A method for identifying the development stage of mosquito larvae based on the head length and eye distance of the mosquito larvae

Abstract

The present application relates to a kind of mosquito larvae development age identification method based on mosquito larvae head length and eye distance, belong to insect identification technical field.The present application provides a kind of mosquito larvae development age identification method, according to the numerical value of mosquito larvae head length and / or eye distance is determined.The present application takes mosquito larvae head length and eye distance as core morphological parameter, with the advantages of fast determination speed, wide application scene, improve the stability and accuracy of age determination.The present application further establishes the mathematical scoring model between head length and eye distance and development age, converts the morphological parameters measured into the score value that can be calculated, realizes the change from experience judgment to vector determination, with stronger objectivity, standardization degree and repeatability.In Toxorhynchites speciosus, Aedes albopictus and Culex quinquefasciatus, it has strong applicability.

Description

Technical Field

[0001] This invention relates to the field of insect identification technology, and in particular to a method for identifying the developmental stage of mosquito larvae based on the head length and eye distance of mosquito larvae. Background Technology

[0002] Mosquitoes are important vector organisms, and their larvae have significant research value in disease transmission research, biological control research, ecological research, and drug efficacy evaluation. Mosquito larvae go through several different developmental stages during their growth and development, and larvae at different developmental stages exhibit significant differences in morphology, physiological state, feeding ability, and sensitivity to external environments and pesticides. Therefore, accurately determining the developmental stage of mosquito larvae is a fundamental task in experimental design and results analysis during relevant research and applications.

[0003] Currently, the methods for determining the developmental stage of mosquito larvae mainly rely on the following categories: The first type of method is the age-based method based on rearing time or molting process. Mosquito larvae are continuously reared under laboratory conditions, and their developmental stages are inferred by recording hatching time, molting time, or instar duration. Under ideal conditions, this method can accurately reflect the larval development process. However, this method requires continuous observation and recording of larvae, resulting in a long operating cycle, high labor intensity, and high requirements for experimental conditions and management. Furthermore, this method is generally only applicable to individuals fully reared in the laboratory; for larval samples of unknown origin or collected from the wild, it is difficult to trace their developmental history, thus rendering it unsuitable for direct application.

[0004] The second type of method is age classification based on the overall body size parameters of the larvae. This method typically infers the larval instar by measuring overall dimensional parameters such as body length, width, or weight, combined with their growth trends throughout development. Body length is widely used due to its relative ease of measurement. However, the overall body size of mosquito larvae is significantly influenced by various factors, including nutritional conditions, population density, aquatic environment, temperature, and individual differences. In practical applications, the body length of larvae at the same developmental instar often fluctuates considerably, and the body length ranges of larvae at different instars may overlap. This leads to unstable thresholds for age classification based on body size parameters, limited resolution, and a high risk of misjudgment, making it difficult to establish a reliable and reproducible standardized age classification scheme.

[0005] The third type of method is a manual interpretation method based on empirical morphological characteristics. Some researchers observe the external morphological characteristics of larvae using dissecting microscopes or microscopes, such as head size, body color changes, and the degree of development of rigid structures, to empirically determine their developmental stage. This type of method relies to some extent on the operator's professional experience and subjective judgment, and the judgment results may vary significantly between different operators. At the same time, this method lacks clear and quantifiable judgment indicators, making it difficult to form a unified technical standard, and it is also not conducive to comparing and reproducing results between different laboratories or different studies.

[0006] Furthermore, none of the aforementioned methods have established a clear mathematical model for age determination based on quantifiable morphological parameters, making it difficult to achieve automated, standardized, and objective age determination. Some methods rely on continuous feeding or long-term observation, making it difficult to quickly determine the age of samples from unknown sources, thus limiting their application scenarios. Age determination methods based on overall body shape parameters are easily affected by environmental factors and individual differences, resulting in large fluctuations in parameters for the same age group and overlap between different age groups, leading to unstable determination thresholds and insufficient accuracy and reliability. Experience-based morphological interpretation methods are highly subjective, lack unified quantitative standards, and have poor consistency among different operators, making it difficult to achieve standardized application. Therefore, existing technologies have not yet provided a stable, objective, and easily measurable method for rapidly and accurately determining the developmental age of mosquito larvae, and further improvements are urgently needed. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for identifying the developmental age of mosquito larvae based on the head length and eye distance of mosquito larvae.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is as follows: In a first aspect, the present invention provides a method for identifying the developmental stage of mosquito larvae, which is determined based on the values ​​of the head length and / or eye distance of the mosquito larvae.

