CN114324334A - Evaluation system of mango germplasm resources nutritional quality - Google Patents
Evaluation system of mango germplasm resources nutritional quality Download PDFInfo
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Abstract
The invention belongs to the technical field of germplasm evaluation, and discloses an evaluation system for mango germplasm resource nutritional quality, which comprises the following steps: the device comprises a culture solution preparation module, a mango seed cultivation module, a temperature monitoring module, a temperature adjusting module, a central control module, an illumination module, an image acquisition module, an image processing module, an image analysis module and a quality evaluation module. The mango germplasm resource nutrition quality evaluation system provided by the invention utilizes the image acquisition module to shoot the seed germination picture, automatically draws a seed germination curve on the basis of the processed image, performs significance difference comparison, extracts the related index parameters of mango seed nutrition quality, can perform high-throughput processing, obtains the dynamic index of the seed germination process, improves the efficiency of seed nutrition quality evaluation and improves the scientificity of evaluation. The evaluation system disclosed by the invention is simple in structure, can realize accurate and reasonable evaluation on the nutritional quality of mango germplasm resources, and provides guidance for mango cultivation.
Description
Technical Field
The invention belongs to the technical field of germplasm evaluation, and particularly relates to an evaluation system for mango germplasm resource nutritional quality.
Background
At present: mango is an original Indian evergreen big arbor of Anacardiaceae, leafy leatheroid, intergrown; small, miscellaneous, yellow or yellowish, forming a terminal panicle. Big stone, squashed, 5-10 cm long, 3-4.5 cm wide, yellow when ripe, sweet in taste, and hard stone. Mango is one of the famous tropical fruits, contains sugar, protein and crude fiber, contains particularly high carotene content which is a precursor of vitamin A and is rare in all fruits, has high vitamin C content, and also contains main nutrient components of minerals, protein, fat and sugar.
In the cultivation of mangoes, the quality of mango seeds has a significant influence on the quality and yield of the fruits. However, in the prior art, a system capable of evaluating the nutritional quality of mango seed germplasm resources is not available, and mango seed evaluation before cultivation cannot be realized.
Through the above analysis, the problems and defects of the prior art are as follows: in the prior art, a system capable of evaluating the nutritional quality of mango seed germplasm resources is unavailable, and mango seed evaluation before cultivation cannot be realized.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an evaluation system for mango germplasm resource nutritional quality.
The invention is realized in such a way, and the mango germplasm resource nutrition quality evaluation system comprises:
the system comprises a culture solution preparation module, a mango seed cultivation module, a temperature monitoring module, a temperature adjusting module, a central control module, an illumination module, an image acquisition module, an image processing module, an image analysis module and a quality evaluation module;
the culture solution preparation module is connected with the central control module and used for preparing the mango seed culture solution through a culture solution preparation program to obtain the mango seed culture solution;
the mango seed cultivation module is connected with the central control module and used for placing the mango seed culture solution into a light-tight container through a mango seed cultivation program and placing mango seeds into the mango seed culture solution for cultivation;
the temperature monitoring module is connected with the central control module and used for monitoring the temperature of the mango seed cultivation environment through the temperature sensor to obtain temperature information;
the temperature adjusting module is connected with the central control module and used for adjusting the temperature according to the acquired temperature information through a temperature adjusting program;
the temperature adjustment is performed according to the acquired temperature information through a temperature adjustment program, and the method comprises the following steps:
acquiring the temperature requirement of mango growth, and determining the temperature range during mango cultivation; the temperature requirement for mango growth is acquired, and comprises the following steps: searching mango growth temperature in a webpage;
determining the synchronization frequency of a local object and a remote data source, wherein the remote data source is a database on a remote Web;
