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Article

Acoustic Characterization for The Feeding Activities of Haliotis discus Hannai

by
Hongyue Lin
1,
Yiyang Qian
1,
Jia Chen
1,2,
Xiaolong Gao
3,4,
Mo Zhang
3,4,
Weiwei You
3,4 and
Rongxin Zhang
5,*
1
School of Electronic Science and Engineering (National Model Microelectronics College), Xiamen University, Xiamen 361005, China
2
Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen 361005, China
3
Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, Xiamen University, Xiamen 361102, China
4
College of Ocean and Earth Sciences, Xiamen University, Xiamen 361102, China
5
Key Laboratory of Underwater Acoustic Communication and Marine Information Technology, Xiamen University, Ministry of Education, Xiamen 361005, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2023, 13(9), 5559; https://doi.org/10.3390/app13095559
Submission received: 10 April 2023 / Revised: 28 April 2023 / Accepted: 28 April 2023 / Published: 29 April 2023
(This article belongs to the Section Applied Biosciences and Bioengineering)
Browse Figures
Versions Notes

Abstract

:
In order to analyze the sound production mechanism and the acoustic characteristics of Haliotis discus hannai during feeding, this paper proposes a multi-source information fusion approach combining passive acoustics with videos. In the experiments, abalones with a shell length of 60 ± 2.7 mm were divided into two groups: Group A was fed with fresh macro algae Gracilaria lemaneiformis as food once each day; Group B was placed on a small amount of sand as impurities at the bottom of the tank. As control groups, Group C did not have abalone or food and Group D did not have abalones but food was added. The eating acoustic signals of abalone were mainly concentrated in the frequency range between 9.49 kHz and 44.36 kHz, wherein the peak frequency is 37.86 ± 2.55 kHz, with the maximum energy −66.43 ± 5.17 dBm/Hz. Each pulse sequence is with a duration of 119.12 ± 70.51 ms and consists of several sub-pulses. Nearly 70% of the pulse sequences consist of 1~2 sub-pulses and the duration of the pulse containing one sub-pulse is 42.62 ± 19.72 ms. The eating rate was kept at 0.61 ± 0.04 times/min at the beginning and was decreased significantly to 0.48 ± 0.08 times/min after 60 min. Note that the characteristic analysis of abalone acoustic signals during feeding are first reported in this manuscript to the best of our knowledge, and this paper also demonstrates that the sound of abalone is produced by scraping and grinding food with radula. Because the eating rate decreases with the reduction in the abalone’s level of hunger, the results may be used as an acoustic indicator of feeding strategy for the abalone aquaculture industry.

