ORIGINAL RESEARCH published: 29 May 2019 doi: 10.3389/fphys.2019.00667 Ultra-Low Power Sensor Devices for Monitoring Physical Activity and Respiratory Frequency in Farmed Fish Juan Antonio Martos-Sitcha 1,2 , Javier Sosa 3 , Dailos Ramos-Valido 3 , Francisco Javier Bravo 4 , Cristina Carmona-Duarte 5 , Henrique Leonel Gomes 6 , Josep Àlvar Calduch-Giner 1 , Enric Cabruja 4 , Aurelio Vega 3 , Miguel Ángel Ferrer 5 , Manuel Lozano 4 , Juan Antonio Montiel-Nelson 3 , Juan Manuel Afonso 7 and Jaume Pérez-Sánchez 1* 1 Nutrigenomics and Fish Growth Endocrinology Group, Institute of Aquaculture Torre de la Sal, Consejo Superior de Investigaciones Científicas (CSIC), Castellón, Spain, 2 Department of Biology, Faculty of Marine and Environmental Sciences, Instituto Universitario de Investigación Marina (INMAR), Campus de Excelencia Internacional del Mar (CEI-MAR), University of Cádiz, Cádiz, Spain, 3 Institute for Applied Microelectronics (IUMA), University of Las Palmas de Gran Canaria, Las Palmas, Spain, 4 Institute of Microelectronics of Barcelona (IMB-CNM), Consejo Superior de Investigaciones Científicas Edited by: (CSIC), Barcelona, Spain, 5 Technological Centre for Innovation in Communications (iDeTIC), University of Las Palmas Francesca Carella, de Gran Canaria, Las Palmas, Spain, 6 Centre for Marine Sciences (CCMAR), Universidade do Algarve, Faro, Portugal, University of Naples Federico II, Italy 7 Aquaculture Research Group, Institute of Sustainable Aquaculture and Marine Ecosystems (IU-ECOAQUA), University Reviewed by: of Las Palmas de Gran Canaria, Las Palmas, Spain Ione Hunt Von Herbing, University of North Texas, United States Integration of technological solutions aims to improve accuracy, precision and Claudio Agnisola, repeatability in farming operations, and biosensor devices are increasingly used for University of Naples Federico II, Italy understanding basic biology during livestock production. The aim of this study was to *Correspondence: Jaume Pérez-Sánchez design and validate a miniaturized tri-axial accelerometer for non-invasive monitoring jaime.perez.sanchez@csic.es; of farmed fish with re-programmable schedule protocols. The current device (AE- jperez@iats.csic.es FishBIT v.1s) is a small (14 mm × 7 mm × 7 mm), stand-alone system with a Specialty section: total mass of 600 mg, which allows monitoring animals from 30 to 35 g onwards. This article was submitted to The device was attached to the operculum of gilthead sea bream (Sparus aurata) Aquatic Physiology, a section of the journal and European sea bass (Dicentrarchus labrax) juveniles for monitoring their physical Frontiers in Physiology activity by measurements of movement accelerations in x- and y-axes, while records Received: 18 December 2018 of operculum beats (z-axis) served as a measurement of respiratory frequency. Data Accepted: 09 May 2019 post-processing of exercised fish in swimming test chambers revealed an exponential Published: 29 May 2019 increase of fish accelerations with the increase of fish speed from 1 body-length to Citation: Martos-Sitcha JA, Sosa J, 4 body-lengths per second, while a close relationship between oxygen consumption Ramos-Valido D, Bravo FJ, (MO2 ) and opercular frequency was consistently found. Preliminary tests in free- Carmona-Duarte C, Gomes HL, Calduch-Giner JÀ, Cabruja E, Vega A, swimming fish kept in rearing tanks also showed that device data recording was able to Ferrer MÁ, Lozano M, detect changes in daily fish activity. The usefulness of low computational load for data Montiel-Nelson JA, Afonso JM and pre-processing with on-board algorithms was verified from low to submaximal exercise, Pérez-Sánchez J (2019) Ultra-Low Power Sensor Devices for Monitoring increasing this procedure the autonomy of the system up to 6 h of data recording Physical Activity and Respiratory with different programmable schedules. Visual observations regarding tissue damage, Frequency in Farmed Fish. Front. Physiol. 10:667. feeding behavior and circulating levels of stress markers (cortisol, glucose, and lactate) doi: 10.3389/fphys.2019.00667 did not reveal at short term a negative impact of device tagging. Reduced plasma levels Frontiers in Physiology | www.frontiersin.org 1 May 2019 | Volume 10 | Article 667 Martos-Sitcha et al. Sensor for Individual Fish Monitoring of triglycerides revealed a transient inhibition of feed intake in small fish (sea bream 50– 90 g, sea bass 100–200 g), but this disturbance was not detected in larger fish. All this considered together is the proof of concept that miniaturized devices are suitable for non-invasive and reliable metabolic phenotyping of farmed fish to improve their overall performance and welfare. Further work is underway for improving the attachment procedure and the full device packaging. Keywords: aquaculture, sensor, swimming tests, fish welfare, physical activity, respiratory frequency, oxygen consumption INTRODUCTION z-directions. Currently, the smallest market size for these tags is 7 mm diameter and 20 mm length with a weight of 2.6 g in air and Biosensor technology is increasingly used for a non-invasive a typical battery life of 1–3 months, depending on measurement measurement during farming and experimental studies of a range periods and transmission intervals. However, as pointed out of variables that are directly or indirectly relevant for animal by Kolarevic et al. (2016), the interference between transmitted health and welfare (Ivanov et al., 2015; Neethirajan et al., 2017). signals limits the use of a large number of acceleration tags in Thus, cameras, sonars, acoustic telemetry and environmental a single rearing unit or in two neighboring units. Otherwise, biosensors of chemical and biological safety risk factors are in the aquatic environment, the use of low radiofrequency currently used to improve feed conversion, product quality and transmission is limited to 1–2 m of maximum communication disease prevention, reducing at the same time the environmental range without repeaters (Palmeiro et al., 2011). Thus, with impact of farming operations (Saberioon et al., 2017; Føre the double aim to produce small sensors and to combine et al., 2018; Enviguard EU project1 ). Such technological solutions measurements of physical activity and energy demand, the design contribute to the estimation of fish biomass for ration size and production of ultra-low power stand-alone devices using assignment and medicinal dosages, or to the design of automated available technology was conducted within the AQUAEXCEL2020 feeding strategies based on fish