Method for regulating conversion efficiency of black soldier fly based on heat storage performance of base material

Abstract

The present application belongs to the field of black soldier fly breeding, and particularly relates to a method for regulating water fly conversion efficiency based on base material heat storage performance. The present application determines the environmental factors that significantly affect the base material heat storage and temperature rise, and establishes a model for regulating the heat storage performance of fly larvae conversion base material. Through simulation of various working conditions, the regulation strategy of base material heat storage performance under the optimal conversion efficiency of producing commodity water fly larvae, producing breeding pupae and waste reduction is explored, which solves the problem of low target efficiency and unstable operation of the fly larvae conversion system caused by the unregulated base material temperature, establishes a base material temperature regulation scheme that takes into account the optimal conversion efficiency, ensures the year-round high efficiency and stability of the fly larvae conversion system, and is conducive to improving the overall treatment level of organic waste, and has an important promoting effect on the scientific and efficient breeding of black soldier fly.

Description

Technical Field

[0001] This invention belongs to the field of black soldier fly farming, specifically involving a method for regulating the conversion efficiency of soldier flies by utilizing the heat storage performance of substrate. Background Technology

[0002] The use of black soldier fly larvae (BSFL) for organic waste treatment has many advantages and is considered a promising new technology with a huge market potential, receiving increasing attention. The conversion of waste by black soldier flies is essentially a process of metabolic transformation of organic matter through insect-fungus interaction. Although BSFL has a relatively wide temperature range (15–47℃), the conversion efficiency of this insect-fungus interaction system is still greatly affected by environmental conditions (especially temperature). Specifically: at a substrate temperature of 24–32℃, the insect-fungus interaction system is most suitable for producing pupae; below 20℃, the substrate cannot ferment and generate heat in time, resulting in poor heat retention, slow BSFL growth, and extremely low conversion efficiency; below 15℃, BSFL enters a dormant state and does not grow; above 35℃, BSFL suffers heat stress and cannot complete pupation, making it unsuitable for breeding; at a substrate temperature of 43–47℃, the upper limit for BSFL growth, the flies may escape or even die. Therefore, in actual production, certain environmental control strategies need to be adopted to control the stability of the base material temperature during the conversion process in order to maintain better production efficiency.

[0003] Especially in tropical and subtropical environments with high base temperatures, the biothermia generated by insect-fungal interactions can easily accumulate in the substrate, raising the temperature to over 35°C, or even exceeding 50°C, far surpassing the upper limit of BSFL growth. Furthermore, due to a lack of specific scientific research to support this, current environmental control methods based on conventional production experience are not only costly but also difficult to maintain stable substrate temperatures, resulting in low conversion efficiency and uncontrollable conversion performance, thus hindering the large-scale and industrialized conversion of black soldier fly waste. Therefore, there is an urgent need to systematically study the influencing factors and mechanisms of substrate temperature changes to guide the regulation of heat storage performance in the conversion bed, achieving heat dissipation and cooling in high-temperature weather and heat storage and insulation in low-temperature weather, thereby achieving high efficiency and stability of the system's target conversion performance. Summary of the Invention

[0004] This invention provides a method for regulating the conversion efficiency of horsefly based on the heat storage performance of substrate. A regulation model is established, and regulation strategies are proposed under three conversion efficiency targets: production of commercial horsefly larvae, pre-pupae of breeding larvae, and waste reduction. By controlling environmental factors (non-nutritive factors), the substrate temperature is maintained at a certain level to avoid the inhibition of heat and cold stress on the insects and ensure the stable and efficient conversion process.

[0005] The technical solution of this invention is implemented as follows:

[0006] Regression equation for the highest temperature of a base material:

[0007] Tmax=187.9636-1.5083×RMC-212.9167×LD+4.0972×H-2.5083×T+1.5×RMC×LD-0.04167×RMC×H+0.0250×RMC×T+2.0000×LD×T

[0008] Among them, T max The maximum temperature of the substrate is expressed in °C; RMC is the initial relative moisture content of the substrate; LD is the initial feed amount per worm, expressed in g DM / worm; H is the initial thickness of the substrate, expressed in cm; and T is the ambient temperature during the rearing process, expressed in °C.

[0009] Furthermore, the T mentioned above max The value is 25-45.

[0010] A method for regulating the heat storage performance of a substrate to control the conversion efficiency of soldier flies includes the following steps:

[0011] (1) Select carbon and nitrogen source materials to make aquaculture substrate that meets the nutritional needs of bursal fly larvae;

[0012] (2) Calculate the Tmax value of the maximum temperature regression equation of the substrate based on the initial relative moisture content of the substrate, the initial feeding amount of a single insect, the initial substrate thickness and the ambient temperature.

[0013] (3) If the value of Tmax is 25-45, it indicates that the breeding conditions meet the requirements; if T max If the value is not within the range of 25-45, adjust one or more parameters such as the initial relative moisture content of the breeding substrate, the initial feed amount per worm, the initial feed thickness, and the ambient temperature to make T max The value reaches 25-45.

