Ampeliscid juvenile artificial feed and response surface optimization method of protein and fat levels thereof
Patent Information
- Application Number
- CN202611125795.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-07-28
- Publication Date
- 2026-09-15
Smart Images
Figure CN122744444A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of feed preparation technology, specifically relating to a compound feed for juvenile sea cucumbers and a response surface methodology for optimizing their protein and fat levels. Background Technology
[0002] *Apostichopus japonicus*, belonging to the phylum Echinodermata, family Stichopodidae, and genus *Apostichopus*, is widely distributed in the shallow waters along the western Pacific coast. It is an important aquaculture species in my country, possessing significant economic and industrial value. In recent years, the artificial aquaculture industry of *Apostichopus japonicus* has developed rapidly, with the scale of cultivation continuously expanding, leading to a growing demand for high-quality formulated feed. The nutrient composition of the feed directly affects the growth performance, digestive physiology, and immune function of *Apostichopus japonicus*, and is also closely related to the nitrogen and phosphorus emission levels and the degree of pollution in the aquaculture environment.
[0003] Protein and fat are the two most critical nutrients in formulated aquatic feeds. Protein is the core structural substance for the growth of tissues and the synthesis of body wall structures in sea cucumbers, and its supply level in the feed directly determines tissue deposition efficiency and weight gain rate. Fat is an important non-protein energy source; appropriate addition can reduce the proportion of protein used for energy metabolism through the protein-saving effect, thereby improving the utilization efficiency of feed protein. At the same time, fat can also serve as a carrier for fat-soluble active ingredients, ensuring the transport and absorption of fat-soluble nutrients. Therefore, determining the appropriate levels of protein and fat in the feed and achieving a reasonable ratio between the two is a core prerequisite for improving the growth performance of sea cucumbers, reducing feed costs, and reducing aquaculture pollution.
[0004] Currently, most studies on the nutritional requirements of sea cucumber mimics employ traditional single-factor gradient experiments, which involve setting different gradients for only one variable—protein or fat—to explore the optimal addition range for each component. While this method can initially determine the suitable addition range for a single nutrient factor, it has significant technical limitations: First, single-factor experiments cannot analyze the synergistic or antagonistic interactions between multiple nutrients, nor can they reproduce the true effects of multiple components working together in actual feed formulations. For example, the regulatory mechanism of fat's energy supply on protein utilization efficiency is difficult to elucidate through a single-factor experiment system. Second, single-factor experiments can only obtain experimental results under discrete gradients, making it impossible to construct continuous and predictable mathematical models. This hinders the accurate prediction of growth effects for arbitrary ratios within the experimental range and fails to provide quantitative support for refined formulation adjustments.
[0005] Response surface methodology (RSM) is a multi-factor optimization experimental method that integrates mathematical modeling and statistical analysis. Through a scientifically designed experimental scheme, it constructs a quadratic polynomial regression model between the response value and multiple independent variables with a limited number of experiments. This allows for the systematic analysis of the main effects, interaction effects, and secondary effects of each factor, and the precise determination of the optimal factor combination. This method offers advantages such as a small number of experiments, a short research cycle, and high accuracy of the regression model, and has been applied in the optimization of nutritional requirements for various aquatic animals. However, research on the joint optimization of protein and fat levels in juvenile sea cucumbers using Rhizoctonia solani is still relatively lacking. A systematic optimization method and precise formulation parameters have not yet been developed, nor has a quadratic regression model that can effectively predict weight gain rate been established. This results in a lack of quantitative theoretical basis for the nutritional design of compound feeds for juvenile sea cucumbers, making it difficult to achieve precise control of protein and fat levels, thus hindering the development and industrial application of precision nutrition feeds for juvenile sea cucumbers. Summary of the Invention
[0006] The purpose of this invention is to provide a response surface methodology for optimizing the protein and fat levels of a juvenile sea cucumber compound feed. This methodology effectively overcomes the shortcomings of single-factor experiments, which cannot reveal the interactions of nutritional factors and are difficult to achieve multi-parameter synergistic optimization. It provides an efficient and reliable research method for optimizing the nutritional levels of juvenile sea cucumber compound feed.
