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Estimating Hydrogen Cyanide in Forage Sorghum (Sorghum bicolor) by Near-Infrared Spectroscopy

Overview of attention for article published in Journal of Agricultural & Food Chemistry, June 2012
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Title
Estimating Hydrogen Cyanide in Forage Sorghum (Sorghum bicolor) by Near-Infrared Spectroscopy
Published in
Journal of Agricultural & Food Chemistry, June 2012
DOI 10.1021/jf205030b
Pubmed ID
Authors

Glen P. Fox, Natalie H. O’Donnell, Peter N. Stewart, Roslyn M. Gleadow

Abstract

Hydrogen cyanide (HCN) is a toxic chemical that can potentially cause mild to severe reactions in animals when grazing forage sorghum. Developing technologies to monitor the level of HCN in the growing crop would benefit graziers, so that they can move cattle into paddocks with acceptable levels of HCN. In this study, we developed near-infrared spectroscopy (NIRS) calibrations to estimate HCN in forage sorghum and hay. The full spectral NIRS range (400-2498 nm) was used as well as specific spectral ranges within the full spectral range, i.e., visible (400-750 nm), shortwave (800-1100 nm) and near-infrared (NIR) (1100-2498 nm). Using the full spectrum approach and partial least-squares (PLS), the calibration produced a coefficient of determination (R(2)) = 0.838 and standard error of cross-validation (SECV) = 0.040%, while the validation set had a R(2) = 0.824 with a low standard error of prediction (SEP = 0.047%). When using a multiple linear regression (MLR) approach, the best model (NIR spectra) produced a R(2) = 0.847 and standard error of calibration (SEC) = 0.050% and a R(2) = 0.829 and SEP = 0.057% for the validation set. The MLR models built from these spectral regions all used nine wavelengths. Two specific wavelengths 2034 and 2458 nm were of interest, with the former associated with C═O carbonyl stretch and the latter associated with C-N-C stretching. The most accurate PLS and MLR models produced a ratio of standard error of prediction to standard deviation of 3.4 and 3.0, respectively, suggesting that the calibrations could be used for screening breeding material. The results indicated that it should be feasible to develop calibrations using PLS or MLR models for a number of users, including breeding programs to screen for genotypes with low HCN, as well as graziers to monitor crop status to help with grazing efficiency.

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Mendeley readers

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The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Unknown 54 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 18%
Student > Master 10 18%
Student > Doctoral Student 8 14%
Student > Ph. D. Student 8 14%
Student > Bachelor 4 7%
Other 6 11%
Unknown 10 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 54%
Environmental Science 4 7%
Chemistry 3 5%
Biochemistry, Genetics and Molecular Biology 2 4%
Medicine and Dentistry 2 4%
Other 4 7%
Unknown 11 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 May 2012.
All research outputs
#20,657,128
of 25,377,790 outputs
Outputs from Journal of Agricultural & Food Chemistry
#15,571
of 19,056 outputs
Outputs of similar age
#141,676
of 181,000 outputs
Outputs of similar age from Journal of Agricultural & Food Chemistry
#107
of 128 outputs
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So far Altmetric has tracked 19,056 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
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We're also able to compare this research output to 128 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.