Method for evaluating quality of highland barley straw feed

Abstract

The invention relates to the technical field of quality evaluation, in particular to a highland barley straw feed quality evaluation method which comprises the following steps: collecting a highland barley straw sample from a highland barley field; pretreating the collected highland barley straw sample; carrying out physicochemical index analysis on the pretreated highland barley straw sample; carrying out quantitative analysis on the main nutritional ingredients of the highland barley straw sample by adopting a near infrared spectrum analysis technology; performing palatability test on the ruminants; the highland barley straw samples are stored under different temperature and humidity conditions, and the storage stability of the highland barley straw is evaluated; statistical analysis: comprehensively evaluating the feeding quality of the highland barley straws; and grading quality. According to the method disclosed by the invention, various physicochemical indexes, nutritional ingredients, storage stability and palatability test results are comprehensively considered, so that the evaluation method is more comprehensive and accurate.

Description

Technical Field

[0001] The invention relates to the technical field of quality assessment, and in particular to a method for assessing the feeding quality of highland barley straw. Background Art

[0002] Highland barley is an important food crop that mainly grows in plateau areas. Its straw is rich in nutrients and is an important source of feed. However, the quality evaluation method of highland barley straw is not perfect at present, which leads to a certain degree of blindness in feed production, affecting the quality of feed and the health of livestock. In the prior art, it is mainly evaluated by sensory evaluation and simple chemical analysis methods. These methods are often highly subjective and the results are not accurate enough. The existing highland barley straw feeding quality evaluation methods have the following main problems:

[0003] Single indicator evaluation: Most evaluation methods only focus on a few physical and chemical indicators or nutritional components, and fail to fully reflect the overall feeding quality of highland barley straw.

[0004] Lack of systematicity: There is a lack of systematic comprehensive analysis among the various evaluation indicators, which leads to one-sided evaluation results and cannot fully reflect the actual feeding effect of highland barley straw.

[0005] Ignoring storage stability: The quality of highland barley straw may change during storage, but existing evaluation methods often ignore the impact of storage stability on feeding quality.

[0006] Insufficient palatability tests: Palatability is an important factor affecting the actual use effect of feed, but the existing technology pays little attention to palatability tests and lacks scientific and systematic palatability evaluation methods. Summary of the invention

[0007] Based on the above purpose, the present invention provides a method for evaluating the feeding quality of highland barley straw.

[0008] A method for evaluating the feeding quality of highland barley straw comprises the following steps:

[0009] S100, sample collection: collecting highland barley straw samples from highland barley fields;

[0010] S200, sample pretreatment: washing, air-drying and crushing the collected highland barley straw samples to make the samples uniformly crushed;

[0011] S300, physical and chemical index detection: physical and chemical index analysis of pretreated highland barley straw samples, including moisture, crude protein, crude fiber, crude fat and ash;

[0012] S400, Nutritional component analysis: Near infrared spectroscopy is used to quantitatively analyze the main nutritional components of highland barley straw samples.

[0013] S500, ruminant palatability test: highland barley straw samples were made into feed for ruminant palatability test, and the feed intake and digestibility of ruminants were recorded;

[0014] S600, storage stability assessment: Store highland barley straw samples under different temperature and humidity conditions for a certain period of time, regularly test the physical and chemical indicators and microbial content of the samples, and evaluate the storage stability of highland barley straw;

[0015] S700, data processing: statistical analysis of the test and experimental results, combined with the physical and chemical indicators, nutritional components, storage stability and palatability test evaluation results, to comprehensively evaluate the feeding quality of highland barley straw;

[0016] S800, quality grading: Based on the comprehensive evaluation results, the feeding quality of highland barley straw is graded into four levels: high quality, good, qualified and unqualified.

[0017] Optionally, the S300 specifically includes:

[0018] S310, moisture detection: Take a certain amount of pre-treated highland barley straw sample, dry it at 105 degrees Celsius to constant weight by drying method, and calculate the moisture content of the sample; the calculation formula of moisture content is:

[0019] The initial weight is the initial weight of the sample, and the dried weight is the weight of the sample after drying at 105 degrees Celsius to a constant weight;

[0020] S320, crude protein detection: Take a certain amount of pretreated highland barley straw sample, use Kjeldahl nitrogen determination method to determine crude protein, and calculate the crude protein content in the sample; the crude protein content is calculated as:

[0021] Among them, the nitrogen content was determined by the Kjeldahl method;

[0022] S330, crude fiber detection: Take a certain amount of pretreated highland barley straw sample, use the neutral detergent fiber method (NDF) and acid detergent fiber method (ADF) to determine the crude fiber content, and calculate the crude fiber content in the sample; the calculation formula is as follows:

[0023]

[0024] S340, crude fat detection: Take a certain amount of pretreated highland barley straw sample, use Soxhlet extraction method to determine the crude fat content, and calculate the crude fat content in the sample; the calculation formula is as follows:

[0025]

[0026] S350, ash content test: Take a certain amount of pretreated highland barley straw sample, burn it to constant weight at 550 degrees Celsius by burning method, and calculate the ash content of the sample; the calculation formula is as follows:

