Effect of Storage Conditions on Freshness Indexes and Mold Count of Fishmeal

Abstract

To explore the effect of storage conditions on the freshness of fishmeal, the acid value (AV), volatile basic nitrogen (VBN), and pH value were used as freshness evaluation indexes to explore the changes in freshness during storage and the influence of mold count on these indexes. The effects of storage temperature and relative humidity (RH) on AV, VBN, pH value, and mold count were studied using a single-factor test, and grey relation analysis (GRA) was used to assess the association between mold count and freshness indexes. The appropriate storage conditions were determined using the technique for order preference by similarity to ideal solution (TOPSIS) method, which provides theoretical support for fishmeal storage. The results showed that the AV increased during the storage of fishmeal, while the VBN and pH value decreased; the pH value tended to be stable in the later storage stage. The VBN and pH values could not be used as evaluation indexes in the early stage of deterioration. Higher storage temperature was conducive to the storage of fishmeal, but higher RH was not. The results of the GRA showed that the mold count was correlated with each freshness index. The correlation between mold count and VBN was the largest, followed by AV, and the correlation with pH value was the smallest. The TOPSIS method finally determined the suitable storage conditions for fishmeal to be around 25 °C for storage temperature and 60% for RH. The results serve as a future reference for the storage of fishmeal.

1. Introduction

Fishmeal is a high-quality animal protein with high protein and amino acid content. It is rich in essential fatty acids, minerals (such as phosphorus, calcium, iron, and zinc), and vitamins (vitamin A, vitamin D, and vitamin B₁₂), and it has high digestibility and good feed effect. It is widely used in aquatic feed for livestock and poultry [1]. However, in its processing, preparation, transportation, and storage, fishmeal can be affected by the raw materials’ quality as well as the external and storage conditions, which may lead to proteolysis and fatty oxidative rancidity, thus degrading its freshness and decreasing its nutritional value. This would not only affect the feeding effect and endanger animal health, but it could also threaten human health [2,3,4]. Therefore, it is of great importance to detect the freshness of fishmeal.

The freshness of fishmeal is usually detected by sensory analysis, which roughly evaluates its shape, structure, color, texture, odor, and particle size. Fresh fishmeal is bulky, non-caking, non-sticky, and non-agglomerated. As the freshness degrades, the feel of the fishmeal gradually becomes hard, inelastic, and non-greasy [5]. In the study by Zhao and Ye, fresh fishmeal is yellowish brown, while stale fishmeal becomes moldy and dark, and loses luster. In terms of smell, fresh fishmeal has a strong fish smell and has no sour, smelly, burnt, or other odors. With the degradation of freshness, the sour, smelly, burnt, and other odors produced by proteolysis and fatty oxidative rancidity gradually become strong [6]. However, the sensory detection method mostly depends on the experience of inspectors, and the results are highly subjective. Therefore, physical and chemical methods are often used to characterize the freshness of fishmeal by determining the corresponding freshness indexes [7]. The main indexes of freshness are volatile base nitrogen (VBN), biogenic amines (cadaverine, histamine, and trimethylamine), and acid value (AV) [8,9,10,11]. In the national standards of China, GB/T 19164-2003 and GB/T 19164-2021, the freshness grade of fishmeal is defined according to the measured values of AV and VBN [12,13]. In addition, the pH value has been introduced as an evaluation index in detecting the freshness of eggs and meat [14,15]. For example, Hu et al. found that pH value and VBN have a strong positive correlation when determining the freshness index of refrigerated grass carp during storage [16]. They used the pH value to characterize the freshness of grass carp and simplified the detection method for fish freshness. Senapati and Sahu [17] found a significant correlation between VBN and pH value in the detection of chicken freshness. Therefore, AV, VBN, and pH values are used as freshness indexes in intuitively evaluating the freshness of fishmeal.

Due to the closed and semi-closed environments used in the processing, transportation, and storage of fishmeal, it is easily contaminated by mold, resulting in moldy odor and agglomeration. This not only affects the feed effect on livestock and poultry, but it also affects the freshness grade [18]. The reproduction of mold consumes nutrients and greatly reduces the nutrition of fishmeal. In addition, mycotoxin, the secondary metabolite of mold, is toxic, which could destroy the kidney, liver, and spleen of cultured animals, reduce the body’s immunity, and cause chronic or acute toxic reactions [18,19,20]. Therefore, it is of great importance to determine the mold count in fishmeal during storage. Meanwhile, exploring the relationship between mold count and freshness indexes is of guiding importance for the maintenance of fishmeal freshness.