[0014] Furthermore, the initial relative moisture content of the base material is calculated as follows: relative moisture content = water saturation × 100%.

[0015] Furthermore, based on the goal of optimizing the production efficiency of commercial horsefly larvae, the regression equation for the substrate larval production rate (PRL) is: PRL = -717.8832 + 13.1731 × RMC - 40.1083 × LD + 6.7346 × H + 7.0297 × T - 0.0913 × RMC × H - 0.0913 × RMC × H - 0.0660 × RMC × RMC - 0.1237 × T × T. At this point, maintaining a substrate relative moisture content of 99%, an ambient temperature of 28℃, and a substrate thickness of less than 2cm results in the highest substrate larval production rate (PRL), with the highest substrate temperature during the conversion process being approximately 37℃. Wherein, RMC is the initial relative moisture content of the substrate; LD is the initial feed amount per larva (g DM / larva); H is the initial substrate thickness (cm); and T is the ambient temperature (℃).

[0016] Furthermore, based on the goal of optimizing the production efficiency of pupae, the weight of 10 worms was BW. 10 The regression equation is BW10 = -23.18225 + 0.362432 × RMC + 5.56098 × LD + 0.023333 × H + 0.334923 × T - 0.001736 × RMC × RMC - 5.24747 × LD × LD - 0.005896 × T × T. At this point, the initial relative moisture content of the substrate is maintained at 104%, the ambient temperature at 28℃, the initial feed amount per worm is 0.5 g DW / worm, the initial substrate thickness is at least 8 cm, and the weight of 10 worms is BW. 10 The highest temperature of the substrate during the conversion process is 29-31℃; where RMC is the initial relative moisture content of the substrate; LD is the initial feed amount per larva, in g DM / larva; H is the initial substrate thickness, in cm; and T is the ambient temperature, in ℃.

[0017] Furthermore, based on the goal of optimizing waste reduction efficiency, the regression equation for the dry matter reduction rate (DMTR) of the substrate is as follows:

[0018] DMTR = -427.5891 + 9.0007 × RMC + 33.6729 × LD + 28.0892 × H + 3.9162 × T - 0.2440 × RMC × H + 0.0679 × RMC × T - 4.7250 × LD × H - 0.1643 × H × T - 0.0584 × RMC × RMC - 71.1562 × LD × LD - 0.0692 × H × H - 0.1590 × T × T. At this point, the initial relative moisture content of the substrate is maintained at 92%, the ambient temperature is 31℃, the initial feed rate is 0.2 g DW / head, and the initial substrate thickness is 3.6 cm or less. The dry matter loss rate DMTR is the highest, and the highest temperature of the substrate during the conversion process is 39-43℃. Wherein, RMC is the relative moisture content of the substrate; LD is the feed rate per larva, in gDM / larva; H is the substrate thickness, in cm; and T is the ambient temperature, in °C.

[0019] The beneficial effects of this invention are:

[0020] This invention identifies environmental factors (relative moisture content, insect density, material thickness, and ambient temperature) that significantly affect the heat storage and temperature rise of the substrate, and establishes a model for regulating the heat storage performance of the substrate for black soldier fly conversion. Through simulations of various operating conditions, it explores the substrate heat storage performance regulation strategies under three optimal conversion efficiency conditions: production of commercial black soldier fly larvae, pre-pupae of breeding insects, and waste reduction. This solves the problem of low target efficiency and unstable operation of the black soldier fly conversion system caused by the inability to control the substrate temperature, and establishes a substrate temperature regulation scheme that takes into account the optimal conversion efficiency, ensuring the year-round high efficiency and stability of the black soldier fly conversion system. This is conducive to improving the overall treatment level of organic waste and has an important promoting effect on the scientific and efficient breeding of black soldier flies. 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 description of the embodiments or the prior art 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 The effect of the initial pH of the substrate on the relative insect production rate.

[0023] Figure 2 The effect of initial substrate thickness on relative insect production rate.

[0024] Figure 3 The effect of ambient temperature on relative insect production rate.

[0025] Figure 4 The effect of initial feeding amount per larva on relative larval production rate.

[0026] Figure 5 The effect of initial moisture content of the substrate on the relative insect production rate.

[0027] Figure 6 The correlation between the heat storage and heating effect of the base material and the characterization index of conversion efficiency is shown.

[0028] Figure 7 Single-factor sensitivity analysis of the highest temperature of the base material.

[0029] Figure 8 The contour plot and response surface plot show the effect of AB on the maximum temperature of the base material.

[0030] Figure 9 The environmental factor levels represent the optimal insect production levels under the experimental conditions. The PRL value in the figure is the maximum value under the experimental conditions; the circles represent the optimal value of this variable under the model simulation.

[0031] Figure 10 The environmental factor levels are based on the optimal insect production level under extended experimental condition 1. The PRL value in the figure is the maximum value under the experimental conditions; the circles represent the optimal value of this variable under the model simulation.