1. Introduction

Aquatic animals produce sounds during predation, feeding, mating, communication, etc. Different from the sounding mechanism of terrestrial animals, which is based on the vibrations produced by air through a tight membrane (that is, vocal cord), most aquatic animals cannot use air. Therefore, their sounding mechanism has limitations and is not as complicated as the terrestrial ones [1].
There are several mechanisms of fish sound production: friction sound produced by rubbing the bones of the body (such as teeth, skull, jaws, gills, fins, and vertebrae), drumming sound produced by the vibration of the swim bladder, stridulation produced by pectoral spines, the sound of waves produced by swimming, etc. [2,3,4,5]. The acoustic characteristics of fish can be used to analyze information, such as the distribution and the activity of fish [6]. Lagardère et al. [7] studied the acoustic characteristics of the feeding activities of Salmo trutta fario, Oncorhynchus mykiss, and Scophthalmus maximus and analyzed their differences under various feeding patterns. The acoustic pressure of Scophthalmus maximus changes significantly during feeding, which can be used in controlling the feeding intensity [8]. Lammers et al. [9] tracked ecological acoustics on coral reefs and other marine habitats, which could be used to infer breeding, feeding, and ecosystems’ condition.
Marine invertebrates have very limited sound production abilities compared with fishes, so there are few related studies, among which shrimp is the most extensively studied. These include bumping, rubbing, carapace vibration, stick–slip friction, biting, bubbling, and contracting muscles [10,11,12,13,14,15,16,17]. There are different sound mechanisms for different behaviors: when the snapping shrimp encounters danger, it will quickly close its frontal chela and make a harsh sound to deter intruders [18]. Some lobsters can make stridulation through the friction of two parts of their bodies to deter predators [19]. Based on the relationship between the hunger level and the activity behavior, researchers can indirectly judge the appetite of Penaeus monodon by detecting the frequency of the acoustic signal during the feeding activity. Therefore, the feeding can be controlled [20].
Mollusks have a lower frequency and smaller range of activity and less sound signals compared with fishes and crustaceans. There are several reasons for this phenomenon; first of all, shellfish do not have the agility and aggressiveness as animals that need to use sound to deter, evade, or attack predators. Secondly, because some gastropoda feed on algae that are at the bottom of the food chain, they do not need to locate their prey by acoustics [1]. In addition, making sound also tends to attract predators [21]. Therefore, there are currently few studies on shellfish, with most research focusing on the sounds produced during eating. Kitting [22] documented the sounds when different species of mollusks rasp different algae or scrape rock. Konzewitsch and Evans [23] used passive acoustic to track the spatial requirement and broad movement of spider conch.
Abalone is an economically important cultured mollusk species in the world and has been regarded as the jewel in the seafood crown for thousands of years in China. With continuous overfishing and water pollution in the wild, more and more natural habitats are destroyed and the number of wild abalones has become lower and lower [24]. As a result, abalone farming production has substantially increased in the past two decades. Therefore, there are many related studies focusing on abalone farming, including genetic breeding [25,26], behavior [27], nutrition and feed [28], physiological ecology [29], etc. However, abalone likes to stay in an environment with relatively dim light, and aquaculture water is always turbid, which makes it difficult to use underwater cameras to observe and study the behaviors of abalone. Kitting pointed out that sounds produced by Haliotis cracherodii can be heard during feeding [22]. However, to the best of our knowledge, there are no studies focusing on abalone acoustics.
Passive acoustic technology is an acoustic method that can be used to detect the sound of animals in their natural environment [30]. In an underwater environment, a hydrophone can be used to monitor the sound actively produced by the target [31]. By studying the acoustic characteristics of aquatic animals, it is possible to crack the biological significance of those sounds and to identify the species and activity behaviors of the vocalizing animals [1].
In underwater environments, acoustic wave is the optimal choice for propagations in most scenarios [32]. Furthermore, passive acoustics do not require any attachments equipped on the detected objects. To monitor the feeding activities of aquatic animals, most of the research relied on direct observation [33] or video recording [34]. These methods, especially direct observation, are difficult for further analyses of the acoustic characteristics. Meanwhile, with passive acoustics, we can clearly review and analyze the acoustic signal. By comparison, the application of passive acoustics in aquaculture has great potential [35]. Therefore, passive acoustics has been used to monitor the behavior, distribution, and sound characteristics of shrimp, whales, manatees, etc. [30]. Smith et al. [20,35] realized the analyses of the feeding sound of prawn and measured the feeding consumption through passive acoustics. Peixoto et al. [36] evaluated the relationship between acoustic signals and diet lengths of Litopenaeus Vannamei through passive acoustics. The research on the acoustic behavior of fishes such as Micropterus salmoide [37,38] and Scophthalmus maximus [8] has also been applied to their farming activities. Based on the extensive acoustic research results of fish and crustaceans, passive acoustics has been gradually applied in the actual aquaculture production process, such as shrimp productions reported by Reis et al. [39].
Our research on the acoustic characteristics of abalone is conducive for further biological research on abalone and can help abalone aquaculture practitioners improve their farming strategies to increase the revenues. Therefore, the objective of this work is to study the acoustic activities of abalone using passive acoustic method in order to quantify the acoustic characteristics of abalone feeding activity and to study the pattern of acoustic signal during abalone feeding. The results can serve the abalone farming industry, wherein the acoustic description and measurement can be adopted for optimizing the feeding strategy and improving the farming efficiency of abalone.
The rest of the paper is organized as follows: Section 2 describes the experimental setup, method, and software and hardware used to record and process the acoustic signals of abalone. In Section 3, the eating process of abalone is described and the acoustic characteristics of abalone feeding activities are analyzed. In Section 4, the eating-based sound production mechanism of abalone is discussed, the relationship between acoustic signals and abalone circadian rhythm is described, and the method used for acoustic signal processing is described. Finally, in Section 5, some conclusions are drawn.

