首页|Jiangsu University Researchers Highlight Recent Research in Artificial Neural Networks (Rapid Detection on the Quality of Salted Duck Eggs Based on Hyperspectral Imaging)

Jiangsu University Researchers Highlight Recent Research in Artificial Neural Networks (Rapid Detection on the Quality of Salted Duck Eggs Based on Hyperspectral Imaging)

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By a News Reporter-Staff News Editor at Network Daily News - Investigatorspublish new report on artificial neural networks. According to news reporting from Zhenjiang, People’sRepublic of China, by NewsRx journalists, research stated, “Salted duck eggs are a type of traditionalChinese pickled delicacy, and moisture and lipid content are important indexes for evaluating the qualityduring processing.”Our news reporters obtained a quote from the research from Jiangsu University: “This study used ahyperspectral imaging (HSI) system in conjunction with chemometrics to investigate the content changeand distribution of moisture and lipid during different salting stages of duck eggs. The HSI was used toobtain reflectance spectral information of salted duck eggs in the 432 961 nm wavelength range. To minimizethe noise in spectral signals, three preprocessing methods including Savitzky-Golay smoothing (SG),Gauss filter smoothing (Gauss), and standard normal variation (SNV) were used. The competitive adaptivereweighted sampling (CARS) was used to select the optimal wavelengths for predicting moisture and lipidcontent, and then the partial least squares regression (PLSR) and artificial neural network (ANN) methodswere used to predict moisture and lipid content quantitatively. Results showed that ANN model couldexhibited a better performance in predicting moisture and lipid content with coefficients of determinationof the protein moisture, yolk moisture and yolk lipid of 0.9306, 0.9552 and 0.8896 respectively. Finally,the ANN model was used to create a distribution map of moisture and lipid content in the profile of saltedduck eggs.”

Jiangsu UniversityZhenjiangPeople’s Republic of ChinaAsiaArtificial Neural Networks

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Jan.25)