|Clark d h,|
|Johnson d a,|
|Kephart k d,|
|Jackson n a,|
Submitted to: Journal of Range Management
Publication Type: Peer reviewed journal
Publication Acceptance Date: 7/9/1994
Publication Date: N/A
Citation: Interpretive Summary: Stable isotopes of carbon are beneficial in evaluating the physiology of plants. Carbon isotope composition is usually analyzed with an isotope ratioing mass spectrometer. Near infrared reflectance spectroscopy (NIRS) was used to estimate carbon isotope composition in alfalfa and various cool-season perennial grasses. Results from our study indicate that NIRS estimation of carbon isotope discrimination were generally quite low and are only slightly higher than results obtained with an isotope ratioing mass spectrometer. In the early stages of a breeding program where the number of samples and costs prohibit analyses by mass spectrometry, this level of predictability may be acceptable. At more advanced phases of a breeding program, however, where there may be few samples and accurate analysis is required, this 80% accuracy level we obtained may not be acceptable. The NIRS method requires less time for analysis, costs less to purchase or maintain, and does not require technicians with considerable training and expertise in chemistry. As a result, for some applications, NIRS may be a suitable alternative to determining carbon isotope discrimination.
Technical Abstract: Stable isotopes of carbon are beneficial in evaluating the physiology of plants. This study determined whether near infrared reflectance spectroscopy could be used to estimate carbon isotope composition in alfalfa and various cool-season perennial grasses. Ground samples were analyzed for stable carbon isotope composition with a dual-inlet, double collector gas isotope mass spectrometer, and values of carbon isotope discrimination were calculated. Subsamples were scanned with a monochromator that collected spectra from 400 to 2,500 nm or a monochromator that collected spectra from 1,100 to 2,500 nm, and values of carbon isotope discrimination were regressed with absorption data. Standard errors of calibration were higher for grasses than for alfalfa. The coefficients of variation for all sample sets were less than 3%. Of the 5 sample sets used for validation, near infrared reflectance correctly identified 77 to 82% of the samples that actually had the lowest carbon isotope discrimination values as determined by mass spectrometer analysis. This level of predictability may be acceptable for identifying breeding lines with high water-use efficiency during the early phases of plant improvement programs.