2. Materials and Methods

2.1. Experimental Design

The Pacific abalones H. discus hannai with shell length of 60 ± 2.7 mm were from Fuda Abalone Farm in Jinjiang, Fujian Province, China. All abalones were transported from the farm into the laboratory and then acclimated in the same environment for 3–5 days before the experiments. The experiments were divided into four groups: abalones in Group A were fed with fresh Gracilaria lemaneiformis once a day at 6 p.m.; Group B were placed on a small amount of sand as impurities at the bottom of the tank. As the control groups, Group C did not have abalone or food and Group D did not have abalone but G. lemaneiformis was added. Throughout the experiments, only one abalone was observed in Groups A and B each time, and each abalone was continuously observed for 5 days. During the experiments, 10 abalones were used in Groups A and B, respectively, and each abalone was only used once. Group A was provided about 5 g of seaweed every day to ensure that the food would not be eaten up, Group B was provided about 10 g of sand for each abalone, and the weight of the food placed in Group D was the same as that in Group A.
During the experiments, acoustic signals were recorded using an acoustic recorder (Song Meter SM4BAT FS Ultrasonic Recorder). Because abalone is a nocturnal benthic animal, an infrared camera (Shenyou 5 megapixel high-definition infrared camera) was used to record abalone’s activities in the environment without artificial light. Table 1 shows the detailed information of the devices.
The abalones were placed in a cylindrical acrylic tank (as shown in Figure 1) filled with fresh seawater. The hydrophone was placed in the center of the tank and connected to an external acoustic recorder. An infrared camera equipped with a filter was placed under the tank to assist the acoustic signal to judge the eating behavior. A layer of sound insulation cotton was wrapped around the data acquisition device to absorb the noise of the surrounding environment, especially the noise from the water circulation device. In order to eliminate the noise as much as possible, we also used sound insulation cotton to wrap the water circulation device and put it as far from the tank as possible.
The water circulation device delivers and oxygenates seawater during the experiment, and it was placed at the same height as the data collection device. During the experiments, the water pump was used to pump water from the water circulation device to the data collection device through the water pipe. At the same time, due to the principle of the connector, the water in the data collection device also flowed back through the water pipe. In this way, the water could be circulated and the two separated devices could also effectively reduce the influence of the noise of the water flow on the acoustic data collection.
During the experiments, the water temperature was controlled in the range of 20 ± 1 °C, and half the seawater was regularly replaced every day to remain fresh. Aeration was used to supply dissolved oxygen. Artificial lighting was not used in the experiments to ensure the normal routine of the abalones. The work of replacing water and feeding was conducted at noon in order to reduce the corresponding interference on the activities of the abalones.

2.2. Acoustic Signals Preprocessing

The software WavePad (Englewood, CO, USA, NCH SOFTWARE PTY, Inc., version 12.69) was used to extract the audio data from the signal, and the software Total Video Audio Converter (USA, Hoo Technologies, Inc., version 3.71) was used to convert the video to mp4 format.
Although the video and audio collection devices are separate, they have the same time stamp, so we used the video editing software Wondershare Filmora X (China, Wondershare Technology, Inc, version 3.5) to combine the synchronized video and audio to observe the correlation between the movements and the acoustic signals of abalone.
In order to analyze the feeding-activities-based acoustic signals in the frequency domain, short-time Fourier analysis (STFA) was used to transform the acoustic signals to the frequency domain, and the time–frequency spectrum was used instead of Fourier transform, which reveals the frequency spectrum of each shorter component.

2.3. Analysis of Acoustic Variables

For the collected audio data, Kaleidoscope (Maynard, MA, USA, wildlife acoustics, version 5.1.9g) was firstly used to manually identify the collected audio data and confirm the effective signal area combined with the video. Figure 2 shows the flowchart of the whole audio and video processing process.
Then, we randomly selected 50 identified acoustic pulses, preprocessed the data, and analyzed the parameters of each pulse signal (as shown in Figure 3). The selected parameters refer to the work of Silva [40]. In order to better reflect the acoustic characteristics, the parameters we used include the minimum and the maximum frequencies (kHz), the peak frequency (kHz), the maximum energy (measured by maximum short-time power spectral density, dBm/Hz), the number of pulses included in each sequence, the duration of each pulse sequence (ms), and the sub-pulse duration (ms). Finally, Originpro 2022 (Originlab, Inc.) was used to draw the boxplots of parameters.

