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Non-Invasive Detection of Protein Content in Several Types of Plant Feed Materials Using a Hybrid Near Infrared Spectroscopy Model

View Article: PubMed Central - PubMed

ABSTRACT

Near-infrared spectroscopy combined with chemometrics was applied to construct a hybrid model for the non-invasive detection of protein content in different types of plant feed materials. In total, 829 samples of plant feed materials, which included corn distillers’ dried grains with solubles (DDGS), corn germ meal, corn gluten meal, distillers’ dried grains (DDG) and rapeseed meal, were collected from markets in China. Based on the different preprocessed spectral data, specific models for each type of plant feed material and a hybrid model for all the materials were built. Performances of specific model and hybrid model constructed with full spectrum (full spectrum model) and selected wavenumbers with VIP (variable importance in the projection) scores value bigger than 1.00 (VIP scores model) were also compared. The best spectral preprocessing method for this study was found to be the standard normal variate transformation combined with the first derivative. For both full spectrum and VIP scores model, the prediction performance of the hybrid model was slightly worse than those of the specific models but was nevertheless satisfactory. Moreover, the VIP scores model obtained generally better performances than corresponding full spectrum model. Wavenumbers around 4500 cm-1, 4664 cm-1 and 4836 cm-1 were found to be the key wavenumbers in modeling protein content in these plant feed materials. The values for the root mean square error of prediction (RMSEP) and the relative prediction deviation (RPD) obtained with the VIP scores hybrid model were 1.05% and 2.53 for corn DDGS, 0.98% and 4.17 for corn germ meal, 0.75% and 6.99 for corn gluten meal, 1.54% and 4.59 for DDG, and 0.90% and 3.33 for rapeseed meal, respectively. The results of this study demonstrate that the protein content in several types of plant feed materials can be determined using a hybrid near-infrared spectroscopy model. And VIP scores method can be used to improve the general predictability of hybrid model.

No MeSH data available.


The RPD value for different kinds of plant feed materials in different NIR models.Model 1 to Model 4 stand for full spectrum specific models, full spectrum hybrid model, VIP scores specific models and VIP scores hybrid model, respectively.
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pone.0163145.g003: The RPD value for different kinds of plant feed materials in different NIR models.Model 1 to Model 4 stand for full spectrum specific models, full spectrum hybrid model, VIP scores specific models and VIP scores hybrid model, respectively.

Mentions: The RPD values that were obtained using different NIR models for each type of plant feed material are presented in Fig 3. The general performance of the hybrid model for each material was slightly worse than those of the specific models. The RPD values for corn DDGS, corn germ meal, corn gluten meal and rapeseed meal decreased by 11.15%, 43.89%, 37.57% and 9.14%, respectively. Notably, the RPD value of DDG increased by 21.58%.


Non-Invasive Detection of Protein Content in Several Types of Plant Feed Materials Using a Hybrid Near Infrared Spectroscopy Model
The RPD value for different kinds of plant feed materials in different NIR models.Model 1 to Model 4 stand for full spectrum specific models, full spectrum hybrid model, VIP scores specific models and VIP scores hybrid model, respectively.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036844&req=5

pone.0163145.g003: The RPD value for different kinds of plant feed materials in different NIR models.Model 1 to Model 4 stand for full spectrum specific models, full spectrum hybrid model, VIP scores specific models and VIP scores hybrid model, respectively.
Mentions: The RPD values that were obtained using different NIR models for each type of plant feed material are presented in Fig 3. The general performance of the hybrid model for each material was slightly worse than those of the specific models. The RPD values for corn DDGS, corn germ meal, corn gluten meal and rapeseed meal decreased by 11.15%, 43.89%, 37.57% and 9.14%, respectively. Notably, the RPD value of DDG increased by 21.58%.

View Article: PubMed Central - PubMed

ABSTRACT

Near-infrared spectroscopy combined with chemometrics was applied to construct a hybrid model for the non-invasive detection of protein content in different types of plant feed materials. In total, 829 samples of plant feed materials, which included corn distillers’ dried grains with solubles (DDGS), corn germ meal, corn gluten meal, distillers’ dried grains (DDG) and rapeseed meal, were collected from markets in China. Based on the different preprocessed spectral data, specific models for each type of plant feed material and a hybrid model for all the materials were built. Performances of specific model and hybrid model constructed with full spectrum (full spectrum model) and selected wavenumbers with VIP (variable importance in the projection) scores value bigger than 1.00 (VIP scores model) were also compared. The best spectral preprocessing method for this study was found to be the standard normal variate transformation combined with the first derivative. For both full spectrum and VIP scores model, the prediction performance of the hybrid model was slightly worse than those of the specific models but was nevertheless satisfactory. Moreover, the VIP scores model obtained generally better performances than corresponding full spectrum model. Wavenumbers around 4500 cm-1, 4664 cm-1 and 4836 cm-1 were found to be the key wavenumbers in modeling protein content in these plant feed materials. The values for the root mean square error of prediction (RMSEP) and the relative prediction deviation (RPD) obtained with the VIP scores hybrid model were 1.05% and 2.53 for corn DDGS, 0.98% and 4.17 for corn germ meal, 0.75% and 6.99 for corn gluten meal, 1.54% and 4.59 for DDG, and 0.90% and 3.33 for rapeseed meal, respectively. The results of this study demonstrate that the protein content in several types of plant feed materials can be determined using a hybrid near-infrared spectroscopy model. And VIP scores method can be used to improve the general predictability of hybrid model.

No MeSH data available.