CN110567941B - Rice seed moisture content grading detection method based on main element spectral intensity - Google Patents
Rice seed moisture content grading detection method based on main element spectral intensity Download PDFInfo
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Abstract
The invention provides a rice seed moisture content grading detection method, which comprises the following steps: s1, selecting rice seeds, putting the rice seeds into a drying bottle, adding distilled water with different masses, and preparing standard rice seed samples; s2, measuring the spectrum of the standard rice seed sample by using a laser-induced breakdown spectrometer in a scanning mode; s3, drying the laser-induced breakdown spectrum of the standard rice seed sample; s4, obtaining the strongest spectral line intensity of the main elements of the rice seeds after drying treatment, and constructing a seed moisture content grading prediction model by utilizing a neural network to obtain the relationship between the seed moisture content and the strongest spectral line intensity of the main elements; s5, obtaining the spectrum of the sample of the rice seed to be measured by adopting a scanning measurement mode; s6, drying the laser-induced breakdown spectrum of the rice seed sample to be detected; and S7, judging the water content of the rice seeds to be detected according to the obtained water content prediction model of the rice seeds and the strongest spectral line intensity of the main elements of all the measurement points in the rice seed samples to be detected.
Description
Technical Field
The invention relates to the technical field of rice seed detection, in particular to a rice seed moisture content grading rapid detection method based on main element spectral intensity.
Background
The rice is one of the most important grain crops in China, at present, the sowing area of the rice in China accounts for 1/4 of the total grain crop area, but the yield of the rice accounts for 1/2 of the total grain crop yield in China. The fluctuation of the rice yield can directly influence the grain supply and threaten the grain safety in China.
The water content of the rice seeds is the percentage of the weight of the water contained in the seeds to the total weight of the seeds, and is also called the water content of the rice seeds. The moisture content of the seeds is one of important indexes reflecting the quality and the storage activity of the seeds and is also one of indexes needing to be measured before the seeds are stored and transported.
The water content in rice seeds directly influences the survival rate of rice seedlings, and further has important influence on the yield of grains. Research shows that the storage time and the sprouting rate of rice seeds are directly influenced by the moisture content in the rice seeds, the seeds with the moisture content of about 6 percent can be stored for a long time, and the sprouting rate of the seeds with the moisture content of more than 14 percent in the next year is reduced by 40 percent.
The method for measuring the water content of the rice seeds is various, and mainly comprises a low constant temperature drying method, a high constant temperature drying method, a rapid moisture meter method and the like. According to the regulation of international seed inspection regulation moisture determination, the low constant temperature drying method is a standard method for determining the moisture content of seeds and is suitable for determining the moisture content of seeds of all species. However, since the low constant temperature drying method takes (17 ± 1) hours of measurement, on one hand, the sample needs to be in an oven overnight, which has a certain potential safety hazard; on the other hand, the method is relatively time-consuming and brings inconvenience to inspection work. Therefore, the accurate and efficient method for detecting the water content of the rice seeds can provide great convenience for the rapid detection, storage and breeding of the rice seeds.
At present, the water content of rice seeds has been analyzed by spectroscopic analysis, but these researchers have used reflectance spectra of rice seeds. The reflection spectrum can only reflect the water content on the surface of the rice seeds, but cannot reflect the water content in the rice seeds.
Disclosure of Invention
In view of the above, the invention provides a rice seed moisture content classification detection method based on the spectral intensity of the main elements, which has higher accuracy and can quickly measure.
A rice seed moisture content grading detection method comprises the following steps:
s1, selecting rice seeds which are full in grains, do not mildew, are basically the same in size and shape and are short in physiological maturity, and removing inclusions and mixed seeds; packaging the screened seeds into a drying bottle according to groups, adding distilled water with different masses, and making into standard rice seed samples with different water contents;
s2, measuring the spectra of the rice seed samples with different water content standards by a laser-induced breakdown spectrometer in a scanning measurement mode;
s3, denoising the laser-induced breakdown spectrum of the standard rice seed sample;
s4, obtaining the intensity of the strongest spectral line of the main elements Si, K, P, Ca, Fe, Al, Mg, Na, Ti and CN molecular chains of the rice seed sample according to the standard rice seed laser-induced breakdown spectrum after denoising treatment. And (3) constructing a hierarchical prediction model of the water content of the rice seeds by using a neural network, and obtaining the relation between the water content of the rice seeds and the strongest spectral line intensity of the main elements of the rice seed sample.