[0027]

[0028] Optionally, the S400 specifically includes:

[0029] S410, sample preparation: taking a quantitative pre-treated highland barley straw sample to ensure the uniformity and fineness of the sample to facilitate the accuracy of near infrared spectroscopy analysis;

[0030] S420, spectral measurement: Place the sample in a near-infrared spectrometer for scanning to obtain the near-infrared spectrum of the sample. The spectral range is 4000cm -1 Up to 10000cm -1 ;

[0031] S430, preprocessing the acquired spectral data using spectral analysis software, including denoising, baseline correction and smoothing, to remove background interference signals;

[0032] S440, model establishment: selecting highland barley straw samples with known component contents, establishing a near infrared spectroscopy analysis model, and correlating spectral data with the nutrient content of the samples by partial least squares (PLS) method;

[0033] S450, ingredient prediction: input the spectral data of the sample to be tested into the established near-infrared spectral analysis model to predict the content of the main nutrients in the sample, including crude protein, crude fat, crude fiber and moisture.

[0034] Optionally, the model building in S440 specifically includes:

[0035] S441, calculate the spectral data matrix X and the nutrient matrix Y:

[0036] X is an n×m matrix, representing the spectral data of n samples at m wavelengths;

[0037] Y is an n×p matrix, representing the content of p nutrients in n samples;

[0038] S442, calculate the weight matrix W and the load matrix P:

[0039] Calculate the weight vector w1 of the first component: select w1 that maximizes the variance of Xw1 and Y;

[0040] Calculate the score vector t1=Xw1 and the load vector

[0041] Perform regression adjustment on X and Y: (where q1 is the load vector in Y associated with t1);

[0042] Repeat the above calculation and regression adjustment to calculate the weight vector w of the subsequent components i , score vector t i and the load vector p i , until a predetermined number of components is reached;

[0043] S443, regression model establishment: calculate regression coefficient matrix B:

[0044] B=W(P T W) -1 Q T Where W is the weight vector w i The matrix composed of P is the matrix of all load vectors p i The matrix composed of Q is the total load vector q i The matrix composed of

[0045] S444, the spectrum data matrix X of the sample to be tested test Make prediction: Y pred =X test B Among them, Y pred is the predicted nutrient content matrix.

[0046] Optionally, the S500 specifically includes:

[0047] S510, sample preparation: mixing the pretreated highland barley straw sample with other conventional feed ingredients in a predetermined ratio to prepare a uniform mixed feed, wherein the mixing ratio is adjusted according to the nutritional requirements of different ruminants;

[0048] S520, feed processing: crushing, mixing and granulating the mixed feed into pellet feed suitable for ruminants to ensure the uniformity and palatability of the feed;

[0049] S530, Experimental design: Select healthy ruminants and divide them into experimental and control groups according to a randomized block design, with no less than 5 animals in each group;

[0050] S540, feeding test: During the test period, the prepared highland barley straw mixed feed was fed to the ruminants in the test group, and the conventional feed was fed to the ruminants in the control group. The feed intake of each animal was recorded at least 3 times a day, and the test period was no less than 2 weeks;

[0051] S550, digestibility determination: One week before the end of the experiment, fecal samples of ruminants were collected, and the undigested matter in the fecal samples was determined by the acid detergent fiber method to calculate the digestibility of the feed;

[0052] S560, data analysis: Statistical analysis was performed on the collected feed intake and digestibility data to evaluate the palatability and digestibility of highland barley straw feed, and compared with the control group to determine the quality of highland barley straw feed.

[0053] Optionally, the S600 specifically includes:

[0054] S610, sample packaging: the pretreated highland barley straw samples are packaged into multiple sealed containers, and the weight of the samples in each container is the same to ensure the uniformity of the samples;

[0055] S620, storage condition setting: the packaged samples are placed in storage environments under different temperature and humidity conditions, the temperature conditions include normal temperature (25°C), medium temperature (35°C) and high temperature (45°C), and the humidity conditions include low humidity (30% relative humidity), medium humidity (60% relative humidity) and high humidity (90% relative humidity);

[0056] S630, storage time setting: samples are stored under different temperature and humidity conditions for 1 month, 3 months, 6 months and 12 months, and multiple time nodes are set for evaluation;

[0057] S640, physical and chemical index detection: at each storage time point, take out some samples and test their physical and chemical indicators;

[0058] S650, Microbial content detection: At each storage time point, take out some samples and test their microbial content, including the total number of bacteria and mold;

[0059] S660, statistical analysis of the physical and chemical indicators and microbial content of samples under different storage conditions and time was performed to evaluate the stability and change trend of highland barley straw samples under different storage conditions.