representing remote data source average variation frequency lambda by using Poisson processiWherein i is 1,2, …, n, n represents the number of remote data sources;
determining the average novelty:
from the resulting mean variation frequency λiDetermining objects, i.e. data items e in a remote Web databaseiCorresponding synchronization frequency fiMaking the average novelty of the local database meet the synchronous resource limitation
At the maximum, the number of the first,
determining the updating frequency according to the data timeliness:
the ith data record r maintained by the data capture system at time tiThe novelty of (c) is as follows:
then the average timeliness of the data record set S consisting of N data records is as follows:
the data record set S is averaged over time and measured:
calculating to obtain theoretical synchronization frequency of each object by using a Lagrange multiplier, and then synchronizing object data according to the theoretical synchronization frequency to enable the average novelty of a local database to reach the maximum value;
the synchronizing the object data according to the theoretical synchronization frequency comprises the following steps:
for all (s, a) initialization table entries Q0(s,a)＝0；
Wherein Q represents professional representation of computer machine learning field, i.e. Q is representation form of reinforcement learning, s represents state, a represents action, Q (s, a) represents result state of applying action a to state s; initializing to 0 value, namely not learning initialization value; in each scenario, the range to the data source is taken as its activity, resulting in a reward value of Ri：
And updating the Q value in a time period 0-t:
wherein q isjRepresents the resultant state value, R, of the jth data record obtained by reinforcement learning in the time interval 0-tjRepresenting the return value obtained by reinforcement learning of the jth data record in the time interval 0-t;
under the premise of resource limitation, namely the maximum interaction times M with the server is a constant value, so that the novelty
Maximum value, F (F)i,λi) Indicating the novelty, ω, corresponding to the ith data recordiIs the importance weight;
detecting the supply amount of warm air and the temperature of a warm air outlet in the working process of the heating device;
judging whether the detected temperature at the warm air outlet is within the temperature range of the mango cultivation, adjusting, and repeatedly and circularly adjusting at intervals;
and the central control module is connected with the culture solution preparation module, the mango seed cultivation module, the temperature monitoring module and the temperature regulation module and is used for controlling the operation of each connection module through the main control computer and ensuring the normal operation of each module.
Further, the mango germplasm resource nutritional quality evaluation system comprises:
the illumination module is connected with the central control module and used for illuminating the mango seeds in cultivation through an illuminating lamp;
the image acquisition module is connected with the central control module and is used for acquiring mango seed images through a camera arranged above the mango seed culture solution to obtain mango seed germination images;
the image processing module is connected with the central control module and is used for processing the collected mango seed germination images through an image processing program to obtain processed images;
the image analysis module is connected with the central control module and used for analyzing the processed image through an image analysis program to obtain an image analysis result;
and the quality evaluation module is connected with the central control module and is used for evaluating the nutritional quality of the mango seeds according to the image analysis result through a quality evaluation program to obtain an evaluation result.
Further, the mango seed culture solution comprises, by mass, 5-6 parts of potassium nitrate, 3-4 parts of calcium superphosphate, 3-4 parts of urea, 1-2 parts of magnesium sulfate, 2-3 parts of manganese sulfate, 1-3 parts of zinc sulfate, 1-2 parts of potassium chloride, 2-3 parts of gamma-polyglutamic acid and 1-2 parts of boric acid.
Further, the preparation of mango seed culture solution by the culture solution preparation procedure to obtain mango seed culture solution comprises:
mixing potassium nitrate, calcium superphosphate, urea, magnesium sulfate, manganese sulfate, zinc sulfate and potassium chloride, and uniformly stirring to obtain a mixed solution;
adding gamma-polyglutamic acid into the mixed solution, and performing ultrasonic dispersion to obtain a dispersion solution;
and (3) dropwise adding boric acid into the dispersion liquid, stirring, and adjusting the pH value of the dispersion liquid to 6.5-7 to obtain the mango seed culture solution.
Further, the light-tight container is a dark blue inner container.