In order to reduce the influence of the pollution on the surface of the rice seeds on the grading detection of the water content of the rice seeds, if the number of times of measurement on the same point of the same rice seed is N1, deleting the data of the previous x1(x1< N1) times of measurement, and constructing a grading prediction model of the water content of the rice seeds by only using the data of the next y1(y1 ═ N1-x1) times of measurement;
s5, measuring the spectrum of the rice seed sample to be measured by a laser-induced breakdown spectrometer in a scanning measurement mode;
s6, carrying out denoising treatment on the laser-induced breakdown spectrum of the rice seed sample to be detected;
and S7, judging the water content of the rice seed to be detected according to the obtained rice seed water content prediction model and the strongest spectral line intensity of the main elements of all the measurement points of the rice seed sample to be detected. Similarly, in order to reduce the influence of the pollution on the surface of the rice seed to be measured on the grading detection of the water content of the rice seed to be measured, if the number of times of measurement at the same point of the same rice seed to be measured is N2, the data of the previous x2 times (x2< N2) times are deleted, and the water content of the rice seed to be measured is judged by only using the data of the later y2 times (y2 is N2-x 2).
By controlling the measurement conditions, the laser-induced breakdown spectroscopy can reflect the water content in the rice seeds, so that the water content of the rice seeds can be measured more accurately. Meanwhile, the laser-induced breakdown spectroscopy is a nondestructive spectrum detection method, and cannot damage rice seeds.
The method analyzes the laser-induced breakdown spectrum intensity of the main elements of the rice seeds, constructs a rice seed water content classification main element laser-induced breakdown spectrum intensity analysis model, and can detect the water content of the rice seeds according to the model.
The rice seed water content grading detection method based on the main element spectral intensity has the following beneficial effects:
the invention obtains the laser-induced breakdown spectrum of the sample by scanning and measuring the rice seed sample to be measured, and obtains the strength of the strongest spectral line of the molecular chains of main elements Si, K, P, Ca, Fe, Al, Mg, Na, Ti and CN of the rice seed sample through the spectrum. And judging the water content of the rice seed to be detected according to a prediction model between the water content of the rice seed and the strongest spectral line intensity of the main elements of the rice seed and the strongest spectral line intensities of the main elements of all measurement points of the sample to be detected. The method can greatly reduce the time required for judging the water content of the rice seeds while accurately judging the water content of the rice seeds to be detected, improves the efficiency and the accuracy for judging the water content of the rice seeds, and can be used for online judgment and measurement of the water content of the rice seeds.
Drawings
Fig. 1 is a flow chart of a rice seed moisture content grading rapid detection method based on spectral intensity of major elements according to an embodiment of the present invention.
Detailed Description
As shown in figure 1, a method for rapidly detecting the moisture content of rice seeds by classification comprises the following steps:
s1, selecting 30 rice seeds which are full, have no mildew, basically the same size and shape and are mature in physiology, and removing impurities and mixed seeds; and packaging the screened seeds into a drying bottle according to groups, and adding distilled water with different masses to prepare standard rice seed samples with different water contents.
And S2, measuring the spectrum of the standard rice seed sample with the water content of 10% and 15% by using an RT100-HP type laser induced breakdown spectrometer in a scanning measurement mode.
Optionally, depending on the technical parameters of the instrument used, the spectral range measured: 222.232-894.746 nm.
S3, denoising the laser-induced breakdown spectrum of the standard rice seed sample.
S4, obtaining the intensity of the strongest spectral line of the main elements Si, K, P, Ca, Fe, Al, Mg, Na, Ti and CN molecular chains of the rice seed sample according to the standard rice seed laser-induced breakdown spectrum after denoising treatment. And (3) constructing a hierarchical prediction model of the water content of the rice seeds by using a neural network, and obtaining the relation between the water content of the rice seeds and the strongest spectral line intensity of the main elements of the rice seed sample.
In order to reduce the influence of the pollution on the surface of the rice seeds on the grading detection of the water content of the rice seeds, the number of times of measurement at the same point of the same rice seed is N1, the data of the former x1 times (x1< N1) times are deleted, and the grading prediction model of the water content of the rice seeds is constructed by only using the data of the latter y1 times (y1 is N1-x 1).
Optionally, the method for constructing the water content prediction model of the rice seed sample can select a neural network method, and can also select other methods, such as a partial least square method, a support vector machine method and the like.
