Application of long-wave near infrared hyperspectral imaging for determination of moisture content of single maize seed
文献类型： 外文期刊
作者： Wang, Zheli 1 ; Fan, Shuxiang 1 ; Wu, Jingzhu 3 ; Zhang, Chi 1 ; Xu, Fengying 4 ; Yang, Xuhai 2 ; Li, Jiangbo 1 ;
作者机构： 1.Beijing Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China
2.Shihezi Univ, Coll Mech & Elect Engn, Shihezi 832003, Peoples R China
3.Beijing Technol & Business Univ, Beijing Key Lab Big Data Technol Food Safety, Beijing 100048, Peoples R China
4.South China Agr Univ, Key Lab Key Technol Agr Machine & Equipment, Minist Educ, Guangzhou 510642, Peoples R China
关键词： Hyperspectral imaging; Maize seed; Moisture content; Wavelength selection
期刊名称：SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY （ 影响因子：3.232； 五年影响因子：2.848 ）
ISSN： 1386-1425
年卷期： 2021 年 254 卷
页码：
收录情况： SCI
摘要： Moisture content (MC) is one of the most important factors for assessment of seed quality. However, the accurate detection of MC in single seed is very difficult. In this study, single maize seed was used as research object. A long-wave near infrared (LWNIR) hyperspectral imaging system was developed for acquiring reflectance images of the embryo and endosperm side of maize seed in the spectral range of 930-2548 nm, and the mixed spectra were extracted from both side of maize seeds. Then, Full spectrum models were established and compared based on different types of spectra. It showed that models established based on spectra of the embryo side and mixed spectra obtained better performance than the endosperm side. Next, a combination of competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA) was proposed to select the most effective wavelengths from full spectrum data. In order to explore the stableness of wavelength selection algorithm, these methods were used for 200 independent experiments based on embryo side and mixed spectra, respectively. Each selection result was used as input of partial least squares regression (PLSR) and least squares support vector machine (LS-SVM) to build calibration models for determining the MC of single maize seed. Results indicated that the CARS-SPA-LS-SVM model established with mixed spectra was optimal for MC prediction in all models by considering the accuracy, stableness and complexity of models. The prediction accuracy of CARS-SPA-LS-SVM model is R-pre = 0.9311 +/- 0.0094 and RMSEP = 1.2131 +/- 0.0702 in 200 independent assessment. The overall study revealed that the long-wave near infrared hyperspectral imaging can be used to non-invasively and fast measure the MC in single maize seed and a robust and accurate model could be established based on CARS-SPA-LS-SVM method coupled with mixed spectral. These results can provide a useful reference for assessment of other internal quality attributes (such as starch content) of single maize seed. (C) 2021 Elsevier B.V. All rights reserved.
- 相关文献
作者其他论文 更多>>
-
Navigation line extraction algorithm for corn spraying robot based on YOLOv8s-CornNet
作者：Guo, Peiliang;Diao, Zhihua;Ma, Shushuai;He, Zhendong;Zhao, Suna;Zhao, Chunjiang;Li, Jiangbo;Zhang, Ruirui;Yang, Ranbing;Zhang, Baohua
关键词：agricultural robotics; computer vision; deep learning; navigation line extraction; network lightweight
-
Online detection of lycopene content in the two cultivars of tomatoes by multi-point full transmission Vis-NIR spectroscopy
作者：Li, Sheng;Wang, Qingyan;Shi, Ruiyao;Li, Jiangbo;Li, Sheng;Yang, Xuhai;Zhang, Qian
关键词：Tomato quality; Nondestructive evaluation; Chemometrics; Least angle regression; Model optimization
-
Detection of Insect-Damaged Maize Seed Using Hyperspectral Imaging and Hybrid 1D-CNN-BiLSTM Model
作者：Wang, Zheli;Chen, Liping;Wang, Zheli;Fan, Shuxiang;An, Ting;Zhang, Chi;Chen, Liping;Huang, Wenqian
关键词：Maize seed; Insect infestation; Hyperspectral imaging; Deep learning; BiLSTM
-
Detection of early decayed oranges by using hyperspectral transmittance imaging and visual coding techniques coupled with an improved deep learning model
作者：Cai, Letian;Zhang, Yizhi;Shi, Ruiyao;Li, Xuetong;Li, Jiangbo;Cai, Letian;Zhang, Junyi;Diao, Zhihua
关键词：Citrus decay detection; Sample expansion; Spectral visual encoding; Improved deep learning; Model optimization
-
Identification of mould varieties infecting maize kernels based on Raman hyperspectral imaging technique combined with multi-channel residual module convolutional neural network
作者：Long, Yuan;Tang, Xiuying;Zhang, Bin;Long, Yuan;Fan, Shuxiang;Zhang, Chi;Huang, Wenqian;Long, Yuan;Fan, Shuxiang;Zhang, Chi;Huang, Wenqian
关键词：Raman hyperspectral imaging; Maize kernels; Mould varieties; Residual unit; Nondestructive detection
-
Identification of early decayed oranges using structured-illumination reflectance imaging coupled with fast demodulation and improved image processing algorithms
作者：Li, Jiangbo;Lu, Yuzhen;Lu, Renfu
关键词：Citrus decay; Defect segmentation; Brightness transformation; Image enhancement; Classification
-
Staggered-Phase Spray Control: A Method for Eliminating the Inhomogeneity of Deposition in Low-Frequency Pulse-Width Modulation (PWM) Variable Spray
作者：Zhang, Chunfeng;Zhao, Chunjiang;Zhang, Chunfeng;Zhai, Changyuan;Zhang, Meng;Zhang, Chi;Zou, Wei;Zhao, Chunjiang;Zhang, Chunfeng;Zou, Wei;Zhai, Changyuan;Zhang, Meng;Zhao, Chunjiang
关键词：precision spray; variable spray; PWM; deposition; duty cycle; frequency