[0060] Optionally, the evaluation of the stability and change trend of the highland barley straw sample under different storage conditions in S660 specifically includes:

[0061] S661, at each storage time point, record the physical and chemical indicators and microbial content (total number of bacteria and total number of molds) of each sample under different temperature and humidity conditions;

[0062] S662, input all recorded data into statistical analysis software (such as SPSS, R, Excel) and organize them into a structured table, where each row represents the measurement data of a sample and each column represents a measurement index, including storage conditions, storage time, physical and chemical indicators and microbial content;

[0063] S663, calculate the mean and standard deviation of each index under different storage conditions and time to understand the basic distribution of the data;

[0064] S664, using variance analysis method, to test the significant effects of storage conditions and storage time on physical and chemical parameters and microbial content. Storage conditions include temperature and humidity.

[0065] S665, based on multiple regression analysis, a relationship model between physical and chemical indicators and microbial content and storage conditions and time was established. The multiple regression model is expressed as:

[0066] Y=β0+β1X1+β2X2+∈, where Y is the physical and chemical index or microbial content, X1 and X2 are the storage conditions and time respectively, β0, β1, β2 are regression coefficients, and ∈ is the error term. The changing trend can be obtained by plotting the changing trend graph of the physical and chemical indexes and microbial content under different storage conditions and time.

[0067] Optionally, the variance analysis formula is: F=between-group mean square error / within-group mean square error, wherein the between-group mean square error represents the difference between groups with different storage conditions and time, and the within-group mean square error represents the variation of samples within the same group.

[0068] Optionally, the S700 specifically includes:

[0069] S710, Data Summary: Summarize all test and experimental results, including physical and chemical indicators, nutritional components, storage stability, and evaluation data of palatability tests, to form a comprehensive data table;

[0070] S720, Data Standardization: Standardize the aggregated data to eliminate the impact of different indicator dimensions so that the data can be compared and analyzed on the same scale;

[0071] S730, weight setting: according to the importance of each indicator to the feed quality assessment, the weight of each indicator is determined by using the hierarchical analysis method;

[0072] S740, the comprehensive score of each sample is calculated using the weighted comprehensive scoring method. The comprehensive scoring formula is: Among them, S is the comprehensive score, w i is the weight of the ith indicator, Z i is the standardized score of the ith indicator;

[0073] S750, conducts statistical analysis on the comprehensive scores, evaluates the performance of different samples on various indicators, and uses drawing tools to draw the comprehensive score distribution diagram of the samples.

[0074] Optionally, the analytic hierarchy process for determining the weight of each indicator specifically includes:

[0075] Establish a hierarchical model: divide the feed quality assessment into the target layer, criterion layer and indicator layer;

[0076] Construct a judgment matrix: Compare the indicators at each level pairwise and construct a judgment matrix A = (a ij ), where a ij Indicates the relative importance of indicator i relative to indicator j;

[0077] Calculate the eigenvector: perform eigenvalue decomposition on the judgment matrix and calculate the eigenvector corresponding to the maximum eigenvalue w=(w1,w2,...,w n ), and normalize it to get the weight of each indicator;

[0078] Consistency test: calculate the consistency index CI and consistency ratio CR to ensure the consistency of the judgment matrix;

[0079]

[0080] Among them, λ max is the maximum eigenvalue of the judgment matrix, n is the order of the matrix, RI is the random consistency index, and when CR < 0.1, the judgment matrix is ​​considered to have satisfactory consistency.

[0081] Beneficial effects of the present invention:

[0082] The present invention comprehensively evaluates the feeding quality of highland barley straw through various tests and analyses such as physical and chemical index detection, nutrient component analysis, storage stability evaluation and palatability test, and adopts standardized processing and weighted comprehensive scoring method to ensure that various indicators are compared and analyzed on the same scale, thereby providing more comprehensive and objective evaluation results, which is helpful to improve the scientific nature of highland barley straw feed production and the overall quality of feed.

[0083] The present invention, in the prior art, the storage stability evaluation of highland barley straw feed is often not comprehensive enough, by storing samples for a long time under different temperature and humidity conditions, regularly testing physical and chemical indicators and microbial content, evaluating the storage stability of highland barley straw samples, through detailed statistical analysis, including variance analysis and regression analysis, comprehensively analyzing the stability and change trend of samples under different storage conditions, this evaluation method ensures the quality stability of highland barley straw feed during storage, and provides a scientific basis for the long-term storage of feed.

[0084] The present invention introduces the hierarchical analysis method into the evaluation of the feeding quality of highland barley straw, and scientifically determines the weight of each evaluation index by constructing a hierarchical structure model, constructing a judgment matrix, calculating characteristic vectors and weights, and performing consistency tests. The application of the hierarchical analysis method ensures the rationality and objectivity of each index in the comprehensive scoring, improves the accuracy and credibility of the evaluation result, and especially comprehensively considers the results of various physical and chemical indicators, nutritional components, storage stability and palatability tests, so that the evaluation method is more comprehensive and accurate, and is helpful to optimize the production and quality control of highland barley straw feed. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0086] Figure 1 A schematic diagram of the evaluation method flow in an embodiment of the present invention;

[0087] Figure 2 The figure is a schematic diagram of the data aggregation process according to an embodiment of the present invention. DETAILED DESCRIPTION

[0088] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0089] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0090] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0091] like Figure 1-Figure 2 As shown, a method for evaluating the feeding quality of highland barley straw comprises the following steps:

[0092] S100, sample collection: collect barley straw samples from barley fields to ensure that the samples are representative;

[0093] a) Sample plot selection: Select multiple representative sample plots in the barley fields. The size of each sample plot is 10 square meters. The sample plots should cover different areas of the barley fields, including the central area, marginal area and low-lying area;

[0094] b) Sample collection: In each sample plot, highland barley straw samples were randomly collected along a "Z"-shaped route, with no less than 10 highland barley straws collected in each sample plot;

[0095] c) Sample mixing: The highland barley straw samples collected from various sample plots were fully mixed to ensure the uniformity and representativeness of the samples;

[0096] d) Sample preservation: The mixed highland barley straw samples are packed into clean sample bags, marked with the collection time, location and sample plot number, and immediately sent to the laboratory for processing;

[0097] S200, sample pretreatment: washing, air-drying and crushing the collected highland barley straw samples to make the samples uniformly crushed;

[0098] a) Sample cleaning: The collected highland barley straw samples were cleaned with clean water to remove dirt, dust and other impurities on the surface of the samples to ensure the purity of the samples;

[0099] b) Sample air drying: The cleaned highland barley straw sample is naturally air-dried in a well-ventilated environment, or dried in a drying device at a low temperature not exceeding 50 degrees Celsius until the water content of the sample drops below 10%;

[0100] c) Sample crushing: The air-dried highland barley straw sample is crushed with a crusher to make the sample uniform and finely crushed, and the particle diameter is controlled to be less than 1 mm;

[0101] d) Sample screening: The crushed sample is screened through a sieve to remove large particles that are not fully crushed to ensure the consistency and uniformity of the sample;

[0102] e) Sample preservation: The processed samples should be packed into dry and clean containers, sealed and preserved, and marked with the sample processing time and number for subsequent physical and chemical index testing and nutritional component analysis;

[0103] S300, physical and chemical index detection: physical and chemical index analysis of pretreated highland barley straw samples, including moisture, crude protein, crude fiber, crude fat and ash;

[0104] S400, Nutritional component analysis: The near infrared spectroscopy analysis technology is used to quantitatively analyze the main nutritional components of highland barley straw samples, mainly including the following steps:

[0105] Sample preparation: Ensure the homogeneity and fineness of the sample to ensure the accuracy of near-infrared spectroscopy analysis.

[0106] Spectrometry: Obtain a near-infrared spectrum of the sample.

[0107] Data processing: Preprocess the spectral data to remove noise and background interference signals.

[0108] Model establishment: Using sample data with known component contents, the spectral analysis model was established by partial least squares (PLS) method. In PLS, the weight matrix W, score vector T and load matrices P and Q were calculated, and the regression coefficient matrix B was calculated;

[0109] Component prediction: Input the spectral data of the sample to be tested into the established model to predict the nutritional content.

[0110] S500, ruminant palatability test: highland barley straw samples were made into feed for ruminant palatability test, and the feed intake and digestibility of ruminants were recorded;

[0111] S600, storage stability assessment: Store highland barley straw samples under different temperature and humidity conditions for a certain period of time, regularly test the physical and chemical indicators and microbial content of the samples, and evaluate the storage stability of highland barley straw;

[0112] S700, data processing: statistical analysis of the test and experimental results, combined with the physical and chemical indicators, nutritional components, storage stability and palatability test evaluation results, to comprehensively evaluate the feeding quality of highland barley straw;

[0113] S800, quality grading: Based on the comprehensive evaluation results, the feeding quality of highland barley straw is graded into four levels: high quality, good, qualified and unqualified.

[0114] S300 specifically includes:

[0115] S310, moisture detection: Take a certain amount of pre-treated highland barley straw sample, dry it at 105 degrees Celsius to constant weight by drying method, and calculate the moisture content of the sample; the calculation formula of moisture content is:

[0116] The initial weight is the initial weight of the sample, and the dried weight is the weight of the sample after drying at 105 degrees Celsius to a constant weight;

[0117] S320, crude protein detection: Take a certain amount of pretreated highland barley straw sample, use Kjeldahl nitrogen determination method to determine crude protein, and calculate the crude protein content in the sample; the crude protein content is calculated as:

[0118] Among them, the nitrogen content was determined by the Kjeldahl method;

[0119] S330, crude fiber detection: Take a certain amount of pretreated highland barley straw sample, use the neutral detergent fiber method (NDF) and acid detergent fiber method (ADF) to determine the crude fiber content, and calculate the crude fiber content in the sample; the calculation formula is as follows:

[0120]

[0121] S340, crude fat detection: Take a certain amount of pretreated highland barley straw sample, use Soxhlet extraction method to determine the crude fat content, and calculate the crude fat content in the sample; the calculation formula is as follows:

[0122]

[0123] S350, ash content test: Take a certain amount of pretreated highland barley straw sample, burn it to constant weight at 550 degrees Celsius by burning method, and calculate the ash content of the sample; the calculation formula is as follows:

[0124]

[0125] S400 specifically includes:

[0126] S410, sample preparation: taking a quantitative pre-treated highland barley straw sample to ensure the uniformity and fineness of the sample to facilitate the accuracy of near infrared spectroscopy analysis;

[0127] S420, spectral measurement: Place the sample in a near-infrared spectrometer for scanning to obtain the near-infrared spectrum of the sample. The spectral range is 4000cm -1 Up to 10000cm -1 ;

[0128] S430, preprocessing the acquired spectral data using spectral analysis software, including denoising, baseline correction and smoothing, to remove background interference signals;

[0129] S440, model establishment: selecting highland barley straw samples with known component contents, establishing a near infrared spectroscopy analysis model, and correlating spectral data with the nutrient content of the samples by partial least squares (PLS) method;

[0130] S450, ingredient prediction: input the spectral data of the sample to be tested into the established near-infrared spectral analysis model to predict the content of the main nutrients in the sample, including crude protein, crude fat, crude fiber and moisture.

[0131] The model building in S440 specifically includes:

[0132] S441, calculate the spectral data matrix X and the nutrient matrix Y:

[0133] X is an n×m matrix, representing the spectral data of n samples at m wavelengths;

[0134] Y is an n×p matrix, representing the content of p nutrients in n samples;

[0135] S442, calculate the weight matrix W and the load matrix P:

[0136] Calculate the weight vector w1 of the first component: select w1 that maximizes the variance of Xw1 and Y;

[0137] Calculate the score vector t1=Xw1 and the load vector

[0138] Perform regression adjustment on X and Y: (where q1 is the load vector in Y associated with t1);

[0139] Repeat the above calculation and regression adjustment to calculate the weight vector w of the subsequent components i , score vector t i and the load vector p i , until a predetermined number of components is reached;

[0140] S443, regression model establishment: calculate regression coefficient matrix B:

[0141] B=W(P T W) -1 Q T Where W is the weight vector w i The matrix composed of P is the matrix of all load vectors p i The matrix composed of Q is the total load vector q i The matrix composed of

[0142] S444, the spectrum data matrix X of the sample to be tested test Make prediction: Y pred =X test B Among them, Y pred is the predicted nutrient content matrix.

[0143] S500 specifically includes:

[0144] S510, sample preparation: mixing the pretreated highland barley straw sample with other conventional feed ingredients in a predetermined ratio to prepare a uniform mixed feed, wherein the mixing ratio is adjusted according to the nutritional requirements of different ruminants;

[0145] S520, feed processing: crushing, mixing and granulating the mixed feed into pellet feed suitable for ruminants to ensure the uniformity and palatability of the feed;

[0146] S530, Experimental design: Select healthy ruminants and divide them into experimental and control groups according to a randomized block design, with no less than 5 animals in each group;

[0147] S540, feeding test: During the test period, the prepared highland barley straw mixed feed was fed to the ruminants in the test group, and the conventional feed was fed to the ruminants in the control group. The feed intake of each animal was recorded at least 3 times a day, and the test period was no less than 2 weeks;

[0148] S550, digestibility determination: One week before the end of the experiment, fecal samples of ruminants were collected, and the undigested substances in the fecal samples were determined by the acid detergent fiber method to calculate the digestibility of the feed. The digestibility calculation formula is:

[0149] Total feed refers to the total mass of feed ingested by the animals during the experiment, and total undigested matter in feces refers to the total mass of undigested fiber in feces measured by the acid detergent fiber method;

[0150] S560, data analysis: Statistical analysis was performed on the collected feed intake and digestibility data to evaluate the palatability and digestibility of highland barley straw feed, and compared with the control group to determine the quality of highland barley straw feed.

[0151] S600 specifically includes:

[0152] S610, sample packaging: the pretreated highland barley straw samples are packaged into multiple sealed containers, and the weight of the samples in each container is the same to ensure the uniformity of the samples;

[0153] S620, storage condition setting: the packaged samples are placed in storage environments under different temperature and humidity conditions, the temperature conditions include normal temperature (25°C), medium temperature (35°C) and high temperature (45°C), and the humidity conditions include low humidity (30% relative humidity), medium humidity (60% relative humidity) and high humidity (90% relative humidity);

[0154] S630, storage time setting: samples are stored under different temperature and humidity conditions for 1 month, 3 months, 6 months and 12 months, and multiple time nodes are set for evaluation;

[0155] S640, physical and chemical index detection: at each storage time point, take out some samples and test their physical and chemical indicators;

[0156] S650, Microbial content detection: At each storage time point, take out some samples and test their microbial content, including the total number of bacteria and mold. The specific method is as follows:

[0157] Total bacterial count test: inoculate the sample suspension on nutrient agar medium, culture at 37°C for 48 hours, and count the total bacterial colonies;

[0158] Total mold count test: inoculate the sample suspension on potato dextrose agar medium, culture at 28°C for 5 days, and count the total number of mold colonies;

[0159] S660, statistical analysis of the physical and chemical indicators and microbial content of samples under different storage conditions and time was performed to evaluate the stability and change trend of highland barley straw samples under different storage conditions.