[0009] To address the problems of existing methods for determining the larval stage of mosquitoes, such as reliance on continuous feeding records, large fluctuations in overall body size parameters, and strong subjectivity of experience-based judgments, this invention provides a method for identifying the developmental stage of mosquito larvae based on head length and eye distance. By establishing a mathematical function relationship between morphological parameters and developmental stage, the measured head length and eye distance are converted into calculable score values, thereby achieving rapid, accurate, and repeatable determination of the developmental stage of mosquito larvae.

[0010] In a preferred embodiment of the present invention, the mosquito includes at least one of Giant Venus flytraperis, Aedes albopictus, and Culex quinquefasciatus.

[0011] In a preferred embodiment of the present invention, the developmental age includes at least one of the following: first age, second age, third age, and fourth age.

[0012] In a preferred embodiment of the present invention, the developmental age of mosquito larvae is determined by a scoring function, wherein the scoring function is: Score = 1.75·HL + 1.30·ED + 0.30, where HL is the head length of the mosquito larva and ED is the eye distance of the mosquito larva. The developmental age of mosquito larvae is determined based on the Score value.

[0013] In a more preferred embodiment of the present invention, the mosquito larvae to be tested are giant mosquito larvae; a score value ≤ 1.609 indicates a first instar; 1.609 < score value ≤ 2.353 indicates a second instar; 2.353 < score value ≤ 3.302 indicates a third instar; and a score value > 3.302 indicates a fourth instar.

[0014] As a more preferred embodiment of the present invention, if the mosquito larva to be tested is an Aedes albopictus larva; a score value ≤ 1.152 indicates a first instar; 1.152 < score value ≤ 1.47 indicates a second instar; 1.47 < score value ≤ 2.091 indicates a third instar; and a score value > 2.091 indicates a fourth instar.

[0015] As a more preferred embodiment of the present invention, if the mosquito larva to be tested is a Culex pipiens larva; a score value ≤ 1.135 indicates a first instar; 1.135 < score value ≤ 1.505 indicates a second instar; 1.505 < score value ≤ 2.233 indicates a third instar; and a score value > 2.233 indicates a fourth instar.

[0016] In a more preferred embodiment of the present invention, the head length is the straight-line distance from the front edge to the back edge of the mosquito larva's head shell, and the eye distance is the minimum distance between the inner edges of the two compound eyes of the mosquito larva.

[0017] In a preferred embodiment of the present invention, a stereomicroscope is used to take high-resolution pictures of the head of each mosquito larva, and the head images of the mosquito larvae are collected to measure the head length and eye distance.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) This invention uses the head length and eye distance of mosquito larvae as core morphological parameters, avoiding reliance on continuous feeding records, molting process observation or long-term development tracking. It can directly determine the age of a single sample and is applicable to laboratory samples and field samples. It has the advantages of fast determination speed and wide applicability.

[0019] (2) Compared with age classification methods based on overall body shape parameters such as body length, body width or weight, the head length and interocular distance selected in this invention are less affected by environmental factors, nutritional conditions and individual differences, and have better differentiation between different age groups. This can reduce the risk of misjudgment caused by parameter overlap between different age groups and improve the stability and accuracy of age determination.

[0020] (3) This invention further establishes a mathematical scoring model between head length and interocular distance and developmental age, transforming the measured morphological parameters into calculable scoring values, thus realizing the transformation from empirical judgment to vectorized judgment. Compared with existing methods that mainly rely on empirical observation or simple parameter interval comparison, this invention has stronger objectivity, standardization and repeatability.

[0021] (4) The present invention makes a determination by combining a scoring model with the corresponding age scoring interval. It can not only give a clear age result, but also facilitates integration with image acquisition system, image analysis program or other computing device, and has the potential to further realize automated age determination.

