i=5&T=2&redirType= Last checked: 10/13/2015 Requires: PDF Reader
MSU catalog number: S 671 .A452
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