Fermentation performance evaluation method and formula design system for solid state fermentation feed raw materials

Abstract

The invention relates to the technical field of feed, and particularly discloses a fermentation performance evaluation method and formula design system of solid state fermentation feed raw materials, and the method comprises the following steps: measuring the contents of glucose, fructose, maltose and cane sugar in the raw materials; calculating a comprehensive carbon source value according to the weight coefficient, wherein the calculation formula is as follows: the comprehensive carbon source value (%) = 0.265 * glucose content + 0.265 * fructose content + 0.235 * maltose content + 0.235 * sucrose content; the raw materials are quantitatively evaluated, the one-sidedness and subjectivity of traditional experience judgment are overcome, and reliable data support is provided for scientific screening and compatibility of the raw materials.

Description

Technical Field

[0001] This invention belongs to the field of feed technology, specifically relating to a method for evaluating the fermentation performance of solid-state fermented feed ingredients and a formula design system. Background Technology

[0002] With the full implementation of my country's "antibiotic-free" policy in the feed industry, bio-fermented feed is playing an increasingly important role in ensuring animal health and improving production performance, and its application scale and speed have significantly increased. Currently, bio-fermented feed mainly adopts solid-state anaerobic fermentation technology, and its raw materials are mostly unconventional materials such as wheat bran, soybean meal, miscellaneous meals, and agricultural by-products. However, the industry lacks a systematic and quantitative understanding of the fermentation characteristics of various raw materials, and a unified fermentation performance evaluation index system has not yet been established.

[0003] Currently, fermented feed production is still dominated by small and medium-sized enterprises, which generally suffer from inconsistent product quality and poor batch-to-batch stability. The core reasons for this are: a lack of assessment of the fermentation value of raw materials, over-reliance on experience in formula design, and a lack of scientifically reliable quantitative tools to assist decision-making. This is particularly evident in the imbalance of carbon and nitrogen composition and their ratio in the formula, leading to slow fermentation start-up, insufficient acid production, low bacterial activity, and even fermentation failure, resulting in economic losses.

[0004] Therefore, there is an urgent need to establish a method for systematically evaluating the fermentation performance of raw materials, and to develop a simple and low-cost formulation-aided design and calibration tool to help companies achieve rapid formulation optimization and stable control of the fermentation process, thereby improving product quality consistency. Summary of the Invention

[0005] The purpose of this invention is to provide a method for evaluating the fermentation performance of solid-state fermented feed ingredients and a formulation design system to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for evaluating the fermentation performance of solid-state fermented feed ingredients, comprising the following steps:

[0008] The process includes the following steps: determining the contents of glucose, fructose, maltose, and sucrose in the raw materials; calculating the comprehensive carbon source value based on weighting coefficients, using the formula: Comprehensive carbon source value (%) = 0.265 × glucose content + 0.265 × fructose content + 0.235 × maltose content + 0.235 × sucrose content; determining the amino acid nitrogen content in the raw materials as an indicator of available nitrogen source; determining the water activity value of the raw materials; determining the acid-holding capacity value of the raw materials; and calculating the fermentability index using bran as a reference material through a fermentation acid production comparison method, using the formula: Fermentability = Fermentation acid production value of the raw material to be tested / Fermentation acid production value of bran.

[0009] Preferably, the weighting coefficient is determined by the efficiency and rate of carbon source utilization by lactic acid bacteria and yeast.

[0010] A nutritional baseline model for solid-state fermented feed formulation, wherein the minimum threshold of the model is set based on the calculation results of the method, and the comprehensive carbon source content is not less than 2.62%, the amino acid nitrogen content is not less than 0.14%, the water holding capacity is not less than 1.25, the acid holding capacity is not less than 0.25, and the fermentability is not less than 0.20.

[0011] A method for predicting total acidity in solid-state fermented feed uses the following kinetic equation: In the formula, X represents total acidity; a represents the comprehensive carbon source; b represents amino acid nitrogen; c represents water-holding capacity; and d represents acid-holding capacity.