behavior in order to avoid EU project. The resulting device (AE-FishBIT) was designed to unnecessary feed waste. Furthermore, the concept of sentinel be implanted on fish operculum for measurements of physical animals fitted with biosensors, initially developed for the dairy activity and respiratory frequency. To the best of our knowledge, industry (Simbeye et al., 2014), has been extended to the culture there is not in the market any device designed to provide of oysters (Andrewartha et al., 2016) and fish (Staaks et al., 2010) simultaneously these two types of measurements. The present with abundant literature on measurements of body temperature, work was envisaged as the proof of concept that data acquired animal position and depth in both wild and farmed fish (e.g., with the constructed prototype (AE-FishBIT v.1s) can be used Clark et al., 2008; Payne et al., 2014; Metcalfe et al., 2016, in a reliable manner at different tank scales for the assessment among others). This approach is essential for the optimization of of physical activity and energy expenditure status of farmed aquaculture operations, and the assessment of welfare and stress fish. This functional validation of the device has been conducted in farmed fish becomes a major challenge for a more efficient and in European sea bass and gilthead sea bream (Sparus aurata) ethical animal production. as the two most significant farmed fish of the Mediterranean With the advent of the MEMS (MicroElectroMechanical aquaculture (FAO, 2018). System) technology, high-precision and low-cost accelerometers are available as components of different electronic gadgets of physical activity (activity trackers, fitness band and heart rate monitors, sport-watches, smart pedometers and wellness MATERIALS AND METHODS monitors, among others). Acceleration data-loggers alone or in combination with pressure, temperature and heart- Hardware Architecture rate biosensors have also been used for tracing movement The proposed device is a programmable and reconfigurable and estimating activity-specific energy expenditure or feeding tri-axial accelerometer for measuring accelerations in x-, y-, behavior in a number of fish species, including juvenile and z-axes in the range of ±8 g and sampling frequencies hammerhead sharks (Sphyrna lewini, Gleiss et al., 2010), sockeye up to 800 Hz. The basic components disposed on a 0.8 mm salmon (Oncorhynchus nerka, Clark et al., 2010), European 4-layer printed circuit board (pcb) are: (i) one accelerometer sea bass (Dicentrarchus labrax, Wright et al., 2014), Atlantic (MMA8451Q; NXP Semiconductors Research, Eindhoven, cod (Gadus morhua, Claireaux et al., 1995), Atlantic salmon Netherlands), (ii) one high performance Li-ion battery (Salmo salar, Kolarevic et al., 2016) and red-spotted groupers (UMAC040130A003TA01; muRata Electronics, Kyoto, Japan) (Epinephelus akaara, Horie et al., 2017). These sensors operate of low charge time (120 s), (iii) one microprocessor (KL17; as acoustic transmitter tags that contain a tri-axial accelerometer, NXP Semiconductors Research) with 256 kb flash memory and which registers gravity forces and acceleration in the x-, y-, and 32 kb RAM memory and (iv) one RFID tagging device (nano- transponder ID-100A-1.25; TROVAN, Madrid, Spain) for rapid 1 www.enviguard.net identification. System integration includes water-proof packaging Frontiers in Physiology | www.frontiersin.org 2 May 2019 | Volume 10 | Article 667 Martos-Sitcha et al. Sensor for Individual Fish Monitoring FIGURE 2 | Device attachment to sea bream operculum. (A) RapID tag is attached to fish operculum with the tag piercing tool. The external side of the tag (B) allows fixation with adhesive of a 3D-printed pocket. (C) Internal side of attached sea bream operculum. (D) Sea bream with an attachment with the RapiID tag and 3D pocket procedure. FIGURE 1 | (A) Electrical probing of pcb-mounted devices. (B) Photograph of The recorded z-axis accelerations generated positive and AE-FishBIT v.1s before encapsulation. (C) Encapsulated AE-FishBIT v.1s in negative signals, related to operculum opening and closing, underwater operation. Flashing led light indicates the end of data acquisition respectively. Other movements superimposed to this z-axis signal program for user reference. were angular accelerations that informed of fish trajectory or side head movement, though the dominant periodic component was always operculum movement. To calculate the respiratory (tested up to 6 bars of pressure in air and seawater environments) frequency, the z-axis signal of the accelerometer was band pass with isolated connector pins. The complete package size of the filtered between 0.5 and 8 Hz to reduce the noise (measurements AE-FishBIT v.1s measures 14 mm × 7.2 mm × 7.0 mm with a were expected below 5 Hz), highlighting the periodic properties total mass of 600 mg in air (Figure 1). of the signal. The numbers of maxima or minima in the recorded signals were registered at a sampling rate of fs = 100 samples per Sensor Location and Attachment second. Then, the signal was derived and the number of crosses Procedure through zero was divided by two to obtain the signal period. The operculum was chosen as the target location for the sensor The signal of the accelerometer was noisy, and the low pass as it allowed monitoring physical activity by measurements filter was not able to eliminate some spurious crosses through of accelerations in x- and y-axes, while records of operculum zero. To alleviate this noise drawback and to obtain a more breathing (z-axis) served as a direct measurement of respiratory accurate estimation of the number of peaks, they were estimated frequency. The device attachment was accomplished using small in N consecutive frames of T seconds. Experimentally, it was and light laboratory tags for identification of experimentation calculated that around half of the frames included spurious animals (RapID tags from RapID Lab, Inc., San Francisco, crosses through zero, increasing the value of the respiratory CA, United States) that were rapidly pierced to opercula of frequency. As trade-off between complex signal denoising anesthetized fish (100 µg/mL 3-aminobenzoic acid ethyl ester processing algorithms and the limited energy and computational MS-222, Sigma, St. Louis, MO, United States). In a second step, capability of the microprocessor, the final number of peaks (Np ) a rigid polyamide PA 2200 3D-printed pocket was fixed with an was defined as the 25% percentile of the N estimations. This 25% innocuous and quick drying aquarium adhesive (cyanoacrylate) percentile was a conservative value below the 50% of usually noisy to the exterior side of the RapID tag. Such approach allowed easy frames. Anyway, values between 20 and 40% provided similar application and removal of the device in the pocket (Figure 2). results. Hence, the respiratory frequency was issued every N · T seconds and it was calculated as: Data Acquisition and Software Fresp = Np /T Processing Software data processing aimed to assess respiratory frequency Values of N, T and fs were heuristically chosen to assure a and fish activity. The first estimation was carried out with the good statistical representation. The value of fs was established as signal of the z-axis of the accelerometer, and the second one was 100 Hz. A value of Ts = 10 seconds was chosen as frame length. derived from the x- and y-axis signals of the accelerometer. This value implied 5 peaks when the respiratory frequency was Frontiers in Physiology | www.frontiersin.org 3 May 2019 | Volume 10 | Article 667 Martos-Sitcha et al. Sensor for Individual Fish Monitoring 2 Hz. N was established equal to 12 (respiratory frequency was activity index by the sensor were programmed through the calculated every 120 s), which allowed a reasonable estimation of FRMD-KL25Z algorithm platform and uploaded to the device. the 25% percentile. This step involved some changes on the algorithm to estimate the To describe the physical activity index of the fish spatio- physical activity index due to the limited computational power temporal movement along the x- and y-axes, we relied on the of the sensor. For this purpose, the standard deviations of dx (n) simple optimization principle that the human movements strives and dy (n) were approximated by: to achieve maximally smooth movements by minimizing the first PT·fs PT·fs temporal derivative of acceleration, or “jerk,” while constraining n=1 dx (n) − µx n=1 dy (n) − µy all higher derivatives to zero (Flash and Hogan, 1985). This fact σx = and σy = T · fs T · fs has been also applied to measure the intensity of the movement of terrestrial livestock (Hamäläinen et al., 2011). In this way, the The energy of the jerk was estimated as: energy of the jerk can be seen as a measure of the intensity of fish movement. To ease microprocessor calculations, the physical Ejerk = σx + σy . activity index was defined as the averaged energy of the jerk along the frame. Similarly to the respiratory rate, the energy of The value of T was changed from 10 to 10.24 s. It means a frame the jerk was estimated on N consecutive frames of T seconds of 1024 data, which is a power of 2, more convenient for the and the 25% percentile provided the activity index measurement. sensor programming. The values of N, T, and fs were the same than in the respiratory frequency algorithm. Functional Testing The procedure was as follows. The accelerations in the x- and Initial tests of the device were conducted in overnight fasted sea y-axis, named ax (n) and ay (n), respectively, were derived as: bream and sea bass juveniles (30–150 g body weight) reared in the indoor experimental facilities of Institute of Aquaculture Torre de dx (n) = ax (n) − ax (n − 1) la Sal (IATS-CSIC, Castellón, Spain) under natural photoperiod dy (n) = ay (n) − ay (n − 1) and temperature conditions (40◦ 50 N; 0◦ 100 E). Fish with the implanted device were exercised in an intermittent-closed swim The standard deviations of dx (n) and dy (n) were calculated: tunnel respirometer of 10 L water volume (Loligo Systems, R v v Viborg, Denmark). The swim tunnel was submerged into a water u PT·f u PT·f bath that served as a water reservoir for flushing the respirometer (d (n) µ ) t i=1 (dy (n) − µy )2 s 2 s u t n=1 x − x u after each closed respirometer run (flush pump: Eheim 1048, σx = and σy = T · fs T · fs 10 L/min; Deizisau, Germany). To ensure constant high water quality, the water bath was connected by a second flush pump where µx and µy were the average of dx (n) and dy (n), (Eheim 1250, 20 L/min; Deizisau, Germany) to a 100 L reservoir respectively. The energy of the jerk was then obtained as: tank coupled to a re-circulatory system equipped with physical q and biological filters and a programmable temperature system Ejerk = σx2 (n) + σy2 (n) fixed at 24–25◦ C. Sea water (80–95% O2 saturation) flowed back into the re-circulatory system by means of gravity, remaining The physical activity index was the 25% percentile of the energies unionized ammonia, nitrites and nitrates almost undetectable of the jerk estimated on N consecutive frames. A summary of along the whole experiment. A thruster within the respirometer the procedure for the calculation of respiratory frequency and was used to generate a swimming current. Water velocities physical activity index is shown in Figure 3. were calibrated with a hand-held digital flow meter that was Processing of the raw data generated by the tri-axial ordered by the controller Movitrac LTE 0.37kW/0.5HP (SEW R accelerometer and stored in the memory of the device required Eurodrive, Normanton, United Kingdom). Respirometry runs data transfer in a computer after tests. Using this procedure, the and chamber flushing were automatically controlled with the autonomy of the device was limited to the amount of memory, DAQ-M instrument (Loligo Systems) connected to a PC R which was able to store a total of 6 min of raw data measured at a equipped with AutoRespTM software (Loligo Systems). Water R rate of 100 samplings per second. It was established that 2 min temperature and O2 saturation within the respirometer were was a reliable time window for statistical calculations, and the measured using a Witrox 1 single channel O2 meter (Loligo R device was then programmed to acquire three sets of 2 min of Systems, Viborg, Denmark), equipped with a needle-type fiber raw data for a given experimental schedule. optical micro-sensor (NTH, PreSens Precision Sensing GmbH, Software development also offered the possibility to Regensburg, Germany) and a temperature probe suspended into process on-board recorded data by means of mathematical the water current within the respirometer. approximations to ease microprocessor function. This approach For testing procedures, anesthetized fish with the AE-FishBIT is not a high memory consuming process, and the autonomy v.1s prototype were transferred into the swim tunnel and allowed of the system could be consequently increased up to 6 h of to recover and acclimate at a swimming speed of 0.5–1.0 continuous data recording, allowing longer schedules as long body-lengths per