Further, the fractional low-order fuzzy function of the digital modulation signal x (t) of the temperature sensor is represented as:
wherein tau is time delay shift, f is Doppler shift, 0 < a, b < alpha/2, x*(t) denotes the conjugate of x (t), when x (t) is a real signal, x (t)＜p＞＝x(t)＜p＞sgn (x (t)); when x (t) is a complex signal, [ x (t)]＜p＞＝x(t)p-1x*(t)。
Further, the analyzing the processed image by the image analysis program to obtain an image analysis result includes:
manually selecting all images of seeds before germination, counting the number of germinated seeds at different time points, and drawing paths of hypocotyl length and radicle length of a single plant in the last image; automatically recording the seed germination process through continuous photographing, and acquiring related index parameters of seed germination by utilizing image analysis; the related index parameters of the seed germination comprise: germination uniformity: the time taken for the germination percentage to increase from 40% to 60%, the time taken for the germination percentage to increase from 25% to 75%, the time taken for the germination percentage to increase from 20% to 80%, the time taken for the germination percentage to increase from 16% to 84%, and the time taken for the germination percentage to increase from 10% to 90%; germination speed: average germination time, maximum germination rate, time taken for the germination rate to reach 10%, and time taken for the germination rate to reach 50%; area under the germination curve; hypocotyl length, radicle length.
Further, the evaluation of the mango seed nutrition quality is performed on the image analysis result through a quality evaluation program to obtain an evaluation result, and the evaluation result comprises:
acquiring an image analysis result and extracting various data in the image analysis result;
associating each item of data with the data type to obtain associated information;
and importing the associated information into a data analysis unit through an Excel table to generate an evaluation result of the mango seed nutritional quality.
It is another object of the present invention to provide a computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface to apply the evaluation system of mango germplasm nutritional quality when executed on an electronic device.
It is another object of the present invention to provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to apply the mango germplasm resource nutritional quality evaluation system.
By combining all the technical schemes, the invention has the advantages and positive effects that: the mango germplasm resource nutrition quality evaluation system provided by the invention utilizes the image acquisition module to shoot the seed germination picture, utilizes the computer software package Germinator of the data analysis unit to automatically draw the seed germination curve on the basis of the processed image, performs significant difference comparison, extracts the related index parameters of the mango seed nutrition quality, can perform high-throughput processing, obtains the dynamic index of the seed germination process, improves the efficiency of seed nutrition quality evaluation and the scientificity of evaluation. The evaluation system disclosed by the invention is simple in structure, can realize accurate and reasonable evaluation on the nutritional quality of mango germplasm resources, and provides guidance for mango cultivation.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
Fig. 1 is a structural block diagram of an evaluation system for mango germplasm resource nutritional quality provided by an embodiment of the invention.
Fig. 2 is a flow chart of an evaluation method for mango germplasm resource nutritional quality provided by the embodiment of the invention.
FIG. 3 is a flow chart of mango seed culture solution preparation by the culture solution preparation procedure provided in the embodiment of the present invention.
Fig. 4 is a flowchart of temperature adjustment according to the acquired temperature information by the temperature adjustment program according to the embodiment of the present invention.
Fig. 5 is a flowchart of evaluating the nutritional quality of mango seeds by using the image analysis result according to the quality evaluation program, so as to obtain an evaluation result.