[0032] Figure 11 The environmental factor levels are based on the optimal insect production rate under extended experimental condition 2. The value of PRL in the figure is the maximum value under the experimental conditions; the circles represent the optimal value of this variable under the model simulation.

[0033] Figure 12 The figures represent the environmental factor levels based on the optimal insect individual under the experimental conditions. The value of BW10 in the figure is the maximum value under the experimental conditions; the circles represent the optimal value of this variable under the model simulation. Figure 13 The environmental factor levels are based on the optimal insect individual under extended experimental condition 1. The value of BW10 in the figure is the maximum value under the experimental conditions; the circles represent the optimal value of this variable under the model simulation.

[0034] Figure 14 Extending the experimental conditions to condition 2, this is based on the environmental factor levels of the optimal insect individual. The value of BW10 in the figure represents the maximum value under the experimental conditions; circles represent the optimal value of this variable under the model simulation.

[0035] Figure 15 The environmental factor levels are based on optimal raw material reduction under the experimental conditions. The value of BW10 in the figure is the maximum value under the experimental conditions; the circles represent the optimal value of this variable under the model simulation. Figure 16 Environmental factor levels based on optimal raw material reduction under extended operating condition 1 of the test. The value of BW10 in the figure is the maximum value under the test conditions; the circles represent the optimal value of this variable under the model simulation.

[0036] Figure 17 The environmental factor levels are based on optimal raw material reduction under extended operating condition 2 of the test. The value of BW10 in the figure is the maximum value under the test conditions; the circles represent the optimal value of this variable under the model simulation. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Example 1

[0039] 1. Study on the influencing factors and regulation model of heat storage performance of horsefly conversion substrate

[0040] Experiments were conducted to investigate the effects of single environmental factors on insect production performance, aiming to screen the types and levels of environmental factors (non-nutritive factors) used in the study of substrate heat storage performance regulation models. The experimental substrate nutrient composition adopted the Gayle feed formula: 50% wheat bran, 30% soybean meal, and 20% corn flour. The initial control conditions for each single-factor experimental substrate were as follows:

[0041] (1) Initial pH value of feed: absolute moisture content 70%, feed thickness 6cm, insect inoculation amount 0.3g dry basis / head, ambient temperature during breeding process 30℃, pH according to experimental conditions.

[0042] (2) Initial thickness of feed (H): absolute moisture content 70%, pH 7.2, insect inoculation amount 0.3g dry basis / head, ambient temperature during breeding process 30℃, feed thickness according to experimental conditions.

[0043] (3) Ambient temperature (T): Absolute moisture content 70%, pH 7.2, insect inoculation amount 0.3g dry base / head, feed thickness 6cm, and ambient temperature during the breeding process according to the experimental conditions.

[0044] (4) Inoculation rate (LD): Absolute moisture content 70%, pH 7.2, feed thickness 6cm, ambient temperature during breeding process 30℃, inoculation rate according to experimental conditions.

[0045] (5) Moisture content (MC): pH 7.2, insect inoculation amount 0.3g dry basis / head, feed thickness 6cm, ambient temperature during breeding process 30℃, moisture content according to experimental conditions.

[0046] Relative insect production rate (%) = (Actual insect production rate at a certain level of the single-factor experiment / Maximum insect production rate at different levels of the single-factor experiment) * 100%

[0047] 1.1 Screening and Level Determination of Environmental Factors

[0048] (1) Initial pH value of the base material

[0049] like Figure 1 As shown, within the pH range of 3–11, the relative insect production rate was close to 100%, with a coefficient of variation (CV) of 1.9%, indicating low dispersion. The initial pH of the substrate, ranging from 3 to 11, covered most materials, but had no significant impact on the relative insect production rate of black soldier fly larvae (BSFL). This suggests that as long as the pH environment is not extreme, it can meet the requirements for efficient insect production, and the initial pH of the material should not be considered as a factor for further experiments.

[0050] (2) Initial thickness of base material (H)

[0051] like Figure 2 As shown, if the initial substrate is too thin, its water retention is poor, and BSFL growth is inhibited; if the substrate is too thick, it is difficult for BSFLs to penetrate and feed, and it is easy to accumulate heat and raise the temperature, affecting the conversion effect. Among them, the relative larval production rate was not significantly different when the initial substrate thickness was 4 cm and 6 cm, but it was significantly higher than other thicknesses. H (initial substrate thickness) is listed as the factor to be investigated in further experiments, with factor levels of 2, 5, and 8 cm.

[0052] (3) Ambient temperature (T)

[0053] like Figure 3 As shown, the relative larval production rate of BSFL was highest at an ambient temperature of 30℃, significantly higher than at other temperature levels. This is consistent with existing reports that "within the range of 24–32℃, the developmental parameters of the larval stage of *Burmese scintillans* reach their optimal level at 28℃, while both lowering and raising the temperature lead to prolonged developmental duration, reduced biomass accumulation, and decreased survival rate." T (ambient temperature) was listed as a factor for further investigation, with factor levels set at 25, 30, and 35℃.

