- Email: [email protected]
An acoustic detector of turbot feeding activity
Aquaculture 221 (2003) 481 – 489 www.elsevier.com/locate/aqua-online
An acoustic detector of turbot feeding activity R. Mallekh a,1, J.P. Lagarde`re a,*, J.P. Eneau b, C. Cloutour c a
CNRS-IFREMER, CREMA L’Houmeau, B.P. 5, 17137 L’Houmeau, France Universite´ de Nantes, IRESTE, BP 60601, 44306 Nantes Cedex 3, France c France Turbot, BP 305, 85330 Noirmoutier, France
b
Received 21 October 2002; received in revised form 23 January 2003; accepted 23 January 2003
Abstract In fish farm conditions, visual observation of fish appetite is often impeded by high fish density and water turbidity. The present study contributes to resolution of this problem by the development of an acoustic method for direct monitoring of turbot feeding activity using sounds emitted by fish during a feeding period. The method uses an acoustic sensor (hydrophone) and a data processing system (acoustic receiver). Feeding sounds were only selected in the 6 – 8 kHz frequency band to reduce interference from background noise. Variances of these filtered signal amplitudes were then calculated by the processing device and represented as a function of time during a given feeding sequence via a software programme. Calibration tests carried out in a turbot fish farm showed a linear relationship between the acoustic signals produced by feeding fish, measured by the acoustic detector, and their demand for feed pellets (i.e. feeding events) estimated by the hand feeder. The use of this new device, as an objective means for control of food supply by fish farmers to adjust food delivery relative to appetite, is discussed. D 2003 Elsevier Science B.V. All rights reserved. Keywords: Aquaculture; Turbot; Scophthalmus maximus; Feeding sounds; Feeding device
1. Introduction Food and feeding are the motors of growth and production, their management being one of the main challenges for aquaculture development. The adjustment of food delivery
* Corresponding author. Tel.: +33-546500608; fax: +33-546500600. E-mail addresses: [email protected] (R. Mallekh), [email protected] (J.P. Lagarde`re). 1 Present address: Faculte´ des Sciences de Sfax, De´partement de Biologie, B.P. 802, 3018 Sfax, Tunisia. Fax: +216-74274437. 0044-8486/03/$ - see front matter D 2003 Elsevier Science B.V. All rights reserved. doi:10.1016/S0044-8486(03)00074-7
482
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
to match fish appetite plays a key role with important economical and ecological drawbacks. Conditions which prevail in intensive aquaculture make this problem complicated. High stocking densities and water turbidity can make it difficult to visually observe fish feeding behaviour. These difficulties can impede the adjustment of food delivery to match variation in fish demand, leading to environmental pollution when overfeeding fish and growth loss when underfeeding fish. In order to solve this problem, several direct and indirect techniques have been developed (see Alana¨ra¨ et al., 2001). Selffeeders may be used for direct adjustment (Boujard et al., 1992; Sa´nchez-Va´squez et al., 1994; Ge´lineau et al., 1998) whereas indirect methods have also been used based on hydroacoustic (Juell, 1991; Summerfelt et al., 1995) or infrared (Blyth et al., 1993, 1999) technology for control of feed waste. A previous study (Lagarde`re and Mallekh, 2000) showed that during feeding, turbot produced sounds ranging from 0 to 10 kHz. High frequency sounds (>6 kHz) were distinguishable from background noise in tanks, which led to the hypothesis that the intensity and duration of this high frequency sound emission could be related to feeding activity and consequently to fish appetite. Thus, the development of an acoustic device able to measure these signals within this characteristic frequency band could provide a new means for monitoring feeding activity in fish farms. Therefore, the principal aims of the present study are (i) the development of an acoustic device capable of converting feeding sound emissions into data, taking into account the intensity of fish feeding activity and (ii) the assessment of the relationship between the number of feed pellets delivered and the resulting turbot feeding sounds.
2. Materials and methods 2.1. Digital signal processing 2.1.1. Step 1: signal filtration Sounds were received via an hydrophone (type Benthos AQ11, sensitivity: 202.5 dB; BENTHOS, North Falmouth, MA 02556, USA) immersed in the fish tank. In order to attenuate the effect of background noise and give a high signal (feeding sound) to ambient noise ratio (ca. 15 dB) (Lagarde`re and Mallekh, 2000), a digital filter was fitted onto the frequency band, characteristic of ingestion feeding signals (6 –8 kHz). This filter was implemented by an elliptic IIR band pass filter ( 40 dB attenuation between 5 and 6 kHz and between 8 and 9 kHz) associated with a 60 Hz high-pass filter to increase the rejection of the very low frequencies. Nevertheless, background noise in the fish farm also transmitted acoustic energy in this frequency band. Consequently, two stages were required to remove ‘‘noise’’ from useful signals: (a) acoustic measurements before feeding (only background noise), (b) acoustic measurements during feeding (background noise + feeding sounds). Useful signals were obtained by subtracting (a) from (b).
