CN113515859A - Nondestructive judgment method for overgrown watermelon seedlings - Google Patents
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Abstract
The invention discloses a nondestructive judgment method for excessive watermelon seedlings. The method is used for judging the overgrown watermelon seedlings and the normal watermelon seedlings, firstly, the phenotype parameters of the plug seedlings of the watermelon are obtained, then, the measured phenotype data are preprocessed, the measurement errors are compensated, the overgrowth value Z is obtained, finally, the overgrowth seedlings and the normal watermelon seedlings are judged according to the overgrowth value Z, and specific judgment rules are provided. The invention can make up the deficiency of manual screening by visual quantitative analysis of data. The established bare-grown seedling nondestructive judgment rule has strong applicability and can be used for watermelon seedlings in various growth periods. The phenotype data of the watermelon seedlings can be acquired through nondestructive measurement modes such as image recognition and the like, so that large-scale intelligent detection of the seedlings is realized. The invention can reduce the workload of artificial seedling screening and obviously reduce the production cost.
Description
Technical Field
The invention belongs to the field of agricultural automation, and particularly relates to a nondestructive judgment method for overgrown watermelon seedlings.
Background
The watermelon plays an important role in the world gardening production, and the watermelon industry enters a rapid growth stage since the last 90 years, and the planting area of the watermelon is continuously increased. China has become the largest watermelon producing and consuming countries in the world, the annual watermelon yield exceeds 6000 million tons, and the annual demand on watermelon seedlings is as high as hundreds of billions. Seedling production enterprises generally use porous one-piece plug trays as containers for seedling culture, and artificially mix substrates to replace soil. The method saves land resources, is suitable for large-scale production of factories and is convenient for mechanized operation. However, in the actual production process, the problems of large seedling density, mutual shading among plants and the like exist, and overgrown seedlings are easily formed due to insufficient illumination. In addition, in order to meet the demand of annual production, the seedlings are also grown under the condition of uncomfortable environment in seasons such as overcast, rainy and high temperature. The conditions of weak light, high temperature and high humidity often cause the excessive growth of seedlings, which is not favorable for the growth of strong seedlings. The overgrown seedlings can not meet the requirements of subsequent planting production, so that the overgrown seedlings need to be screened out in time in the seedling raising process. How to screen out the overgrown seedlings becomes the key problem of the standardized production of the watermelon seedling at present.
In the watermelon seedling raising process, external morphological indexes such as plant height and stem thickness are generally observed, whether the watermelon seedlings grow excessively or not is judged through empirical judgment, subjective judgment is achieved, intuitiveness is poor, and large-scale detection of the seedlings is not facilitated.
In conclusion, the technical staff in the field needs to solve the problem of how to provide a comprehensive evaluation index capable of accurately judging whether watermelon seedlings are overgrown or not for helping producers and scientific researchers to accurately judge the watermelon seedlings.
Disclosure of Invention
Technical problem to be solved
The invention aims to solve the technical problem of providing a method for nondestructively and quantitatively judging the excessive watermelon seedlings by using visual data, thereby improving the efficiency of manually screening the excessive seedlings and realizing large-scale intelligent detection on the watermelon seedlings in each growing period.
(II) technical scheme
In order to solve the problems, the invention provides the following technical scheme, and provides a nondestructive judging method for the overgrown watermelon seedlings, which comprises the following specific steps.
The method for nondestructively judging the spindly watermelon seedlings is characterized by being used for judging the spindly watermelon seedlings and normal watermelon seedlings and comprising the following steps of:
s1, acquiring phenotypic parameters of watermelon plug seedlings, wherein the parameters comprise hypocotyl length, root length, stem thickness and the like;
s2, preprocessing the phenotype data obtained by measurement and compensating the measurement error;
s3, obtaining a bare growth value Z,
and S4, judging the spindly seedlings and the normal seedlings according to the spindly growth value Z.
More specifically, in step S1, acquiring a phenotype parameter of the watermelon plug seedling, specifically, acquiring the phenotype parameter by means of image recognition; firstly, an image acquisition device is used for shooting a watermelon seedling phenotype photo, then image preprocessing is carried out, and phenotype parameters of the watermelon seedling are respectively calculated by combining an image recognition algorithm.