[0054] (4) Feeding amount per larva (LD)

[0055] like Figure 4 As shown, larval density reflects the aggregation effect of larvae and the degree of nutrient utilization by individuals. Larval density was characterized by the amount of dry matter fed per larva. As shown in the figure, under a feed rate variation gradient of 0.2 g dry matter / larva, the relative larval production rate of BSFL significantly decreased with increasing feed rate. Surveys indicated that the experimental and production feed rate was 0.3–0.4 g dry matter / larva. Therefore, D (feed amount per larva) was selected as a factor for further experiments, with factor levels of 0.1, 0.3, and 0.5 g dry matter / larva.

[0056] (5) Moisture content (MC)

[0057] The role of water is to dissolve nutrients and oxygen to ensure that BSFL meets its oxygen and nutrient requirements. Figure 5 As shown, the initial moisture content of the feed has a significant impact on the insect production rate. The relative insect production rate first increases and then decreases with the increase of the absolute moisture content in the feed. Figure 5 The results of two experiments are shown. The decimals on the upper bars represent the water saturation of the material, and the percentages on the lower bars represent the absolute moisture content. These can be selected as factors for further experiments. Compared to the previous index that uses absolute moisture content (AMC) to characterize the moisture state of materials, relative moisture content (RMC) (Relative moisture content = water saturation × 100% = actual absolute mass moisture content of the material / absolute mass moisture content of the material at water saturation × 100%) integrates both air permeability and dissolved nutrients, and can overcome the influence of material properties.

[0058] like Figure 5 As shown in the figure below, the relative insect production rate was highest at water saturation levels of 0.95 and 1.00, at 97.4% and 99.9% respectively, with no significant difference (P<0.05). This was significantly higher than the production rate under adjacent moisture conditions, corresponding to absolute moisture contents of 78% and 82%. The RMC levels in further experiments were 85%, 95%, and 105%.

[0059] Based on the analysis of the experimental results on the effects of the above single environmental factors on insect production performance, the factors used to study the heat storage performance of the substrate were determined to be relative moisture content (RMC), insect density (LD), substrate thickness (H), and ambient temperature (T). The selection levels of these factors for the Box-Behnken design response surface methodology research on the control model are shown in Table 3.

[0060] Table 3. Levels and values ​​of experimental factors

[0061] Environmental factors unit Factor Code Code-1 Level Code +1 level Relative Moisture Content (RMC) ％ A 85 105 Insect density LD gDM / head B 0.1 0.5 Material thickness H cm C 2 8 Incubation temperature T ℃ D 25 35

[0062] 1.2 Study on Influencing Factors and Regulation Models of Heat Storage Performance of Tabanus Conversion Substrate

[0063] Based on the above four environmental factors, a Box-Behnken response surface methodology study was conducted to analyze the correlation between the heat storage and temperature rise effect of the substrate and the conversion efficiency index. The index characterizing the heat storage performance of the substrate was identified as the "maximum temperature of the substrate," and a control model was established. Control strategies were proposed based on three conversion objectives: production of commercial horsefly larvae, pre-pupae of breeding larvae, and waste reduction. The experimental design is shown in Table 4.

[0064] Table 4 Box-Behnken experimental design and values ​​of various factors

[0065]

[0066]

[0067] 1.2.1 Correlation between the heat storage and temperature rise effect of the base material and the conversion efficiency index

[0068] The correlation between the heat storage and temperature rise effect of the base material and the conversion efficiency index is as follows: Figure 6 As shown in the graph (analyzed using Origin software), the highest substrate temperature (measured and statistically analyzed daily at the original temperature) was significantly positively correlated with the average temperature (measured and calculated daily at the original temperature), cumulative temperature (measured and calculated at the original temperature), and dry matter loss rate (measured / calculated), and significantly negatively correlated with the weight per 10 larvae and the larval conversion rate. Furthermore, the larval conversion rate was significantly negatively correlated with the substrate larval production rate. Therefore, the highest substrate temperature affects the larval production rate by influencing the larval conversion rate. This demonstrates that substrate temperature has a significant impact on conversion efficiency, and the conversion efficiency of horsefly can be controlled by regulating the highest substrate temperature during the conversion process.

[0069] 1.2.2 Base Material Heat Storage and Temperature Rise Control Model

[0070] Using the highest temperature of the substrate (Tmax) as the response value, the Analysis module of Design-Expert 12 software was used to determine the optimal fitting model based on a quadratic polynomial regression equation, combined with model fitting analysis and variance analysis results. The influence of single factors and their interactions was analyzed using single-factor sensitivity curves and contour plots, and a substrate heat storage and temperature rise control strategy was proposed. The variance analysis results of the experimental data are shown in Table 5.

[0071] Table 5. Maximum temperature of base material (T) max Response surface model variance analysis

[0072]

[0073] Note: ** indicates extremely significant difference (P < 0.01); * indicates significant difference (P < 0.05).