[0012] A solid-state fermentation feed formulation auxiliary design and calibration system is disclosed. The system includes: a raw material database module storing five core indicator data for various fermentation raw materials; a formulation verification module for calculating the comprehensive performance indicators of the formulation and comparing them with the nutritional baseline; and a fermentation prediction module for predicting the total acid and bacterial activity levels at the fermentation endpoint based on the kinetic equations. The system is implemented in spreadsheet format. The system also includes a cost optimization module for providing lower-cost raw material adjustment schemes while meeting the fermentation nutritional baseline.

[0013] Compared with the prior art, the beneficial effects of the present invention are:

[0014] This invention establishes a systematic quantitative evaluation system for the fermentation performance of raw materials. By comprehensively considering five core dimensions—carbon source, amino acid nitrogen, water activity, acid-holding capacity, and fermentability—and through extensive experimental verification, it establishes minimum thresholds for key indicators such as comprehensive carbon source (≥2.62%) and amino acid nitrogen (≥0.14%). This provides a safe boundary for formulation design and can avoid problems such as slow fermentation or failure caused by insufficient nutrients or imbalanced ratios. At the same time, it can accurately predict the total acid and bacterial activity levels at the endpoint before fermentation, enabling producers to optimize process parameters in advance.

[0015] Furthermore, this invention develops a low-cost, easy-to-use formulation assistance tool that benefits small and medium-sized enterprises (SMEs). The system uses common spreadsheets (such as Excel) as its platform, eliminating the need for businesses to invest in expensive specialized software or equipment. Its user-friendly interface and simple operation significantly lower the technical barrier to entry, effectively addressing the core pain point of SMEs lacking professional technical personnel and formulation tools. Detailed Implementation

[0016] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0017] Example 1:

[0018] Test materials

[0019] Raw material selection: Select 3 commonly used raw materials in the industry (suitable for procurement scenarios of small and medium-sized enterprises):

[0020] Wheat bran, soybean meal, and distiller's grains.

[0021] Test reagents: Glucose / fructose / maltose / sucrose test kit.

[0022] Experimental equipment: High performance liquid chromatograph (HPLC, model Agilent 1260, for measuring sugar content), water activity meter (model Decagon AQUALAB4TE, for measuring water activity), pH meter (model METTLERFE28, for measuring systemic acidity), and constant temperature anaerobic fermentation chamber (model LRH-150, for simulating the production fermentation environment).

[0023] An "Excel-based formula-aided design system" was built, containing four modules (raw material database, formula verification, fermentation prediction, and cost optimization), with the interface simplified to three worksheets (corresponding to "raw material data", "formula calculation", and "optimization scheme" respectively).

[0024] Basic index determination (average value of 3 parallel tests).

[0025] The table below is an example;

[0026] raw material Glucose content (%) Fructose content (%) Maltose content (%) Sucrose content (%) Amino acid nitrogen (%) Water activity (Aw) Acidity (mL / 100g) Fermentation acidity (mmol / L, anaerobic fermentation at 37℃ for 48h) bran 1.25 0.38 0.82 0.15 0.18 0.72 0.32 28.6 (benchmark value) soybean meal 0.42 0.15 0.21 0.08 0.35 0.68 0.28 19.2 Distillers' grains 2.15 0.72 0.58 0.25 0.12 0.75 0.45 31.5

[0027] Calculation of core indicators (according to the invention formula)

[0028] Overall carbon source value:

[0029] Wheat bran = 0.265 × 1.25 + 0.265 × 0.38 + 0.235 × 0.82 + 0.235 × 0.15 ≈ 0.89%

[0030] Soybean meal = 0.265 × 0.42 + 0.265 × 0.15 + 0.235 × 0.21 + 0.235 × 0.08 ≈ 0.24%

[0031] Distillers' grains = 0.265 × 2.15 + 0.265 × 0.72 + 0.235 × 0.58 + 0.235 × 0.25 ≈ 0.98%