3. Results

This section is divided into four subheadings according to the content of the results. It provides a concise and accurate description of the feeding process of abalone, the acoustic signal, the relationship between the acoustic signal and the level of hunger, and the experimental conclusions that can be drawn.

3.1. Eating-Based Sound Production

For the experiments outlined in Section 2.1, the acoustic signals of abalone feeding activities were collected only in Groups A and B (as shown in Figure 4). Groups C and D did not have eating acoustic signals similar to Groups A and B, so they were not included in the analysis.
Based on the videos, we selected the eating process of abalone. Since abalone tends to stand still or move slowly on the edge of the tank during the experiments, we judged the eating behavior of the abalone according to the following selection principles: the abalone is moving or near the food, the mouth of the abalone has eating actions, and the acoustic recorder recorded the sound produced during these processes. At the beginning, the abalone slowly crept to the vicinities of the food. During the movement, the abalone opened its mouth, exposed its jaws, and clung to search for the food. When abalone ingested the seaweed, there was a clear acoustic pulse signal produced. Sometimes the mouth closed briefly and remained still after eating but, at the same time, there was still a clear acoustic pulse signal produced. The acoustic signal disappeared immediately when the abalone stopped eating and moved away from the food.

3.2. Signals of Eating Different Substances

There are obvious differences in the acoustic signals when abalones eat different foods. The pulse sequence duration of Group A is about 20 ms shorter than that of Group B. Each pulse sequence in Group A consists of 1~2 sub-pulses, while, in Group B, it consists of more than two sub-pulses. The peak frequency of Group A is in the range of 30~40 kHz, while the peak frequency of Group B is around 10 kHz, 20 kHz, and 30 kHz. The amplitude of the peak frequency of Group A is higher than that of Group B. Referring to Figure 3 and Figure 5, we can see that there are differences in HF, PF, and LF between the acoustic signals when abalones eat different foods (seaweed and sand). Meanwhile, in the control groups, no acoustic signal similar to the eating signals was collected.

3.3. Analysis of Eating Acoustic Signals

This work analyzed the signals in the frequency domain (as shown in Figure 6) and the time domain (as shown in Figure 7). The low frequency is 9.49 ± 0.38 kHz, the high frequency is 44.36 ± 0.59 kHz, the frequency peak is 37.86 ± 2.55 kHz, and the maximum energy is −66.43 ± 5.17 dBm/Hz. The duration of each pulse sequence is 119.12 ± 70.51 ms and consists of several sub-pulses. Among them, nearly 70% of the pulse sequences are composed of 1~2 sub-pulses, and the duration of the pulse containing one sub-pulse is 42.62 ± 19.72 ms.

3.4. Relationship between the Eating Rate and the Hunger Level

The relationship between the eating rate and the hunger level was analyzed in this work. The feeding process of abalone is intermittent, which means abalone will rest for a while after eating and then continue to eat. Therefore, we counted the frequency of the eating signal pulse sequence of the same eating continuous sequence within 1 min intervals (as shown in Figure 8). In the early stage of feeding, the frequency of signals remained at 0.61 ± 0.04 times/min and, after 60 min, the frequency of signals decreased significantly and remained at 0.48 ± 0.08 times/min. It can be inferred that, in the early stage of feeding, the abalone had a higher hunger level and a faster eating rate. As the feeding time increased, the degree of hunger was getting lower and its eating rate decreased significantly.