second (BL/s), until their measurements of as the battery of the device is operative. Algorithms for direct O2 consumption rates (MO2 ) reached a constant low plateau. on-board calculation of respiratory frequency and physical This was achieved when the regression line between the O2 Frontiers in Physiology | www.frontiersin.org 4 May 2019 | Volume 10 | Article 667 Martos-Sitcha et al. Sensor for Individual Fish Monitoring FIGURE 3 | Procedure diagram for the calculation of respiratory frequency and physical activity index. consumption and time after transfer was not significantly respiration indexes. Fish remained fasted during the day of data different from zero during four consecutive 5 min intervals, recording to avoid the possible distortion produced by feeding. and it typically happened after 30–45 min with MO2 around To check how blood markers of stress and welfare were 220–240 mgO2 /kg/h (Martos-Sitcha et al., 2018). After this affected by prototype implantation, polyamide PA 2200 dummy acclimation period, water velocity was increased in 0.5 BL/s steps, devices (same size and weight than the functional prototype) and specimens were submitted to controlled speeds between were implanted in active feeding sea bass (100–200 g) and 1 and 4 BL/s during the first testing approaches, or from sea bream of two different class of size (50–90 g; 300–500 g), 1 BL/s until exhaustion in the final on-board validation of reared at 22–24◦ C. After 1 week, tagged and non-tagged fish data recording. The range between 1 and 4 BL/s for the first (n = 5–7 fish per group) were anesthetized and blood was tests was chosen to assure that AE-FishBIT measurements were quickly taken from caudal vessels with heparinized syringes. obtained in the linear increase of metabolic rates according to A blood aliquot was centrifuged at 3,000 × g for 20 min at O2 consumption (Martos-Sitcha et al., 2018). Each swimming 4◦ C, and the plasma was stored at −80◦ C until the subsequent interval at a given velocity lasted 5 min, consisting in “flush- biochemical assays. Plasma glucose levels were measured by the wait-measurement” cycles (60 s flush interval to exchange the glucose oxidase method (Thermo Fisher Scientific, Waltham, respirometer water = “flush”; 30 s mixing phase in closed MA, United States) adapted to 96-well microplates. Blood mode = “wait”; and a 210 s MO2 measuring period in closed lactate was measured in deproteinized samples (perchloric mode = “measurement”). During the measurement interval, acid 8%) using an enzymatic method based on the use of O2 saturation of the swim tunnel water was recorded every lactate dehydrogenase (Instruchemie, Delfzijl, Netherlands). second. MO2 was automatically calculated by the AutoRespTM Plasma triglycerides (TG) were determined using lipase/glycerol software from linear decreases (r2 = 0.98–1.0) in chamber O2 kinase/glycerol−3−phosphate oxidase reagent (Thermo Fisher saturation during the measurement period at each discrete and Scientific). Plasma cortisol levels were analyzed using an EIA kit specific speed using the appropriate constants for O2 solubility in (Kit RE52061 m IBL, International GmbH, Germany). The limit seawater (salinity, temperature, and barometric pressure). After of detection of the assay was 2.46 ng/mL with intra- and inter- the swim tunnel test, fish were anesthetized again to recover the assay coefficients of variation lower that 3 and 5%, respectively. AE-FishBIT for data download. For each fish, three data sets of 2 min raw data were acquired by the device at different speed Ethics Statement steps. Additional tests were conducted in order to check the No mortalities were observed during fish manipulation and correlation of raw data calculated parameters with those coming data recording, and all the described procedures were approved from the on-board algorithms. To achieve this validation, devices by the Ethics and Animal Welfare Committee of Institute of were programmed to simultaneously store raw data (3 steps of Aquaculture Torre de la Sal and carried out according to 2 min data sets) and algorithm processed results. the National (Royal Decree RD53/2013) and the current EU For tests conducted with free-swimming fish (sea bream legislation (2010/63/EU) on the handling of experimental fish. 292.5 ± 20.5 body weight, sea bass 161.6 ± 14.9 body weight) in 500 L tanks (stocking density ranging between 6 and 8 kg m−3 for Statistical Analysis both species), six devices were programmed to acquire 2 min raw Daily variation of respiratory frequency and physical activity data sets at three discrete times 1 day after device implantation index in free-swimming sea bream and sea bass was analyzed by (10:00 a.m., 2:00 p.m., and 6:00 p.m.). This schedule covered one-way ANOVA. Blood parameters of tagged and non-tagged a wide range of possible circadian variations in activity and (control) groups were compared by means of Student’s t-test. Frontiers in Physiology | www.frontiersin.org 5 May 2019 | Volume 10 | Article 667 Martos-Sitcha et al. Sensor for Individual Fish Monitoring Analyses were performed using the SigmaPlot Version 13 for Windows (Systat Software Inc., Chicago, IL, United States). Multivariate partial least-squares discriminant analysis (PLS-DA) of data on respiratory frequency and physical activity index of exercised sea bream in the 1–6 BL/s water speed range was conducted with the EZ-info software (Umetrics, Sweden). The quality of the PLS-DA model was evaluated by R2Y and Q2Y parameters, which indicated the fitness and prediction ability, respectively. RESULTS Initials tests for the assessment of the functional significance of calculated outputs relied on PC post-processing of raw data. Challenges in the swim tunnel respirometer showed for both sea bream (Figure 4A) and sea bass (Figure 4B) a linear increase of MO2 in the 1–4 BL/s speed range. The calculated respiratory frequency by data post-processing paralleled MO2 . At the same swimming speed, MO2 and the calculated respiratory frequency were consistently higher in sea bream than in sea bass. However, for a given MO2 , the respiratory frequency was similar for both species as shown by the correlation plot of these two variables when all data were put together (Figure 4C). Regarding physical activity index, it increased exponentially rather than linearly with the increase of swimming speed, as the total jerk magnitude only reflects fish-related accelerations (Figure 5). This pattern was observed both in sea bream and sea bass, though it became more evident in sea bream at swimming