Determination of soluble solids content of multiple varieties of tomatoes by full transmission visible-near infrared spectroscopy
文献类型： 外文期刊
作者： Li, Sheng 1 ; Li, Jiangbo 2 ; Wang, Qingyan 2 ; Shi, Ruiyao 2 ; Yang, Xuhai 1 ; Zhang, Qian 1 ;
作者机构： 1.Shihezi Univ, Coll Mech & Elect Engn, Shihezi, Peoples R China
2.Beijing Acad Agr & Forestry Sci, Intelligent Equipment Res Ctr, Beijing, Peoples R China
3.Xinjiang Prod & Construct Corps Key Lab Modern Agr, Shihezi, Peoples R China
4.Minist Agr & Rural Affairs, Key Lab Northwest Agr Equipment, Shihezi, Peoples R China
5.Minist Educ, Engn Res Ctr Prod Mechanizat Oasis Characterist Ca, Shihezi, Peoples R China
关键词： tomato; soluble solids content; online detection; full transmission; quantitative analysis model
期刊名称：FRONTIERS IN PLANT SCIENCE （ 影响因子：4.1； 五年影响因子：5.3 ）
ISSN： 1664-462X
年卷期： 2024 年 15 卷
页码：
收录情况： SCI
摘要： Introduction Soluble solids content (SSC) is a pivotal parameter for assessing tomato quality. Traditional measurement methods are both destructive and time-consuming.Methods To enhance accuracy and efficiency in SSC assessment, this study employs full transmission visible and near-infrared (Vis-NIR) spectroscopy and multi-point spectral data collection techniques to quantitatively analyze SSC in two tomato varieties ('Provence' and 'Jingcai No.8' tomatoes). Preprocessing of the multi-point spectra is carried out using a weighted averaging approach, aimed at noise reduction, signal-to-noise ratio improvement, and overall data quality enhancement. Taking into account the potential influence of various detection orientations and preprocessing methods on model outcomes, we investigate the combination of partial least squares regression (PLSR) with two orientations (O1 and O2) and two preprocessing techniques (Savitzky-Golay smoothing (SG) and Standard Normal Variate transformation (SNV)) in the development of SSC prediction models.Results The model achieved the best results in the O2 orientation and SNV pretreatment as follows: 'Provence' tomato (Rp = 0.81, RMSEP = 0.69 degrees Brix) and 'Jingcai No.8' tomatoes (Rp = 0.84, RMSEP = 0.64 degrees Brix). To further optimize the model, characteristic wavelength selection is introduced through Least Angle Regression (LARS) with L1 and L2 regularization. Notably, when lambda=0.004, LARS-L1 produces superior results ('Provence' tomato: Rp = 0.95, RMSEP = 0.35 degrees Brix; 'Jingcai No.8' tomato: Rp = 0.96, RMSEP = 0.33 degrees Brix).Discussion This study underscores the effectiveness of full transmission Vis-NIR spectroscopy in predicting SSC in different tomato varieties, offering a viable method for accurate and swift SSC assessment in tomatoes.
- 相关文献
作者其他论文 更多>>
-
Advancements of UAV and Deep Learning Technologies for Weed Management in Farmland
作者：Zhang, Jinmeng;Yu, Feng;Zhang, Qian;Wang, Ming;Yu, Jinying;Tan, Yarong;Yu, Feng
关键词：unmanned aerial vehicle; convolutional neural network; deep learning; weed detection; weed management
-
An Original UV Adhesive Watermelon Grafting Method, the Grafting Device, and Experimental Verification
作者：Zhang, Xin;Kong, Linghao;Lu, Hanwei;Zhang, Xin;Feng, Qingchun;Li, Tao;Jiang, Kai;Zhang, Qian
关键词：watermelon grafting; UV adhesive; fluent; VOF-DPM numerical simulation; grafting device; test
-
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
-
Changes in climate attributes and harvest area structures jointly determined spatial-temporal variations in water footprint of maize in the Beijing-Tianjin-Hebei region
作者：Huai, Heju;Zhang, Qian;Liu, Min;Tang, Xiumei;Huai, Heju;Zhang, Qian;Liu, Min;Tang, Xiumei
关键词：Beijing-Tianjin-Hebei; Irrigation; Maize production; Rainfall; Water use efficiency
-
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 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
-
Analysis of Crop Irrigation Water Requirements and Water Scarcity Footprint in the Beijing-Tianjin-Hebei Region Based on the GeoSim-AquaCrop Model
作者：Huai, Heju;Zhang, Qian;Li, Zuolin;Tang, Xiumei;Huai, Heju;Zhang, Qian;Li, Zuolin;Tang, Xiumei;Liang, Lina
关键词：yield; irrigation water requirements; water scarcity footprint; AquaCrop