Fu and Wang found that egg quality was affected by temperature, relative humidity (RH), and gas environment during storage and transportation [15]. Zhu et al. explored the quality changes in rapeseed due to the modification of moisture content, RH, and temperature during storage; they subsequently optimized the storage parameters [21]. Therefore, storage conditions have a great impact on the quality of agricultural products, especially temperature and RH. Fishmeal is also susceptible to changes in temperature and RH, and freshness is not easy to control during storage [22]. In the study of Chen and Wang, the influence of storage temperature and RH on the freshness of fishmeal was explored, but the value range used for temperature and RH was too large and was different from the actual storage conditions [23]. Therefore, taking into account the actual situation of fishmeal storage in China, it is of great importance to explore the influence of temperature and RH on the freshness of fishmeal during storage and provide a theoretical basis for the storage of fishmeal in real life.

In summary, it is highly practical to study the influence of storage conditions on the freshness of fishmeal and mold count. In this paper, AV, VBN, and pH values were used as the evaluation indexes of fishmeal freshness. Through a single-factor test, the changes in the freshness indexes and mold count of fishmeal under different storage conditions were explored. The grey relation analysis (GRA) was used to analyze the correlation between mold count and freshness indexes, as well as to explore the influence of mold count on the freshness of fishmeal. Finally, the technique for order preference by similarity to ideal solution (TOPSIS) method was used to determine the suitable storage conditions, which serve as a reference for the reasonable storage of fishmeal.

2. Materials and Methods

2.1. Materials, Reagents, and Instruments

The fishmeal used was freshly imported seawater fishmeal, which was provided by New Hope Group. It was processed under the designed storage conditions to obtain the corresponding samples.

In this experiment, an anhydrous ethanol ether solution (anhydrous ether and ethanol were mixed at a ratio of 2:1) of 0.1 mol/L KOH solution, 0.1 mol/L HCl solution, NaOH solution (400 g/L), H₃BO₃ solution (20 g/L), and physiological saline (8.5 g/L) was used. The indicators included the phenolphthalein indicator, methyl red indicator, and bromocresol green indicator. Magnesium oxide (MgO) and CzapekDox agar were also utilized in the experiment. The configuration of the CzapekDox agar was according to the national standard of China, GB/T 13092-2006 in Table S1 for detail [24]. All the reagents used were analytically pure and were from the Sinopharm Chemical Reagent Co., Ltd. (Beijing, China). The distilled water was from Watsons.

The instruments used in this experiment were an electronic balance (ME204, METTLER TOLEDO, Zürich, Switzerland), artificial climate incubator (RGX-250B, Tianjin Sailidesi Experimental Analysis Instrument Factory, Tianjin, China), con-stant-temperature shaker (THZ-100, Shanghai Yiheng Instrument, Shanghai, China), automatic Kjeldahl nitrogen analyzer (K1160, Haineng Scientific Instrument, Shandong, China), low-temperature high-speed centrifuge (VELOCITY 14R Pro, Techcomp, Maryland, UK), thermostatic incubator (ADX-SHP-160, Wuhan Andexin Testing Equipment, Wuhan, China), ultra-clean bench (SW-CJ-2FD, Jinan Senya Experimental Instrument, Jinan, China), vertical automatic electrothermal pressure steam sterilization pot (LX-B50L, Hefei Huatai Medical Equipment, Hefei, China), and a pH meter (SevenExcellence, METTLER TOLEDO, Zürich, Switzerland).

2.2. Methods

2.2.1. Single-Factor Test Design

In this section, a single-factor test was designed, with the storage temperature, RH, and time selected as the influencing factors. The AV, VBN, and pH values were taken as the freshness indexes of fishmeal, which were used to explore the influence of storage conditions on fishmeal freshness and examine the changes in mold count during storage. According to the national meteorological information center of China [25], the average temperature of feed mills in China is 14.4 °C–33.2 °C, with a monthly average RH of 43–82% (Guangdong, Hubei, Jiangsu province); thus, the single-factor test scheme was set, as shown in

Table 1. Single-factor test scheme.

No.	RH/%	Temperature/°C
1 *	40	25
2 *	50	25
3	60	25
4	70	25
5	80	25
6 *	60	15
7 *	60	20
8	60	30
9	60	35

Note: * represents sampling every 5 days, and the rest was sampled every 2 days.