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
483
2.1.2. Step 2: signal processing Data gathering and processing of feeding sounds were based on Digital Signal Processing technology (Analog Devices, ADSP-2181; Analog Devices, Norwood, MA O2062-9106, USA). We used an algorithm that calculated the useful signal variance within the 6– 9 kHz frequency band. The instantaneous values calculated represented a hypothetical measure of feeding activity. Data were stored on a microcomputer, as MS-Dos files. A 32-Mbit DSP internal memory was used to store and implement all the algorithms: the digital filter algorithm and the algorithm used to calculate feeding signal variance. All steps are given in Table 1. 2.2. Relationship between the signal variance and the number of ingested pellets 2.2.1. Experimental design This experiment was carried out in the France Turbot fish farm (Noirmoutier Island, France), between May and July 2002, where water temperature was between 15 and 21 jC. Feed composition, feeding practices and farm design were presented in Mallekh et al. (1998). The aim was to study the relationship between the variance of the feeding sounds (feeding activity) and the number of ingested feed pellets. Ten turbot groups of about 450 –550 g mean weight and 1500 kg biomass were fed different rations from 1900 to 16 000 feed pellets (i.e. from 0.034% to 0.270% body weight). Each ration was divided into shares of about 200– 300 g and hand distributed to fish groups at regular time intervals (ca. 2 – 3 s). To allow for total ingestion of dispensed feed (dispensed c ingested), confirmed by the visual observation of fish reaction to dispensed feed, distributed rations were calculated to be lower than the average ones usually consumed by turbot with respect to water temperature. For each feeding sequence, the acoustic signal within the 6– 8 kHz frequency band was measured. The measurement unit was composed of the hydrophone (data acquisition) linked to the new acoustic device (data processing) connected to a microcomputer (data storage). A cylindrical net of about 0.5 m in diameter suspended by metallic bars and stabilised by a heavy bottom was used to protect the hydrophone from accidental collision with fish. The hydrophone was maintained at about 0.2 m above the tank bottom. The impact of distributed pellets on the water surface of a fish-less tank was recorded by the detector in order to evaluate the contribution of this factor to the overall acoustic signals displayed by the device during fish feeding. To assess the potential use of the
Table 1 Acquisition, processing and representation of turbot feeding sounds
Background noise was measured before feeding fish (see text).
484
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
acoustic device for the adjustment of feed dispensation to actual appetite, a turbot group was fed in excess and acoustic measurements were performed as above. 2.2.2. Data analyses For each feeding sequence, the graph given by the detector represents the development of the acoustic signal variance as a function of time. To calculate all the signals emitted during a given feeding sequence, we measured the area (A) delimited by the graph and the x and y axes. A represents the feeding activity. Z te A¼ at ts
where ts and te are the start and the end of a feeding sequence, respectively; and at, the acoustic signal variance at time t. To evaluate the relationship between feeding activity (A) and the corresponding number of distributed food pellets (Np), a least square linear regression was fitted using Systat 7.0 for Windows. For the group fed to excess, an instantaneous signal variance graph was divided into successive sections of 4 s width each and the area of a given section was calculated. Then, the cumulative sum of successive elementary areas was plotted as a function of distributed feed. 2.3. Use of the acoustic detector The hydrophone was immersed inside the fish tank and the acoustic device was actioned just before feeding fish to measure and memorize background noise level (initialisation
Fig. 1. An example of instantaneous feeding activity graph plotted by the acoustic device during a feeding sequence for a turbot group (mean weight 0.550 kg, number 3198), which were fed a ration of 0.15% body weight (9500 feed pellets).
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
485
stage that took ca. 3 – 4 s). During fish feeding, the detector measured the new sound level (background noise + feeding sounds), then calculated the variance of the useful signal (feeding sound) after subtracting the memorized background noise level. The liquid crystal display (LCD) screen displayed the result as a whole value and as a bargraph. Nevertheless, instantaneous values showed strong fluctuations and were difficult to use by aquaculturists as an indication of fish appetite. In order to reduce these fluctuations and give more practical information, the algorithm was modified to calculate and display the moving average of 64 instantaneous values, resulting in a delay of about 1.5 s. All electronics used for filtration and processing of sounds were contained within a metallic case measuring 250 263 100 mm and weighing 4 kg. For each feeding sequence, the variance of feeding sounds as a function of time was plotted using a software programme linked to the detector via a PC connection (see example of results in Fig. 1).
3. Results 3.1. Relationship between the signal variance and the number of ingested pellets In Fig. 1, we have presented an example of graph given by the acoustic device following a supply of a ration for a fish group. In most cases, the development of feeding activity as a function of time was characterised by a high level of the acoustic signal variance (more than 60 for this example) at the beginning of feeding, followed by a progressive, but marked, or abrupt fall. Low and constant feeding activity characterised non-motivated fish groups (low appetite which was marked by the non-reaction of fish to
Fig. 2. The linear regression between the number of distributed feed pellets and the resulting feeding activity of different turbot groups of ca. 0.4 – 0.7 kg mean weight and 1500 – 2000 kg biomass each. Thin lines delimit the confidence interval calculated as mean F 2 standard error.