[0007] The objective of this invention is achieved through the following technical solution: This invention provides a response surface methodology for optimizing the protein and fat levels in a formulated feed for juvenile sea cucumbers, comprising the following steps: (1) Using the crude protein and crude fat levels in the feed as independent variables and the weight gain rate of juvenile sea cucumbers as the response value, a central composite design was adopted to set up multiple experimental treatments and prepare experimental feeds with corresponding nutrient levels. (2) Select healthy juvenile sea cucumbers and randomly assign them to each experimental treatment group for breeding experiments. After the experiment, the weight gain rate of each group of juvenile sea cucumbers was measured. (3) Perform quadratic polynomial regression fitting on the weight gain rate data obtained from the experiment to construct a quadratic regression prediction model of weight gain rate with respect to protein level and fat level; (4) The extreme value optimization of the quadratic regression prediction model was carried out by the response surface methodology to obtain the optimal combination of protein and fat levels in the compound feed of juvenile sea cucumber.
[0008] Furthermore, in step (1), the crude protein level is set within the range of 4% to 20%, and the crude fat level is set within the range of 1% to 5%; the central composite design adopts the central composite sequential design mode, setting two factors and five coding levels, with coding levels being -α, -1, 0, +1, and +α in sequence, where α = √2 ≈ 1.414; a total of 13 experimental groups are set up, including 4 factorial point groups, 4 pivot point groups and 5 central point groups, with 3 parallel culture units set up in each group.
[0009] Furthermore, in step (3), the expression for the quadratic regression prediction model is: R = -11.13114 + 13.38177A + 5.36432B + 0.364242AB - 0.462068A 2 -2.36342B 2 In the formula, R is the weight gain rate of juvenile sea cucumber (in %), A is the percentage of crude protein in the feed, and B is the percentage of crude fat in the feed. The p-value of the quadratic regression prediction model is 0.0009, which is highly significant. The p-value of the model lack of fit is 0.5302, which is not significant. The model determination coefficient R² = 0.9236.
[0010] Furthermore, in step (2), the juvenile sea cucumbers are healthy individuals artificially bred from the same batch, with an initial weight of 9-10g; the breeding experiment period is 56 days, the water temperature is controlled at 13-19℃ during the breeding period, the water pH is 7.8-8.2, the dissolved oxygen content is greater than 5mg / L, and the ammonia nitrogen and nitrite content are both less than 0.05mg / L; the fish are fed once a day at a fixed time, and the feed is prepared into a mud-like state before feeding. One-third of the volume of disinfected seawater is replaced daily and the uneaten feed and feces are cleaned up.
[0011] Furthermore, in step (4), the optimal combination of levels obtained by optimization is 15.398% crude protein and 2.322% crude fat, corresponding to a maximum weight gain rate of 98.102% predicted by the model; the method also includes a model verification step: the verification feed is prepared according to the optimal combination of levels, and three parallel breeding units are set up to carry out verification experiments. The breeding conditions are consistent with the formal experiment. The measured weight gain rate of juvenile sea cucumber is 97.029%, and the relative error with the model prediction value is 1.079%.
[0012] The present invention also provides a compound feed for juvenile sea cucumbers, wherein the crude protein content of the compound feed is 15.4% and the crude fat content is 2.32%; the nutritional level of the compound feed is determined by the response surface methodology.
[0013] Furthermore, the raw materials of the compound feed consist of fish meal, Sargassum powder, kelp powder, scallop edge powder, attractant yeast powder, wheat flour, fish oil, compound premix and sea mud.
