Construction method of effective component prediction model for silage corn and application thereof

A technology for silage corn and nutritional components, which is applied in the direction of measuring devices, analysis materials, and material analysis through optical means, which can solve the problem that the nutritional components of silage corn cannot be quickly and accurately measured, and achieve saving of feeding costs and low detection costs , The effect of no reagent consumption

Pending Publication Date: 2019-10-18
河南省饲草饲料站
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to provide a method for constructing a predictive model of the nutritional components of silage corn, and further a...

Method used

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  • Construction method of effective component prediction model for silage corn and application thereof
  • Construction method of effective component prediction model for silage corn and application thereof
  • Construction method of effective component prediction model for silage corn and application thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0037] Embodiment 1: Utilize chemical analysis method to analyze the nutrient composition of silage corn

[0038] 1. Pretreatment of Silage Corn Samples

[0039] Put the silage corn into an electric blast drying oven, and dry it in an oven at 105°C until the water content is reduced to about 1.6-12.8%, then use a high-speed grinder to crush the sample, and then use a sampling sieve to sieve the dried straw. The 40-mesh sample was stored in a ziplock bag, and the subsequent steps were carried out after 24 hours of equilibrating the moisture.

[0040] 2. Determination of nutrient content

[0041] For determination of crude protein, refer to "Determination of Crude Protein in GB / T 6432-1994 Feed"; for determination of crude fat, refer to "Determination of Crude Fat in Feed"; For the determination of starch, refer to "ZYA-SL-005-2017 Anthrone colorimetric method for the determination of starch"; for neutral detergent fiber, refer to "GB / T20806-2006 Determination of neutral deter...

Embodiment 2

[0046] Example 2: Near-infrared spectrum collection of silage corn

[0047] Put the silage corn sample with a particle size of 40 mesh into a sample cup with a diameter of 9.4 cm and a depth of 4.8 cm. The volume of the sample is about 1 / 2 to 2 / 3 of the cup body, and gently put it into the cup cover to ensure that the bottom of the sample cup is No gaps.

[0048] The near-infrared spectrum of the silage corn samples was collected by using the grating continuous spectrum mode of the Spectrastar 1400XL-3 near-infrared spectrometer of Unity Company in the United States in the range of wavenumbers from 1400nm to 2500nm. The spectral collection rate is 45 degs / sec, the wavelength accuracy is 1nm, and the sample is scanned twice.

[0049] The main components of silage corn are crude protein, crude fat, water, starch, neutral detergent fiber, and acid detergent fiber. These components have strong absorption in the near-infrared region.

[0050] Such as figure 1As shown, the main c...

Embodiment 3

[0051] Example 3: Analysis of near-infrared spectral characteristics of silage corn

[0052] Select 154 representative samples from various places in Henan Province, detect and analyze the content of each active ingredient according to the method described in Example 1, and collect the near-infrared spectra of each sample according to the method in Example 2.

[0053] Then use the Ucal data analysis software of Unity Company in the United States to perform detrend correction (Detrend) and standard normal variable transformation (SNV) preprocessing on the diffuse reflectance raw spectra of the obtained silage corn samples.

[0054] The spectrogram after detrend correction (Detrend) and standard normal variable transformation (SNV) preprocessing is as follows figure 2 shown.

[0055] From figure 2 It can be seen that the preprocessed spectrum can accurately find that the region that contributes to the accuracy of the model is between 1900nm and 2500nm.

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Abstract

The invention discloses a construction method of an effective component prediction model for silage corn and application thereof, thereby solving technical problems of resource wasting and low economic benefit. The method comprises: taking a sample, drying the sample and pulverizing the dried sample; analyzing crude protein, moisture, neutral detergent fiber, acid detergent fiber and starch content values; carrying out near-infrared spectrometer scanning and collecting on the sample by means of grating continuous spectroscopy of an near-infrared spectroscopy; and carrying out detrending correction and standard normal variable transformation preprocessing on an original spectrum of diffuse reflection of obtained data, and then establishing a corresponding prediction model by using a partialleast squares method and detecting content of nutrients in silage corn by using the model. According to the invention, on the basis of combination of the near-infrared spectroscopy technology with chemometrics method, a qualitative and quantitative calibration mathematical model between chemical values of main components of silage corn and near-infrared spectroscopy data is established by using multivariate data analysis software, thereby establishing a rapid component of the main components of silage corn and laying a foundation for precise feeding.

Description

technical field [0001] The invention relates to the technical field of feed detection, in particular to a construction method and application of a predictive model for nutritional components of silage corn. Background technique [0002] Silage corn refers to the harvesting of all green plants on the ground including fruit ears during the suitable harvesting period of corn, which is chopped and processed, and is suitable for silage fermentation to make silage to feed grass-fed livestock such as cattle and sheep. A kind of corn. The high-efficiency compound bacterial agent added to the silage corn can decompose a large amount of cellulose, hemicellulose, and even some lignin under a suitable anaerobic environment, and convert them into sugars. Sugars are converted into lactic acid, acetic acid and propionic acid through organic acid fermentation, and inhibit the reproduction of harmful bacteria such as butyric acid bacteria and mold, and finally achieve the same storage effec...

Claims

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Application Information

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IPC IPC(8): G01N21/359
CPCG01N21/359
Inventor 兰尊海宋洛文牛岩王彦华杨利锋王红艺郭文英韩晶
Owner 河南省饲草饲料站
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