[0022] (5) This invention proposes an age-based scoring method based on head length and eye distance. A specific scoring function was established in *Gnaphalium glabra*, and the scoring value was observed to increase with age in *Aedes albopictus* and *Culex quinquefolia*, indicating that the method is highly applicable to *Gnaphalium glabra*, *Aedes albopictus*, and *Culex quinquefolia*. Attached Figure Description

[0023] Figure 1 The values ​​represent the interocular distance, head length, and body length of the larvae. Specifically, a represents the first instar larva of *Aedes albopictus*; b represents the second instar larva of *Aedes albopictus*; c represents the third instar larva of *Aedes albopictus*; d represents the fourth instar larva of *Aedes albopictus*; e represents the first instar larva of *Aedes albopictus*; f represents the second instar larva of *Aedes albopictus*; g represents the third instar larva of *Aedes albopictus*; h represents the fourth instar larva of *Aedes albopictus*; i represents the first instar larva of *Culex pipiens quinquefolius*; j represents the second instar larva of *Culex pipiens quinquefolius*; k represents the third instar larva of *Culex pipiens quinquefolius*; and l represents the fourth instar larva of *Culex pipiens quinquefolius*.

[0024] Figure 2 This diagram illustrates the measurement of the interocular distance, head length, and body length of a giant maggot larva under a microscope. In the diagram, a represents the interocular distance; b represents the head length; and c represents the body length.

[0025] Figure 3 Scatter plot of the distribution of different instars of giant maggot larvae in the space of head length (HL) and eye distance (ED). Figure 4 This is a distribution chart of the scores for different instars of the giant mosquito larvae. Detailed Implementation

[0026] To better illustrate the purpose, technical solution, and advantages of this invention, the invention will be further described below with reference to specific embodiments. Unless otherwise specified, other materials and reagents used in the embodiments are commercially available.

[0027] Example 1 To determine stable morphological parameters suitable for mosquito larval instar determination, statistical analysis was performed on body length, interocular distance, and head length of *Aedes albopictus*, *Culex quinquefolia*, and *Culex quinquefolia* at different instars. The sample sizes for each instar were: 54 first-instar larvae, 49 second-instar larvae, 47 third-instar larvae, and 38 fourth-instar larvae, for a total of 188 larval samples.

[0028] Figure 1 This study presents the distribution data of body length, interocular distance, and head length for different mosquito species (Gastropoda glabripennis, Aedes albopictus, and Culex quinquefolia) during the first to fourth instar periods. Figure 1 a to Figure 1 As shown in d, the interocular distance and head length of *Aedes albopictus* gradually increase at different instars, while the body length varies considerably and exhibits significant fluctuations. Figure 1 e to Figure 1 h) and Culex quinquefolia (h) Figure 1 i to Figure 1 The data from l) also showed a similar trend, with eye distance and head length exhibiting more stable changes and better separation between different instars. While body length showed an increasing trend with instar across different mosquito species, it fluctuated significantly, with some overlap between instars. In contrast, eye distance and head length showed more stable changes across instars and better separation between different instars. Further statistical results indicated that eye distance and head length both exhibited a characteristic of increasing with instar with relatively small fluctuations across different mosquito species, making them suitable as key morphological parameters for instar determination. Therefore, head length (HL) and eye distance (ED) were selected as the basic parameters for establishing the instar scoring model.

[0029] By comparing with body length data, the changes in head length and interocular distance are more stable and can serve as an effective basis for age classification.

[0030] Example 2: Determination of Larval Stage of Giant Flower Mosquito (1) Sample acquisition and processing Larval samples of *Gymnocypris glabripennis* were collected, and their true developmental instars were determined based on continuous rearing records or molting observations. The larvae were divided into four groups: first instar, second instar, third instar, and fourth instar. Larvae of each instar were placed in a glass slide groove or a transparent container, and an appropriate amount of water was added to maintain the natural morphology of the larvae.

[0031] (2) Image acquisition and calibration High-resolution images of each larva's head were taken using a stereomicroscope to measure head length and interocular distance. The images were captured at a resolution of 1000×1000 pixels to ensure accuracy. Figure 2 This demonstrates how to measure the head length of mosquito larvae under a microscope. Figure 2 b) Eye distance ( Figure 2 a) and body length ( Figure 2 c) The image length is calibrated using a microscopic scale to establish the correspondence between pixels and actual length.

[0032] (3) Morphological parameter measurement Using ImageJ image processing software or a microscope imaging system, the head length (the straight-line distance from the anterior to the posterior edge of the head capsule) and interocular distance (the minimum distance between the inner edges of the two compound eyes) of each larval sample were extracted. Each sample was measured three times independently, and the average value was taken as the final result. The corresponding head length and interocular distance values ​​for each sample were recorded separately.