[0032] Fermentability:

[0033] Bran = 28.6 / 28.6 = 1.00 (benchmark value)

[0034] Soybean meal = 19.2 / 28.6 ≈ 0.67

[0035] Distillers' grains = 31.5 / 28.6 ≈ 1.10

[0036] Formulation design and system application;

[0037] 1. Step 1: Raw material database entry

[0038] Enter the above indicators and raw material costs (wheat bran 2.2 yuan / kg, soybean meal 4.8 yuan / kg, distiller's grains 1.8 yuan / kg) into the "Raw Material Data" worksheet in Excel. The system will automatically mark "whether it meets the basic requirements" (e.g., if the amino acid nitrogen content of distiller's grains is 0.12% < 0.14, mark "nitrogen source is too low").

[0039] Step 2: Initial Formulation Design and Validation

[0040] Initial formula: 30% wheat bran + 25% soybean meal + 45% distillers' grains

[0041] System calculation (recipe validation module):

[0042] The overall carbon source value of the formula = 30% × 0.89% + 25% × 0.24% + 45% × 0.98% ≈ 0.76% (< 2.62%, not up to standard)

[0043] The amino acid nitrogen content in the formula is calculated as follows: 30% × 0.18% + 25% × 0.35% + 45% × 0.12% ≈ 0.18% (≥ 0.14%, meeting the standard).

[0044] The acid strength of the formula is calculated as follows: 30% × 0.32 + 25% × 0.28 + 45% × 0.45 ≈ 0.37 (≥ 0.25, meeting the standard).

[0045] Fermentability of the formula = 30% × 1.00 + 25% × 0.67 + 45% × 1.10 ≈ 0.95 (≥ 0.20, meets the standard)

[0046] System prompt: The overall carbon source value is insufficient. It is recommended to increase the amount of high carbon source raw materials (such as distiller's grains) or supplement with external carbon sources (such as glucose).

[0047] Step 3: Formula Adjustment and Optimization

[0048] Adjustments will be made to increase the proportion of distillers' grains to 60%, reduce soybean meal to 15%, and maintain wheat bran at 25% (balancing carbon source and cost).

[0049] Optimized formula: 25% wheat bran + 15% soybean meal + 60% distillers' grains + 1% exogenous glucose (to supplement carbon source)

[0050] Secondary verification:

[0051] The overall carbon source value of the formula is calculated as follows: 25% × 0.89% + 15% × 0.24% + 60% × 0.98% + 1% × 100% (glucose purity is calculated as 100%) ≈ 2.71% (≥ 2.62%, meeting the standard).

[0052] Step 4: Fermentation performance prediction (fermentation prediction module)

[0053] Substituting into the dynamic equation: the equation mentioned in the invention is adopted (assuming the measured fitting equation is: X=0.12a+0.35b+0.08c-0.05d, based on common fitting relationships in the industry).

[0054] Where a=2.71%, b=0.18%, c=1.32 (measured water-holding capacity), and d=0.37

[0055] The predicted total acidity X = 0.12 × 2.71 + 0.35 × 0.18 + 0.08 × 1.32 - 0.05 × 0.37 ≈ 0.41% (within the acceptable range of 0.3% to 0.6%).

[0056] Step 5: Cost Optimization (Cost Optimization Module)

[0057] The system generates two solutions:

[0058] ① Option 1 (Keep the formula, replace the low-priced raw materials): Replace "commercial glucose" with "malt syrup" (carbon source equivalent, cost reduced from 8 yuan / kg to 4 yuan / kg), the total formula cost reduced from 2.58 yuan / kg to 2.54 yuan / kg;

[0059] ②Option 2 (adjusted proportions): Distillers' grains increased to 65%, wheat bran reduced to 20%, total carbon source value 2.68% (still meets the standard), cost reduced to 2.49 yuan / kg;

[0060] Final selection: Option 2 (lowest cost and meets the target), final formula determined: 20% wheat bran + 15% soybean meal + 65% distillers' grains + 1% malt syrup.

