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Rapid detection method for beta vulgaris quality

A detection method and sugar beet technology, applied in the direction of measuring devices, material analysis through optical means, instruments, etc., can solve the problems of cumbersome price, time-consuming operation, high cost, etc., and achieve the effect of simple operation, low power consumption, and saving money

Inactive Publication Date: 2014-09-10
QIQIHAR UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, the quality appraisal of sugar beet by sugar enterprises is after the acquisition, which is time-consuming, cumbersome and expensive
The application of near-infrared spectroscopy in sugar beet quality analysis can bring great convenience to sugar beet variety breeding and field production management. However, there is no method for detecting the quality of sugar beets using near-infrared spectroscopy in the prior art.

Method used

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  • Rapid detection method for beta vulgaris quality
  • Rapid detection method for beta vulgaris quality
  • Rapid detection method for beta vulgaris quality

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0038] Example 1 Establishment of regression model

[0039] The establishment of partial least squares regression model of sugar beet quality detection index and near-infrared characteristic wavelength spectrum is as follows:

[0040] 1. Collect a total of 380 samples of 28 varieties of sugar beet, and put them in a sample bag after being sawed and paste.

[0041] The sample will be pretreated (see figure 2 ) The beet saw paste samples are evenly spread in a sample cup with a diameter of 75mm, and scanned 60 times with a resolution of 5nm using a near-infrared analyzer. The temperature of the sample and the environment are both 20±2℃, and the spectral scanning range is 900~1700nm. , Get the near-infrared scanning spectrogram, see the original picture image 3 . Repeat the sample loading measurement twice to maintain the uniformity of the sample loading and obtain the average spectral curve.

[0042] 2. Perform the first derivative (FD), standard normal variable transformation (SNV),...

Embodiment 2

[0045] Example 2 Quality inspection of samples to be tested

[0046] Based on the regression model established in Example 1, quality testing and grading of 70 samples to be tested were performed, and the steps were as follows:

[0047] 1. Pretreatment of the sample to be tested (e.g. figure 2 );

[0048] 2. Spectral scanning of the sample to be tested by the near-infrared analyzer;

[0049] 3. The test results of the sugar content index of the sample to be tested are shown in Table 1.

[0050] Table 1 Comparison of the predicted value of sugar content of sugar beet samples with the measured value of traditional methods

[0051]

[0052]

[0053] One-way analysis of variance results P = 0.9549, r = 0.9599, SEP = 0.439, Bias = 0.023

[0054] From the above analysis results, it can be seen that there is no significant difference between the predicted value of the near-infrared sugar content model and the laboratory true value (P = 0.9549), the correlation between the two sets of data is goo...

Embodiment 3

[0055] Example 3 Establishment of a near-infrared detection model for large sugar beet particles

[0056] The establishment of partial least squares regression model of sugar beet quality detection index and near-infrared characteristic wavelength spectrum is as follows:

[0057] 1. A total of 115 representative sugar beet samples were selected, and they were made into large sugar beet particles and then packed in a sample bag for uniform numbering, and spectral scanning was used for standby.

[0058] Obtaining large beet particles: clean the beet sample, remove the leaf crown, and evenly cut it into 2mm*2mm*2mm particles. Spread the sugar beet particle sample evenly in a sample cup with a diameter of 75mm, and use a near-infrared analyzer to scan 60 times with a resolution of 5nm. The temperature of the sample and the environment are both 20±2℃, and the spectral scan range is 900~1700nm. A near-infrared scan spectrum is displayed. Repeat the sample loading measurement twice to mai...

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Abstract

The invention discloses a rapid detection method for beta vulgaris quality, and belongs to the technical field of quality detection of agricultural products. The method comprises: utilizing a near infrared spectrometer to acquire an infrared spectrogram of a beta-vulgaris sample subjected to paste-sawing pretreatment, performing spectrum pretreatment on the near infrared spectrogram, employing partial least squares and performing internal interaction verification to establish a mathematical model, and according to the mathematical model to predict the sugar degree, the sodium content and the nitrogen content of a to-be detected sample. The provided method has the characteristics of being simple in operation, green, environment-friendly, low in detection cost, rapid in detection speed, capable of realizing simultaneous detection on multiple indexes of beta vulgaris quality, relatively high in accuracy, and the like, and is suitable for rapid detection on beta vulgaris quality.

Description

Technical field [0001] The invention relates to a rapid detection method for sugar beet quality, and belongs to the technical field of agricultural product quality detection. Background technique [0002] For a long time, due to the limitation of traditional analysis technology, the raw material purchasing system based on the quality-based price has not been established in my country's sugar companies, and the raw material purchasing has been priced by weight. Growers blindly pursue high yield, light quality, and low-quality raw materials greatly increase the consumption of sugar factories. Therefore, it is of great significance to realize the rapid detection of sugar beet quality and price evaluation by quality. [0003] The quality of beet has an important influence on the sugar yield, especially the sugar content index. Sugar beet sugar content can significantly affect the efficiency and economic benefits of sugar production by sugar companies. At the same time, the realizatio...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/359
Inventor 杨勇郑喜群任健赵丽影杨庆余
Owner QIQIHAR UNIVERSITY
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