[0033] (4) Establishment of age-based scoring model Based on the known instar larval data of *Gymnocalycium glabra*, statistical analysis was performed on head length and interocular distance to establish an instar scoring function, as shown in equation (1): Score=1.75·HL+1.30·ED+0.30 Formula (1) Where HL represents head length in mm and ED represents interocular distance in mm.

[0034] (5) Scoring and Age Determination Substitute the measured head length and interocular distance values ​​into the scoring function described above to calculate the score for each sample. Based on the distribution of score values ​​for samples from different age groups, determine the corresponding age-specific scoring intervals.

[0035] Table 1 As shown in Table 1, the developmental stage of the giant mosquito larvae is determined based on the range of the score values ​​of the test samples.

[0036] (6) Results and Effects like Figure 3 As shown, the larvae of the magnificent giant mosquito exhibit a clear stratified distribution in the two-dimensional parameter space of head length (HL) and eye distance (ED), with good separability between different instars.

[0037] like Figure 4 As shown, the distribution of score values ​​for samples of different ages exhibits clear interval separation, with virtually no overlap between the ages, indicating that the established scoring model can effectively distinguish between different developmental ages.

[0038] The above results indicate that the age scoring model based on head length and eye distance established in this invention can achieve rapid and accurate determination of the developmental age of giant mosquito larvae.

[0039] (7) To further verify the accuracy of the established scoring model, another batch of independently collected giant mosquito larvae was selected as the verification group. The true age of the verification group was determined based on continuous feeding records or molting observation results, and the head length (HL) and interocular distance (ED) were measured to calculate the corresponding score.

[0040] In the validation population, the sample sizes of first-instar, second-instar, third-instar, and fourth-instar larvae were 40, 40, 40, and 40 respectively (a total of 160).

[0041] The calculated score values ​​were compared with the pre-established age scoring intervals in Table 1. The results showed that the scores of all samples fell within the scoring intervals of their corresponding real ages, and the judgment results were highly consistent with the actual ages, verifying that the scoring model and scoring intervals had good accuracy and reliability.

[0042] Example 3: Determination of the larval stage of Aedes albopictus mosquitoes (1) Sample acquisition and parameter measurement Samples of Aedes albopictus larvae were collected, and their true developmental instars were determined based on continuous rearing records or molting observations. The samples were divided into first, second, third, and fourth instars. Following the method in Example 1, images of the larval heads were acquired and calibrated, and their head length (HL) and interocular distance (ED) were measured.

[0043] (2) Scoring calculation Substitute the measured head length (HL) and interpupillary distance (ED) into the scoring function (1) established in Example 1 to calculate the score value (Score) for each sample.

[0044] (3) Results Analysis The results showed that the score value of Aedes albopictus larvae increased with developmental age, and there was a clear stratified distribution between different ages. Furthermore, compared with Giant Siberian mosquitoes, the score value ranges for each age differed, indicating differences in the distribution of morphological parameters among different mosquito species.

[0045] According to the statistical results, the range of Scores for each instar of Aedes albopictus larvae is shown in Table 2.

[0046] Table 2 The intervals between different age groups are clearly separated and do not overlap, further demonstrating that the scoring method of the present invention also has good age differentiation ability in Aedes albopictus.

[0047] The above results indicate that the scoring method based on head length and interocular distance proposed in this invention also has a good tendency to differentiate age groups in Aedes albopictus.

[0048] (4) To further verify the accuracy of the established scoring function (1) and the corresponding Score value range, another batch of independently collected Aedes albopictus larvae were selected as the verification population.

[0049] The validation population was determined to be of the true developmental age based on continuous feeding records or molting observations, and head length (HL) and interocular distance (ED) were measured using the same method to calculate the corresponding score. In the validation population, the sample sizes of first-instar, second-instar, third-instar, and fourth-instar larvae were 40, 40, 40, and 40, respectively (a total of 160 larvae).

[0050] The calculated score values ​​were compared with the age score ranges established in Table 2. The results showed that the score values ​​of all samples fell within the range of their corresponding true ages, and the age determination results were highly consistent with the actual ages, verifying the accuracy and applicability of the scoring method in Aedes albopictus.

[0051] Example 4: Determination of the larval stage of Culex pipiens quinquefolia (1) Sample acquisition and parameter measurement Larval samples of Culex pipiens quinquefolia were collected, and their developmental stages were determined based on continuous rearing records or molting observations. The samples were divided into first, second, third, and fourth instars. Following the method in Example 1, images of the larval heads were acquired and calibrated, and head length (HL) and interocular distance (ED) were measured.