More specifically, in step S2, the measured phenotype data is preprocessed, including data outlier cleaning, sorting the measured watermelon seedling phenotype parameter data in ascending order, removing data records that obviously belong to outliers, regarding the data records as missing items, and then performing data interpolation.
More specifically, in step S4, the spindly seedlings and the normal seedlings are determined according to the spindly value Z, and the specific determination rule is,
if the vain growth value Z is more than 0.3, the vain growth phenomenon of the seedling is obvious;
if the value of the vain growth is more than or equal to 0.2 and less than or equal to 0.3, the seedling is vain growth but not serious;
if the value Z of the vain growth is less than 0.2, the seedling does not show the vain growth phenomenon.
(III) advantageous effects
Compared with the prior art, the invention has obvious and positive technical effects and is embodied in the following aspects. According to the method, a targeted overgrowth model can be established according to key phenotype indexes in the growth process of the watermelon seedlings, and the method adopts the forms of phenotype extraction and quantitative analysis and evaluation to accurately judge whether the watermelon seedlings are overgrowth seedlings, so that the defect of manual empirical judgment can be overcome, and high-throughput detection and judgment can be realized. The phenotype data of the invention is obtained by a nondestructive testing mode, the operation is simple and convenient, and the production cost is reduced. The method for judging the overgrown watermelon seedlings can be flexibly suitable for judging the watermelon seedlings in different growth periods, the model has good robustness, and the method is suitable for judging the watermelon seedlings from one leaf and one heart to three leaves and one heart without changing the parameters of the model according to the change of the growth period. The excessive growth value can be used for accurately judging excessive growth of the watermelon seedlings, the subsequent growth and development processes of the watermelon seedlings cannot be influenced, and the method is convenient and reliable and can be popularized and applied in production.
Drawings
FIG. 1 is a comparison graph of the ratio of the vain and the normal seedling
FIG. 2 is a comparison graph of the bare-grown values of watermelon seedlings in a growing period of one leaf and one heart
FIG. 3 is a comparison graph of the bare-grown watermelon seedlings in the growing period of two leaves and one heart
FIG. 4 is a comparison graph of the vain growth values of watermelon seedlings in the three-leaf single-heart growth period
Detailed Description
The invention provides a nondestructive judging method for the overgrown watermelon seedlings, which aims to solve the technical problem. The technical scheme of the invention is specifically described below by combining the drawings and the specific implementation examples in the specification.
The culture medium is prepared by using a tray with 72 holes, and the medium is prepared by mixing turf (with the grain diameter of 0-6mm), vermiculite (with the grain diameter of 2-4mm) and perlite (with the grain diameter of 2-4mm) in a ratio of 3: 1 (volume ratio). And when the watermelon seedlings grow for 13d, 18d and 23d respectively, randomly selecting 20 seedlings in three growth states, and measuring the phenotype data of the watermelon in three periods of one leaf and one heart, two leaves and one heart and three leaves and one heart. The watermelon seedling variety is 'Yantian red star'.
Phenotypic parameters were measured including hypocotyl length, root length, stem thickness.
The determination method comprises the following steps: first a high quality picture of the measured phenotype is taken. Extracting skeletons of roots and hypocotyls in the two-dimensional image, thinning the skeletons into a curve, obtaining the length of a single pixel point forming the curve, and approximately estimating the root length and the hypocotyl length by the curve length. And extracting a stem skeleton, and performing clustering and ellipse fitting on the pixel point cloud at the measurement position to estimate the stem thickness. The phenotype measurement values of watermelon seedlings from one-leaf one-heart to three-leaf one-heart are obtained by the method, and the unit of hypocotyl length is (mm), the unit of stem thickness is (mm) and the unit of root length is (mm).
Substituting phenotype data of watermelon seedlings into vain value model
And (6) carrying out inspection. FIG. 1 is a comparison of the vain length values of two groups of seedlings. As can be seen, the value of vain for most of the micro-vain seedlings is smaller than that of vain seedlings and larger than that of normal seedlings.