[0160] The evaluation of the stability and change trend of highland barley straw samples under different storage conditions in S660 specifically includes:

[0161] S661, at each storage time point, record the physical and chemical indicators and microbial content (total number of bacteria and total number of molds) of each sample under different temperature and humidity conditions;

[0162] S662, input all recorded data into statistical analysis software (such as SPSS, R, Excel) and organize them into a structured table, where each row represents the measurement data of a sample and each column represents a measurement index, including storage conditions, storage time, physical and chemical indicators and microbial content;

[0163] S663, calculate the mean and standard deviation of each index under different storage conditions and time to understand the basic distribution of the data; for example, taking moisture content as an example:

[0164]

[0165] in, is the mean, S is the standard deviation, X i is the moisture content of the sample, n is the number of samples;

[0166] S664, using variance analysis method, to test the significant effects of storage conditions and storage time on physical and chemical parameters and microbial content. Storage conditions include temperature and humidity.

[0167] S665, based on multiple regression analysis, a relationship model between physical and chemical indicators and microbial content and storage conditions and time was established. The multiple regression model is expressed as:

[0168] Y=β0+β1X1+β2X2+∈, where Y is the physical and chemical index or microbial content, X1 and X2 are the storage conditions and time respectively, β0, β1, β2 are regression coefficients, and ∈ is the error term. The changing trend can be obtained by plotting the changing trend graph of the physical and chemical indexes and microbial content under different storage conditions and time.

[0169] Variance analysis formula: F = mean square error between groups / mean square error within groups, where the mean square error between groups represents the difference between different storage conditions and time groups, and the mean square error within groups represents the variation of samples within the same group. The specific calculation steps are as follows:

[0170] 1. Calculate the sum of squares between groups (SSB): Among them, k is the number of groups, n i is the number of samples in the i-th group, is the mean of the i-th group, is the overall mean;

[0171] 2. Calculate the within-group sum of squares (SSE):

[0172]

[0173] Among them, X ij is the observed value of the jth sample in the i-th group.

[0174] 3. Calculate the mean square error (MSB) between groups and the mean square error (MSE) within groups:

[0175]

[0176] Among them, N is the total number of samples.

[0177] 4. Calculate the F value:

[0178] In variance analysis, the P value (significance level) is used to judge the significance of the effects of various storage conditions and time on physical and chemical indicators and microbial content. If the P value is less than the set significance level (0.05), it is considered that the factor has a significant effect on the indicator.

[0179] S700 specifically includes:

[0180] S710, Data Summary: Summarize all test and experimental results, including physical and chemical indicators, nutritional components, storage stability, and evaluation data of palatability tests, to form a comprehensive data table;

[0181] S720, Data Standardization: Standardize the aggregated data to eliminate the impact of different indicator dimensions so that the data can be compared and analyzed on the same scale. The standardization formula is:

[0182] Among them, Z is the standardized data, X is the original data, μ is the mean, and σ is the standard deviation;

[0183] S730, weight setting: according to the importance of each indicator to the feed quality assessment, the weight of each indicator is determined by using the hierarchical analysis method;

[0184] S740, the comprehensive score of each sample is calculated using the weighted comprehensive scoring method. The comprehensive scoring formula is: Among them, S is the comprehensive score, w i is the weight of the ith indicator, Z i is the standardized score of the ith indicator;

[0185] S750, conducts statistical analysis on the comprehensive scores, evaluates the performance of different samples on various indicators, and uses drawing tools to draw the comprehensive score distribution diagram of the samples.

[0186] The weights of each indicator determined by the hierarchical analysis method include:

[0187] Establish a hierarchical model: divide the feed quality assessment into the target layer, criterion layer and indicator layer;

[0188] Construct a judgment matrix: Compare the indicators at each level pairwise and construct a judgment matrix A = (a ij ), where a ij Indicates the relative importance of indicator i relative to indicator j;

[0189] Calculate the eigenvector: perform eigenvalue decomposition on the judgment matrix and calculate the eigenvector corresponding to the maximum eigenvalue w=(w1,w2,...,w n ), and normalize it to get the weight of each indicator;

[0190] Consistency test: calculate the consistency index CI and consistency ratio CR to ensure the consistency of the judgment matrix;

[0191]

[0192] Among them, λ maxis the maximum eigenvalue of the judgment matrix, n is the order of the matrix, RI is the random consistency index, and when CR < 0.1, the judgment matrix is ​​considered to have satisfactory consistency.

[0193] In the hierarchical model:

[0194] Target layer: Comprehensively evaluate the feeding quality of highland barley straw;

[0195] Criteria level: physical and chemical indicators, nutritional ingredients, storage stability, palatability test;

[0196] Index layer: moisture, crude protein, crude fiber, crude fat, ash, total bacteria count, total mold count;

[0197] Compare the indicators at each level in pairs and construct a judgment matrix. The matrix example is as follows:

[0198]

[0199]

[0200] In the quality classification, the specific classification standards are:

[0201] Excellent: comprehensive score above 90 points;

[0202] Good: comprehensive score between 75-90 points;

[0203] Pass: Comprehensive score between 60-75 points;

[0204] Failure: The overall score is below 60 points;

[0205] By retesting some samples, the reliability and accuracy of the comprehensive evaluation results are verified to ensure the scientific nature and stability of the evaluation method.