[0074] Analysis of variance of the response surface methodology for the maximum temperature (Tmax) of the base material showed that the model was highly significant (P < 0.001) and insignificant (P = 0.2484 > 0.05), indicating a good fit. The model's coefficient of determination R0 was also high. 2 = 0.8706, Corrected coefficient of determination R Adj 2 =0.8188, all are not less than 0.8, and R Pre 2 and R Adj 2 The difference between the two values ​​is 0.1292, which is less than 0.2, indicating that the model can reflect the experimental data well and the regression equation has a good fit, resulting in a small experimental error. The CV (%) is 5.06, which is less than 10%, indicating a small coefficient of variation and thus a small experimental error. The signal-to-noise ratio is 17.61, which is greater than 4, indicating that the model design is reasonable and can be used for result prediction.

[0075] Under the significance level (p<0.05), the linear terms relative moisture content A (p<0.0001), single larvae feeding amount B (p=0.0013), ambient temperature D (p=0.0005), and interaction term AB (p=0.0057) in the maximum substrate temperature Tmax regression model were all significant, reaching the extremely significant level, while other terms were not significant.

[0076] Based on the analysis of Table 5, the coded data model based on each environmental factor variable is obtained: Tmax=38.24-5.17×A-2.08×B+0.42×C+2.33×D+3×A×B-1.25×A×C+0.25×A×D+2×B×D......(Regression Equation 1),

[0077] The model transformed into actual data for each environmental factor variable is: Tmax=187.9636-1.5083×RMC-212.9167×LD+4.0972×H-2.5083×T+1.5×RMC×LD-0.04167×RMC×H+0.0250×RMC×T+2.0000×LD×T.....(Regression Equation 2)

[0078] In regression equation (1): Tmax is the highest temperature of the substrate, °C; A, B, C, and D are the statistical codes for environmental factor variables: relative moisture content RMC (%), single worm feeding amount LD (g DM / head), substrate thickness H (cm), and culture temperature T (°C).

[0079] According to the Box-Behnken experimental design principle, a factor-coded data model can be used to predict the response based on a given level of each factor, with a high level coded as +1 and a low level as -1. The coded model can identify the relative influence of each factor by comparing factor coefficients; however, a model based on actual factor data can be used to predict the response of each factor at a given level. The level of each factor should be specified in its original units. Because the coefficients in this model are scaled according to the units of each factor, the intercept is not centered in the design space and cannot be used to determine the relative influence of each factor.

[0080] 1.2.3 Factor Influence Effect Analysis

[0081] The four factors A, B, C, and D in Table 5 have significant effects on the maximum temperature of the substrate, with varying degrees of influence. The order of influence is: A** > D** > B** > C. Factors A, B, and D are all highly significant, while C is not significant. Based on the data model (regression equation 1) coded for each environmental factor variable: Tmax = 38.24 - 5.17 × A - 2.08 × B + 0.42 × C + 2.33 × D + 3 × A × B - 1.25 × A × C + 0.25 × A × D + 2 × B × D), the coefficient of the first-order term D is positive, while the coefficients of the first-order terms A and B are negative. This indicates that factor D is positively correlated with Tmax, while factors A and B are negatively correlated with Tmax. This is consistent with the results of the single-factor sensitivity analysis of the maximum temperature of the substrate.

[0082] Based on a quadratic regression model (coded data model) using the highest temperature of the base material, response surface plots and contour plots of the interaction terms AB with respect to Tmax, which have significant interactive effects, are drawn, as shown below. Figure 7-8 As shown.

[0083] As the initial relative moisture content of the substrate and the feeding amount per larva increased, Tmax decreased, indicating that reducing the larvae density and increasing the relative moisture content of the substrate in the conversion bed lowered the maximum substrate temperature, thus alleviating heat stress in the larvae. Studies have shown that 43-47℃ is the upper limit of black soldier fly larvae growth (Tmax). Therefore, the heat storage and temperature rise performance of the substrate should be controlled primarily by adjusting its relative moisture content. Secondly, the heat storage and temperature rise performance of the bioconversion bed can be controlled by regulating the ambient temperature and the initial larvae feeding amount in the substrate.

[0084] 1.2.4 Multi-objective-based control strategy for the thermal storage performance of base materials

[0085] To achieve three production objectives in black soldier fly bioconversion (production of commercial soldier fly larvae, production of pre-pupae for breeding stock, and waste reduction), mathematical models were established using substrate larvae production rate (PRL), body weight per 10 larvae (BW10), and dry matter reduction rate (DMTR) as response values. These models established the relationships between environmental factors A (relative moisture content, RMC), B (feed amount per larva, LD), C (substrate thickness, H), and D (ambient temperature, T) and the response indicators. The results are shown in Tables 6 and 7. Furthermore, considering actual production conditions, the range of environmental factor levels was expanded. The Optimization module in Design-Expert 12 software was used to analyze the stability of each environmental factor level under different operating conditions to achieve optimal conversion efficiency, exploring strategies for regulating substrate heat storage performance under optimal conversion efficiency.