486
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
Fig. 3. (a) The instantaneous feeding activity graph of a turbot group fed in excess a ration of 16 000 pellets. (b) Cumulative sum of feeding activity measured from (a), during successive time intervals of 4 s each, for a turbot group fed to excess. The distributed ration was divided into 20 portions of ca. 800 pellets each and distributed at time intervals of ca. 3 s, thus the time evolution of the cumulative sum of distributed feed pellets can be calculated. Arrows indicate the start and the end of feed supply.
distributed feed pellets). Measures of feed pellet impact on the water surface of a fish-less tank, gave a signal variance ranging from 0 to 1. Consequently, the contribution of this factor to the displayed feeding activity was considered to be negligible. In Fig. 2, we have plotted the area of feeding activity time graphs (A) vs. the corresponding number of distributed feed pellets. This relationship is described by a linear regression (parameter values are given with their confidence intervals): A ¼ 11:08ðF107:6Þ þ 0:109ðF0:012ÞNp
ðr2 ¼ 0:832; n ¼ 75; P < 0:001Þ
This relationship is highly significant and the axis intercept is not significantly different from zero. The dispersion of values, especially those for the high rations, was caused by fluctuations in fish appetite (variable reaction to dispensed feed pellets). For the turbot group fed in excess (Fig. 3), the cumulative feeding activity graph can be divided into four phases: – – – –
Lag phase: representing the required period to stimulate fish feeding, ca. 4 –5 s; Marked increasing phase, ca. 20 s; Slowing phase: reduced feeding activity; Stabilisation phase: no variation of the cumulative feeding activity (plateau = satiation) beyond a ration of ca. 13 000 pellets (0.24% body weight). No acoustic response to dispensed feed pellets was detected above this level.
4. Discussion 4.1. Originality and performances of the acoustic detector Acoustic techniques are widely used in fish research and exploitation. The main application is fish stock assessment and abundance (Anonyme, 1996; Demer et al., 2000;
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
487
Carrera et al., 2001). This technique is based on the reflection by the fish body of generated sounds. The acoustic device we present differs from these fishery methods, since it is based on the passive reception, filtration and processing of a biophysical signal. The acoustic detector should be compared to interactive feeders, which allow the estimation of actual fish appetite. Nevertheless, the proposed acoustic system differs from self feeders (Alana¨ra¨ et al., 2001; Jobling et al., 2001), since no contact is required between fish and sensor, and from hydroacoustic detection of non-consumed pellets (Juell, 1991; Summerfelt et al., 1995) since it uses sounds generated by feeding fish (Lagarde`re and Mallekh, 2000). The comparison between the number of dispensed (and supposedly consumed) feed pellets and the integration of signal variance during a feeding sequence demonstrates a linear relationship, i.e. the signal variances are directly proportional to the number of feed pellets ingested by fish with insignificant alteration by the noise generated by pellet impact on the water surface. This result demonstrates the reliability of the equivalence between signal variance and feeding activity. Graphs generated by the device represent the relationship between the number of distributed food pellets and the number of feeding events and not the number of feeding fish, though this difference is not important for the aquaculturist who is primarily interested in the global response of fish to distributed feed pellets. For a given ration, variability of detected feeding activity seems to correspond to the considerable short-term fluctuation in food intake observed not only for turbot (Mallekh et al., 1998), but also for other species, such as Atlantic salmon (Kadri et al., 1991; Juell, 1995; Blyth et al., 1999) and rainbow trout (Alana¨ra¨, 1992). 4.2. Applications and limitations The quality of the acquisition and the transfer of signals from a fish tank to the processing unit plays an important role in the efficiency of this new device. For this reason, the hydrophone should be in a good state and protected from any contact with fish, since this can generate false signals. Moreover, in some fish farms, water is highly oxygenated. High oxygen concentrations generate micro-bulls which attenuate acoustic transmissions and affect the system’s efficiency. Since the processed signal is a ratio between the feeding sounds mixed to background noise during feeding and the background noise measured before, the extraction of feeding sounds from background noise is easier when the latter is lower. Therefore, the use of the acoustic device in external ponds and rearing cages, where sources of noise are generally lower, would be highly efficient. In addition, this method could be used at different water depths and consequently it would seem suitable for the majority of farming systems (earthen ponds, concrete tanks, cages, etc.). 4.3. Future developments The use of the acoustic device for the control of feed delivery requires the determination of a limit (or threshold) level below which we consider that fish were no longer interested in food. For the turbot group fed to excess (Fig. 3), the increase of cumulative
488
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
feeding activity at the beginning is high, then it falls progressively until becoming insignificant (plateau) i.e. no fish reaction to distributed feed = actual maximum feed intake. Therefore, food supply should be stopped at latest upon reaching this plateau, i.e. when dA/dt = 0. Nevertheless, for good management of fish farming, an optimal ration which provides a compromise between feed conversion and growth performances, is below the maximum (generally about 80%; Muller-Feuga, 1999; i.e. ca. 2.8 kg feed in the case of Fig. 3). The present version of the acoustic device calculates the signal variance and gives a succession of values. In the next version, it would be interesting for the acoustic device to provide a measure of time cumulative feeding activity which could be used as a means for controlling feed delivery in fish farms by indicating the moment when feed supply should be stopped to avoid wastage (at least when cumulative feeding activity reaches a plateau). The authors would like to thank Dr. Sunil Kadri for his relevant revision. This work was financially supported by the ‘‘Cellule de Valorisation de la Recherche du CNRS’’ and the ‘‘Conseil Re´gional de Poitou-Charentes’’.
