Digital method for rapidly evaluating loss severity of alfalfa diseases and insects

A technology of disease degree, disease and insect pests, applied in the field of digital fine grass and agriculture

Active Publication Date: 2016-01-20
HEILONGJIANG BAYI AGRICULTURAL UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Alfalfa is widely planted as a high-quality forage grass, and there are few reports on the rapid estimation method of alfalfa plant diseases and insect pest losses in the process of continuous improvement of alfalfa planting technology

Method used

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  • Digital method for rapidly evaluating loss severity of alfalfa diseases and insects
  • Digital method for rapidly evaluating loss severity of alfalfa diseases and insects
  • Digital method for rapidly evaluating loss severity of alfalfa diseases and insects

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Experimental program
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Effect test

Embodiment

[0038] S1. Analyze the focus area and non-focus area of ​​the alfalfa leaf, summarize the common disease degree and its RGB color component rule, and construct the color decision tree component system of the leaf focus area and non-focus area accordingly; figure 1 shown.

[0039] S2, calculating the leaf disease rate

[0040] S21, calculate the long H row and wide L column of the whole picture (with one pixel unit as a row (column)), then find the H row, L column, H row and L column, and calculate three of these four rows (columns) respectively The average values ​​avgR, avgG, avgB of each component (RGB);

[0041] S22, the difference between the three components of each pixel of the picture and the four average values ​​of the corresponding components is then compared with the average value, as long as one of the ratios is less than 0.15 (assuming that x is a certain pixel point), this pixel point will be changed to is a grayscale pixel, that is, each value of the pixel is ...

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Abstract

The invention discloses a digital method for rapidly evaluating the loss severity of alfalfa diseases and insects. According to the technical scheme of the method, firstly, the focal regions and the non-focal regions of alfalfa leaves are analyzed and then the common disease degree and the RGB color component law thereof are generalized. After that, a color decision-making tree component system for the focal regions and the non-focal regions of alfalfa leaves is established accordingly. The visual processing flow of digital pictures is integrated as one, so that the method is suitable for non-computer professionals to use. At the same time, the functions of batch processing, data exporting and the like are realized, so that the method can be used for processing volume data. Based on the geometric projection imaging rule, the inscribed circle calculation manner is adopted, so that the geometric deformation avoided. The calculation accuracy is improved. Moreover, binary pictures for the healthy regions and the non-healthy regions of alfalfa leaves are constructed, and then the pictures are displayed and compared. In this way, the method can be applied to alfalfa leaves of smaller than 0.5 m in both length and width, with the diameters of the focal regions thereof to be larger than 1mm, and the area statistical precision of the focal regions thereof to be larger than 95%.

Description

technical field [0001] The invention belongs to the field of digitized fine grass industry and agricultural technology combining a method for estimating losses of pasture diseases and insect pests with digital imaging and computer technology, and in particular relates to a digital method for quickly evaluating the loss degree of alfalfa diseases and insect pests. Background technique [0002] China is one of the big agricultural countries in the world, but crops are facing various agricultural disasters. Crop diseases and insect pests are one of the main agricultural disasters in our country. It has the characteristics of various types, great impact, and frequent outbreaks. The scope and severity of its occurrence and severity often cause heavy losses to our national economy, especially agricultural production. In recent years, with the deepening of my country's opening up to the outside world, foreign invasive diseases, insect pests and weeds have continued to increase. Wit...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/40
CPCG06T2207/10024G06T2207/30188
Inventor 刘香萍杨智明李国良曲善民海涛
Owner HEILONGJIANG BAYI AGRICULTURAL UNIVERSITY
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