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A digital method for rapidly assessing the degree of damage caused by diseases and insect pests in alfalfa

A technology of pests and diseases, alfalfa, applied in the field of digital fine grass and agriculture, to achieve the effect of preventing code tampering and leakage, easy operation, and reducing geometric deformation

Active Publication Date: 2020-04-03
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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  • A digital method for rapidly assessing the degree of damage caused by diseases and insect pests in alfalfa
  • A digital method for rapidly assessing the degree of damage caused by diseases and insect pests in alfalfa
  • A digital method for rapidly assessing the degree of damage caused by diseases and insect pests in alfalfa

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0040] 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.

[0041] S2, calculating the leaf disease rate;

[0042] S21. Calculate the total length of H rows and the width of L columns in the whole picture, and take one pixel unit as a row or column, then find the Hxth row, Lxth column, Hth row and Lth column, and calculate these two rows and two columns respectively The average value of the three components of , namely avgR, avgG, avgB, the three components refer to RGB;

[0043] 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 wi...

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Abstract

The invention discloses a digital method for quickly evaluating the loss degree of alfalfa diseases and insect pests. It analyzes the lesion area and non-lesion area of ​​alfalfa leaves, summarizes the common disease degree and its RGB color component rule, and constructs the leaf lesion area and non-lesion area accordingly. Lesion color decision tree component system. It integrates the visual processing flow of digital pictures and is suitable for non-computer professionals to operate and use; it also has functions such as batch processing and data export, and is suitable for processing large amounts of data; Geometric deformation improves calculation accuracy; binary images of healthy and unhealthy areas of leaves are constructed, and display and comparison are provided; it is suitable for leaves whose length and width are less than 0.5m, and the range and accuracy are as follows: The statistical accuracy of the lesion area of ​​the alfalfa leaf is more than 95% in the range larger than 1mm.

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 Patents(China)
IPC IPC(8): G06T7/00G06T7/90G06T7/62
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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