[0206] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0207] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for evaluating the feeding quality of highland barley straw, characterized in that: The following steps are involved: S100, sample collection: collecting highland barley straw samples from highland barley fields; S200, sample pretreatment: washing, air-drying and crushing the collected highland barley straw samples to make the samples uniformly crushed; S300, physical and chemical index detection: physical and chemical index analysis of pretreated highland barley straw samples, including moisture, crude protein, crude fiber, crude fat and ash; S400, Nutritional component analysis: Use near infrared spectroscopy to quantitatively analyze the main nutritional components of highland barley straw samples; S500, ruminant palatability test: highland barley straw samples were made into feed for ruminant palatability test, and the feed intake and digestibility of ruminants were recorded; S600, storage stability assessment: Store highland barley straw samples under different temperature and humidity conditions, regularly test the physical and chemical indicators and microbial content of the samples, and assess the storage stability of highland barley straw; S700, data processing: statistical analysis of the test and experimental results, combined with the physical and chemical indicators, nutritional components, storage stability and palatability test evaluation results, to comprehensively evaluate the feeding quality of highland barley straw; S800, quality grading: Based on the comprehensive evaluation results, the feeding quality of highland barley straw is graded into four levels: high quality, good, qualified and unqualified.

2. A method for evaluating the feeding quality of highland barley straw according to claim 1, characterized in that: The S300 specifically includes: S310, moisture detection: take a certain amount of pretreated highland barley straw sample, dry it at 105 degrees Celsius to constant weight by drying method, and calculate the moisture content of the sample; S320, crude protein detection: take a certain amount of pretreated highland barley straw sample, use Kjeldahl nitrogen determination method to determine crude protein, and calculate the crude protein content in the sample; S330, crude fiber detection: take a certain amount of pretreated highland barley straw sample, use neutral detergent fiber method and acid detergent fiber method to measure crude fiber, and calculate the crude fiber content in the sample; S340, crude fat detection: taking a certain amount of pretreated highland barley straw sample, using Soxhlet extraction method to measure crude fat, and calculating the crude fat content in the sample; S350, ash content detection: Take a certain amount of pretreated highland barley straw sample, burn it to constant weight at 550 degrees Celsius using the incineration method, and calculate the ash content of the sample.

3. A method for evaluating the feeding quality of highland barley straw according to claim 1, characterized in that: The S400 specifically includes: S410, sample preparation: taking a quantitative pre-treated highland barley straw sample to ensure the uniformity and fineness of the sample; S420, spectral measurement: Place the sample in a near-infrared spectrometer for scanning to obtain the near-infrared spectrum of the sample. The spectral range is 4000cm -1 Up to 10000cm -1 ; S430, preprocessing the acquired spectral data using spectral analysis software, including denoising, baseline correction and smoothing, to remove background interference signals; S440, model establishment: selecting highland barley straw samples with known component contents, establishing a near infrared spectroscopy analysis model, and correlating spectral data with the nutrient content of the samples by partial least squares method; S450, ingredient prediction: input the spectral data of the sample to be tested into the established near-infrared spectral analysis model to predict the content of the main nutrients in the sample, including crude protein, crude fat, crude fiber and moisture.

4. A method for evaluating the feeding quality of highland barley straw according to claim 3, characterized in that: The model building in S440 specifically includes: S441, calculate the spectral data matrix X and the nutrient matrix Y: X is an n×m matrix, representing the spectral data of n samples at m wavelengths; Y is an n×p matrix, representing the content of p nutrients in n samples; S442, calculate the weight matrix W and the load matrix P: Calculate the weight vector w1 of the first component: select w1 that maximizes the variance of Xw1 and Y; Calculate the score vector t1=Xw1 and the load vector Perform regression adjustment on X and Y: Repeat the above calculation and regression adjustment to calculate the weight vector w of the subsequent components i , score vector t i and the load vector p i , until a predetermined number of components is reached; S443, regression model establishment: calculate regression coefficient matrix B: B=W(P T W) -1 Q T Where W is the weight vector w i The matrix composed of P is the matrix of all load vectors p i The matrix composed of Q is the total load vector q i The matrix composed of S444, the spectrum data matrix X of the sample to be tested text Make prediction: Y pred =X test B Among them, Y pred is the predicted nutrient content matrix.