4. Discussions

4.1. Eating-Based Sound Production Mechanism

The digestive system of abalone is on the left side of the adductor muscle that is in the middle of the body. The digestive organ includes mouth, gullet, stomach, intestine rectum, and anus. In the mouth, there are jaws, radula, and salivary glands. The radula is the main tool for abalone to take food. The front part of the radula has abrasion during the long-term eating behavior, related to the way abalone scrapes food [41]. When the abalone eats, the mouth is firstly opened. Under the action of the muscles and cartilage, the radula sticks out of the mouth and the back of the radula faces the food. When the radula retracts into the mouth, the back of the radula fully contacts the food surface and starts to scrape the food. The ingested food is first chopped by the jaws, then ground by the radula, mixed with saliva, and finally sent to the esophagus through the pharyngeal flap.
During the experiments, the acoustic signal disappeared immediately when the abalone left the food after feeding. Taking account of the physiological structure of the abalone, the digestion of the food is a continuous process. If there is sound in the process of digesting food, the acoustic signal can still be collected after the abalone stops eating, which is contrary to the experimental results. Therefore, the possibility that the abalone produces sound when digesting food is ruled out.
Through the audio and video data collected in the experiments, it can be found that the appearance time of the acoustic signal is almost synchronized with the action of the abalone ingesting food, indicating that the sound is mainly produced during the process of ingesting food. The main activities of abalone during ingesting are scraping and grinding of the radula and chopping food with the jaw. In the experiments of Group B, it was observed that the jaw was exposed after feeding, while the acoustic signal was still produced. Thus, the possibility of the sound produced by the jaw chopping is also ruled out.
Therefore, it is considered that the eating-based acoustic signal is mainly produced by scraping and grinding the food with the radula. Because there was a significant difference in the eating signal of abalones in Group A and Group B, it indicates that the generation of abalone ingesting sound is also related to the type of food.
Marine animals have different mechanisms to produce eating-based sounds, but few are similar to the eating-based sound mechanism of the abalone. A “click” sound is produced by the maxipellids and mandibles of shrimps when they cut and tear food [20,42]. A “click” sound is also produced by the movement of supraoccipital–coronet articulation of seahorse during feeding [43,44]. Sounds are produced when clownfish lower the hyoid apparatus rapidly and close the mouth at the same time [45,46]. Sounds are produced as an exaptation during feeding because of the movement of the upper and lower pharyngeal jaws of Haemulon flavolineatum [47]. Sounds and a head snap are produced during feeding of Syngnathus fuscus Syngnathus floridae [48]. The cerato-mandibular (c-md) ligament plays a sound maker role in both feeding and communication in damselfishes [49].

4.2. The Relationship between Acoustic Signals and Abalone Circadian Rhythm

Circadian rhythm is the regular behavior for organisms to adapt to circadian changes. It can help organisms predict changes in the environment and change their own behavioral and physiological characteristics to gain a survival advantage [50]. For nocturnal animals, their activities and physiological indicators are higher at night than during the day [51]. Abalone is a nocturnal animal and has a and longer crawling distance and movement time at night [52].
All the eating acoustic signals of abalone collected in this experiment showed significantly more at night than during the daytime (as shown in Figure 9). The signals mainly appear between 18:00 and 6:00, which is consistent with the habit of abalone as a nocturnal animal. In addition, there are two peaks of eating signals at night between 21:00 and 24:00 and between 03:00 and 06:00; this is consistent with the fact that abalone has two eating peaks at night [53]. The result shows that there is a correlation between eating acoustic signals and abalone circadian rhythm, which also indicates the possibility of using acoustics to study the circadian rhythm.

4.3. Acoustic Signal Processing Methods

The acoustic signal of feeding activities cannot be treated as a stationary random signal macroscopically, but its characteristics change little in a short period of time and can be treated as stationary microscopically. STFA is often used for analysis of slowly time-variant signal frequency spectrum. Therefore, STFA is suitable for analysis of the acoustic signal of feeding activities.
In order to apply STFA, the signal needs to be framed first, and then each frame is processed by Fourier transform.
In the framing process, each frame usually needs to contain multiple pitch periods. Because the acoustic signal frequency of abalone’s feeding activity is greater than 3.5 kHz and the sampling frequency is 96 kHz, the duration of each frame is set to 3 ms in the analyses, which makes a frame contain several periods. That is, the sample of each frame is 288. The frame shift is half of the frame length; then, each framed signal can be expressed as:
y i ( n ) = ω ( n ) ∗ x ( ( i − 1 ) ∗ FS + n ) , 1 ≤ n ≤ FL , 1 ≤ i ≤ F
where i is the number of the frame, n is the length of the frame, FL is the frame length, F is the total number of frames of audio data, ω ( n ) is the window function, FS is the frame shift length, and y i ( n ) is the value of the i-th frame.
The software used for data processing in this work is MATLAB and the drawing software is OriginPro. All the software and hardware used are shown in Table 2.