Optionally, the size of x1 in the deletion data is determined according to the pollution condition of the rice seed surface, and x1 is 4.
And S5, measuring the spectrum of the rice seed sample to be measured by using a laser-induced breakdown spectrometer in a scanning measurement mode.
The spectral measurement manner and the measurement conditions should be the same as those in step S2.
S6, denoising the laser-induced breakdown spectrum of the rice seed sample to be detected.
The method for denoising the laser-induced breakdown spectroscopy of the rice seed sample to be measured should be the same as that of step S3.
And S7, judging the water content of the rice seed to be detected according to the obtained rice seed water content prediction model and the strongest spectral line intensity of the main elements of all the measurement points of the rice seed sample to be detected. Similarly, in order to reduce the influence of the pollution on the surface of the rice seed to be measured on the grading detection of the water content of the rice seed to be measured, if the number of times of measurement at the same point of the same rice seed to be measured is N2, the data of the previous x2 times (x2< N2) times are deleted, and the water content of the rice seed to be measured is judged by only using the data of the later y2 times (y2 is N2-x 2).
Optionally, determining the size of x2 in the deleted data according to the pollution condition of the surface of the rice seed to be detected, wherein x2 is 4.
The implementation of the invention has the following advantages: the method for detecting the water content of the rice seeds by adopting the laser-induced breakdown spectroscopy has the characteristics of high speed, high efficiency, low cost, good test reproducibility, capability of on-line analysis and the like, and has high measurement accuracy.
In conclusion, the method can efficiently and quickly realize the grading and quick detection of the water content of the rice seeds.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in random access memory, read only memory, electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
It is understood that various other changes and modifications may be made by those skilled in the art based on the technical idea of the present invention, and all such changes and modifications should fall within the protective scope of the claims of the present invention.
Claims (5)
1. A rice seed moisture content grading detection method based on main element spectral intensity is characterized by comprising the following steps:
s1, selecting rice seeds which are plump in grains, do not mildew, have the same size and shape and are mature physiologically, and removing impurities and miscellaneous seeds; packaging the screened seeds into a drying bottle according to groups, adding a plurality of distilled water with different masses, and making a plurality of standard rice seed samples with different water contents;
s2, measuring the spectrums of the plurality of standard rice seed samples obtained in the step S1 by a laser-induced breakdown spectrometer in a scanning measurement mode;
in the step S2, the measured spectrum range is 250-800 nm;
s3, denoising the laser-induced breakdown spectrum of the standard rice seed sample;
s4, obtaining the intensity of the strongest spectral line of main elements Si, K, P, Ca, Fe, Al, Mg, Na, Ti and CN molecular chains of the rice seed sample according to the standard rice seed laser-induced breakdown spectrum after denoising treatment, and constructing a hierarchical prediction model of the water content of the rice seed by using a neural network to obtain the relation between the water content of the rice seed and the intensity of the strongest spectral line of the main elements of the rice seed sample;
s5, measuring the spectrum of the rice seed sample to be measured by a laser-induced breakdown spectrometer in a scanning measurement mode;
s6, carrying out denoising treatment on the laser-induced breakdown spectrum of the rice seed sample to be detected;
and S7, judging the water content of the rice seed to be detected according to the obtained rice seed water content prediction model and the strongest spectral line intensity of the main elements of all the measurement points of the rice seed sample to be detected.
2. The rice seed moisture content classification detection method based on principal element spectral intensity as claimed in claim 1, wherein in step S4, a method for constructing a rice seed sample moisture content prediction model is a neural network method, and if the number of measurements at the same point of the same rice seed is N1, the data of the previous x1 measurements are deleted, wherein x1 is less than N1, and only the data of the next y1 measurements are used to construct the rice seed moisture content classification prediction model, wherein y1 is N1-x 1.
3. The rice seed moisture content classification detection method based on principal element spectral intensity as claimed in claim 2, wherein in step S4, the value of x1 is not less than 4.
4. The method as claimed in claim 1, wherein in step S7, if the number of measurements on the same point of the same rice seed is N2, the previous x2 measurements are deleted, wherein x2 is less than N2, and the moisture content of the rice seed is determined by using only the last y2 measurements, wherein y2 is N2-x 2.
5. The rice seed moisture content classification detection method based on principal element spectral intensity as claimed in claim 4, wherein in step S7, the value of x2 is not less than 4.
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