A modeling method of vis-nir spectral features of leaf cadmium content based on wt-lssvr

A technology of spectral characteristics and modeling methods, applied in the field of plant detection, can solve problems such as large model randomness and deep algorithm fit

Active Publication Date: 2020-07-31
SHENZHEN LOTUT INNOVATION DESIGN CO LTD
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Problems solved by technology

However, the use of the above two invention patent algorithms has problems such as not performing deep-level algorithm fitting, and the established model is relatively random.

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  • A modeling method of vis-nir spectral features of leaf cadmium content based on wt-lssvr
  • A modeling method of vis-nir spectral features of leaf cadmium content based on wt-lssvr
  • A modeling method of vis-nir spectral features of leaf cadmium content based on wt-lssvr

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Embodiment Construction

[0041] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0042] Such as figure 1 As shown, the present embodiment takes tomato leaves as an example to illustrate the quantitative detection of heavy metal cadmium content in tomato leaves. The technical scheme adopted is as follows:

[0043] (1) Cultivation experiment Soilless cultivation of tomato was carried out in a Venlo-type greenhouse in order to obtain a purer experimental sample. The tomato sample was planned to be Hongfen No. 1. Tomato seeds are first raised in the nutrient matrix tank, and the nutrient solution is used to cultivate the seedlings before the 3-leaf stage. The nutrient solution is ...

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Abstract

The invention discloses a leaf cadmium content visible light-near infrared spectrum (Vis-NIR) spectral feature modeling method based on wavelet transform-partial least squares support vector regression (WT-LSSVR). Effective spectral sensitive band data extraction is performed on visible light-near infrared spectrums (Vis-NIR) of tomato leaves under stress of different concentrations of heavy metalcadmium, an atomic absorption spectrometry is utilized to measure heavy metal cadmium contents in leaves to obtain a leaf heavy metal cadmium content label set, and extracted sensitive characteristicwavelength and a WT-LSSVR feature modeling algorithm are utilized to finish leaf cadmium content Vis-NIR spectral feature modeling. The modeling method has the advantages of quick detection speed, high cadmium content predicting accuracy, high cadmium content predicting efficiency, no damage to leaves, ability in quantitatively detecting different cadmium residue contents of the same variety of tomatoes, ability in predicting cadmium residue contents of unknown leaves and the like.

Description

technical field [0001] The invention belongs to the field of plant detection, and in particular relates to a WT-LSSVR-based Vis-NIR spectral feature modeling method for cadmium content in leaves. Background technique [0002] Green vegetables are one of the most abundantly consumed crops in the world and are rich in antioxidants such as vitamin C, vitamin E, polyphenols and carotenoids, etc. Relevant experimental studies have shown that vitamin C plays an important role in human health, including improving human immunity and reducing the incidence of Alzheimer's disease. In addition, regular consumption of green vegetables will enhance the body's resistance to diseases including cancer, cardiovascular and cerebrovascular diseases. Under normal conditions, the growth of crops is closely related to the soil environment. Heavy metal cadmium (Cd) pollution stress is a major agricultural problem among soil planting hazards, and has been deeply studied in crop-related informatio...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N21/31G06Q10/04
CPCG01N21/31G01N21/3103G06Q10/04
Inventor 孙俊周鑫武小红戴春霞沈继锋杨宁
Owner SHENZHEN LOTUT INNOVATION DESIGN CO LTD
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