Method for detecting canopy moisture content of leaf vegetable crops

Abstract

The invention provides a method for detecting canopy moisture content of leaf vegetable crops. The method comprises the following steps: filtering spectrum, performing gradient extraction on characteristic wavelength by adopting a backward interval partial least square algorithm, a genetic algorithm and a continuous projection algorithm; performing wavelet denoising on a front view image and a top view image, extracting canopy projection area, canopy perimeter and plant height as growth characteristics of the leaf vegetable crops, extracting color component mean value of each of RGB space and HSI space as the color characteristic, extracting entropy, secondary moment, contrast ratio and homogeneity in six color co-occurrence matrixes constructed by the RGB space and the HSI space; and reducing dimension of the characteristic wavelength and the image characteristic by using kernel principle component analysis, establishing a detection model of the canopy moisture content of the leaf vegetable crops by using an extreme learning machine algorithm. Through the adoption of a plurality of chemometrics algorithms and image processing methods, the internal and external information of the canopy of the leaf vegetable crops are fully acquired, and the nondestructive detection of the canopy moisture content of the leaf vegetable crops is realized.

Description

technical field [0001] The invention belongs to the field of crop water content detection, in particular to a method for detecting the water content of the canopy of leafy vegetable crops. Background technique [0002] The agricultural proverb says, "Water is responsible for harvesting or not, and more or less is due to fertilizer". This sentence fully understands the important role of water in agricultural production. Leafy vegetables are mostly shallow-rooted crops, which are sensitive to water, and leafy vegetables Crop plants have many leaves, large leaf area, large transpiration, and high water consumption. When water stress occurs, the photochemical activity of pigments in the body is weakened, which hinders the absorption of nutrients and limits the transportation of nutrients from roots to leaves. [0003] Traditional crop canopy moisture content detection uses the dry-wet weight method, but this method is a destructive detection method that needs to destroy samples;...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the deficiencies in the prior art, the present invention provides a method for detecting the moisture content of the canopy of leafy vegetable crops, which uses multiple chemometric algorithms and multiple image processing methods to overcome the unrepresentative and unrepresentative image extraction of characteristic wavelengths. Incomplete feature extraction and other problems have further improved the detection accuracy and provided a basis for precise water management of leafy vegetable crops

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