[0014] Furthermore, each kilogram of the compound premix contains the following nutrients: Vitamin A 400,000 IU, Vitamin D3 100,000 IU, Vitamin E 5,000 mg, Vitamin K3 1,000 mg, Vitamin B1 800 mg, Vitamin B2 800 mg, Vitamin B6 800 mg, and Vitamin B2. 12 6.0mg, Vitamin C 15000mg, D-calcium pantothenate 2800mg, Nicotinamide 5000 mg, Folic acid 380mg, D-biotin 8.0mg, Inositol 7000mg, Magnesium 4000mg, Zinc 2000mg, Manganese 1500mg, Copper 450mg, Iron 1800mg, Cobalt 70mg, Iodine 60mg, Selenium 20mg.
[0015] Furthermore, the compound feed is prepared by the following method: all solid raw materials are crushed by a pulverizer and passed through a 60-mesh sieve. Each solid raw material is weighed according to the formula ratio and mixed evenly. Then, liquid raw materials such as fish oil are added and stirred continuously. After adding an appropriate amount of distilled water and mixing thoroughly, the mixture is placed in a 60°C oven to dry. After cooling, it is sealed and stored.
[0016] Furthermore, the formulated feed is used for the cultivation of juvenile sea cucumbers with an initial weight of 9-10g. It is prepared as a mud-like substance before feeding, and the daily feeding amount is 2% of the total weight of the juvenile sea cucumbers. It can improve the weight gain rate of juvenile sea cucumbers and regulate the activity of trypsin, lipase and amylase.
[0017] The beneficial effects of this invention are as follows: This invention employs a central composite sequential design in response surface methodology, using feed protein and fat levels as independent variables and the weight gain rate of juvenile sea cucumbers as the response value to conduct nutritional optimization research. Compared to traditional single-factor gradient experiments, which can only examine the suitable range of a single nutritional factor, this invention can systematically analyze the combined effects of two nutritional factors on the growth of juvenile sea cucumbers, and can intuitively reflect the interaction patterns between factors. It also has the advantages of fewer experimental groups, shorter research period, and higher accuracy of regression models, and can establish a continuous and quantifiable quadratic prediction model. This effectively makes up for the shortcomings of single-factor experiments, which cannot reveal the interaction of nutritional factors and are difficult to achieve multi-parameter synergistic optimization. It provides an efficient and reliable research method for optimizing the nutritional level of compound feed for sea cucumbers.
[0018] The quadratic regression model for the weight gain rate of juvenile sea cucumbers constructed in this invention is highly significant overall, with no significant model lack of fit and a coefficient of determination of 0.9236, indicating good model fit and stable predictive ability for the weight gain rate of juvenile sea cucumbers under different protein and fat levels. Independent validation experiments confirmed that the relative error between the actual weight gain rate of juvenile sea cucumbers under the optimal nutrient ratio and the model's predicted value was only 1.079%, further verifying the model's accuracy and practicality. Analysis of variance clarified that both protein and fat have significant positive effects on the weight gain rate of juvenile sea cucumbers, with protein having a greater impact than fat. Furthermore, it was confirmed that there was no significant interaction between the two within the experimental range of 4%–20% protein and 1%–5% fat. The secondary effect of protein reached a highly significant level, while the secondary effect of fat was not significant. This clearly elucidates the differences and changing patterns of the roles of the two nutrient factors in the growth process of juvenile sea cucumbers, providing a clear quantitative basis for the precise adjustment of feed formulations and the design of nutritional balance.