[0086] Table 6 Model Construction

[0087]

[0088] Note: Insect production rate PRL (%) = BSFL dry weight obtained after the experiment / initial substrate dry weight * 100%; BW10 is the weight of 10 insects; Dry matter reduction rate DMTR (%) = (initial substrate dry weight - substrate dry weight at the end of the experiment) / initial substrate dry weight * 100%.

[0089] Table 7 Evaluation Indicators for Each Model

[0090]

[0091] Note: ** indicates extremely significant difference (P < 0.01); * indicates significant difference (P < 0.05).

[0092] (1) Regulation of substrate heat storage performance based on optimal efficiency of producing commercial horsefly larvae

[0093] The environmental factor levels for the optimal insect production under different operating conditions are shown in the figure. Figure 9-11 The variations in environmental factors and conversion efficiency levels under different operating conditions are shown in Table 9. The experimental conditions refer to general production conditions, i.e., the range of environmental factor values ​​used in this experiment; Condition Extension 1 and Condition Extension 2 are the ranges of environmental factor values ​​under two extreme operating conditions achievable in actual production; the conventional group represents normal aquaculture conditions without environmental factor regulation; and the optimal groups 1-4 are the four operating condition treatment groups obtained after optimization analysis based on the mathematical model of substrate insect production rate and the Tmax model.

[0094] Table 9-1 shows that the optimal insect production rate under different working conditions is 31%–37%, with a coefficient of variation of 7.47%, which is greater than 5%, indicating that it is influenced by environmental factors to some extent. The coefficients of variation for relative moisture content, ambient temperature, and maximum feed temperature are less than 0.5%, while the coefficients of variation for feed thickness and initial feed amount per insect are 53.45% and 69.03% (highly variable), respectively. The optimal insect production rate increases as the initial feed amount per insect decreases and the feed thickness decreases. Therefore, under the optimal insect production rate, the values ​​of relative moisture content, ambient temperature, and maximum feed temperature are relatively stable, and the maximum temperature is within the normal growth range of BSFL. The feed thickness and initial feed amount per insect have a significant impact on insect production, and the optimal insect production rate increases as the initial feed amount per insect decreases and the feed thickness decreases; these are factors that need to be controlled.

[0095] Furthermore, the optimal method for controlling the heat storage performance of substrate based on the production efficiency of commercial black soldier fly larvae was derived as follows: by maintaining the initial relative moisture content of the substrate (approximately 99%) and the ambient temperature during the breeding process (28℃), combined with appropriately increasing the initial larval density (high value under each condition) and decreasing the initial substrate thickness (below 2cm, low value under each condition), the optimal larval production rate can be guaranteed. As shown in Table 9-2, after actual breeding experiments, the statistical analysis of each PRL value showed no significant difference from the PRL value calculated by the PRL mathematical model formula. Moreover, by controlling environmental factors, the PRL values ​​of each treatment could be significantly higher than those of conventional breeding methods. This indicates that the PRL mathematical model and Tmax model obtained in this invention can not only accurately predict the PRL value, but also significantly improve the larval production rate of black soldier fly substrate.

[0096] Table 9-1 Analysis of Factors and Conversion Efficiency under Different Working Conditions

[0097] Operating conditions RMC LD H T Tmax PRL unit ％ gDM / head cm ℃ ℃ ％ Test conditions 98.4 0.10 2.0 28.4 37.3 31.1 Condition Extension 1 99.1 0.05 1.0 28.4 37.2 34.8 Condition Extension 2 99.4 0.01 0.5 28.4 37.3 37.4 A 98.9 0.05 1.2 28.4 37.3 34.5 SD 0.4 0.04 0.6 0.0 0.0 2.6 CV / % 0.4 69.03 53.5 0.0 0.1 7.5

[0098] Table 9-2 Test results under different optimized operating conditions

[0099] Operating conditions RMC LD H T Tmax PRL simulated values Aquaculture Statistics PRL unit ％ gDM / head cm ℃ ℃ ％ ％ conventional 87.5 0.10 8.0 29.0 48.0 18.5 18.48 Optimal 1 99.0 0.10 2.0 28.0 36.8 31.4 31.03 Optimal 2 99.0 0.05 1.0 28.0 37.3 35.1 35.45 Optimal 3 99.0 0.01 0.5 28.0 37.6 37.7 37.64 Optimal 4 99.0 0.05 1.2 28.0 37.3 34.8 34.72

[0100] (2) Regulation of substrate heat storage performance based on optimal production efficiency of seed pupae

[0101] Environmental factor levels for optimal insect weight under different working conditions are shown in the figure. Figure 12-14 The variations in environmental factors and conversion efficiency levels under different operating conditions are shown in Table 10-1. The experimental conditions refer to general production conditions, i.e., the range of environmental factor values ​​used in this experiment; Condition Extension 1 and Condition Extension 2 are the ranges of environmental factor values ​​under two extreme operating conditions achievable in actual production; the conventional group represents normal aquaculture conditions without environmental factor regulation; and the optimal groups 1-4 are the four operating condition treatment groups obtained after optimization analysis using the BW10 mathematical model and the Tmax model.