References Alana¨ra¨, A., 1992. The effect of time-restricted demand feeding on feeding activity, growth and feed conversion in rainbow trout (Oncorhynchus mykiss). Aquaculture 108, 357 – 368. Alana¨ra¨, A., Kadri, S., Paspatis, M., 2001. Feeding management. In: Houlihan, D., Boujard, T., Jobling, M. (Eds.), Food Intake in Fish. Blackwell Science, London, pp. 332 – 353. Anonyme, 1996. Application de l’acoustique au domaine vivant aquatique. Oce´anis 22, 1 – 32. Blyth, P.J., Purser, G.J., Russell, J.F., 1993. Detection of feeding rhythms in sea-caged Atlantic salmon using new feeder technology. In: Reinersten, H., Dahle, L.A., Jørgensen, L., Tvinnereim, K. (Eds.), Fish Farming Technology. Balkema, Rotterdam, pp. 209 – 215. Blyth, P.J., Kadri, S., Valdimarsson, S.K., Mitchell, D.F., Purser, G.J., 1999. Diurnal and seasonal variation in feeding patterns of Atlantic salmon, Salmo salar L., in sea cages. Aquacult. Res. 30, 539 – 544. Boujard, T., Dugy, X., Genner, D., Gosset, C., Grig, G., 1992. Description of a modular, low cost, eater meter for the study of feeding behavior and food-preferences in fish. Physiol. Behav. 52, 1101 – 1106. Carrera, P., Meixide, M., Porteiro, C., Miquel, J., 2001. Study of the blue whiting movements around the Bay of Biscay using acoustic methods. Fish. Res. 50, 151 – 161. Demer, D., Barange, M., Boyd, A.J., 2000. Measurements of three-dimensional fish school velocities with an acoustic Doppler current profiler. Fish. Res. 47, 201 – 214. Ge´lineau, A., Corraze, G., Boujard, T., 1998. Effects of restricted ration, time restricted access and reward level on volontary food intake, growth, and growth heterogeneity of rainbow trout (Oncorhynchus mykiss) fed on demand with self-feeders. Aquaculture 167, 247 – 258. Jobling, M., Cove`s, D., Damsgard, B., Kristiansen, H.R., Koskela, J., Petursdottir, T.E., Kadri, S., Gudmundsson, O., 2001. Techniques for measuring feed intake. In: Houlihan, D., Boujard, T., Jobling, M. (Eds.), Food Intake in Fish. Blackwell Science, London, pp. 49 – 87. Juell, J.-E., 1991. Hydroacoustic detection of food waste—a method to estimate maximum food intake of fish population in sea cages. Aquacult. Eng. 10, 207 – 217. Juell, J.-E., 1995. The behaviour of Atlantic salmon in relation to efficient cage-rearing. Rev. Fish Biol. Fish. 5, 320 – 335. Kadri, S., Metcalfe, N.B., Huntingford, F.A., Thorpe, J.E., 1991. Daily feeding rhythms in Atlantic salmon in sea cages. Aquaculture 92, 219 – 224. Lagarde`re, J.P., Mallekh, R., 2000. Feeding sounds of the turbot (Scophthalmus maximus) and their potential use in the control of the feed supply in aquaculture: I. Spectrum analysis of the feeding sounds. Aquaculture 189, 251 – 258.
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
489
Mallekh, R., Lagarde`re, J.P., Be´gout Anras, M.L., Lafaye, J.Y., 1998. Variability in appetite of turbot, Scophthalmus maximus under intensive rearing conditions: the role of environmental factors. Aquaculture 165, 123 – 138. Muller-Feuga, A., 1999. Growth as a function of rationing: a model applicable to fish and microalgae. J. Exp. Mar. Biol. Ecol. 236, 1 – 13. Sa´nchez-Va´squez, F.J., Martı´nez, M., Zamora, M., Madrid, J.A., 1994. Design and performance of an accurate demand feeder for the study of feeding behaviour in sea bass, Dicentrarchus labrax L. Physiol. Behav. 58, 789 – 794. Summerfelt, S.T., Holland, K.H., Hankins, J.A., Durant, M.D., 1995. A hydroacoustic waste feed controller for tank systems. Water Sci. Technol. 31, 123 – 129.