. A total of 5 kg of fishmeal was laid on an enamel plate and stored in an incubator for 30 days under the conditions shown in Table 1. Samples weighing 200 g were taken for testing. Three groups of parallel tests were performed for each condition.

2.2.2. Detection Methods for Freshness Indexes and Mold Count

The freshness evaluation indexes for fishmeal, including AV, VBN, pH value, and mold count, were obtained according to the following detection methods.

The determination of AV was performed according to the national standard of China, GB/T 19164-2003 [12]. A total of 5 ± 0.01 g of fishmeal sample was placed into a conical flask, and 50 mL of the anhydrous ethanol ether solution was added, which was then evenly mixed and filtered. The filtrate was repeatedly washed with 20 mL of the anhydrous ethanol ether solution. After combining the filtrate, 2–3 drops of the phenolphthalein indicator were added and titrated with the KOH solution until it appeared red and did not fade within 30 s. Based on GB/T 19164-2003, the AV can be expressed as follows [12]:

$$AV=\frac{V\times c\times 56.11}{m}$$

(1)

where V is the consumed volume of the KOH solution (mL), c is the concentration of the KOH solution (mol/L), and m is the mass of the fishmeal (g).

The determination of VBN was performed according to the national standard of China, GB/T 19164-2021 [13]. A total of 5 ± 0.01 g of fishmeal sample was placed into a conical flask, and 100 mL distilled water was subsequently added. The mixture was shaken at a rate of 260 times per minute for 30 min at room temperature, and it was allowed to stand for 5 min. Then, a fishmeal dipping solution was obtained through dry filtration. A total of 20 mL fishmeal dipping solution and 20 mL distilled water with 2 drops of defoamer and 1 g MgO were carefully poured into the distillation tube, and then connected to an automatic Kjeldahl nitrogen analyzer for measurement. Based on GB/T 19164-2021, the VBN can be calculated as follows [13]:

$$VBN=\frac{\left(V_1-V_0\right)\times c\times 14}{m\times V_3/V_2}\times 100$$

(2)

where c is the concentration of the HCl solution (mol/L), V₀, V₁, V₂, and V₃ are the volumes of the HCl solution consumed by reagent blank (mL), the HCl solution consumed by the fishmeal dipping solution (mL), the distilled water added during extraction (mL), and the fishmeal dipping solution removed (mL), respectively; m is the mass of the fishmeal (g).

The determination of the pH value was performed according to the national standard of China, GB 5009.237-2016 [26]. A total of 5 ± 0.01 g of fishmeal sample was placed into a conical flask, and 50 mL distilled water was subsequently added. The mixture was shaken for 30 min at room temperature at a rate of 260 times per minute, and it was allowed to stand for 5 min. The fishmeal dipping solution was subsequently obtained through dry filtration. The pH value of the fishmeal dipping solution was measured three times, and the average value was taken.

The determination of the mold count was performed according to the national standard of China, GB/T 13092-2006 [24]; however, the antibiotics were not added. A total of 25 ± 0.5 g of fishmeal sample was placed into a sterilized beaker, and it was diluted with 225 mL sterilized physiological saline. After shaking for 30 min, it was successively diluted 10 times until an appropriate gradient was obtained. A total of 1 mL fishmeal diluent was absorbed into a sterilized Petri dish; this was repeated twice for each concentration. Then, the appropriate amount of CzapekDox agar was poured into the Petri dish. After the CzapekDox agar solidified, the Petri dishes were turned over and stored at 25 °C for 7 days in the constant temperature incubator. Finally, the count and calculation were performed, and the results are reported in logarithmic units (lg CFU/g).

2.3. Data Processing

2.3.1. Grey Relation Analysis (GRA) Method

To obtain the correlation between mold count and the freshness indexes, GRA was adopted to explore the influence of mold count on the freshness of fishmeal. As part of grey system theory, GRA is suitable for solving problems with complicated interrelationships between multiple factors and variables. GRA is a method for determining the degree of correlation between factors based on their similarity; it was developed by Deng [27]. Briefly, the calculation process of GRA is as follows.

