کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5134105 1492074 2017 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
How to predict the sugariness and hardness of melons: A near-infrared hyperspectral imaging method
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
How to predict the sugariness and hardness of melons: A near-infrared hyperspectral imaging method
چکیده انگلیسی


- Near-infrared hyperspectral image technique was used for melon property prediction.
- Different values of a property of melon showed different spectral curves.
- Both full spectral and important spectral space can be used to predict melon sweetness and hardness.
- The distribution map of melon sweetness can be obtained through its hyperspectral images.

Hyperspectral imaging (HSI) in the near-infrared (NIR) region (900-1700 nm) was used for non-intrusive quality measurements (of sweetness and texture) in melons. First, HSI data from melon samples were acquired to extract the spectral signatures. The corresponding sample sweetness and hardness values were recorded using traditional intrusive methods. Partial least squares regression (PLSR), principal component analysis (PCA), support vector machine (SVM), and artificial neural network (ANN) models were created to predict melon sweetness and hardness values from the hyperspectral data. Experimental results for the three types of melons show that PLSR produces the most accurate results. To reduce the high dimensionality of the hyperspectral data, the weighted regression coefficients of the resulting PLSR models were used to identify the most important wavelengths. On the basis of these wavelengths, each image pixel was used to visualize the sweetness and hardness in all the portions of each sample.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Food Chemistry - Volume 218, 1 March 2017, Pages 413-421
نویسندگان
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