5. Conclusions

The abalone is accompanied by some obvious acoustic signals when eating different kinds of substances, which is firstly verified by our experiments. This paper analyzed the features of the acoustic signals, demonstrated the relationship between the hunger level and the eating rate, and revealed the mechanism of the eating-based sound production, that is, the acoustic signal is mainly produced by the process of scraping and grinding food with abalone’s radula. The results of our work can become the foundation of abalone acoustic research, providing a basis for measuring indicators, such as the eating rate, hunger, or health state of abalone from an acoustic perspective. These indicators discussed in our work can be applied as an acoustic method to estimate feeding consumption during abalone culture and be an alternative to the traditional methods in the study of feeding behavior. In order to increase the collections of acoustic information on feeding behaviors, the authors also intend to apply the passive acoustic method to verify whether abalone produces acoustic signals in other behaviors and understand the details and rules of the acoustic signals of abalone in different species, age groups, and food intake.

Author Contributions

Conceptualization, Y.Q.; data curation, H.L. and Y.Q.; formal analysis, H.L. and Y.Q.; funding acquisition, J.C., W.Y. and R.Z.; investigation, H.L.; methodology, H.L. and Y.Q.; resources, X.G. and M.Z.; software, H.L.; visualization, H.L.; writing—original draft, H.L.; writing—review and editing, J.C. and R.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Fujian Provincial S & T Project with grant number 2020N5001, the Science and Technology Projects of Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM) with grant number HRTP202231, the National Nature Science Foundation of China with grant number 62001404, and the Seed Industry Innovation and Industrialization in Fujian Province with grant number 2021FJSCZY02.

Institutional Review Board Statement

Ethical review and approval were not required for the animal study because Animal Ethics approval was not required for invertebrate gastropods. All the experimental procedures were performed according to the guideline for the care and use of laboratory animals by the local ethics committee.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data will be made available on request.