An acoustic detector of turbot feeding activity R. Mallekh a,1, J.P. Lagarde`re a,*, J.P. Eneau b, C. Cloutour c a
CNRS-IFREMER, CREMA L’Houmeau, B.P. 5, 17137 L’Houmeau, France Universite´ de Nantes, IRESTE, BP 60601, 44306 Nantes Cedex 3, France c France Turbot, BP 305, 85330 Noirmoutier, France
b
Received 21 October 2002; received in revised form 23 January 2003; accepted 23 January 2003
Abstract In fish farm conditions, visual observation of fish appetite is often impeded by high fish density and water turbidity. The present study contributes to resolution of this problem by the development of an acoustic method for direct monitoring of turbot feeding activity using sounds emitted by fish during a feeding period. The method uses an acoustic sensor (hydrophone) and a data processing system (acoustic receiver). Feeding sounds were only selected in the 6 – 8 kHz frequency band to reduce interference from background noise. Variances of these filtered signal amplitudes were then calculated by the processing device and represented as a function of time during a given feeding sequence via a software programme. Calibration tests carried out in a turbot fish farm showed a linear relationship between the acoustic signals produced by feeding fish, measured by the acoustic detector, and their demand for feed pellets (i.e. feeding events) estimated by the hand feeder. The use of this new device, as an objective means for control of food supply by fish farmers to adjust food delivery relative to appetite, is discussed. D 2003 Elsevier Science B.V. All rights reserved. Keywords: Aquaculture; Turbot; Scophthalmus maximus; Feeding sounds; Feeding device
1. Introduction Food and feeding are the motors of growth and production, their management being one of the main challenges for aquaculture development. The adjustment of food delivery
* Corresponding author. Tel.: +33-546500608; fax: +33-546500600. E-mail addresses: [email protected] (R. Mallekh), [email protected] (J.P. Lagarde`re). 1 Present address: Faculte´ des Sciences de Sfax, De´partement de Biologie, B.P. 802, 3018 Sfax, Tunisia. Fax: +216-74274437. 0044-8486/03/$ - see front matter D 2003 Elsevier Science B.V. All rights reserved. doi:10.1016/S0044-8486(03)00074-7
482
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
to match fish appetite plays a key role with important economical and ecological drawbacks. Conditions which prevail in intensive aquaculture make this problem complicated. High stocking densities and water turbidity can make it difficult to visually observe fish feeding behaviour. These difficulties can impede the adjustment of food delivery to match variation in fish demand, leading to environmental pollution when overfeeding fish and growth loss when underfeeding fish. In order to solve this problem, several direct and indirect techniques have been developed (see Alana¨ra¨ et al., 2001). Selffeeders may be used for direct adjustment (Boujard et al., 1992; Sa´nchez-Va´squez et al., 1994; Ge´lineau et al., 1998) whereas indirect methods have also been used based on hydroacoustic (Juell, 1991; Summerfelt et al., 1995) or infrared (Blyth et al., 1993, 1999) technology for control of feed waste. A previous study (Lagarde`re and Mallekh, 2000) showed that during feeding, turbot produced sounds ranging from 0 to 10 kHz. High frequency sounds (>6 kHz) were distinguishable from background noise in tanks, which led to the hypothesis that the intensity and duration of this high frequency sound emission could be related to feeding activity and consequently to fish appetite. Thus, the development of an acoustic device able to measure these signals within this characteristic frequency band could provide a new means for monitoring feeding activity in fish farms. Therefore, the principal aims of the present study are (i) the development of an acoustic device capable of converting feeding sound emissions into data, taking into account the intensity of fish feeding activity and (ii) the assessment of the relationship between the number of feed pellets delivered and the resulting turbot feeding sounds.
2. Materials and methods 2.1. Digital signal processing 2.1.1. Step 1: signal filtration Sounds were received via an hydrophone (type Benthos AQ11, sensitivity: 202.5 dB; BENTHOS, North Falmouth, MA 02556, USA) immersed in the fish tank. In order to attenuate the effect of background noise and give a high signal (feeding sound) to ambient noise ratio (ca. 15 dB) (Lagarde`re and Mallekh, 2000), a digital filter was fitted onto the frequency band, characteristic of ingestion feeding signals (6 –8 kHz). This filter was implemented by an elliptic IIR band pass filter ( 40 dB attenuation between 5 and 6 kHz and between 8 and 9 kHz) associated with a 60 Hz high-pass filter to increase the rejection of the very low frequencies. Nevertheless, background noise in the fish farm also transmitted acoustic energy in this frequency band. Consequently, two stages were required to remove ‘‘noise’’ from useful signals: (a) acoustic measurements before feeding (only background noise), (b) acoustic measurements during feeding (background noise + feeding sounds). Useful signals were obtained by subtracting (a) from (b).