In the figure: 1. a culture solution preparation module; 2. a mango seed cultivation module; 3. a temperature monitoring module; 4. a temperature adjustment module; 5. a central control module; 6. an illumination module; 7. an image acquisition module; 8. an image processing module; 9. an image analysis module; 10. and a quality evaluation module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides an evaluation system for mango germplasm resource nutrition quality, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the system for evaluating the nutritional quality of mango germplasm resources provided by the embodiment of the present invention includes:
the culture solution preparation module 1 is connected with the central control module 5 and is used for preparing mango seed culture solution through a culture solution preparation program to obtain mango seed culture solution;
the mango seed cultivation module 2 is connected with the central control module 5 and used for placing the mango seed culture solution into a light-tight container through a mango seed cultivation program and placing mango seeds into the mango seed culture solution for cultivation;
the temperature monitoring module 3 is connected with the central control module 5 and used for monitoring the temperature of the mango seed cultivation environment through a temperature sensor to obtain temperature information;
the temperature adjusting module 4 is connected with the central control module 5 and is used for adjusting the temperature according to the acquired temperature information through a temperature adjusting program;
the central control module 5 is connected with the culture solution preparation module 1, the mango seed cultivation module 2, the temperature monitoring module 3, the temperature adjusting module 4, the illumination module 6, the image acquisition module 7, the image processing module 8, the image analysis module 9 and the quality evaluation module 10, and is used for controlling the operation of each connecting module through a main control computer and ensuring the normal operation of each module;
the illumination module 6 is connected with the central control module 5 and is used for illuminating the mango seeds under cultivation through an illuminating lamp;
the image acquisition module 7 is connected with the central control module 5 and used for acquiring mango seed images through a camera arranged above the mango seed culture solution to obtain mango seed germination images;
the image processing module 8 is connected with the central control module 5 and is used for processing the collected mango seed germination images through an image processing program to obtain processed images;
the image analysis module 9 is connected with the central control module 5 and used for analyzing the processed image through an image analysis program to obtain an image analysis result;
and the quality evaluation module 10 is connected with the central control module 5 and is used for evaluating the nutritional quality of the mango seeds according to the image analysis result through a quality evaluation program to obtain an evaluation result.
As shown in fig. 2, the method for evaluating the nutritional quality of mango germplasm resources provided by the embodiment of the invention comprises the following steps:
s101, preparing a mango seed culture solution by a culture solution preparation module by utilizing a culture solution preparation program to obtain a mango seed culture solution;
s102, placing mango seed culture solution into a light-tight container by a mango seed culture module by utilizing a mango seed culture program, and placing mango seeds into the mango seed culture solution for culture;
s103, monitoring the temperature of the mango seed cultivation environment by using a temperature sensor through a temperature monitoring module to obtain temperature information; adjusting the temperature by using a temperature adjusting program through a temperature adjusting module according to the acquired temperature information;
s104, controlling the operation of each connecting module by using a main control computer through a central control module to ensure the normal operation of each module; the illumination module illuminates mango seeds under cultivation by using an illuminating lamp;
s105, acquiring mango seed images by using a camera arranged above the mango seed culture solution through an image acquisition module to obtain mango seed germination images; processing the collected mango seed germination images by using an image processing program through an image processing module to obtain processed images;
s106, analyzing the processed image by using an image analysis program through an image analysis module to obtain an image analysis result; and evaluating the nutritional quality of the mango seeds by using a quality evaluation program through a quality evaluation module to obtain an evaluation result.
The mango seed culture solution provided by the embodiment of the invention comprises, by mass, 5-6 parts of potassium nitrate, 3-4 parts of calcium superphosphate, 3-4 parts of urea, 1-2 parts of magnesium sulfate, 2-3 parts of manganese sulfate, 1-3 parts of zinc sulfate, 1-2 parts of potassium chloride, 2-3 parts of gamma-polyglutamic acid and 1-2 parts of boric acid.
As shown in fig. 3, the preparation of mango seed culture solution by the culture solution preparation procedure according to the embodiment of the present invention to obtain mango seed culture solution includes:
s201, mixing potassium nitrate, calcium superphosphate, urea, magnesium sulfate, manganese sulfate, zinc sulfate and potassium chloride, and uniformly stirring to obtain a mixed solution;
s202, adding gamma-polyglutamic acid into the mixed solution, and performing ultrasonic dispersion to obtain a dispersion solution;
s203, dripping boric acid into the dispersion liquid, stirring, and adjusting the pH value of the dispersion liquid to 6.5-7 to obtain the mango seed culture liquid.
The light-tight container provided by the embodiment of the invention is a dark blue inner container.