[0052] (2) Scoring calculation The measured head length (HL) and interpupillary distance (ED) are substituted into the scoring function (1) established in Example 1 to calculate the score value for each sample.

[0053] (3) Results Analysis The analysis results show that the score value of Culex pipiens quinquefolius larvae also increases with age, exhibiting certain stratification characteristics between different age groups. Compared with Giant Venus flavipes, the score value ranges for each age group differ, but the overall trend is consistent.

[0054] Based on the statistical results, the range of Scores for each larval stage of Culex pipiens quinquefolius is shown in Table 3.

[0055] Table 3 The score ranges for each age group increased with developmental stage, and there was a clear separation between adjacent ages, indicating that the scoring method also has good age differentiation ability in Culex pipiens quinquefasciatus.

[0056] The above results further demonstrate that the age scoring method based on head length and interocular distance proposed in this invention also has a good age differentiation trend in Culex pipiens quinquefasciatus.

[0057] (4) To further verify the applicability of the scoring function and scoring interval in Culex pipiens quinquefolius, this invention selected another batch of independently collected Culex pipiens quinquefolius larvae as a verification population.

[0058] The validation population was determined to be of the true developmental age based on continuous feeding records or molting observations, and head length (HL) and interocular distance (ED) were measured using the same method to calculate the corresponding score. In the validation population, the sample sizes of first-instar, second-instar, third-instar, and fourth-instar larvae were 40, 40, 40, and 40, respectively (a total of 160 larvae).

[0059] The calculated score values ​​were compared with the age score ranges established in Table 3. The results showed that the score values ​​of all samples fell within the range of their corresponding true ages, and the age determination results were highly consistent with the actual ages, verifying the accuracy and reliability of the scoring method in Culex pipiens quinquefasciatus.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A method for identifying the developmental stage of mosquito larvae, characterized in that, The determination is made based on the head length and / or eye distance of the mosquito larvae.

2. The method for identifying the developmental stage of mosquito larvae as described in claim 1, characterized in that, The mosquitoes include at least one of Giant Venus flytrapati Shiva, Aedes albopictus, and Culex quinquefasciatus.

3. The method for identifying the developmental stage of mosquito larvae as described in claim 1, characterized in that, The developmental age includes at least one of the following: first age, second age, third age, and fourth age.

4. The method for identifying the developmental stage of mosquito larvae as described in claim 1, characterized in that, The developmental age of mosquito larvae is determined by a scoring function: Score = 1.75·HL + 1.30·ED + 0.30, where HL is the head length of the mosquito larva and ED is the eye distance of the mosquito larva. The developmental age of mosquito larvae is determined based on the Score value.

5. The method for identifying the developmental stage of mosquito larvae as described in claim 4, characterized in that, If the mosquito larvae to be tested are *Gymnodon davidianus* larvae; a score value ≤ 1.609 indicates a first instar; 1.609 < score value ≤ 2.353 indicates a second instar; 2.353 < score value ≤ 3.302 indicates a third instar; and a score value > 3.302 indicates a fourth instar.

6. The method for identifying the developmental stage of mosquito larvae as described in claim 4, characterized in that, If the mosquito larvae to be tested are Aedes albopictus larvae; a score value ≤ 1.152 indicates a first instar; 1.152 < score value ≤ 1.47 indicates a second instar; 1.47 < score value ≤ 2.091 indicates a third instar; and a score value > 2.091 indicates a fourth instar.

7. The method for identifying the developmental stage of mosquito larvae as described in claim 4, characterized in that, If the mosquito larvae to be tested are Culex pipiens larvae; a score value ≤ 1.135 indicates a first instar; 1.135 < score value ≤ 1.505 indicates a second instar; 1.505 < score value ≤ 2.233 indicates a third instar; and a score value > 2.233 indicates a fourth instar.

8. The method for identifying the developmental stage of mosquito larvae as described in claim 1, characterized in that, The head length is the straight-line distance from the front edge to the back edge of the mosquito larva's head shell, and the eye distance is the minimum distance between the inner edges of the two compound eyes of the mosquito larva.

9. The method for identifying the developmental stage of mosquito larvae as described in claim 8, characterized in that, High-resolution images of the head of each mosquito larva were taken using a stereomicroscope to measure head length and interocular distance.

Images