[0019] This invention, through response surface methodology optimization, yielded the optimal nutritional profile for juvenile sea cucumber (Stichopus japonicus) feed: 15.398% protein and 2.322% fat. This nutritional ratio perfectly aligns with the benthic, omnivorous physiological characteristics of juvenile sea cucumbers. It provides sufficient structural protein for the growth of the juvenile body wall tissue, achieving a high weight gain rate, while the appropriate fat content supplies energy and essential fatty acids, promoting the absorption and utilization of fat-soluble nutrients. This avoids the problems of excessive protein levels increasing the burden on metabolism and ammonia excretion, and imbalanced fat levels leading to metabolic disorders. Under this nutritional ratio, juvenile sea cucumbers can maintain good digestive enzyme activity levels, ensuring efficient digestion and absorption of feed nutrients. Simultaneously, the rational nutritional structure reduces nitrogen and phosphorus emissions during the aquaculture process, lowering the risk of aquatic pollution, thus balancing aquaculture efficiency and ecological benefits.
[0020] This invention clearly defines the composition of feed ingredients, preparation process, and corresponding breeding management parameters. The feed ingredients are widely available and the preparation process is simple and controllable, facilitating large-scale industrial production. Based on the effect of fat on weight gain, while ensuring adequate protein supply, the source and proportion of fat can be flexibly adjusted within a wide range during actual production, without causing drastic fluctuations in the weight gain rate of juvenile sea cucumbers. This facilitates flexible control of formulation costs and localization of raw materials. The findings of this research provide solid theoretical support and directly applicable technical solutions for the development of precision-nutritional compound feeds for juvenile sea cucumbers, and have significant practical value for improving the growth performance, feed utilization efficiency, and industrial technology level of juvenile sea cucumber farming. Attached Figure Description
[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0022] Figure 1 This is a graph showing the range of changes in water temperature, pH, and salinity during the culture experiment of juvenile sea cucumbers. Figure 2 The surface plot and contour plot show the response of the interaction between dietary protein and fat to the weight gain rate of juvenile sea cucumbers. Detailed Implementation
[0023] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as a limitation of the present invention, but rather as a more detailed description of certain aspects, features, and embodiments of the present invention.
[0024] It should be understood that the terminology used in this invention is merely for describing particular embodiments and is not intended to limit the invention. Furthermore, with respect to numerical ranges in this invention, it should be understood that each intermediate value between the upper and lower limits of the range is also specifically disclosed. Every smaller range between any stated value or intermediate value within a stated range, and any other stated value or intermediate value within said range, is also included in this invention. The upper and lower limits of these smaller ranges may be independently included or excluded from the range.
[0025] Unless otherwise stated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. While only preferred methods and materials have been described herein, any methods and materials similar or equivalent to those described herein may be used in the implementation or testing of this invention. All references to this specification are incorporated by way of citation to disclose and describe methods and / or materials associated with those references. In the event of any conflict with any incorporated reference, the content of this specification shall prevail.
[0026] Various modifications and variations can be made to the specific embodiments described in this specification without departing from the scope or spirit of the invention, as will be apparent to those skilled in the art. Other embodiments derived from this specification will also be apparent to those skilled in the art. This specification and embodiments are merely exemplary.
[0027] The terms “include,” “including,” “have,” “contain,” etc., used in this article are all open-ended terms, meaning that they include but are not limited to.
[0028] The present invention will be further described in detail below with reference to specific embodiments and accompanying drawings. The following embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Experimental methods in these embodiments that do not specify specific conditions were performed according to conventional experimental conditions in the art or according to the conditions recommended by the reagent / instrument manufacturer; unless otherwise specified, all reagents and consumables used are commercially available conventional analytical grade reagents.
[0029] Example 1: Response surface methodology optimization experiment on protein and fat levels in a compound feed for juvenile sea cucumbers. 1. Experimental Materials and Equipment (1) Laboratory animals Juvenile *Apostichopus japonicus* used in the experiment were obtained from Yingrui Marine Fisheries Co., Ltd. in Xiapu County, Ningde City, Fujian Province, and were healthy individuals from the same batch bred that year. The culture experiment was conducted at the experimental base of the Fujian Provincial Marine Fisheries Seed Industry Research Center. Prior to the experiment, the juvenile *Apostichopus japonicus* were temporarily housed in sterilized culture tanks, fed commercial feed for two weeks, and then fasted for 24 hours. 780 healthy individuals with good body condition and similar weight (initial weight approximately 10.0g) were selected for the formal culture experiment. The response surface methodology validation experiment used juvenile *Apostichopus japonicus* from the same batch, with an initial weight of approximately 9.0g, consistent with the initial size of the response surface methodology experiment.