Firstly, the reference sequence (mold count), denoted as x₀, and the comparison sequence (each freshness index), denoted as x_i, are determined in order to find the degree of relation between them, respectively.

$$x_0={\left(x_0\left(1\right),x_0\left(2\right),\dots ,x_0\left(n\right)\right)}^T$$

(3)

$$x_i={\left(x_i\left(1\right),x_i\left(2\right),\dots ,x_i\left(n\right)\right)}^T$$

(4)

The reference sequence and comparison sequence were used to normalize, respectively, according to Formulas (5) and (6).

$$x_0^{\prime }\left(k\right)=\frac{x_0(k)}{\frac{1}{n}{\displaystyle \sum _{k=1}^n{x}_0(k)}}$$

(5)

$$x_i^{\prime }\left(k\right)=\frac{x_i(k)}{\frac{1}{n}{\displaystyle \sum _{k=1}^n{x}_i(k)}}$$

(6)

The coefficients of grey incidence ξ(x₀′(k), x_i′(k)) (sometimes termed as, grey/point relation coefficients) are calculated according to Formula (7). Finally, the grey grade γ_i was obtained according to Formula (8). The grey grade represents a numerical measurement of the correlation between the reference sequence and the comparison sequence.

$$\xi (x_0^{\prime }(k),x_i^{\prime }(k))=\frac{\min (i)\min (k)\left|x_0^{\prime }(k)-x_i^{\prime }(k)\right|+\rho \max (i)\max (k)\left|x_0^{\prime }(k)-x_i^{\prime }(k)\right|}{\left|x_0^{\prime }(k)-x_i^{\prime }(k)\right|+\rho \max (i)\max (k)\left|x_0^{\prime }(k)-x_i^{\prime }(k)\right|}$$

(7)

$${\gamma }_i=\frac{1}{n}{\displaystyle \sum _{k=1}^n{\xi }_i\left(x_0^{\prime }\left(k\right),x_i^{\prime }\left(k\right)\right)}$$

(8)

where the distinctive coefficient is represented by ρ and is assumed to be ρ = 0.5 as a distinctive coefficient.

2.3.2. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Method

To obtain suitable storage conditions for fishmeal, the TOPSIS method was adopted to comprehensively evaluate the effect of storage on fishmeal [28]. The TOPSIS method is an evaluation scheme and analysis method for multiple indexes and schemes based on the Euclidean distance of the evaluated object and the ideal goal; it was developed by C.L. Hwang and K. Yoon and proposed in 1981 [29]. According to the fishmeal freshness indexes under different storage conditions on the 30th day, the positive ideal solution and the negative ideal solution in the system under different storage conditions were constructed to reflect the difference between the various storage conditions, and the comprehensive distance between the positive ideal solution and the negative ideal solution of any scheme under those conditions was subsequently evaluated.

Firstly, the data needed to be normalized. The measured values of AV and VBN were normalized as the interval-type index. Taking the best interval (a, b) as an example, the data were obtained according to Formula (9). The intermediate-type index is usually used to evaluate the pH value. For the normalized intermediate-type index, it was necessary to determine the best value. The data were obtained according to Formula (10). Then, the normalized data were standardized, and the standardized matrix Z of n rows and m columns was calculated, as shown in Formula (11).

$${\widehat{x}}_i=\{\begin{array}{c}1-\frac{a-x_i}{M},x_i<a\\ 1,a<x_i<b\\ 1-\frac{x_i-b}{M},x_i>b\end{array}$$

(9)

Here, $M=\max \left\{a-\min \left\{x_i\right\},\max \left\{x_i\right\}-b\right\}$.

$${\widehat{x}}_i=1-\frac{x_i-x_{best}}{M}$$

(10)

Here, x_best is the best pH value, and M = max{|x_i-x_best|}.

$$Z=\left[\begin{array}{cccc}{z}_{11}& z_{12}& \cdots & z_{im}\\ z_{21}& z_{22}& \cdots & z_{2m}\\ ⋮& ⋮& \ddots & ⋮\\ z_{n1}& z_{n2}& \cdots & z_{nm}\end{array}\right]$$

(11)

Here, $z_{ij}=\frac{x_{ij}}{\sqrt{{\displaystyle {\sum }_{i=1}^n{x}_{ij}^2}}}$, x_ij is each element in the matrix, n is the number of schemes to be evaluated, and m represents the indexes.

