Detection method and system for spectrum detection of nutritional status of fruit tea tree

Abstract

The invention discloses a detection method and system for spectral detection of the nutritional status of a fruit tea tree. The method comprises the following steps: S1, acquiring multispectral data of a tea tree canopy through a multispectral image acquisition device; acquiring multispectral data of a canopy central area of each tea tree sample; s2, the nitrogen content of the tea trees is obtained based on an H2SO4-H2O2 digestion-Nessler colorimetric method; s3, analyzing the multispectral data; s4, by analyzing the correlation between the spectral characteristic variables and the nitrogen content, selecting the spectral characteristic variables to establish a plurality of regression analysis models; s5, by analyzing the correlation between the high-frequency information after binary wavelet decomposition and the nitrogen content, selecting a wave band to establish a prediction model; s6, verifying the accuracy of the established regression analysis model, and taking the regression analysis model with relatively high accuracy and stability as a detection model of the nitrogen content of the tea tree; and S7, using the detection model to detect the actual nutritional status of the fruit tea tree. The method disclosed by the invention can be used for rapidly and nondestructively detecting the nutrient element content of the fruit tea tree and predicting the nutrient element content.

Description

technical field [0001] The invention belongs to the technical field of spectral detection, and in particular relates to a detection method and system for spectral detection of the nutritional status of fruit tea trees. Background technique [0002] Nutrient elements such as nitrogen, phosphorus, and potassium are important chemical elements that promote the growth and development of plant leaves. Effective detection of the content of nutrient elements in the leaves of fruit tea trees is conducive to the precise fertilization and cultivation management of fruit tea trees. Significance. [0003] Although the traditional chemical method is intuitive and accurate to detect the nutrient content of tea trees, the operation is complicated and cumbersome, destroying the sample material, and it is impossible to detect large-scale planted fruit tea gardens in real time, quickly and non-destructively. At present, multispectral technology is widely used in the monitoring and detection ...

AI Technical Summary

Problems solved by technology

At present, there are few complete detection systems, and there are relatively few studies on the construction of inversion models by using wavelet analysis to separate the low-frequency information and high-frequency information of the original spectral data

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