[0030] (2) Feed ingredients The experimental feed ingredients included fishmeal, Sargassum powder, kelp powder, scallop edge powder, attractant yeast powder, wheat flour, fish oil, compound premix (containing compound vitamins and compound minerals), and marine mud. The basic nutritional components of each feed ingredient are shown in Table 1 below: Table 1. Main components of feed ingredients (%)
[0031] The nutritional components provided per kilogram of premix are: Vitamin A 400,000 IU, Vitamin D3 100,000 IU, Vitamin E 5,000 mg, Vitamin K3 1,000 mg, Vitamin B1 800 mg, Vitamin B2 800 mg, Vitamin B6 800 mg, and Vitamin B1... 12 6.0mg, Vitamin C 15000mg, D-calcium pantothenate 2800mg, Nicotinamide 5000mg, Folic acid 380mg, D-biotin 8.0mg, Inositol 7000mg, Magnesium 4000mg, Zinc 2000mg, Manganese 1500mg, Copper 450mg, Iron 1800mg, Cobalt 70mg, Iodine 60mg, Selenium 20mg.
[0032] (3) Experimental equipment and analysis software The equipment used in the experiment included a grinder, a 60-mesh standard sieve, a feed mixer, a 60℃ constant temperature oven, a plastic aquaculture tank, an oxygen pump, an electronic balance, and an ice tray. Data processing was performed using Excel software, SPSS 18.0 statistical software, and Design-Expert 12 experimental design software.
[0033] 2. Preparation of experimental feed This experiment employed a central composite design to set up 13 experimental diets with different protein and fat levels. The composition of each diet formulation and the measured nutrient components are shown in Table 2 below. Table 2. Experimental feed formulation and nutrient composition analysis (%)
[0034] The specific process for feed preparation is as follows: After crushing various solid raw materials with a pulverizer, they are sieved through a 60-mesh sieve; each raw material is accurately weighed according to the formula, and added in the order of solid raw materials first and then liquid raw materials while continuously stirring to ensure that the raw materials are fully mixed; after adding an appropriate amount of distilled water, the mixture is placed in a mixer for further thorough mixing; the mixed feed material is placed in a 60℃ oven to dry, cooled, and then sealed for storage for later use.
[0035] 3. Design and Management of Aquaculture Experiments (1) Response surface analysis experimental design This experiment employed a central composite sequential design (CCC) within a central composite design framework. The independent variables were feed protein level (factor A, range 4%–20%) and fat level (factor B, range 1%–5%), with the weight gain rate of juvenile sea cucumbers as the response value. A two-factor, five-level coding system was implemented (coding levels were -α, -1, 0, +1, +α, where α = √2 ≈ 1.414). The correspondence between the coding levels and actual levels of each factor is shown in Table 3 below. Table 3. Coding Table for Experimental Factor Levels
[0036] Note: In actual feed formulation, -1 and +1 levels are rounded to 6.5% and 17.5% (protein), and 1.5% and 4.5% (fat), respectively.
[0037] The experiment consisted of 13 experimental groups, including 4 factorial points (coded as ±1, ±1), 4 axis points (coded as ±α, 0 or 0, ±α), and 5 center points (coded as 0, 0). Each group had 3 parallel tanks, totaling 39 independent experimental units. The rearing experiments were conducted in plastic tanks measuring 75cm x 50cm x 40cm, with 20 juvenile sea cucumbers stocked in each tank. The actual protein and fat levels, group type, and measured weight gain for each experimental group are shown in Table 4 below. Table 4. Results of grouping and weight gain rate in the central composite design experiment.
