Quantitative determination and characteristic wavelength selection of available nitrogen in coco-peat by NIR spectroscopy

Lu, Bing; Liu, Nihong; Li, Huiling; Yang, Kefei; Hu, Can; Wang, Xufeng; Li, Zhengxuan; Shen, Zhixiong; Tang, Xiuying

doi:10.1016/j.still.2019.04.015

Cited by 35 publications

(10 citation statements)

References 26 publications

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“…This is due to the fewer variables that were input in the MLR model (Zhou et al., 2010), which will decrease the model complexity and model error (Wang et al., 2016). Moreover, the MLR model needs fewer requirements in computer processes and operation, and this would provide a potential practical application (Lu et al., 2019).…”

Section: Discussionmentioning

confidence: 99%

Hyperspectral estimation of soil organic matter and clay content in loess plateau of China

Chao

Qiao

et al. 2021

Agronomy Journal

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Visible and near-infrared reflectance (Vis-NIR) spectroscopy is considered a promising tool for the estimation of soil properties. Soil clay content and soil organic matter (SOM) are main components affecting soil spectra. Accurate assessment of clay content and SOM is essential before achieving accurate prediction for other soil properties. Selecting the proper spectral transformation technique and optimal calibration method are important processes to improve model performance. In this study, a total of 240 soil samples were collected from the main area of winter wheat (Triticum aestivum L.) fields in the Southwest region of Shanxi province, northern China. Six spectral pre-treatments and three multivariate methods were utilized to realize the estimation of clay content and SOM. Finally, the important spectral wavelengths were identified

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Section: Discussionmentioning

confidence: 99%

Hyperspectral estimation of soil organic matter and clay content in loess plateau of China

Chao

Qiao

et al. 2021

Agronomy Journal

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“…The performance of the model was assessed using the correlation coefficient of the model (R), the root mean square error (RMSE, Equation ( 2)), the ratio of prediction to deviation (RPD, Equation ( 3)), and ratio error range (RER, Equation ( 4)). When R approaches 1, the root mean square error of calibration (RMSEC) and root mean squared error of prediction (RMSEP) are smaller and closer, indicating that the spectral information of the calibration set has been fully extracted and the model has a good stability, high fitting degree, and good predictive ability (Lu et al, 2019).…”

Section: Modeling Methodsmentioning

confidence: 99%

Determination of the total viable count of Chinese meat dishes by near‐infrared spectroscopy: A predictive model

Cao

Wei

Xing

et al. 2021

J. Food Process. Preserv.

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The total viable count (TVC) is an important index that reflects the freshness, contamination, and spoilage of dishes. Presently, near-infrared spectroscopy (NIR) is widely used for the assessment of TVC in raw meat, but there are few reports on the application of NIR spectroscopy to evaluate the TVC of Chinese meat dishes. Also, in the existing research, the modeling samples are industrial products, which makes

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“…The analysis is time-consuming and costly. 27 The strength of the chemical detection method lies in its high accuracy, which has been widely accepted in academic circles and practice. In the current study, the total nitrogen content of rubber leaves was obtained by the Kjeldahl determination method and then used as the reference data in the model constructing process.…”

Section: Methodsmentioning

confidence: 99%

Fractional order modeling and recognition of nitrogen content level of rubber tree foliage

Tang

et al. 2020

Journal of Near Infrared Spectroscopy

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The Nondestructive estimation method of nitrogen content level of rubber tree foliage was investigated utilizing nearinfrared (NIR) spectroscopy and Grünwald-Letnikov fractional calculus. Four models, including partial least squares discriminant analysis (PLS-DA), support vector machine (SVM), extreme learning machine (ELM) and convolutional neural networks (CNN) are applied to construct the nitrogen estimation model. The results show that models established by 0.6-order or 1.6-order spectra achieved better performance than models with integer-order spectra. Afterward, the successive projections algorithm (SPA) is applied to reduce the number of variables, which is critical for developing portable nitrogen-level detector devices for rubber trees. The PLS-DA method achieved the best performance with an optimal recognition rate (97.73%) using the 1.6-order spectra. The results suggest that nitrogen content of rubber trees could be reliably estimated by fractional calculus processed NIR spectra. The method proposed here has a wide range of applicability and can provide more useful information for NIR spectral analysis in agriculture as well as other fields.

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Quantitative determination and characteristic wavelength selection of available nitrogen in coco-peat by NIR spectroscopy

Cited by 35 publications

References 26 publications

Hyperspectral estimation of soil organic matter and clay content in loess plateau of China

Hyperspectral estimation of soil organic matter and clay content in loess plateau of China

Determination of the total viable count of Chinese meat dishes by near‐infrared spectroscopy: A predictive model

Fractional order modeling and recognition of nitrogen content level of rubber tree foliage

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