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
483
2.1.2. Step 2: signal processing Data gathering and processing of feeding sounds were based on Digital Signal Processing technology (Analog Devices, ADSP-2181; Analog Devices, Norwood, MA O2062-9106, USA). We used an algorithm that calculated the useful signal variance within the 6– 9 kHz frequency band. The instantaneous values calculated represented a hypothetical measure of feeding activity. Data were stored on a microcomputer, as MS-Dos files. A 32-Mbit DSP internal memory was used to store and implement all the algorithms: the digital filter algorithm and the algorithm used to calculate feeding signal variance. All steps are given in Table 1. 2.2. Relationship between the signal variance and the number of ingested pellets 2.2.1. Experimental design This experiment was carried out in the France Turbot fish farm (Noirmoutier Island, France), between May and July 2002, where water temperature was between 15 and 21 jC. Feed composition, feeding practices and farm design were presented in Mallekh et al. (1998). The aim was to study the relationship between the variance of the feeding sounds (feeding activity) and the number of ingested feed pellets. Ten turbot groups of about 450 –550 g mean weight and 1500 kg biomass were fed different rations from 1900 to 16 000 feed pellets (i.e. from 0.034% to 0.270% body weight). Each ration was divided into shares of about 200– 300 g and hand distributed to fish groups at regular time intervals (ca. 2 – 3 s). To allow for total ingestion of dispensed feed (dispensed c ingested), confirmed by the visual observation of fish reaction to dispensed feed, distributed rations were calculated to be lower than the average ones usually consumed by turbot with respect to water temperature. For each feeding sequence, the acoustic signal within the 6– 8 kHz frequency band was measured. The measurement unit was composed of the hydrophone (data acquisition) linked to the new acoustic device (data processing) connected to a microcomputer (data storage). A cylindrical net of about 0.5 m in diameter suspended by metallic bars and stabilised by a heavy bottom was used to protect the hydrophone from accidental collision with fish. The hydrophone was maintained at about 0.2 m above the tank bottom. The impact of distributed pellets on the water surface of a fish-less tank was recorded by the detector in order to evaluate the contribution of this factor to the overall acoustic signals displayed by the device during fish feeding. To assess the potential use of the
Table 1 Acquisition, processing and representation of turbot feeding sounds
Background noise was measured before feeding fish (see text).
484
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
acoustic device for the adjustment of feed dispensation to actual appetite, a turbot group was fed in excess and acoustic measurements were performed as above. 2.2.2. Data analyses For each feeding sequence, the graph given by the detector represents the development of the acoustic signal variance as a function of time. To calculate all the signals emitted during a given feeding sequence, we measured the area (A) delimited by the graph and the x and y axes. A represents the feeding activity. Z te A¼ at ts
where ts and te are the start and the end of a feeding sequence, respectively; and at, the acoustic signal variance at time t. To evaluate the relationship between feeding activity (A) and the corresponding number of distributed food pellets (Np), a least square linear regression was fitted using Systat 7.0 for Windows. For the group fed to excess, an instantaneous signal variance graph was divided into successive sections of 4 s width each and the area of a given section was calculated. Then, the cumulative sum of successive elementary areas was plotted as a function of distributed feed. 2.3. Use of the acoustic detector The hydrophone was immersed inside the fish tank and the acoustic device was actioned just before feeding fish to measure and memorize background noise level (initialisation
Fig. 1. An example of instantaneous feeding activity graph plotted by the acoustic device during a feeding sequence for a turbot group (mean weight 0.550 kg, number 3198), which were fed a ration of 0.15% body weight (9500 feed pellets).
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
485
stage that took ca. 3 – 4 s). During fish feeding, the detector measured the new sound level (background noise + feeding sounds), then calculated the variance of the useful signal (feeding sound) after subtracting the memorized background noise level. The liquid crystal display (LCD) screen displayed the result as a whole value and as a bargraph. Nevertheless, instantaneous values showed strong fluctuations and were difficult to use by aquaculturists as an indication of fish appetite. In order to reduce these fluctuations and give more practical information, the algorithm was modified to calculate and display the moving average of 64 instantaneous values, resulting in a delay of about 1.5 s. All electronics used for filtration and processing of sounds were contained within a metallic case measuring 250 263 100 mm and weighing 4 kg. For each feeding sequence, the variance of feeding sounds as a function of time was plotted using a software programme linked to the detector via a PC connection (see example of results in Fig. 1).
3. Results 3.1. Relationship between the signal variance and the number of ingested pellets In Fig. 1, we have presented an example of graph given by the acoustic device following a supply of a ration for a fish group. In most cases, the development of feeding activity as a function of time was characterised by a high level of the acoustic signal variance (more than 60 for this example) at the beginning of feeding, followed by a progressive, but marked, or abrupt fall. Low and constant feeding activity characterised non-motivated fish groups (low appetite which was marked by the non-reaction of fish to
Fig. 2. The linear regression between the number of distributed feed pellets and the resulting feeding activity of different turbot groups of ca. 0.4 – 0.7 kg mean weight and 1500 – 2000 kg biomass each. Thin lines delimit the confidence interval calculated as mean F 2 standard error.