[0038] (2) Daily management of aquaculture The rearing cycle is 56 days (8 weeks). During the rearing period, a full-feeding diet is given daily at 17:00. Before feeding, the feed is mixed and prepared into a slurry-like consistency according to a fixed ratio, ensuring even dispersion in the water. The initial feeding amount is 2% of the total weight of each group of juvenile sea cucumbers, and the amount is adjusted daily based on the daily feeding behavior. Seawater disinfected with chlorine dioxide is replaced daily, with each replacement representing 1 / 3 of the total water volume. Uneaten feed and feces are removed simultaneously. Aeration pumps are continuously operated to ensure sufficient dissolved oxygen in the water. Each tank is thoroughly cleaned every two weeks.
[0039] Throughout the experiment, the water temperature was controlled between 13 and 19°C, the pH was maintained between 7.8 and 8.2, the dissolved oxygen content was greater than 5 mg / L, and the ammonia nitrogen and nitrite contents were both less than 0.05 mg / L. The dynamic changes in water temperature, pH, and salinity during the experiment are as follows: Figure 1 As shown.
[0040] like Figure 1 As shown, a total of 9 monitoring nodes were set up during the experimental period to record water quality parameters. The water temperature showed a trend of first slightly increasing and then gradually decreasing over time, with the lowest water temperature being 13.3℃ and the highest being 19.0℃. The water salinity fluctuated between 27 and 32, and the pH value fluctuated between 7.8 and 8.2. All water quality parameters were within a stable range.
[0041] (3) Model validation experiment The validation feed was formulated based on the optimal protein and fat levels (15.398% protein, 2.322% fat) obtained from response surface methodology. Three parallel tanks were set up, with 20 juvenile sea cucumbers in each tank. The selection of experimental materials and the breeding management methods were completely consistent with the aforementioned response surface analysis experiment, and the breeding cycle was 8 weeks. After the experiment, the weight gain rate of each group was calculated and compared with the model prediction value to verify the reliability of the model.
[0042] 4. Indicator Measurement and Calculation Methods (1) Weight gain rate determination After the breeding experiment, the sea cucumbers were fasted for 24 hours. Twelve sea cucumbers were randomly selected from each tank, placed on a tray with ice, and their body surface moisture was wiped off before being accurately weighed. The weight gain rate (WG, %) was calculated according to the following formula: WG(%)=[(W t [(g)-W0(g)] / W0(g)*100; In the formula, W0 is the initial weight of the sea cucumber (g), W tThe final weight (g) of the sea cucumber (Stichopus japonicus).
[0043] (2) Digestive enzyme activity assay After the experiment, digestive tissues of the sea cucumber were collected, and the activities of three digestive enzymes—trypsin, lipase, and amylase—were measured. Enzyme activity was expressed in U / mg prot. The digestive enzyme activity results for the 13 experimental groups are shown in Table 5 below. Table 5. Effects of different protein and fat ratios in feed on the digestive enzyme activity of juvenile sea cucumbers.
[0044] 5. Data Processing and Model Building The experimental data were analyzed using Excel software to calculate the mean and standard error. One-way ANOVA and independent samples t-test were performed using SPSS 18.0 software. P < 0.05 was considered statistically significant, and P < 0.01 was considered highly statistically significant. Design-Expert 12 software was used for quadratic multinomial regression fitting, significance testing, ANOVA, and response surface methodology.
[0045] With weight gain rate as the response value R, protein level as the independent variable A, and fat level as the independent variable B, the fitted quadratic polynomial regression equation is as follows: R = -11.13114 + 13.38177A + 5.36432B + 0.364242AB - 0.462068A 2 -2.36342B 2 .