The fractional low-order fuzzy function of the digital modulation signal x (t) of the temperature sensor provided by the embodiment of the invention is expressed as follows:
wherein tau is time delay shift, f is Doppler shift, 0 < a, b < alpha/2, x*(t) denotes the conjugate of x (t), when x (t) is a real signal, x (t)＜p＞＝|x(t)|＜p＞sgn (x (t)); when x (t) is a complex signal, [ x (t)]＜p＞＝|x(t)|p-1x*(t)。
As shown in fig. 4, the temperature adjustment according to the acquired temperature information by the temperature adjustment program according to the embodiment of the present invention includes:
s301, acquiring the temperature requirement for mango growth, and determining the temperature range for mango cultivation;
s302, detecting the supply quantity of warm air and the temperature of a warm air outlet in the working process of the heating device;
and S303, judging whether the detected temperature at the warm air outlet is within the temperature range of the mango cultivation, adjusting, and repeatedly and circularly adjusting at intervals.
The method for acquiring the temperature requirement for mango growth provided by the embodiment of the invention comprises the following steps: searching mango growth temperature in a webpage;
determining the synchronization frequency of a local object and a remote data source, wherein the remote data source is a database on a remote Web;
representing remote data source average variation frequency lambda by using Poisson processiWherein i is 1,2, …, n, n represents the number of remote data sources;
determining the average novelty:
from the resulting mean variation frequency λiDetermining objects, i.e. data items e in a remote Web databaseiCorresponding synchronization frequency fiMaking the average novelty of the local database meet the synchronous resource limitation
At the maximum, the number of the first,
determining the updating frequency according to the data timeliness:
the ith data record r maintained by the data capture system at time tiThe novelty of (c) is as follows:
then the average timeliness of the data record set S consisting of N data records is as follows:
the data record set S is averaged over time and measured:
calculating to obtain theoretical synchronization frequency of each object by using a Lagrange multiplier, and then synchronizing object data according to the theoretical synchronization frequency to enable the average novelty of a local database to reach the maximum value;
the synchronizing the object data according to the theoretical synchronization frequency comprises the following steps:
for all (s, a) initialization table entries Q0(s,a)＝0；
Wherein Q represents professional representation of computer machine learning field, i.e. Q is representation form of reinforcement learning, s represents state, a represents action, Q (s, a) represents result state of applying action a to state s; initializing to 0 value, namely not learning initialization value; in each scenario, the range to the data source is taken as its activity, resulting in a reward value of Ri：
And updating the Q value in a time period 0-t:
wherein q isjRepresents the resultant state value, R, of the jth data record obtained by reinforcement learning in the time interval 0-tjDenotes the jthRecording the data into a return value obtained by reinforcement learning within a time interval of 0-t;
under the premise of resource limitation, namely the maximum interaction times M with the server is a constant value, so that the novelty
Maximum value, F (F)i,λi) Indicating the novelty, ω, corresponding to the ith data recordiIs the importance weight.
The image analysis method for analyzing the processed image by the image analysis program provided by the embodiment of the invention to obtain the image analysis result comprises the following steps:
manually selecting all images of seeds before germination, counting the number of germinated seeds at different time points, and drawing paths of hypocotyl length and radicle length of a single plant in the last image; automatically recording the seed germination process through continuous photographing, and acquiring related index parameters of seed germination by utilizing image analysis; the related index parameters of the seed germination comprise: germination uniformity: the time taken for the germination percentage to increase from 40% to 60%, the time taken for the germination percentage to increase from 25% to 75%, the time taken for the germination percentage to increase from 20% to 80%, the time taken for the germination percentage to increase from 16% to 84%, and the time taken for the germination percentage to increase from 10% to 90%; germination speed: average germination time, maximum germination rate, time taken for the germination rate to reach 10%, and time taken for the germination rate to reach 50%; area under the germination curve; hypocotyl length, radicle length.