Conflicts of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. The experimental setup and abalone in the abalone acoustic experiments. (A): The data collection device is 50 cm in diameter, 25 cm in height, and there is no cover. The water circulation device is equipped with an aerator and a water pump and connected to the collection device with two water pipes; (B): experimental setup. In order to display the experimental devices, we removed the barriers, such as sound insulation cotton, in advance; (C): the picture of H. discuss hannai used in the experiments; (D): the location of the Fuda Abalone Farm, where the abalones used in the experiments came from.
Figure 1. The experimental setup and abalone in the abalone acoustic experiments. (A): The data collection device is 50 cm in diameter, 25 cm in height, and there is no cover. The water circulation device is equipped with an aerator and a water pump and connected to the collection device with two water pipes; (B): experimental setup. In order to display the experimental devices, we removed the barriers, such as sound insulation cotton, in advance; (C): the picture of H. discuss hannai used in the experiments; (D): the location of the Fuda Abalone Farm, where the abalones used in the experiments came from.
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Figure 2. The flowchart of the audio and video processing process.
Figure 2. The flowchart of the audio and video processing process.
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Figure 3. Time–frequency spectrum of an eating pulse signal. The color bar represents the signal intensity, and the arrows with labels “LF”, “HF”, “PF”, and “TD” represent low, high, and peak frequencies and the duration of pulse sequence, respectively. The color represents the strength of the signal on different frequency components, with dark blues corresponding to low signals. Conversely, brighter colors correspond to progressively stronger signals.
Figure 3. Time–frequency spectrum of an eating pulse signal. The color bar represents the signal intensity, and the arrows with labels “LF”, “HF”, “PF”, and “TD” represent low, high, and peak frequencies and the duration of pulse sequence, respectively. The color represents the strength of the signal on different frequency components, with dark blues corresponding to low signals. Conversely, brighter colors correspond to progressively stronger signals.
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Figure 4. Illustrations of abalones during eating. The light reflected by the tank is infrared light and no artificial visible light source is used during the experiment. (A) Images of abalone in Group A. The abalone is feeding on G. lemaneiformis, and none of the abalone touched the stone used to hold the food while eating; (B) images of abalone in Group B.
Figure 4. Illustrations of abalones during eating. The light reflected by the tank is infrared light and no artificial visible light source is used during the experiment. (A) Images of abalone in Group A. The abalone is feeding on G. lemaneiformis, and none of the abalone touched the stone used to hold the food while eating; (B) images of abalone in Group B.
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Figure 5. Time–frequency spectrum of eating pulse signals of abalone. (A) Group A. The abalone was fed with G. lemaneiformis once each day; (B) Group B. A small amount of sand was placed at the bottom of the tank as impurities.
Figure 5. Time–frequency spectrum of eating pulse signals of abalone. (A) Group A. The abalone was fed with G. lemaneiformis once each day; (B) Group B. A small amount of sand was placed at the bottom of the tank as impurities.
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Figure 6. Feature maps in frequency domain. (A) Feature map of the low frequency; (B) feature map of the peak frequency; (C) feature map of the high frequency; (D) feature map of the maximum energy. The box contains the interquartile range, the line in the box represents the median, and the upper and the lower horizontal lines represent the minimum and the maximum values. Rectangular points represent the mean and diamond points are the outliers (>1.5 IQR or <−1.5 IQR).
Figure 6. Feature maps in frequency domain. (A) Feature map of the low frequency; (B) feature map of the peak frequency; (C) feature map of the high frequency; (D) feature map of the maximum energy. The box contains the interquartile range, the line in the box represents the median, and the upper and the lower horizontal lines represent the minimum and the maximum values. Rectangular points represent the mean and diamond points are the outliers (>1.5 IQR or <−1.5 IQR).
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Figure 7. Feature maps in time domain. (A) Number of sub-pulses. (B) Duration of pulse-train; (C) duration of pluses with one sub-pulse.
Figure 7. Feature maps in time domain. (A) Number of sub-pulses. (B) Duration of pulse-train; (C) duration of pluses with one sub-pulse.
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Figure 8. Changes in abalone eating rate over time. It shows the exponential relationship (R2 = 0.6345) between time and the eating rate.
Figure 8. Changes in abalone eating rate over time. It shows the exponential relationship (R2 = 0.6345) between time and the eating rate.
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Figure 9. Changes in the number of acoustic signals of abalone eating over time. In this experiment, 24 eating sounds were collected, with a total of 827 signals. All signals are divided into 8 groups according to the time of appearance; every group is three hours.
Figure 9. Changes in the number of acoustic signals of abalone eating over time. In this experiment, 24 eating sounds were collected, with a total of 827 signals. All signals are divided into 8 groups according to the time of appearance; every group is three hours.
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Table
Table 1. The detailed information of the equipment used in the experiments.
Table 1. The detailed information of the equipment used in the experiments.
EquipmentParameter NameParameter Information
Song Meter SM4BAT FS Ultrasonic RecorderChannels1
Recording Format16-bit PCM WAV
Supported Sample Rates (kHz)192, 256, 384, and 500
Amplifier Gain0 or 12 dB
High Pass FilterSelectable 2-pole at 16 kHz
Anti-alias Filter2-pole at 156 kHz
Equivalent Input Noisein dBVrms (>10 kHz, 0 dB gain)
Shenyou 5 megapixel high-definition infrared cameralens size3.6 mm
video formatH.265
SNR≥48 dB
pixel5 million
Table
Table 2. Hardware and software information used for data processing.
Table 2. Hardware and software information used for data processing.
HardwareVersion
CPUAMD Ryzen 5 3500U
GPURadeon Vega 8 Graphics
RAM8G
SoftwareVersion
MatlabR2021a
OriginPro2022
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MDPI and ACS Style

Lin, H.; Qian, Y.; Chen, J.; Gao, X.; Zhang, M.; You, W.; Zhang, R. Acoustic Characterization for The Feeding Activities of Haliotis discus Hannai. Appl. Sci. 2023, 13, 5559. https://doi.org/10.3390/app13095559

AMA Style

Lin H, Qian Y, Chen J, Gao X, Zhang M, You W, Zhang R. Acoustic Characterization for The Feeding Activities of Haliotis discus Hannai. Applied Sciences. 2023; 13(9):5559. https://doi.org/10.3390/app13095559

Chicago/Turabian Style

Lin, Hongyue, Yiyang Qian, Jia Chen, Xiaolong Gao, Mo Zhang, Weiwei You, and Rongxin Zhang. 2023. "Acoustic Characterization for The Feeding Activities of Haliotis discus Hannai" Applied Sciences 13, no. 9: 5559. https://doi.org/10.3390/app13095559

APA Style

Lin, H., Qian, Y., Chen, J., Gao, X., Zhang, M., You, W., & Zhang, R. (2023). Acoustic Characterization for The Feeding Activities of Haliotis discus Hannai. Applied Sciences, 13(9), 5559. https://doi.org/10.3390/app13095559

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