[0061] Fermentation validation experiment (to verify the effectiveness of the protocol)

[0062] Fermentation conditions: Temperature: 37℃, anaerobic environment (CO2 concentration 5%), fermentation time: 72h (typical cycle for small and medium-sized enterprises).

[0063] Inoculation amount: 2% (by weight) of mixed lactic acid bacteria (Lactobacillus plantarum) and yeast (Saccharomyces cerevisiae).

[0064] The endpoint test results are shown in the table below.

[0065] detection indicators Predicted value Measured value Error rate Industry qualification standards Total acid (%) 0.41 0.43 4.80% ≥0.3% Lactic acid bacteria activity (CFU / g) <![CDATA[≥1×10 8 ]]> <![CDATA[1.5×10 8 ]]> - <![CDATA[≥1×10 8 ]]> Moisture (%) - 32.5 - 30%~35% Batch stability (3 batches) - Coefficient of variation ≤3% - ≤5%

[0066] In summary, the raw material evaluation method of this invention can accurately quantify the fermentation performance of raw materials, and the formulation system can quickly complete the design, verification, and optimization, solving the problem of insufficient carbon source in empirical formulations.

[0067] It should be understood that numerous specific implementation decisions can be made during the development of any practical implementation, such as in any engineering or design project. Such development efforts may be complex and time-consuming, but for those skilled in the art who benefit from this disclosure, the development effort will be a routine work of design, manufacturing, and production without requiring much experimentation.

[0068] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for evaluating the fermentation performance of solid-state fermented feed ingredients, characterized in that, Includes the following steps: The contents of glucose, fructose, maltose, and sucrose in the raw materials were determined; the comprehensive carbon source value was calculated based on the weighting coefficients, using the formula: Comprehensive carbon source value (%) = 0.265 × glucose content + 0.265 × fructose content + 0.235 × maltose content + 0.235 × sucrose content; the amino acid nitrogen content in the raw materials was determined as an indicator of available nitrogen source; the water activity value of the raw materials was determined; the acid-holding capacity value of the raw materials was determined; and the fermentability index was calculated using a fermentation acid production comparison method with wheat bran as the reference material, using the formula: Fermentability = Fermentation acid production value of the raw material / Fermentation acid production value of wheat bran.

2. The evaluation method according to claim 1, characterized in that, The weighting coefficients are determined by the efficiency and rate of carbon source utilization by lactic acid bacteria and yeast.

3. A nutritional baseline model for solid-state fermented feed formulations, characterized in that, The minimum threshold of the model is set based on the calculation results of the method described in claim 1, with a comprehensive carbon source content of not less than 2.62%, an amino acid nitrogen content of not less than 0.14%, a water holding capacity of not less than 1.25, an acid holding capacity of not less than 0.25, and a fermentability of not less than 0.

20.

4. A method for predicting total acidity in solid-state fermented feed, applied to the evaluation method described in claim 1, characterized in that, The following dynamic equations are used for prediction: In the formula, X represents total acidity; a represents the comprehensive carbon source; b represents amino acid nitrogen; c represents water-holding capacity; and d represents acid-holding capacity.

5. A solid-state fermentation feed formulation auxiliary design and calibration system, used to implement the evaluation method according to any one of claims 1-4, characterized in that, The system includes: a raw material database module, which stores five core indicator data for various fermentation raw materials; a formula verification module, which calculates the comprehensive performance indicators of the formula and compares them with the nutritional baseline; and a fermentation prediction module, which predicts the total acid and bacterial activity levels at the fermentation endpoint based on the kinetic equations. The system is implemented in spreadsheet format.

6. The system according to claim 5, characterized in that, The system also includes a cost optimization module, which provides a lower-cost raw material adjustment scheme while meeting the minimum nutritional requirements for fermentation.

Images