speeds over 3 BL/s. Registered values in free-swimming fish were in the measurable range by the PC-tested algorithms in the swim tunnel. In both fish species, the calculated respiratory frequency in holding tanks did not show significant daily variations from 10:00 a.m. to 6:00 p.m., ranging the respiratory frequency between 2.4–2.3 breaths/second in sea bream and 2.2– 1.8 breaths/second in sea bass (Figure 6A). For the measurements of physical activity, the range of variation was also higher in sea bass, being statistically significant the decrease of physical activity from 0.150 ± 0.004 to 0.033 ± 0.001 relative units (P < 0.05). The observed decrease in sea bream varied from 0.147 ± 0.003 to 0.087 ± 0.005 relative units (P = 0.12) (Figure 6B). For validation of on-board algorithms, a second step of swim tunnel tests was conducted. Sea bream juveniles of 80– 100 g were exercised over 1–6 BL/s until exhaustion (fish were FIGURE 4 | (A) Measurements of MO2 (mgO2 /kg/h; gray circles) and considered exhausted when they rested at the back grid for at respiratory frequency (breaths/s; black triangles) of sea bream (35–60 g body least 5 s). Simultaneous raw data storage and algorithm on- weight range) with increasing speed in the swim tunnel respirometer. Each board calculations allowed the comparison of both approaches point represents mean ± SEM of 6–10 measurements from a total of 16 fish. for the calculation of respiratory frequency and physical activity (B) Measurements of MO2 (mgO2 /kg/h; gray circles) and respiratory indexes over the same 2 min period, and close linear correlations frequency (breaths/s; red triangles) of sea bass (90–150 g body weight range) with increasing speed in the swim tunnel respirometer. Each point represents near to 1 between on-board and PC-calculated values were mean ± SEM of 6 measurements. (C) Correlation plot of MO2 and respiratory found (Figure 7). The different dynamics of on-board calculated frequency values for each sea bream (black circles) and sea bass (red circles) parameters from low to submaximal exercise were observed. individual. Respirometer measurements of MO2 increased linearly up to a swim speed of 4.5 BL/s, paralleling the increase in the respiratory frequency, with a maximum respiratory frequency defined as the maximum O2 consumption in exercised fish, (MRF) close to 4 BL/s (Figures 8A,B). This short delay in might be due, at least in part, to the instantaneous nature of the achievement of the maximum metabolic rate (MMR), sensor measurements (gill breathing) compared to the buffered Frontiers in Physiology | www.frontiersin.org 6 May 2019 | Volume 10 | Article 667 Martos-Sitcha et al. Sensor for Individual Fish Monitoring metabolic condition and welfare. To achieve this end, different technological solutions already available as research tools or commercial products were initially considered (Tamayo et al., 2013; Bandodkar and Wang, 2014; Tamsin, 2015), but given the cost and methodological limitations when operating underwater, it was decided that the use of mechanical devices was more feasible than other options based on electric and/or optical sensors. The AE-FishBIT tri-axial accelerometer is able to register physical activity and operculum beats (two in one) as a direct measure of respiratory frequency. This sensor device was designed to work in stand-alone mode (no wireless data transmission) due to the constraints in size, weight, battery consumption and signal transmission in aquatic environments (Lloret et al., 2012; Climent et al., 2014). The AE-FishBIT also included a tag RFID system for an easier operability and data processing during fish data recording from resting to moderate or FIGURE 5 | Output of physical activity index with increasing speed in the very active behavior under aerobic and/or anaerobic conditions. swim tunnel respirometer for sea bream (black circles) and sea bass (red When the system was tested in exercised juveniles, close circles). Each point represents mean ± SEM of 6–10 measurements. correlations were found between O2 consumption and calculated respiratory frequency in both sea bream and sea bass. For measurements of physical activity, the jerk of accelerations changes in the measurements of O2 concentrations in the 10- increased exponentially rather that linearly with the increase L chamber of respirometer. In any case, these two types of of swimming speed (Figures 4, 5). Indeed, the jerk magnitude respiration measurements decreased progressively and markedly is independent of orientation and it only reflects accelerations, with the increased contribution of anaerobic metabolism close to which are theoretically zero at the constant speeds imposed submaximal exercise. Likewise, measurements of physical activity in the swim tunnel controlled conditions. It should then be achieved a maximum activity at 5 BL/s. This was preceded assumed that when fish are induced to swim against the water by a slight decrease of slope at 4.5 BL/s that became clearly current, the physical activity index will reflect the resistance of negative with the enhancement of the unsustainable anaerobic fish to match current water speed. Then, the steady increase metabolism close to submaximal exercise (Figure 8C). Any of of this index could be related with the number of intermittent the analyzed variables was informative enough to ascertain the (burst-and-coast) swimming bursts (Marras et al., 2010). Further aerobic/anaerobic scope when considered individually. However, increase in water speed should force a transition from burst- given their different dynamic patterns in response to exercise, and-coast to continuous swimming that would decrease the multivariate analyses with on-board processed data resulted in number of burst and consequently decrease the physical activity a fairly good differentiation of aerobic/anaerobic fish condition index under forced swimming conditions (Figure 8C). Thus, the along the first component, with a 59% of total variance explained vigorous and irregular tail movements of fish resulted in a non- (R2Y) and 57% predicted (Q2Y) by the two components of the linear increase of the jerk of accelerations. This activity feature discriminant model (Figure 9). was more evident in the case of sea bream, which probably The impact of device attachment in fish physiology was reflects a lower capability for fast swimming in comparison assessed by comparisons of circulating levels of markers of stress to sea bass with the spindle-shaped body characteristic of an and welfare in tagged and non-tagged (control) free-swimming active predator (Spitz et al., 2013), as indicates its common fish 1 week after implantation of dummy devices. No differences name in France “le loup de mer”. Likewise, for a given were found in circulating levels of cortisol (Figure 10A), glucose MO2 , measurements of jerk accelerations were higher in free- (Figure 10B) or lactate (Figure 10C) in 100–200 g sea bass nor sea swimming fish than in forced exercised fish (swim tunnel), bream for the two class of size analyzed. By contrast, TG levels where a more static position limits changes of trajectory and in 50–90 g sea bream and 100–200 sea bass were significantly accelerations (Figures 4–6). From tests conducted across the lowered (P < 0.01) in tagged fish in comparison with non-tagged light-phase in free-swimming animals, it is also conclusive that ones (Figure 10D). This disturbance was not detected in larger the range of variation was higher for measurements of physical fish (>300 g sea bream). activity rather than respiratory frequency, especially in the case of sea bass (Figure 6). However, this issue needs to be corroborated with a more continuous circadian data recording with the advent DISCUSSION of new AE-FishBIT versions. The usefulness of behavior monitoring remains yet to be fully The present study is the proof of concept of the work exploited in aquaculture practice, though it is well known that conducted within the AQUAEXCEL2020 EU project for the swimming performance provides a complete measurement of design, programming and testing of a miniaturized device animal fitness and perhaps stress behavior in fish kept under (AE-FishBIT v.1s) intended for individual fish phenotyping of specific environmental conditions (Nelson, 1989; Plaut, 2001; Frontiers in Physiology | www.frontiersin.org 7 May 2019 | Volume 10 | Article 667 Martos-Sitcha et al. Sensor for Individual Fish Monitoring FIGURE 6 | (A) Daily variation of respiratory frequency values in free-swimming sea bream (292.5 ± 20.5 g mean body weight; white bars) and sea bass (161.6 ± 14.9 g mean body weight; black bars) in 500-L tanks. Each bar represents mean ± SEM of 6 measurements. (B) Daily variation of physical activity values in free-swimming sea bream (white bars) and sea bass (black bars) in 500-L tanks. Each bar represents mean ± SEM of 6 measurements from the same 6 individuals. Different superscript letters indicate significant differences (P < 0.05; one-way ANOVA). Remen et al., 2016). Thus, measurements of MO2 , and secondly (Argyrosomus regius) (Peixoto et al., 2017), challenged at water respiratory frequency, can be considered a good measurement temperatures close to those set in our experimental approach. of the energy expended by fish to integrate a wide-range of Thus, given the close parallelism between measurements of physiological processes influenced by both endogenous (e.g., MO2 and respiratory frequency, we can conclude that the AE- size, age, and fish strain) and exogenous (light, temperature, O2 FishBIT provided reliable results of O2 consumption in a wide- concentration, time of day, etc.) factors. In our experimental physiological range not only when the energy requirements conditions, MO2 increased in sea bream and sea bass from did not exceed the O2 demand for a sustainable aerobic 230–270 to 370–400 mgO2 /kg/h with the increase of swimming metabolism, but also during the anaerobic phase that was speed from 1 to 4 BL/s (Figures 4A,B). These reported largely increased at submaximal exercise (Ejbye-Ernst et al., values are in line with those found in previous studies in 2016). This was demonstrated by additional swimming tests sea bream (Martos-Sitcha et al., 2018), European sea bass (Figures 7–9), prolonged until fish exhaustion at 6 BL/s, which (Claireaux et al., 2006) or other farmed fish, such as meager also served to corroborate the suitability of on-board algorithms Frontiers in Physiology | www.frontiersin.org 8 May 2019 | Volume 10 | Article 667 Martos-Sitcha et al. Sensor for Individual Fish Monitoring FIGURE 7 | Validation of on-board algorithms from low to submaximal exercise. Values are mean of six sea bream juveniles (141.3 ± 7.4 g mean body weight). (A) Correlation plot for a given swimming speed between respiratory frequency values calculated for 2 min raw data post-processed on a PC (x-axis) or on-board (y-axis). (B) Correlation plot for a given swimming speed between physical activity index values calculated for 2 min raw data post-processed on a PC (x-axis) or on-board (y-axis). of respiratory frequency and physical activity through aerobic and anaerobic conditions. The weight of the first AE-FishBIT prototype is 600 mg in air with an estimated 50% of buoyancy. These features make it very FIGURE 8 | Respirometer and on-board output from low to submaximal convenient for its use in fish of 30–35 g onwards, according to the exercise. Values are the mean ± SEM of six sea bream juveniles (95.2 ± 3.7 g empirical “2% tag/body mass” rule for implanted devices (Winter, mean body weight) (A) Respirometer measurements of MO2 (mgO2 /kg/h) with increasing swimming speed. Maximum metabolic rate (MMR) is marked. 1996; Jepsen et al., 2004). Recent works claim that this rule can (B) Respiratory frequency (breaths/s) with increasing swimming speed. The be even extended for some fish species up to 7% of body mass maximum respiratory frequency (MRF) is marked. (C) Physical activity index without detrimental effects on performance or survival (Smircich with increasing swimming speed. and Kelly, 2014; Makiguchi and Kojima, 2017). In the present study, we assessed the influence of device implantation on fish welfare by measurements of blood biochemical parameters in (cortisol, glucose, and lactate) 1 week after device attachment both sea bream and sea bass, and no differences were found regardless of body weight (50->300 g). During this time, the between tagged and non-tagged fish in classical stress markers observed feeding behavior was also considered to be quite similar Frontiers in Physiology | www.frontiersin.org 9 May 2019 | Volume 10 | Article 667 Martos-Sitcha et al. Sensor for Individual Fish Monitoring FIGURE 9 | PLS-DA score plot of on-board calculated parameters at different swimming speeds before (black squares) and after (red squares) the achievement of the MMR in sea bream juveniles from low to submaximal exercise. in tagged and non-tagged fish. However, the observed decrease as demonstrated by the correlations of PC and on-board outputs in plasma TG levels in tagged 100–200 g sea bass and 50– in sea bream