486
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
Fig. 3. (a) The instantaneous feeding activity graph of a turbot group fed in excess a ration of 16 000 pellets. (b) Cumulative sum of feeding activity measured from (a), during successive time intervals of 4 s each, for a turbot group fed to excess. The distributed ration was divided into 20 portions of ca. 800 pellets each and distributed at time intervals of ca. 3 s, thus the time evolution of the cumulative sum of distributed feed pellets can be calculated. Arrows indicate the start and the end of feed supply.
distributed feed pellets). Measures of feed pellet impact on the water surface of a fish-less tank, gave a signal variance ranging from 0 to 1. Consequently, the contribution of this factor to the displayed feeding activity was considered to be negligible. In Fig. 2, we have plotted the area of feeding activity time graphs (A) vs. the corresponding number of distributed feed pellets. This relationship is described by a linear regression (parameter values are given with their confidence intervals): A ¼ 11:08ðF107:6Þ þ 0:109ðF0:012ÞNp
ðr2 ¼ 0:832; n ¼ 75; P < 0:001Þ
This relationship is highly significant and the axis intercept is not significantly different from zero. The dispersion of values, especially those for the high rations, was caused by fluctuations in fish appetite (variable reaction to dispensed feed pellets). For the turbot group fed in excess (Fig. 3), the cumulative feeding activity graph can be divided into four phases: – – – –
Lag phase: representing the required period to stimulate fish feeding, ca. 4 –5 s; Marked increasing phase, ca. 20 s; Slowing phase: reduced feeding activity; Stabilisation phase: no variation of the cumulative feeding activity (plateau = satiation) beyond a ration of ca. 13 000 pellets (0.24% body weight). No acoustic response to dispensed feed pellets was detected above this level.
4. Discussion 4.1. Originality and performances of the acoustic detector Acoustic techniques are widely used in fish research and exploitation. The main application is fish stock assessment and abundance (Anonyme, 1996; Demer et al., 2000;
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
487
Carrera et al., 2001). This technique is based on the reflection by the fish body of generated sounds. The acoustic device we present differs from these fishery methods, since it is based on the passive reception, filtration and processing of a biophysical signal. The acoustic detector should be compared to interactive feeders, which allow the estimation of actual fish appetite. Nevertheless, the proposed acoustic system differs from self feeders (Alana¨ra¨ et al., 2001; Jobling et al., 2001), since no contact is required between fish and sensor, and from hydroacoustic detection of non-consumed pellets (Juell, 1991; Summerfelt et al., 1995) since it uses sounds generated by feeding fish (Lagarde`re and Mallekh, 2000). The comparison between the number of dispensed (and supposedly consumed) feed pellets and the integration of signal variance during a feeding sequence demonstrates a linear relationship, i.e. the signal variances are directly proportional to the number of feed pellets ingested by fish with insignificant alteration by the noise generated by pellet impact on the water surface. This result demonstrates the reliability of the equivalence between signal variance and feeding activity. Graphs generated by the device represent the relationship between the number of distributed food pellets and the number of feeding events and not the number of feeding fish, though this difference is not important for the aquaculturist who is primarily interested in the global response of fish to distributed feed pellets. For a given ration, variability of detected feeding activity seems to correspond to the considerable short-term fluctuation in food intake observed not only for turbot (Mallekh et al., 1998), but also for other species, such as Atlantic salmon (Kadri et al., 1991; Juell, 1995; Blyth et al., 1999) and rainbow trout (Alana¨ra¨, 1992). 4.2. Applications and limitations The quality of the acquisition and the transfer of signals from a fish tank to the processing unit plays an important role in the efficiency of this new device. For this reason, the hydrophone should be in a good state and protected from any contact with fish, since this can generate false signals. Moreover, in some fish farms, water is highly oxygenated. High oxygen concentrations generate micro-bulls which attenuate acoustic transmissions and affect the system’s efficiency. Since the processed signal is a ratio between the feeding sounds mixed to background noise during feeding and the background noise measured before, the extraction of feeding sounds from background noise is easier when the latter is lower. Therefore, the use of the acoustic device in external ponds and rearing cages, where sources of noise are generally lower, would be highly efficient. In addition, this method could be used at different water depths and consequently it would seem suitable for the majority of farming systems (earthen ponds, concrete tanks, cages, etc.). 4.3. Future developments The use of the acoustic device for the control of feed delivery requires the determination of a limit (or threshold) level below which we consider that fish were no longer interested in food. For the turbot group fed to excess (Fig. 3), the increase of cumulative
488
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
feeding activity at the beginning is high, then it falls progressively until becoming insignificant (plateau) i.e. no fish reaction to distributed feed = actual maximum feed intake. Therefore, food supply should be stopped at latest upon reaching this plateau, i.e. when dA/dt = 0. Nevertheless, for good management of fish farming, an optimal ration which provides a compromise between feed conversion and growth performances, is below the maximum (generally about 80%; Muller-Feuga, 1999; i.e. ca. 2.8 kg feed in the case of Fig. 3). The present version of the acoustic device calculates the signal variance and gives a succession of values. In the next version, it would be interesting for the acoustic device to provide a measure of time cumulative feeding activity which could be used as a means for controlling feed delivery in fish farms by indicating the moment when feed supply should be stopped to avoid wastage (at least when cumulative feeding activity reaches a plateau). The authors would like to thank Dr. Sunil Kadri for his relevant revision. This work was financially supported by the ‘‘Cellule de Valorisation de la Recherche du CNRS’’ and the ‘‘Conseil Re´gional de Poitou-Charentes’’.