As shown in fig. 5, the evaluation of the nutritional quality of mango seeds by using the image analysis result according to the quality evaluation program provided by the embodiment of the present invention to obtain an evaluation result includes:
s401, acquiring an image analysis result and extracting various data in the image analysis result;
s402, associating each item of data with the data type to obtain associated information;
and S403, importing the related information into a data analysis unit through an Excel table to generate an evaluation result of the mango seed nutritional quality.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made by those skilled in the art within the technical scope of the present invention disclosed herein, which is within the spirit and principle of the present invention, should be covered by the present invention.
Claims (10)
1. The mango germplasm resource nutritional quality evaluation system is characterized by comprising:
the culture solution preparation module is connected with the central control module and used for preparing the mango seed culture solution through a culture solution preparation program to obtain the mango seed culture solution;
the mango seed cultivation module is connected with the central control module and used for placing the mango seed culture solution into a light-tight container through a mango seed cultivation program and placing mango seeds into the mango seed culture solution for cultivation;
the temperature monitoring module is connected with the central control module and used for monitoring the temperature of the mango seed cultivation environment through the temperature sensor to obtain temperature information;
the temperature adjusting module is connected with the central control module and used for adjusting the temperature according to the acquired temperature information through a temperature adjusting program;
the temperature adjustment is performed according to the acquired temperature information through a temperature adjustment program, and the method comprises the following steps:
acquiring the temperature requirement of mango growth, and determining the temperature range during mango cultivation; the temperature requirement for mango growth is acquired, and comprises the following steps: searching mango growth temperature in a webpage;
determining the synchronization frequency of a local object and a remote data source, wherein the remote data source is a database on a remote Web;
representing remote data source average variation frequency lambda by using Poisson processiWherein i is 1,2, …, n, n represents the number of remote data sources;
determining the average novelty:
from the resulting mean variation frequency λiDetermining objects, i.e. data items e in a remote Web databaseiCorresponding synchronization frequency fiMaking the average novelty of the local database meet the synchronous resource limitation
At the maximum, the number of the first,
determining the updating frequency according to the data timeliness:
the ith data record r maintained by the data capture system at time tiThe novelty of (c) is as follows:
then the average timeliness of the data record set S consisting of N data records is as follows:
the data record set S is averaged over time and measured:
calculating to obtain theoretical synchronization frequency of each object by using a Lagrange multiplier, and then synchronizing object data according to the theoretical synchronization frequency to enable the average novelty of a local database to reach the maximum value;
the synchronizing the object data according to the theoretical synchronization frequency comprises the following steps:
for all (s, a) initialization table entries Q0(s,a)＝0；
Wherein Q represents professional representation of computer machine learning field, i.e. Q is representation form of reinforcement learning, s represents state, a represents action, Q (s, a) represents result state of applying action a to state s; initializing to 0 value, namely not learning initialization value; in each scenario, the range to the data source is taken as its activity, resulting in a reward value of Ri：
And updating the Q value in a time period 0-t:
wherein q isjRepresents the resultant state value, R, of the jth data record obtained by reinforcement learning in the time interval 0-tjRepresenting the return value obtained by reinforcement learning of the jth data record in the time interval 0-t;
under the premise of resource limitation, namely the maximum interaction times M with the server is a constant value, so that the novelty
Maximum value, F (F)i,λi) Indicating the novelty, ω, corresponding to the ith data recordiIs the importance weight;
detecting the supply amount of warm air and the temperature of a warm air outlet in the working process of the heating device;
judging whether the detected temperature at the warm air outlet is within the temperature range of the mango cultivation, adjusting, and repeatedly and circularly adjusting at intervals;
and the central control module is connected with the culture solution preparation module, the mango seed cultivation module, the temperature monitoring module and the temperature regulation module and is used for controlling the operation of each connection module through the main control computer and ensuring the normal operation of each module.