juveniles, exercised from low to submaximal exercise 90 g sea bream would be indicative of, at least, a transient (Figure 7). This long coverage of exercise activity also highlighted impairment of feed intake. This finding was not observed in that the system remained highly informative of metabolic the largest sea bream (>300 g), being this fact indicative of condition with the shift of aerobic to unsustainable anaerobic the importance of defining the critical fish size to minimize metabolism, which reduces the efficiency of ATP production and the impact of tag burden in welfare and behavior in different promotes the accumulation of deleterious by-products (e.g., H+ , aquaculture scenarios (Figure 10). In parallel, important research lactate) (Richards, 2009; Seibel, 2011). Indeed, aerobic locomotor efforts continue to be made to reduce the dimensions and weight activity is powered by red oxidative muscle fibers, but when of upcoming AE-FishBIT prototypes, keeping or even increasing approaching their maximum power capacity, a gait transition to the functional features of the device. At short-medium term, the anaerobic fueling is assisted by the activation of fast white muscle main envisaged hardware strategies for this miniaturization will fibers that results in fatigue and depletion of muscle glycogen consider the use of: (i) flexible kapton instead of the current depots (Kieffer, 2000; Sänger and Stoiber, 2001). Some degree pcb rigid substrate, (ii) lighter and smaller long-life batteries and of activation of anaerobic metabolism occurs before reaching (iii) improved circuit packaging architecture based on Flip Chip MMR, as it has been determined in different experimental models (Lau, 2016) or embedded wafer level ball grid array (eWLB) (Burgetz et al., 1998; Lee et al., 2003; Hinch et al., 2006; Teulier technologies (Meyer et al., 2008). These solutions are based on et al., 2013), including sea bream and guppy (Poecilia reticulata) currently available commercial components, but as a part of semi- (Ejbye-Ernst et al., 2016). However, as pointed out before, the industrialization packaging and production we cannot exclude closely related MRF and MMR will mark the start of a burst- the design of custom integrated circuits as the most ambitious assisted swimming, resulting in a change of metabolic scope and and technologically challenging procedure for the final product swimming energy partitioning (Peake and Farrell, 2004; Peake, miniaturization. 2008; Marras et al., 2013; Svendsen et al., 2015). Importantly, Data processing and software improvements with on-board this energy transitioning can be monitored by the AE-FishBIT algorithms are also key steps on the prototype development device, as discriminant multivariate analysis distinguished two due to its major impact on data recording autonomy, which main groups of fish behavior when the achieved MRF-MMR makes possible different short- and long-time schedules, adjusted was taken as main criteria of aerobic/anaerobic classification for instance to 2 days (2 min recording each 15 min), 8 days (Figure 9). This complex trade-off is mediated by O2 sensors (2 min recording each 60 min) or 24 days (2 min recording (Norin and Clark, 2016), being defined the O2 limiting saturation each 180 min). This relatively high autonomy also requires (LOS) as the O2 threshold level that is no longer sufficient to a low computational load, which did not compromise the maintain MO2 at a given temperature and voluntary swimming usefulness of the microprocessor mathematical approximations, activity (Remen et al., 2013, 2015). Acute hypoxia drives to Frontiers in Physiology | www.frontiersin.org 10 May 2019 | Volume 10 | Article 667 Martos-Sitcha et al. Sensor for Individual Fish Monitoring FIGURE 10 | Plasma levels of (A) cortisol, (B) glucose, (C) lactate, and (D) triglycerides represented as a percentage of non-tagged control values. Each bar represents mean ± SEM of n = 5–7 for each fish species (sea bream, sea bass) and class of size (405.3 ± 13.9 g; 69.2 ± 2.6; 172.9 ± 14.9 g). Asterisks indicate statistically significant differences with control (P < 0.01, Student’s t-test). the re-adjustment of sea bream mitochondrial machinery at procedures in fish are usually related to telemetry devices in transcriptional level, leading to a more efficient O2 -carrying large fish, with application near the dorsal or anal fins (Jepsen capacity in blood cells (Martos-Sitcha et al., 2017). Different et al., 2015). At the present stage, the RapID tag and 3D pocket types of adaptive responses also occur under moderate hypoxia approach has served for the short-term validation experiences, (above LOS), which reflects the tissue-specific responsiveness but this system procedure was not operative for more than 1– of liver, heart, skeletal muscle and blood cells, according to 2 weeks due to the appearance of macroscopic signals of damage their metabolic capabilities and O2 availability (Martos-Sitcha and necrosis caused by loosening at the piercing location. This et al., unpublished). Indeed, fish transcriptomic meta-analysis in problem has been currently solved with the use of corrosion- response to a vast array of challenged conditions highlights the resistant self-piercing fish tags (National Band & Tag Company, key role of mitochondria in front of different cellular stresses, Newport, KY, United States) as the AE-FishBIT support. In our including hypoxia, hypercortisolism and malnutrition (Calduch- hands, the complete attachment implantation procedure takes Giner et al., 2014). In particular, sea bream juveniles exposed to less than 1 min, but automatization procedures like those used thermal stress or multiple sensory perception stressors (shaking, for massive fish vaccination (Skala Maskon, Stjørdal, Norway) sound, light flashes, and water flow reversal) show adaptive need to be implemented for a more practical and routine use responses of glycolytic pathways and mitochondrial respiratory of this device in fish farming. In any case, specific attachment chain (Bermejo-Nogales et al., 2014). How these adjustments at procedures need to be validated for each fish species, size cellular level can be correlated with the monitored AE-FishBIT and physiological condition in different aquaculture scenarios parameters is the upcoming envisaged challenge in a scenario of through production cycles. global change with increases of temperature, ocean acidification Further improvements envisaged in the AE-FishBIT device and reduced O2 concentrations (Gruber, 2011). include a more compact