The positive ideal and negative ideal solutions of the matrix Z are determined for z⁺ and z⁻, respectively.

$$z^{+}=\left[z_1^{+},z_2^{+},\dots ,z_m^{+}\right]=\left[\max \left\{z_{11},z_{21},\dots ,z_{n1}\right\},\max \left\{z_{12},z_{22},\dots ,z_{n2}\right\},\dots ,\max \left\{z_{1m},z_{2m},\dots ,z_{nm}\right\}\right]$$

(12)

$$z^{-}=\left[z_1^{-},z_2^{-},\dots ,z_m^{-}\right]=\left[\min \left\{z_{11},z_{21},\dots ,z_{n1}\right\},\min \left\{z_{12},z_{22},\dots ,z_{n2}\right\},\dots ,\min \left\{z_{1m},z_{2m},\dots ,z_{nm}\right\}\right]$$

(13)

The separation measures, using the n-dimensional Euclidean distance, are calculated. The separation of each scheme from the positive ideal solution is given as follows:

$$d_i^{+}=\sqrt{{\displaystyle \sum _{j=1}^m{\left(z_j^{+}-z_{ij}\right)}^2}}$$

(14)

Similarly, the separation from the negative ideal solution is given as follows:

$$d_i^{-}=\sqrt{{\displaystyle \sum _{j=1}^m{\left(z_j^{-}-z_{ij}\right)}^2}}$$

(15)

For each scheme, the ratio S_i is calculated as follows:

$$S_i=\frac{d_i^{-}}{d_i^{+}+d_i^{-}}$$

(16)

where 0 ≤ S_i ≤ 1. When d_i⁺ is smaller, that is, the separation between the scheme and the positive ideal solution is the smallest, the larger S_i is, the better the scheme is.

3. Results and Discussion

3.1. Effect of Storage Conditions on Freshness Indexes and Mold Count

3.1.1. Effect of Storage Conditions on AV

The changes in the AV of fishmeal stored at different temperatures for 30 days are shown in Figure 1a. These different AVs had a significant difference (p < 0.05). The AV of fishmeal firstly increased and then decreased slowly, showing an overall upward trend at lower storage temperatures (15 °C and 20 °C), which is consistent with Chen and Wang’s results [23]. Furthermore, it showed a decreasing–increasing–decreasing trend, and a downward trend as a whole at higher storage temperatures (25 °C, 30 °C, and 35 °C). After 16 days of storage, the AV of fishmeal was less than 3 mg/g at higher storage temperatures, and the fishmeal was super fresh [30]. This was because the higher storage temperature was not conducive to the growth of microorganisms, and the activity of related enzymes decreased. Thus, it was not conducive to the rancidity and decomposition of fat, resulting in a decrease in the value of the AV. Figure 1b shows the changes in the AV of fishmeal under different RH for 30 days. Under the storage condition of 80% RH, the AV was 3.32 mg/g on the 2nd day, and the fishmeal was super fresh [30]. On the eighth day, the AV increased significantly, and after 30 days, the AV increased to more than 5 mg/g, and the final freshness of the fishmeal was generally fresh, but also corrupt. Relatively high RH promoted the oxidative rancidity of fat and reduced the freshness [18]. Therefore, fishmeal should be stored at low RH.

3.1.2. Effect of Storage Conditions on VBN

Figure 2a shows the changes in the VBN of fishmeal stored at different temperatures for 30 days. In the early stage of storage, the VBN decreased slowly, and there was little change in the VBN in the middle of the storage period. In the later stage of storage, the VBN showed a downward trend and increased occasionally in some periods. This was because the VBN was mainly composed of ammonia, primary amine, secondary amine, and tertiary amine, which were related to the activity of enzymes and the growth of microorganisms. It was not conducive to the growth of microorganisms under higher storage temperatures. Thus, the amount of VBN was reduced [31]. Figure 2b shows the effect of RH on the VBN. The VBN of fishmeal under different RH for 30 days showed a decreasing trend, which indicates that the VBN is not suitable for use as a freshness index of early deterioration. Only under the storage condition of 80% RH, the VBN of fishmeal decreased firstly and then increased, and significantly increased in the later storage. This was because a higher RH could promote the reproduction and growth of microorganisms as well as enzyme activity, and it could also increase the decomposition rate of nitrogen-containing compounds [32], therefore increasing the amount of ammonia, trimethylamine, and dimethylamine.

