Determination of Fatty Acid Content of Rice during Storage Based on Feature Fusion of Olfactory Visualization Sensor Data and Near-Infrared Spectra

Lu, Hong-Ping; Jiang, Hui; Chen, Quansheng

doi:10.3390/s21093266

Cited by 12 publications

(3 citation statements)

References 36 publications

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“…Back propagation neural network (BP) is a multi-layer feed-forward network algorithm based on error back propagation that presents high self-learning and adaptive ability [ 42 ]. It mainly realizes nonlinear mapping between input and output through learning.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Mutton Adulteration under the Effect of Mutton Flavour Essence Using Hyperspectral Imaging Combined with Machine Learning and Sparrow Search Algorithm

Fan

Zhu

et al. 2022

Foods

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The evaluation of mutton adulteration faces new challenges because of mutton flavour essence, which achieves a similar flavour between the adulterant and mutton. Hence, methods for classifying and quantifying the adulterated mutton under the effect of mutton flavour essence, based on near-infrared hyperspectral imaging (NIR-HSI, 1000–2500 nm) combined with machine learning (ML) and sparrow search algorithm (SSA), were proposed in this study. After spectral preprocessing via first derivative combined with multiple scattering correction (1D + MSC), classification and quantification models were established using back propagation neural network (BP), extreme learning machine (ELM) and support vector machine/regression (SVM/SVR). SSA was further used to explore the global optimal parameters of these models. Results showed that the performance of models improves after optimisation via the SSA. SSA-SVM achieved the optimal discrimination result, with an accuracy of 99.79% in the prediction set; SSA-SVR achieved the optimal prediction result, with an RP2 of 0.9304 and an RMSEP of 0.0458 g·g−1. Hence, NIR-HSI combined with ML and SSA is feasible for classification and quantification of mutton adulteration under the effect of mutton flavour essence. This study can provide a theoretical and practical reference for the evaluation and supervision of food quality under complex conditions.

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Section: Methodsmentioning

confidence: 99%

Evaluation of Mutton Adulteration under the Effect of Mutton Flavour Essence Using Hyperspectral Imaging Combined with Machine Learning and Sparrow Search Algorithm

Fan

Zhu

et al. 2022

Foods

View full text Add to dashboard Cite

show abstract

“…Additionally, the protein bodies, particularly the core, contain a high concentration of lipids. These lipids are primarily composed of linoleic, oleic, and palmitic acids [61]. Rice oil contains between 29 and 42% linoleic acid and between 0.8 and 1% linolenic acid as essential fatty acids [62].…”

Section: Lipidsmentioning

confidence: 99%

Rice for Food Security: Revisiting Its Production, Diversity, Rice Milling Process and Nutrient Content

et al. 2022

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Rice is food consumed regularly and is vital for the food security of over half the world’s population. Rice production on a global scale is predicted to rise by 58 to 567 million tonnes (Mt) by 2030. Rice contains a significant number of calories and a wide variety of essential vitamins, minerals, and other nutritional values. Its nutrients are superior to those found in maize, wheat, and potatoes. It is also recognised as a great source of vitamin E and B5 as well as carbohydrates, thiamine, calcium, folate, and iron. Phytic acid and phenols are among the phenolic compounds found in rice, alongside sterols, flavonoids, terpenoids, anthocyanins, tocopherols, tocotrienols, and oryzanol. These compounds have been positively linked to antioxidant properties and have been shown to help prevent cardiovascular disease and diabetes. This review examines recent global rice production, selected varieties, consumption, ending stocks, and the composition of rice grains and their nutritional values. This review also includes a new method of paddy storage, drying, and grading of rice. Finally, the environmental impacts concerning rice cultivation are discussed, along with the obstacles that must be overcome and the current policy directions of rice-producing countries.

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“…The fusion of data obtained with complementary techniques was recently reported as a promising option to improve the completeness and accuracy of the results [ 33 ]. Data fusion was tested and reported in different areas, such as health [ 34 , 35 ], agriculture [ 36 , 37 , 38 ] and food [ 17 , 39 ], among others. In this paper, a multi-sensor data-fusion approach is applied to classify textile fibers based on NIR and MIR spectroscopy.…”

Section: Introductionmentioning

confidence: 99%

Classification of Textile Samples Using Data Fusion Combining Near- and Mid-Infrared Spectral Information

2022

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There is an urgent need to reuse and recycle textile fibers, since today, low recycling rates are achieved. Accurate classification methods for post-consumer textile waste are needed in the short term for a higher circularity in the textile and fashion industries. This paper compares different spectroscopic data from textile samples in order to correctly classify the textile samples. The accurate classification of textile waste results in higher recycling rates and a better quality of the recycled materials. The data fusion of near- and mid-infrared spectra is compared with single-spectrum information. The classification results show that data fusion is a better option, providing more accurate classification results, especially for difficult classification problems where the classes are wide and close to one another. The experimental results presented in this paper prove that the data fusion of near- and mid-infrared spectra is a good option for accurate textile-waste classification, since this approach allows the classification results to be significantly improved.

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Determination of Fatty Acid Content of Rice during Storage Based on Feature Fusion of Olfactory Visualization Sensor Data and Near-Infrared Spectra

Cited by 12 publications

References 36 publications

Evaluation of Mutton Adulteration under the Effect of Mutton Flavour Essence Using Hyperspectral Imaging Combined with Machine Learning and Sparrow Search Algorithm

Evaluation of Mutton Adulteration under the Effect of Mutton Flavour Essence Using Hyperspectral Imaging Combined with Machine Learning and Sparrow Search Algorithm

Rice for Food Security: Revisiting Its Production, Diversity, Rice Milling Process and Nutrient Content

Classification of Textile Samples Using Data Fusion Combining Near- and Mid-Infrared Spectral Information

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