[0046] An analysis of variance was performed on the above regression model, and the results are shown in Table 6 below: Table 6. Analysis of variance results of the quadratic regression model for weight gain rate
[0047] The analysis of variance results show that the regression model has a p-value of 0.0009, reaching a highly significant level; the p-value for the model's lack of fit is 0.5302, which is greater than 0.05, indicating no significant lack of fit; the model's coefficient of determination R0... 2 =0.9236, indicating that the model fits well and can be used to predict the weight gain rate of juvenile sea cucumbers under different protein and fat levels.
[0048] From the perspective of single-factor effects, the effect of protein on weight gain rate was highly significant, and the effect of fat on weight gain rate was significant. Based on the F-value, the influence of the two factors on weight gain rate was: protein > fat. From the perspective of quadratic effects, the quadratic term A² for protein was highly significant and had a negative coefficient, indicating that weight gain rate followed a parabolic trend of first increasing and then decreasing with increasing protein levels, suggesting a clear optimal value. The quadratic term B² for fat was not significant, but its coefficient was also negative. The p-value of the interaction term AB was greater than 0.05, indicating that within the experimental range, there was no significant interaction between protein and fat on weight gain rate.
[0049] 6. Response Surface Analysis and Solution of Optimal Conditions Using Design-Expert 12 software, response surface plots and contour plots were generated to show the weight gain rate as a function of protein and fat levels, such as... Figure 2 As shown.
[0050] like Figure 2 As shown, the overall response surface exhibits a hill-like shape, indicating that there are suitable ranges for both protein and fat levels to promote weight gain in juvenile sea cucumbers; levels that are too low or too high are detrimental to growth. The contour lines are approximately elliptical, suggesting that there is room for optimization in the combination of the two nutritional factors.
[0051] The regression model was optimized using software to obtain the factor codes corresponding to the maximum weight gain rate: A=0.472 (corresponding to an actual protein level of 15.398%), B=-0.339 (corresponding to an actual fat level of 2.322%), and the model predicted a maximum weight gain rate of 98.102%.
[0052] 7. Model Validation Results A validation experiment was conducted using feed formulated with the optimal nutritional levels (15.398% protein and 2.322% fat) obtained through optimization. After 8 weeks of rearing, the actual measured average weight gain rate of juvenile sea cucumbers was 97.029%, which was very close to the model prediction value of 98.102%, with a relative error of only 1.079%. This indicates that the response surface methodology model established in this study has good prediction accuracy and reliability, and can be effectively used to optimize the protein and fat levels in the formulated feed for juvenile sea cucumbers.
[0053] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not 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 response surface methodology for optimizing protein and fat levels in a formulated feed for juvenile sea cucumbers, characterized in that... Includes the following steps: (1) Using the crude protein and crude fat levels in the feed as independent variables and the weight gain rate of juvenile sea cucumbers as the response value, a central composite design was adopted to set up multiple experimental treatments and prepare experimental feeds with corresponding nutrient levels. (2) Select healthy juvenile sea cucumbers and randomly assign them to each experimental treatment group for breeding experiments. After the experiment, the weight gain rate of each group of juvenile sea cucumbers was measured. (3) Perform quadratic polynomial regression fitting on the weight gain rate data obtained from the experiment to construct a quadratic regression prediction model of weight gain rate with respect to protein level and fat level; (4) The extreme value optimization of the quadratic regression prediction model was carried out by the response surface methodology to obtain the optimal combination of protein and fat levels in the compound feed of juvenile sea cucumber.
2. The response surface optimization method according to claim 1, characterized in that, In step (1), the crude protein level is set in the range of 4% to 20%, and the crude fat level is set in the range of 1% to 5%. The central composite design adopts the central composite sequential design mode, setting two factors and five coding levels, with coding levels of -α, -1, 0, +1, and +α in sequence, where α = √2 ≈ 1.
414. A total of 13 experimental groups are set up, including 4 factorial point groups, 4 pivot point groups and 5 central point groups, with 3 parallel culture units in each group.