References Alana¨ra¨, A., 1992. The effect of time-restricted demand feeding on feeding activity, growth and feed conversion in rainbow trout (Oncorhynchus mykiss). Aquaculture 108, 357 – 368. Alana¨ra¨, A., Kadri, S., Paspatis, M., 2001. Feeding management. In: Houlihan, D., Boujard, T., Jobling, M. (Eds.), Food Intake in Fish. Blackwell Science, London, pp. 332 – 353. Anonyme, 1996. Application de l’acoustique au domaine vivant aquatique. Oce´anis 22, 1 – 32. Blyth, P.J., Purser, G.J., Russell, J.F., 1993. Detection of feeding rhythms in sea-caged Atlantic salmon using new feeder technology. In: Reinersten, H., Dahle, L.A., Jørgensen, L., Tvinnereim, K. (Eds.), Fish Farming Technology. Balkema, Rotterdam, pp. 209 – 215. Blyth, P.J., Kadri, S., Valdimarsson, S.K., Mitchell, D.F., Purser, G.J., 1999. Diurnal and seasonal variation in feeding patterns of Atlantic salmon, Salmo salar L., in sea cages. Aquacult. Res. 30, 539 – 544. Boujard, T., Dugy, X., Genner, D., Gosset, C., Grig, G., 1992. Description of a modular, low cost, eater meter for the study of feeding behavior and food-preferences in fish. Physiol. Behav. 52, 1101 – 1106. Carrera, P., Meixide, M., Porteiro, C., Miquel, J., 2001. Study of the blue whiting movements around the Bay of Biscay using acoustic methods. Fish. Res. 50, 151 – 161. Demer, D., Barange, M., Boyd, A.J., 2000. Measurements of three-dimensional fish school velocities with an acoustic Doppler current profiler. Fish. Res. 47, 201 – 214. Ge´lineau, A., Corraze, G., Boujard, T., 1998. Effects of restricted ration, time restricted access and reward level on volontary food intake, growth, and growth heterogeneity of rainbow trout (Oncorhynchus mykiss) fed on demand with self-feeders. Aquaculture 167, 247 – 258. Jobling, M., Cove`s, D., Damsgard, B., Kristiansen, H.R., Koskela, J., Petursdottir, T.E., Kadri, S., Gudmundsson, O., 2001. Techniques for measuring feed intake. In: Houlihan, D., Boujard, T., Jobling, M. (Eds.), Food Intake in Fish. Blackwell Science, London, pp. 49 – 87. Juell, J.-E., 1991. Hydroacoustic detection of food waste—a method to estimate maximum food intake of fish population in sea cages. Aquacult. Eng. 10, 207 – 217. Juell, J.-E., 1995. The behaviour of Atlantic salmon in relation to efficient cage-rearing. Rev. Fish Biol. Fish. 5, 320 – 335. Kadri, S., Metcalfe, N.B., Huntingford, F.A., Thorpe, J.E., 1991. Daily feeding rhythms in Atlantic salmon in sea cages. Aquaculture 92, 219 – 224. Lagarde`re, J.P., Mallekh, R., 2000. Feeding sounds of the turbot (Scophthalmus maximus) and their potential use in the control of the feed supply in aquaculture: I. Spectrum analysis of the feeding sounds. Aquaculture 189, 251 – 258.
R. Mallekh et al. / Aquaculture 221 (2003) 481–489
489
Mallekh, R., Lagarde`re, J.P., Be´gout Anras, M.L., Lafaye, J.Y., 1998. Variability in appetite of turbot, Scophthalmus maximus under intensive rearing conditions: the role of environmental factors. Aquaculture 165, 123 – 138. Muller-Feuga, A., 1999. Growth as a function of rationing: a model applicable to fish and microalgae. J. Exp. Mar. Biol. Ecol. 236, 1 – 13. Sa´nchez-Va´squez, F.J., Martı´nez, M., Zamora, M., Madrid, J.A., 1994. Design and performance of an accurate demand feeder for the study of feeding behaviour in sea bass, Dicentrarchus labrax L. Physiol. Behav. 58, 789 – 794. Summerfelt, S.T., Holland, K.H., Hankins, J.A., Durant, M.D., 1995. A hydroacoustic waste feed controller for tank systems. Water Sci. Technol. 31, 123 – 129.