Estimating hydrogen cyanide in forage sorghum (Sorghum bicolor) by near-infrared spectroscopy

Glen P Fox, Natalie O'Donnell, Peter N Stewart, Roslyn M Gleadow

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12 Citations (Scopus)

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 (MRS) 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.
Original languageEnglish
Pages (from-to)6183 - 6187
Number of pages5
JournalJournal of Agricultural and Food Chemistry
Volume60
Issue number24
DOIs
Publication statusPublished - 2012

Cite this

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title = "Estimating hydrogen cyanide in forage sorghum (Sorghum bicolor) by near-infrared spectroscopy",
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 (MRS) 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.",
author = "Fox, {Glen P} and Natalie O'Donnell and Stewart, {Peter N} and Gleadow, {Roslyn M}",
year = "2012",
doi = "10.1021/jf205030b",
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volume = "60",
pages = "6183 -- 6187",
journal = "Journal of Agricultural and Food Chemistry",
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Estimating hydrogen cyanide in forage sorghum (Sorghum bicolor) by near-infrared spectroscopy. / Fox, Glen P; O'Donnell, Natalie; Stewart, Peter N; Gleadow, Roslyn M.

In: Journal of Agricultural and Food Chemistry, Vol. 60, No. 24, 2012, p. 6183 - 6187.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Estimating hydrogen cyanide in forage sorghum (Sorghum bicolor) by near-infrared spectroscopy

AU - Fox, Glen P

AU - O'Donnell, Natalie

AU - Stewart, Peter N

AU - Gleadow, Roslyn M

PY - 2012

Y1 - 2012

N2 - 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 (MRS) 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.

AB - 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 (MRS) 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.

UR - http://pubs.acs.org/doi/pdf/10.1021/jf205030b

U2 - 10.1021/jf205030b

DO - 10.1021/jf205030b

M3 - Article

VL - 60

SP - 6183

EP - 6187

JO - Journal of Agricultural and Food Chemistry

JF - Journal of Agricultural and Food Chemistry

SN - 0021-8561

IS - 24

ER -