[0102] Table 10-1 shows that the optimal average weight of individual insects under different working conditions is 2.2 g / 10 insects, with a coefficient of variation of 3.95% (small variation), indicating minimal influence from environmental factors. Among environmental factors, the substrate thickness has the largest coefficient of variation at 32.78% (moderate variation); the coefficients of variation for relative moisture content, initial feed amount per insect, and ambient temperature are all less than 5% (small variation). Therefore, by maintaining a relatively high level of relative moisture content (104%), ambient temperature (28℃), and initial feed amount per insect (0.5 g DW / insect), and maintaining a high initial substrate thickness (at least 8 cm, the highest value under each working condition), it is possible to ensure the acquisition of superior pupae. This is also a substrate heat storage performance control method based on the optimal production efficiency of pupae.

[0103] As shown in Table 10-2, after actual breeding experiments, the statistical analysis of each BW10 value showed no significant difference from the BW10 value calculated by the BW10 mathematical model formula. Furthermore, the BW10 value of the treatment group regulated by environmental factors was significantly higher than that of the conventional breeding method. This indicates that the BW10 mathematical model and Tmax model obtained in this invention can not only accurately predict the BW10 value but also significantly increase the weight of 10 black soldier fly larvae, resulting in a significant improvement in the efficiency of pupal production.

[0104] Table 10-1 Analysis of Factors and Conversion Efficiency under Different Working Conditions

[0105] parameter RMC LD H T Tmax BW10 unit ％ gDM / head cm ℃ ℃ g / 10 heads Test conditions 104.4 0.50 8.0 28.4 31.6 2.1 Condition Extension 1 104.4 0.53 10.0 28.4 31.1 2.2 Condition Extension 2 104.4 0.53 15.0 28.4 29.9 2.3 A 104.4 0.52 11.0 28.4 30.9 2.2 SD 0.0 0.02 3.6 0.0 0.9 0.1 CV / % 0.0 3.33 32.8 0.0 2.9 4.0

[0106] Table 10-2 Test results under different optimized conditions

[0107]

[0108]

[0109] (3) Regulation of thermal storage performance of substrate based on optimal waste reduction efficiency

[0110] The environmental factor levels for optimal raw material reduction under different operating conditions are shown above. Figure 15-17 The variations in environmental factors and conversion efficiency levels under different operating conditions are shown in Table 11-1. The experimental conditions refer to general production conditions, i.e., the range of environmental factor values ​​used in this experiment; Condition Extension 1 and Condition Extension 2 are the ranges of environmental factor values ​​under two extreme operating conditions achievable in actual production; the conventional group represents normal aquaculture conditions without environmental factor regulation; and the optimal groups 1-4 are the four operating condition treatment groups obtained after optimization analysis using the DMTR mathematical model and the Tmax model.

[0111] As shown in Table 11-2, the optimal raw material reduction level under different operating conditions is 71.7%, with a coefficient of variation of 0.58% (small variation), indicating minimal impact from environmental factors. The average material thickness is 1.71 cm, but height varies, with a coefficient of variation of 80.17%. The average relative moisture content, initial feed amount per larva, ambient temperature, and maximum material temperature are 92.37%, 0.2 g DM / larva, 31.12℃, and 40.72℃, respectively, with coefficients of variation less than 15% (small variation). Therefore, by maintaining the relative moisture content (92%), ambient temperature (31℃), and initial feed amount per larva (0.2 g DW / larva), combined with appropriately reducing the initial material thickness (3.6 cm and below), waste reduction efficiency and operational efficiency can be improved. This is also based on the method of controlling the heat storage performance of the substrate to optimize waste reduction efficiency.

[0112] Actual aquaculture trials showed no significant difference between the DMTR values ​​obtained and those calculated using the DMTR mathematical model. Furthermore, the DMTR values ​​of the treatment group regulated by environmental factors were significantly higher than those calculated using conventional aquaculture methods. This demonstrates that the combination of the DMTR mathematical model and the Tmax model obtained in this invention can not only accurately predict DMTR values ​​but also guide the efficient and stable reduction of waste in the soldier fly conversion system. This also indicates that current conventional operating conditions are conducive to waste reduction.