3.1.3. Effect of Storage Conditions on pH Value

The changes in the pH value of fishmeal stored at different temperatures for 30 days are shown in Figure 3a. These different pH values were significantly different (p < 0.05). The pH value of fishmeal stored at 15 °C, 20 °C, and 25 °C first decreased and then increased. At the later storage, the pH value tended to be stable. At 30 °C and 35 °C, the pH value of fishmeal changed greatly, and the trend was the same for the pH value of fishmeal stored at a lower temperature. The change in pH value was consistent with the results of Abdollahi et al. [33] and Liu et al. [34]. The initial sharp decrease in pH value was due to the release of inorganic phosphate by ATP degradation and/or accumulation of lactic acid during anaerobic glycolysis, and the later increase may be due to the accumulation of alkaline compounds, such as biogenic amines and ammonia. The effect of RH on the pH value of fishmeal is shown in Figure 3b. Except for fishmeal under 80% RH, the pH value of fishmeal stored under other RHs showed a decreasing–increasing–decreasing trend, and an overall downward trend, and it tended to be stable in the later storage. The pH value of fishmeal stored under 80% RH showed an increasing–decreasing–significantly increasing trend, and an overall increasing trend, which was the same as the variation of VBN shown in Figure 2b. The increase in pH value was due to changes in alkaline compounds and autolysis. The accumulation of alkaline metabolites promoted the increase of pH value, which could be used as an indicator of the deterioration process.

3.1.4. Effect of Storage Conditions on Mold Count

Figure 4 presents the changes in the mold count in fishmeal under different storage conditions. The storage temperature had no significant effect on mold count (p > 0.05). The RH had a significant effect on mold count (p < 0.05). Figure 4b shows that the mold count in fishmeal under 80% RH increased significantly after 10 days; the fishmeal became highly moldy after 15 days. Upon comparison of Figure 2b and Figure 3b, the time during which mold thrived occurred in roughly the same time period as the rapid increase in the VBN and the pH value. It was inferred that mold accelerated the decomposition of nutrients in fishmeal and affected its freshness.

3.2. GRA between Mold Count and Freshness Indexes

Since the time when the VBN and pH value rapidly increased and the time when the molds multiplied were relatively close, it was speculated that the mold count had a certain relationship with the freshness indexes of fishmeal. The change in each freshness index of fishmeal and the logarithmic change in mold count was regarded as a system of dynamic changes in storage time and storage conditions. To obtain the correlation between fishmeal freshness indexes and mold count during storage, the GRA was used to analyze the degree of correlation between the AV, VBN, and pH value of fishmeal and mold count, and to determine the influence of mold count on the freshness index of fishmeal. The GRA is a kind of grey system analysis method that measures the degree of correlation between indexes. It is a relatively objective method for evaluating the weight of indexes, which is not demanding on data and can be used to solve the problem of a small amount of data and incomplete information [35]. Usually, the GRA is greater than 0.8, which indicates that the object of analysis has a strong correlation degree. Between 0.3 and 0.8 indicates that there is a weak correlation degree. Less than 0.3 indicates that there is no correlation [36,37].

Figure 5 shows the GRA between the freshness indexes and mold count of fishmeal under different temperatures. Generally, the GRA between mold count and the freshness indexes of fishmeal showed a similar trend at different temperatures. The mold count was weakly correlated with the VBN, AV, and pH values, but strongly correlated with some storage time. Among them, the mold count had the largest GRA with VBN, followed by AV, and it had the smallest GRA with the pH value. That is, the VBN was the most affected, while the pH value was less affected by the mold count. With the increase in storage temperature, the effect of mold count on AV was enhanced during the later storage. Under the storage conditions of all temperatures except for 15 °C, the GRA between the mold count and AV increased after 26 days of storage, all of which had a strong correlation. With the increase in temperature, the GRA between mold count and VBN decreased slightly, which may be related to the production mechanism of VBN. The GRA between mold count and pH value was hardly affected by temperature. With the increase in temperature, the GRA between the mold count and pH value had little change.

Figure 6 shows the GRA between the freshness indexes and mold count of fishmeal under different RHs. These GRA values were the same as the GRA obtained at the storage temperature. With the increase in RH, the effect of mold count on AV was enhanced at the later storage. Under the storage conditions of all RH except for 40% RH, the GRA between mold count and AV increased after 26 days of storage, all of which had a strong correlation. The GRA between mold count and VBN increased; that is, the mold count had a strong correlation with VBN after 26 days of storage under all storage conditions, except for 40% RH and 50% RH. During the whole storage period under 80% RH, the mold count and VBN had a strong correlation, which could verify the conclusion of the single-factor test. Under high RH, mold proliferation accelerated the decomposition of nutrients, especially nitrogenous substances, as well as the process of fishmeal deterioration, which led to an increase in VBN. Compared with storage temperature, the mold count and pH values were more affected by RH. In addition to 60% RH, the mold count and pH value had a strong correlation after 26 days of storage under the other RH storage conditions.