Substituting the phenotype data of the watermelon seedlings in three periods of one leaf and one heart, two leaves and one heart and three leaves and one heart into the overgrowth model to respectively obtain the overgrowth value comparison graphs of the watermelon seedlings in different growth periods as shown in the figures 2, 3 and 4. As can be seen from FIGS. 2-4, the model is suitable for watermelon seedlings of different growth periods. The spindling value distribution of the watermelon seedlings in each growth period is also approximately the same: the distribution of the vain growth values of the vain growth seedlings is more than 0.3; z is more than or equal to 0.2 and less than or equal to 0.3; the distribution of the vain growth values of normal seedlings is Z less than 0.2. Thus, the value model of the invention is used
And the judgment rule can effectively identify the spindly seedlings and the normal seedlings in different growth periods, thereby obtaining positive technical effects. The model has good robustness.
The specific examples described in the application are only illustrative of the spirit of the invention. Various modifications, additions and substitutions of types may be made by those skilled in the art without departing from the spirit of the invention or exceeding the scope of the invention as defined in the accompanying claims.
Claims (4)
1. The method for nondestructively judging the spindly watermelon seedlings is characterized by being used for judging the spindly watermelon seedlings and normal watermelon seedlings and comprising the following steps of:
s1, acquiring phenotype parameters of the watermelon plug seedlings, wherein the parameters comprise hypocotyl length, root length, stem thickness and the like;
s2, preprocessing the phenotype data obtained by measurement and compensating the measurement error;
s3, obtaining a bare growth value Z,
and S4, judging the spindly seedlings and the normal seedlings according to the spindly growth value Z.
2. The method for nondestructively judging the excessive watermelon seedling according to claim 1, wherein the phenotypic parameters of the plug seedlings of the watermelon are obtained in step S1, specifically by means of image recognition; firstly, an image acquisition device is used for shooting a watermelon seedling phenotype photo, then image preprocessing is carried out, and phenotype parameters of the watermelon seedling are respectively calculated by combining an image recognition algorithm.
3. The method for judging the excessive watermelon seedling according to claim 1, wherein the step S2 comprises the steps of preprocessing the measured phenotype data, cleaning abnormal data, sorting the measured watermelon seedling phenotype parameter data according to an ascending order, removing data records obviously belonging to abnormal values, regarding the data records as missing items, and performing data interpolation.
4. The nondestructive judgment method for the spindly seedling of the watermelon according to claim 1, wherein the spindly seedling and the normal seedling are judged according to the spindly value Z in step S4, and the specific judgment rule is as follows:
if the vain growth value Z is more than 0.3, the vain growth phenomenon of the seedling is obvious;
if the value of the vain growth is more than or equal to 0.2 and less than or equal to 0.3, the seedling is vain growth but not serious;
if the value Z of the vain growth is less than 0.2, the seedling does not show the vain growth phenomenon.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101881726A (en) * | 2010-06-18 | 2010-11-10 | 北京农业智能装备技术研究中心 | Nondestructive detection method for comprehensive character living bodies of plant seedlings |
| CN106651617A (en) * | 2016-12-29 | 2017-05-10 | 深圳前海弘稼科技有限公司 | Seedling monitoring method and device based on greenhouse environment |
| JP2019071802A (en) * | 2017-10-13 | 2019-05-16 | 有限会社竹内園芸 | Seedling data generating system, seedling discriminating system, seedling data generating program, seedling discriminating program, seedling data generating device, and seedling discriminating device |
| CN110064601A (en) * | 2019-05-23 | 2019-07-30 | 仲恺农业工程学院 | Seedling detection and classification system and classification method for vegetable grafting |
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- 2021-07-07 CN CN202110774779.2A patent/CN113515859B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101881726A (en) * | 2010-06-18 | 2010-11-10 | 北京农业智能装备技术研究中心 | Nondestructive detection method for comprehensive character living bodies of plant seedlings |
| CN106651617A (en) * | 2016-12-29 | 2017-05-10 | 深圳前海弘稼科技有限公司 | Seedling monitoring method and device based on greenhouse environment |
| JP2019071802A (en) * | 2017-10-13 | 2019-05-16 | 有限会社竹内園芸 | Seedling data generating system, seedling discriminating system, seedling data generating program, seedling discriminating program, seedling data generating device, and seedling discriminating device |
| CN110064601A (en) * | 2019-05-23 | 2019-07-30 | 仲恺农业工程学院 | Seedling detection and classification system and classification method for vegetable grafting |
Non-Patent Citations (3)
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| SHENGYONG XU等: "《Three-Dimensional Reconstruction and Phenotype Nondestructive Measurement Technology for Rape Roots》", 《2020 IEEE 40TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS)》 * |
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