[0113] Table 11-1 Analysis of the variation of environmental factors and conversion efficiency levels under different operating conditions

[0114] parameter RMC LD H T Tmax DMTR unit ％ gDM / head cm ℃ ℃ ％ Test conditions 89.0 0.18 3.6 29.3 43.0 71.3 Condition Extension 1 93.4 0.20 1.0 31.7 39.9 71.7 Condition Extension 2 94.7 0.22 0.5 32.3 39.3 72.3 A 92.4 0.20 1.7 31.1 40.7 71.7 SD 2.4 0.02 1.4 1.3 1.6 0.4 CV / % 2.6 8.16 80.2 4.1 4.0 0.6

[0115] Table 11-2 Test results under different optimized operating conditions

[0116] parameter RMC LD H T Tmax DMTR simulated values DMTR Aquaculture Statistics unit ％ gDM / head cm ℃ ℃ ％ ％ conventional 87.5 0.20 5.0 29.0 44.2 72.3 72.29 Optimal 1 92.4 0.18 3.6 31.0 41.1 70.0 70.02 Optimal 2 92.4 0.20 1.0 31.0 40.2 71.9 71.77 Optimal 3 92.4 0.22 0.5 31.0 39.9 72.2 72.55 Optimal 4 92.4 0.20 1.7 31.0 40.4 71.4 71.28

[0117] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for regulating the heat storage performance of a substrate to control the conversion efficiency of soldier flies, characterized in that, Includes the following steps: (1) Select carbon and nitrogen source materials to make aquaculture substrate that meets the nutritional needs of bursal fly larvae; (2) Statistically analyze the relative moisture content of the substrate, the amount of feed per insect, the substrate thickness, and the ambient temperature. Calculate the T value of the maximum temperature regression equation for the substrate based on the maximum temperature regression equation. max Numerical value; the regression equation: T max =187.9636-1.5083×RMC - 212.9167×LD + 4.0972×H - 2.5083×T + 1.5×RMC × LD - 0.04167×RMC ×H + 0.0250×RMC × T + 2.0000×LD × T; where, T max The maximum temperature of the substrate is expressed in °C; RMC is the relative moisture content of the substrate, expressed in %; LD is the feed amount per worm, expressed in g DM / worm; H is the substrate thickness, expressed in cm; T is the ambient temperature, expressed in °C. (3) If T max If the value is 25-45, it indicates that the breeding conditions meet the requirements; if T max If the value is not within the range of 25-45, adjust one or more parameters such as the relative moisture content of the breeding substrate, the amount of feed per worm, the thickness of the feed, and the ambient temperature to make T max The value reached 25-45; The relative moisture content of the substrate is calculated as follows: Relative moisture content = water saturation × 100%. Based on the goal of optimizing the production efficiency of commercial horsefly larvae, the regression equation for the substrate larval production rate (PRL) is: PRL = -717.8832 + 13.1731 × RMC - 40.1083 × LD + 6.7346 × H + 7.0297 × T - 0.0913 × RMC × H - 0.0913 × RMC × H - 0.0660 × RMC × RMC - 0.1237 × T × T, where RMC is the relative moisture content of the substrate; LD is the feed amount per larva, in g DM / larva; H is the substrate thickness, in cm; and T is the ambient temperature, in °C.

2. The method as described in claim 1, characterized in that, The highest insect production rate (PRL) was achieved when the initial relative moisture content of the substrate was 99%, the ambient temperature during the breeding process was 28℃, and the initial substrate thickness was less than 2cm. The highest substrate temperature during the conversion process was approximately 37℃.

3. The method as described in claim 1, characterized in that, To optimize the production efficiency of pupae, the weight of 10 worms was BW. 10 The regression equation is BW10 = -23.18225 + 0.362432×RMC + 5.56098×LD + 0.023333×H +0.334923 ×T-0.001736×RMC×RMC-5.24747×LD×LD-0.005896×T×T, where RMC is the relative moisture content of the substrate; LD is the feed amount per worm, in g DM / worm; H is the substrate thickness, in cm; and T is the ambient temperature, in ℃.

4. The method as described in claim 3, characterized in that, The initial relative moisture content of the substrate is 104%, the ambient temperature during the rearing process is 28℃, the initial feed amount per worm is 0.5 g DW / head, the initial substrate thickness is at least 8cm, and the weight of 10 worms is BW. 10 The highest temperature of the base material during the conversion process is 29-31℃.

5. The method as described in claim 1, characterized in that, Based on the goal of optimizing waste reduction efficiency, the regression equation for the dry matter reduction rate (DMTR) of the substrate is: DMTR = -427.5891 + 9.0007 × RMC + 33.6729 × LD + 28.0892 × H + 3.9162 × T - 0.2440 × RMC × H + 0.0679 × RMC × T - 4.7250 × LD × H - 0.1643 × H × T - 0.0584 × RMC × RMC - 71.1562 × LD × LD - 0.0692 × H × H - 0.1590 × T × T, where RMC is the relative moisture content of the substrate; LD is the feed amount per insect (g DM / insect); H is the substrate thickness (cm); and T is the ambient temperature (°C).

6. The method as described in claim 5, characterized in that, The initial relative moisture content of the substrate was 92%, the ambient temperature during the breeding process was 31℃, the initial feed amount was 0.2 g DW / head, the initial substrate thickness was 3.6 cm or less, the dry matter reduction rate (DMTR) was the highest, and the highest substrate temperature during the conversion process was 39-43℃.

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