Method for quantitatively analyzing plant nutrient content index based on leaf image characteristics

Abstract

The invention belongs to the field of plant nutrition and in particular relates to a method for quantitatively analyzing plant nutrient content index based on leaf image characteristics. The method is characterized by acquiring representative sample leaves to carry out image acquisition on the sample leaves after carrying out culture in lack of nutritional elements on the given plants and obtaining the color characteristic sets and shape characteristic sets of the leaves through conversion; establishing relationship mapping tables between the leaf nutrient content index level and the color and shape characteristic sets and establishing color standards at the corresponding levels; and then analyzing images of the samples after acquiring the images of the leaves to be detected, taking the Euclidean distance as the matching evaluation index and searching the tables to obtain the nutrient index level value according to the corresponding color standards after optimizing matching. The method has the following advantages: the generality and the adaptability are stronger; the accurate nutrient content index value can be given according to the images of the leaves to be detected; and the process is simple, the detection speed is high and the method is easy to popularize.

Description

technical field [0001] The invention belongs to the field of plant nutrition, and specifically relates to a quantitative analysis method for plant nutrient content indicators based on leaf image features, which is a quantitative analysis method for extracting nutrient content indicators based on plant leaf image features. Background technique [0002] Obtaining plant nutrient deficiency information based on the analysis of plant leaf image features to provide support for agricultural production decisions such as plant cultivation precision fertilization, yield prediction, growth analysis, and nutritional analysis is an intelligent analysis method for plant nutrition based on machine vision developed in recent years. Its characteristics It simply uses the strong correlation between plant nutrition and leaf appearance image features (linear or nonlinear agrochemical model), and extracts corresponding leaf image features through image analysis to obtain plant nutrition informati...

AI Technical Summary

Problems solved by technology

However, directly adopting high-end equipment for detection has high cost and long cycle, which is not conducive to popularization

2) Non-parametric (empirical) model: In ancient my country, there was experience in judging the nutritional status of rice leaves by visually observing the color of rice leaves; in the 1970s, Japan used the "color card" method to determine the nutritional status of rice, but these The methods are all affected by the visual factors of the observer and the differences of the comparison objects, and the validity of the judgment results is not high.

[0007] In conclusion, judging from the relevant domestic and foreign scientific and technological achievements of plant nutrition image analysis technology, the currently used plant nutrition intelligent analysis method has the following deficiencies: 1) Using a certain experimental strong correlation model to compare with the preset threshold directly gives The analysis results show that this model has different c

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