design (Figure 11) with the reallocation Another important challenge is the improvement of the of the connection pins for charge and data transmission in device attachment procedure to the operculum. External tagging the bottom side of pcb. The enclosure of the device is a Frontiers in Physiology | www.frontiersin.org 11 May 2019 | Volume 10 | Article 667 Martos-Sitcha et al. Sensor for Individual Fish Monitoring programmable schedules. Validity and functional significance of tri-axial accelerations has been assessed under forced and voluntary exercise, and further work is underway to improve semi-industrial packaging and production. From a functional point of view, data analysis depicts the potential use of the proposed prototype for assessing the gait transition of metabolic scope and energy partitioning. The expected impact is the improvement of metabolic phenotyping in a slight invasive manner for the implementation of fish management and selective breeding. The prototype can also contribute to establish more strict and reliable welfare standards, and a better perception of quality controls in aquaculture production. The prototype is protected by a registered patent (P201830305). ETHICS STATEMENT All procedures were approved by the Ethics and Animal Welfare Committee of Institute of Aquaculture Torre de la Sal and carried out according to the National (Royal Decree RD53/2013) and the current EU legislation (2010/63/EU) on the handling of experimental fish. FIGURE 11 | Schematic 3D view of the intended AE-FishBIT v.2 prototype AUTHOR CONTRIBUTIONS before (A) and after packaging (B). JP-S coordinated the different research teams. JS, DR-V and JM-N assembled the device components and implemented protective packaging that completely covers the edge of the software programming. CC-D and MF established mathematical printed circuit, which will improve the insulation of the parameters for data outputs and on-board algorithm sensor components. Additionally, the new printed circuit is approximations. FB, EC, AV, and ML worked on device manufactured in multilayer technology without through holes. packaging and insulation procedures. JP-S, JM-S, and JA The combination of the compact pcb and the protective enclosure conducted functional tests. JM-S, JC-G, and JP-S wrote the results in a fully sealed device with a minimum increase of the manuscript. All authors edited the manuscript and read and total weight (around 900 mg). The design can stand water contact approved the final manuscript. with the connector pins and the supply voltage of the battery is protected by a diode that prevents its discharge. During the experiments, data transmission signals are always in the high FUNDING impedance state, which prevents the leakage of electrical current. This project has received funding from the European Union’s The new intended prototype (AE-FishBIT v.2) has been tested Horizon 2020 Research and Innovation Programme under underwater for more than 24 h without any additional protection grant agreement No. 652831 (AQUAEXCEL2020 , Aquaculture in the electrical contacts. For longer experimental periods, the infrastructures for excellence in European fish research electrical contacts will be further protected with an adhesive towards 2020). This publication reflects the views only of waterproof lid. The removable cap will be adapted to be combined the authors, and the European Commission cannot be held with the best attachment procedure for each fish species and responsible for any use which may be made of the information experiment protocols. contained therein. Additional funding was obtained from project SURF (TEC2014-60527-C2-1-R) of the Spanish Ministry of Economy and Competitiveness and the European Regional CONCLUSION Development Fund (FEDER). A miniaturized device to register at the same time fish operculum beats (respiratory frequency) and physical activity has been ACKNOWLEDGMENTS designed, produced and tested in sea bream and sea bass as the proof of concept of the functional significance of the We acknowledge support of the publication fee by the CSIC calculated data. The basic operating mode is stand-alone with Open Access Publication Support Initiative through its Unit of autonomy of 6 h of continuous data recording with different Information Resources for Research (URICI). Frontiers in Physiology | www.frontiersin.org 12 May 2019 | Volume 10 | Article 667 Martos-Sitcha et al. Sensor for Individual Fish Monitoring REFERENCES Physiology of Fish. Fish Physiology Series, Vol. 24, eds K. Sloman, S. Balshine, and R. Wilson (London: Academic Press), 240–285. Andrewartha, S. J., Elliott, N. G., McCulloch, J. W., and Frappell, P. B. (2016). Horie, J., Mitamura, H., Ina, Y., Mashino, Y., Noda, T., Moriya, K., et al. (2017). 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Brauner (San Diego, CA: Elsevier), 443–485. doi: 10.1016/s1546-5098(08)00010-1 Conflict of Interest Statement: The authors declare that the research was Saberioon, M., Gholizadeh, A., Cisar, P., Pautsina, A., and Urban, J. (2017). conducted in the absence of any commercial or financial relationships that could Application of machine vision systems in aquaculture with emphasis on fish: be construed as a potential conflict of interest. state-of-the-art and key issues. Rev. Aquac. 9, 369–387. doi: 10.1111/raq. 12143 Copyright © 2019 Martos-Sitcha, Sosa, Ramos-Valido, Bravo, Carmona-Duarte, Sänger, A. M., and Stoiber, W. (2001). “Muscle fiber diversity and plasticity,” in Fish Gomes, Calduch-Giner, Cabruja, Vega, Ferrer, Lozano, Montiel-Nelson, Afonso Physiology: Muscle Development and Growth, ed. I. A. Johnston (San Diego, CA: and Pérez-Sánchez. This is an open-access article distributed under the terms Academic Press), 187–250. doi: 10.1016/s1546-5098(01)18008-8 of the Creative Commons Attribution License (CC BY). The use, distribution or Seibel, B. A. (2011). Critical oxygen levels and metabolic suppression in oceanic reproduction in other forums is permitted, provided the original author(s) and the oxygen minimum zones. J. Exp. Biol. 214, 326–336. doi: 10.1242/jeb.049171 copyright owner(s) are credited and that the original publication in this journal Simbeye, D. S., Zhao, J., and Yang, S. (2014). Design and deployment of wireless is cited, in accordance with accepted academic practice. No use, distribution or sensor networks for aquaculture monitoring and control based on virtual reproduction is permitted which does not comply with these terms. Frontiers in Physiology | www.frontiersin.org 14 May 2019 | Volume 10 | Article 667