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This article in CS

  1. Vol. 30 No. 1, p. 202-207
     
    Received: Dec 7, 1988
    Published: Jan, 1990


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doi:10.2135/cropsci1990.0011183X003000010044x

Prediction of Botanical Composition Using NIRS Calibrations Developed from Botanically Pure Samples

  1. S. W. Coleman ,
  2. S. Christiansen and
  3. J. S. Shenk
  1. U SDA-ARS, Forrage and Livestock Res. Lab., P.O. Box 1199, El Reno, OK 73036
    M IAC, B. P. 290, Settat, Morroco, P.O. Box 1199, El Reno, OK 73036
    D ep. of Agronomy, Pennsylvania State Univ., University Park, PA 16802

Abstract

Abstract

Point quadrat, hand separation, and histological methods for determining botanical composition are tedious, time consuming, and expensive. Near-infrared reflectance spectroscopy (NIRS) was used as a rapid method to predict botanical composition of grass-legume mixtures clipped from field plots. Our objective was to determine if a group of samples, each consisting of one of three botanical components, could be used for calibration in lieu of samples containing mixtures of the components. Calibration equations were developed for NIRS prediction of a number of legumes, Caucasian bluestem [(Bothriochloa caucasica (Trin.) C.E. Hubb.], and cheatgrass (Bromus tectorum L.). Hand separations of clipped mixtures were used to validate the calibration equations. All forage samples were grown in silty soils of the Dale series. Some evidence existed for an interaction between light scatter and mixing of two pure species, but it was eliminated effectively by second derivative transformation of the spectra. Biases existed for all components (36-61 g/kg) but were smaller than standard errors of performance (52-104 g/kg), except for legumes. Linearity was excellent for prediction for percentage legume, and validation was more precise for legume than for Caucasian bluestem or cheatgrass. This method of calibration for a closed population is recommended. Care must be taken to validate equations using mixed samples to insure linearity of unknowns between the extremes. Further, unknowns should be scanned along with calibration samples so that the same day to day instrument variation is associated with both sample sets.

Contribution of the USDA-ARS in cooperation with The Pennsylvania State Univ., University Park, PA 16802.

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Copyright © 1990. Crop Science Society of America, Inc.Copyright © 1990 by the Crop Science Society of America, Inc.