3. The response surface optimization method according to claim 1, characterized in that, In step (3), the expression for the quadratic regression prediction model is: R = -11.13114 + 13.38177A + 5.36432B + 0.364242AB - 0.462068A 2 -2.36342B 2 In the formula, R is the weight gain rate of juvenile sea cucumber (in %), A is the percentage of crude protein in the feed, and B is the percentage of crude fat in the feed. The p-value of the quadratic regression prediction model is 0.0009, which is highly significant. The p-value of the model lack of fit is 0.5302, which is not significant. The model determination coefficient R² = 0.9236.
4. The response surface optimization method according to claim 1, characterized in that, In step (2), the juvenile sea cucumbers are healthy individuals artificially bred from the same batch, with an initial weight of 9-10g; the breeding experiment period is 56 days, the water temperature is controlled at 13-19℃, the water pH is 7.8-8.2, the dissolved oxygen content is greater than 5mg / L, and the ammonia nitrogen and nitrite content are both less than 0.05mg / L; the fish are fed once a day at a fixed time, and the feed is prepared into a mud-like state before feeding. One-third of the volume of disinfected seawater is replaced daily and the uneaten feed and feces are cleaned up.
5. The response surface methodology according to claim 1, characterized in that, In step (4), the optimal combination of crude protein and crude fat is 15.398% and 2.322%, respectively, which corresponds to a maximum weight gain rate of 98.102% predicted by the model. The method also includes a model verification step: the verification feed is prepared according to the optimal combination of crude protein and 2.322% of crude fat, and three parallel breeding units are set up to carry out verification experiments. The breeding conditions are the same as those in the formal experiment. The measured weight gain rate of juvenile sea cucumber is 97.029%, and the relative error with the model prediction is 1.079%.
6. A compound feed for juvenile sea cucumbers, characterized in that, The compound feed contains 15.4% crude protein and 2.32% crude fat. The nutritional level of the compound feed is determined by the response surface methodology as described in any one of claims 1 to 5.
7. The sea cucumber juvenile compound feed according to claim 6, characterized in that, The raw materials for the compound feed consist of fish meal, Sargassum powder, kelp powder, scallop edge powder, attractant yeast powder, wheat flour, fish oil, compound premix, and sea mud.
8. The sea cucumber juvenile compound feed according to claim 7, characterized in that, Each kilogram of the compound premix contains the following nutrients: Vitamin A 400,000 IU, Vitamin D3 100,000 IU, Vitamin E 5,000 mg, Vitamin K3 1,000 mg, Vitamin B1 800 mg, Vitamin B2 800 mg, Vitamin B6 800 mg, Vitamin B... 12 6.0mg, Vitamin C 15000mg, D-calcium pantothenate 2800mg, Nicotinamide 5000 mg, Folic acid 380mg, D-biotin 8.0mg, Inositol 7000mg, Magnesium 4000mg, Zinc 2000mg, Manganese 1500mg, Copper 450mg, Iron 1800mg, Cobalt 70mg, Iodine 60mg, Selenium 20mg.
9. The sea cucumber juvenile compound feed according to claim 6, characterized in that, The compound feed is prepared by the following method: all solid raw materials are crushed by a pulverizer and passed through a 60-mesh sieve. Each solid raw material is weighed according to the formula ratio and mixed evenly. Then, liquid raw materials such as fish oil are added and stirred continuously. After adding an appropriate amount of distilled water and mixing thoroughly, the mixture is placed in a 60°C oven to dry. After cooling, it is sealed and stored.
10. The sea cucumber juvenile compound feed according to claim 6, characterized in that, The formulated feed is used for the cultivation of juvenile sea cucumbers with an initial weight of 9-10g. It is prepared as a mud-like substance before feeding and the daily feeding amount is 2% of the total weight of the juvenile sea cucumbers. It can improve the weight gain rate of juvenile sea cucumbers and regulate the activity of trypsin, lipase and amylase.