3.3. Comprehensive Evaluation

In this section, the TOPSIS method was used to comprehensively evaluate the freshness indexes of fishmeal during storage, and the suitable temperature and RH for storage were determined according to the evaluation results. According to the national standard of China, GB/T 19164-2003, and GB/T 19164-2021, and combined with data from the experiment, AV was normalized according to the optimal level of the interval-type value of (2,3), and VBN was normalized according to the optimal level of the interval-type value of (90,110). According to the AV and VBN, the freshness grade of fishmeal was determined, and then, the average pH value of super fresh fishmeal was 5.914. Therefore, the pH value of fishmeal was normalized according to the optimal level of the intermediate-type value of 5.914.

The freshness indexes of fishmeal under different storage conditions at 30 days were scored and ranked using the TOPSIS method. The evaluation results for storage temperature and RH are shown in

Table 2. The evaluation results of the TOPSIS method under different storage conditions.

	Group	Score	Ranking
Temperature	15 °C	0.1320	5
	20 °C	0.1756	4
	25 °C	0.2670	1
	30 °C	0.2013	3
	35 °C	0.2241	2
RH	40% RH	0.2136	2
	50% RH	0.2101	3
	60% RH	0.3113	1
	70% RH	0.1947	4
	80% RH	0.0702	5

. At different storage temperatures, the scores of fishmeal stored for 30 days have the following order: 25 °C > 35 °C > 30 °C > 20 °C > 15 °C; that is, the freshness of the fishmeal stored at 25 °C was the best, much higher than 15 °C and 20 °C. The possible reason is that higher temperatures inhibited the growth and autolysis of molds and so the fishmeal could be kept in a relatively fresh grade [38]. The fishmeal stored for 30 days under different RH is ranked as follows: 60% RH > 40% RH > 50% RH > 70% RH > 80% RH. The freshness of fishmeal stored under 60% RH was the best, and the freshness grades of fishmeal stored under 40% RH, 50% RH, and 70% RH were relatively close, which were far better than the effect of 80% RH on storage. High RH would accelerate spoilage and reduce the freshness of fishmeal, which is not conducive to its storage.

4. Conclusions

In this paper, the AV, VBN, and pH values were used as freshness indexes, and the effects of storage conditions on the freshness indexes and mold count of fishmeal were studied. In other words, the changes in the AV, VBN, pH value, and mold count with storage time under different storage conditions were determined. The main conclusions are as follows:

(1) The effects of storage conditions on the freshness indexes and mold count of fishmeal were determined using a single-factor test. During storage, the AV showed an overall upward trend due to the oxidative rancidity of fat. Due to the decomposition of volatile substances such as nitrogen, VBN had the trend of gentle decreasing–steady change–continuous decreasing and showed a downward trend on the whole. The pH value of fishmeal tended to be stable during storage, and the overall trend was decreasing. Therefore, the VBN and pH values should not be used as evaluation indexes for freshness in the early stage of fishmeal deterioration. The AV, VBN, pH value, and mold count of fishmeal under higher relative temperature decreased in the later storage, and the freshness grade of fishmeal was better. That is, a higher storage temperature is conducive to the storage of fishmeal. During the later storage, the AV, VBN, pH value, and mold count of fishmeal under higher RH increased significantly, while the freshness grade decreased. Therefore, higher RH is not conducive to fishmeal storage.

(2) GRA was used to analyze the effect of mold count on the freshness indexes of fishmeal. The results showed that the mold count was correlated with each freshness index. The GRA between the mold count and VBN was the largest, followed by AV, while the GRA with pH value was the smallest. In the later storage, the GRA between the mold count and each freshness index increased, and the mold count had a strong correlation with AV and VBN. Therefore, inhibiting the thriving of molds is of great importance for maintaining the freshness of fishmeal during storage. Using the TOPSIS method, the freshness of fishmeal was comprehensively evaluated to determine suitable storage conditions. Finally, within an acceptable range for the mold count, the suitable storage conditions for fishmeal were determined to be a temperature of around 25 °C and a 60% RH, which serve as a reference for fishmeal storage.