5. A method for evaluating the feeding quality of highland barley straw according to claim 1, characterized in that: The S500 specifically includes: S510, sample preparation: mixing the pretreated highland barley straw sample with other conventional feed ingredients in a predetermined ratio to prepare a uniform mixed feed, wherein the mixing ratio is adjusted according to the nutritional requirements of different ruminants; S520, feed processing: crushing, mixing and granulating the mixed feed to make pellet feed suitable for ruminants; S530, Experimental design: Select healthy ruminants and divide them into experimental and control groups according to a randomized block design, with no less than 5 animals in each group; S540, feeding test: During the test period, the prepared highland barley straw mixed feed was fed to the ruminants in the test group, and the conventional feed was fed to the ruminants in the control group. The feed intake of each animal was recorded at least 3 times a day, and the test period was no less than 2 weeks; S550, digestibility determination: One week before the end of the experiment, fecal samples of ruminants were collected, and the undigested matter in the fecal samples was determined by the acid detergent fiber method to calculate the digestibility of the feed; S560, data analysis: Statistical analysis was performed on the collected feed intake and digestibility data to evaluate the palatability and digestibility of highland barley straw feed, and compared with the control group to determine the quality of highland barley straw feed.

6. A method for evaluating the feeding quality of highland barley straw according to claim 1, characterized in that: The S600 specifically includes: S610, sample packaging: packaging the pretreated highland barley straw sample into a plurality of sealed containers, wherein the weight of the sample in each container is the same; S620, storage condition setting: placing the packaged samples in storage environments under different temperature and humidity conditions, including room temperature, medium temperature and high temperature, and low humidity, medium humidity and high humidity; S630, storage time setting: samples are stored under different temperature and humidity conditions for 1 month, 3 months, 6 months and 12 months, and multiple time nodes are set for evaluation; S640, physical and chemical index detection: at each storage time point, take out some samples and test their physical and chemical indicators; S650, Microbial content detection: At each storage time point, take out some samples and test their microbial content, including the total number of bacteria and mold; S660, statistical analysis of the physical and chemical indicators and microbial content of samples under different storage conditions and time was performed to evaluate the stability and change trend of highland barley straw samples under different storage conditions.

7. A method for evaluating the feeding quality of highland barley straw according to claim 6, characterized in that: The evaluation of the stability and change trend of highland barley straw samples under different storage conditions in S660 specifically includes: S661, at each storage time point, record the physical and chemical indicators and microbial content of each sample under different temperature and humidity conditions; S662, input all recorded data into statistical analysis software and organize them into a structured table, where each row represents the measurement data of a sample and each column represents a measurement index, including storage conditions, storage time, physical and chemical indicators and microbial content; S663, calculate the mean and standard deviation of each index under different storage conditions and time to understand the basic distribution of the data; S664, using variance analysis method, examine the effects of storage conditions and storage time on physical and chemical parameters and microbial content. Storage conditions include temperature and humidity. S665, based on multiple regression analysis, a relationship model between physical and chemical indicators and microbial content and storage conditions and time was established. The multiple regression model is expressed as: Y=β0+β1X1+β2X2+∈, where Y is the physical and chemical index or microbial content, X1 and X2 are the storage conditions and time respectively, β0, β1, β2 are regression coefficients, and ∈ is the error term. The changing trend can be obtained by plotting the changing trend graph of the physical and chemical indexes and microbial content under different storage conditions and time.

8. A method for evaluating the feeding quality of highland barley straw according to claim 7, characterized in that: The variance analysis formula is: F=inter-group mean square error / intra-group mean square error, wherein the inter-group mean square error represents the difference between different storage conditions and time groups, and the intra-group mean square error represents the variation of samples within the same group.

9. A method for evaluating the feeding quality of highland barley straw according to claim 1, characterized in that: The S700 specifically includes: S710, Data Summary: Summarize all test and experimental results, including physical and chemical indicators, nutritional components, storage stability, and evaluation data of palatability tests, to form a comprehensive data table; S720, Data Standardization: Standardize the aggregated data to eliminate the impact of different indicator dimensions so that the data can be compared and analyzed on the same scale; S730, weight setting: according to the importance of each indicator to the feed quality assessment, the weight of each indicator is determined by using the hierarchical analysis method; S740, the comprehensive score of each sample is calculated using the weighted comprehensive scoring method. The comprehensive scoring formula is: Among them, S is the comprehensive score, w i is the weight of the ith indicator, Z i is the standardized score of the ith indicator; S750, conduct statistical analysis on the comprehensive scores, evaluate the performance of different samples on various indicators, and draw a distribution diagram of the comprehensive scores of the samples.

10. A method for evaluating the feeding quality of highland barley straw according to claim 1, characterized in that: The weight of each indicator determined by the analytic hierarchy process specifically includes: Establish a hierarchical model: divide the feed quality assessment into the target layer, criterion layer and indicator layer; Construct a judgment matrix: Compare the indicators at each level pairwise and construct a judgment matrix A = (a ij ), where a ij Indicates the relative importance of indicator i relative to indicator j; Calculate the eigenvector: perform eigenvalue decomposition on the judgment matrix and calculate the eigenvector corresponding to the maximum eigenvalue w=(w1,w2,...,w n ), and normalize it to get the weight of each indicator; Consistency test: calculate the consistency index CI and consistency ratio CR to ensure the consistency of the judgment matrix; Among them, λ max is the maximum eigenvalue of the judgment matrix, n is the order of the matrix, RI is the random consistency index, and when CR < 0.1, the judgment matrix is ​​considered to have satisfactory consistency.

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