2. The mango germplasm resource nutritional quality evaluation system of claim 1, wherein the mango germplasm resource nutritional quality evaluation system comprises:
the illumination module is connected with the central control module and used for illuminating the mango seeds in cultivation through an illuminating lamp;
the image acquisition module is connected with the central control module and is used for acquiring mango seed images through a camera arranged above the mango seed culture solution to obtain mango seed germination images;
the image processing module is connected with the central control module and is used for processing the collected mango seed germination images through an image processing program to obtain processed images;
the image analysis module is connected with the central control module and used for analyzing the processed image through an image analysis program to obtain an image analysis result;
and the quality evaluation module is connected with the central control module and is used for evaluating the nutritional quality of the mango seeds according to the image analysis result through a quality evaluation program to obtain an evaluation result.
3. The mango germplasm resource nutrition quality evaluation system according to claim 1, wherein the mango seed culture solution comprises, by mass, 5-6 parts of potassium nitrate, 3-4 parts of calcium superphosphate, 3-4 parts of urea, 1-2 parts of magnesium sulfate, 2-3 parts of manganese sulfate, 1-3 parts of zinc sulfate, 1-2 parts of potassium chloride, 2-3 parts of gamma-polyglutamic acid and 1-2 parts of boric acid.
4. The mango germplasm resource nutrition quality evaluation system of claim 1, wherein the preparation of mango seed culture solution through a culture solution preparation program to obtain mango seed culture solution comprises:
mixing potassium nitrate, calcium superphosphate, urea, magnesium sulfate, manganese sulfate, zinc sulfate and potassium chloride, and uniformly stirring to obtain a mixed solution;
adding gamma-polyglutamic acid into the mixed solution, and performing ultrasonic dispersion to obtain a dispersion solution;
and (3) dropwise adding boric acid into the dispersion liquid, stirring, and adjusting the pH value of the dispersion liquid to 6.5-7 to obtain the mango seed culture solution.
5. The mango germplasm resource nutritional quality evaluation system of claim 1, wherein the light-tight container is a dark blue inner container.
6. The mango germplasm resource nutritional quality evaluation system according to claim 1, wherein the fractional low-order fuzzy function of the digital modulation signal x (t) of the temperature sensor is represented as:
wherein tau is time delay shift, f is Doppler shift, 0 < a, b < alpha/2, x*(t) denotes the conjugate of x (t), when x (t) is a real signal, x (t)＜p＞＝|x(t)|＜p＞sgn (x (t)); when x (t) is a complex signal, [ x (t)]＜p＞＝|x(t)|p-1x*(t)。
7. The mango germplasm resource nutritional quality evaluation system of claim 2, wherein the analysis of the processed image by the image analysis program to obtain the image analysis result comprises:
manually selecting all images of seeds before germination, counting the number of germinated seeds at different time points, and drawing paths of hypocotyl length and radicle length of a single plant in the last image; automatically recording the seed germination process through continuous photographing, and acquiring related index parameters of seed germination by utilizing image analysis; the related index parameters of the seed germination comprise: germination uniformity: the time taken for the germination percentage to increase from 40% to 60%, the time taken for the germination percentage to increase from 25% to 75%, the time taken for the germination percentage to increase from 20% to 80%, the time taken for the germination percentage to increase from 16% to 84%, and the time taken for the germination percentage to increase from 10% to 90%; germination speed: average germination time, maximum germination rate, time taken for the germination rate to reach 10%, and time taken for the germination rate to reach 50%; area under the germination curve; hypocotyl length, radicle length.
8. The mango germplasm resource nutritional quality evaluation system of claim 2, wherein the evaluation of mango seed nutritional quality by the image analysis result through a quality evaluation program to obtain an evaluation result comprises:
acquiring an image analysis result and extracting various data in the image analysis result;
associating each item of data with the data type to obtain associated information;
and importing the associated information into a data analysis unit through an Excel table to generate an evaluation result of the mango seed nutritional quality.
9. A computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for applying the mango germplasm nutritional quality assessment system of any one of claims 1 to 8 when executed on an electronic device.
10. A computer readable storage medium storing instructions which, when executed on a computer, cause the computer to apply the mango germplasm resource nutritional quality assessment system of any one of claims 1 to 8.
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