Dietary self-selection in ﬁsh: a new approach to studying ﬁsh...

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Dietary self-selection in fish: a new approach to studying fishnutrition and feeding behavior

Rodrigo Fortes da Silva . Alexandre Kitagawa .

Francisco Javier Sanchez Vazquez

Received: 1 July 2015 / Accepted: 21 November 2015 / Published online: 30 November 2015

� Springer International Publishing Switzerland 2015

Abstract The principles of modern aquaculture

encourage the development of fish feeds containing

low fish meal content and several types of plant

ingredients plus nutrients to avoid depleting global fish

stocks and to reduce costs. However, food constituents

can affect animal nutrition and feeding behavior, so the

effect of different diets on fish behavior and growth

needs to be understood to optimize the use of nutrients

and to improve fish welfare. The development of

multiple-choice self-feeding systems led to a new

perspective for investigating these issues in aquaculture

species. Our purpose with this review is to summarize

the information that has been published to date on this

topic and to identify gaps in knowledge where research

is needed. Key subjects are assessed under the follow-

ing major headings: How do we study dietary selection

in fish?What food signals do fish use to choose the right

diet? and How do fish respond to food challenges? The

present review will provide a picture of the main results

obtained to date in these studies in aquaculture fish

species, as well as perspectives for future research in the

field.

Keywords Food intake � Macronutrient �Micronutrient �Nutritional target �Nutritional wisdom

Introduction

Aquaculture has achieved spectacular development

indices worldwide and is considered one of the fastest

growing sectors por food production. These indices of

development are likely to be retained to maintain

current consumption levels of fish products (FAO

2009; Bosma and Verdegem 2011). Indeed, in the next

two decades, up to two-thirds of seafood for human

beings will be provided by the aquaculture industry

(FAO 2009).

The efficiency of food intake and nutrient utiliza-

tion are the two main biological factors determining

the economic viability of aquaculture; therefore, fish

farmers must have precise control of the food supply to

achieve maximum growth with minimal waste and

environmental impact. Classic nutritional studies are

usually time-consuming and involve a large number of

animals. However, there are new tools to study

nutrition, and these methodologies are considered

essential to stimulate new concepts of study in fish

R. F. da Silva (&)

Laboratory of Fish Nutrition and Feeding Behaviour

(AquaUFRB), Faculty of Fishing Engineering (NEPA),

Center of Agricultural Science, Environmental and

Biological (CCAAB), University of Bahia (UFRB),

Cruz das Almas 44380-000, Bahia, Brazil

e-mail: [email protected]

A. Kitagawa

Department of Agronomy, Faculty of Agricultural

Sciences, Unifenas University, Alfenas 37130-000, Brazil

F. J. Sanchez Vazquez

Department of Physiology, Faculty of Biology, University

of Murcia, 30100 Murcia, Spain

123

Rev Fish Biol Fisheries (2016) 26:39–51

DOI 10.1007/s11160-015-9410-1

nutrition. For example, the technique of stable isotopes

has been used to establish a general outline of the

metabolic pathway, using the isotopic forms of a given

chemical element to mark a metabolite (Xia et al.

2015). Another technique is the controlled tube-feeding

method of radiolabeled nutrients, which allows us to

estimate the fraction evacuated, catabolized and

retained for each nutrient in fish larvae. This method

has been applied to study the digestion, absorption and

metabolism of proteins and lipids in larvae of different

species of fish (Conceicao et al. 2009). However, a

revolutionary concept is the use of geometric and

spatial models of nutrition, which take into account the

behavioral responses of the fish confronted with the

diets under study; these models have been used to

define the ideal balance ofmacronutrients to develop an

optimal diet for whitefish (Coregonus lavaretus) (Ruo-

honen et al. 2007). A combination of mixture design

theory and state-space models of nutrition (the geo-

metric framework, GF) can be used to derive a 5-step

protocol for multi-criterion diet optimization. Step 1

involves selecting the focal nutritional axes for mod-

eling, step 2 uses mixture theory to choose an optimal

selection of experimental diets to test in experiments,

step 3 entails using GF to plot and interpret intake and

growth arrays, step 4 involves plotting response

variables onto intake arrays, and step 5 uses multi-

criterion optimization to combine and weigh several

relevant response variables. This concept has been

suggested for application to several fish species

(Raubenheimer et al. 2012).

Technological innovation depends on advances that

must be spread to improve the techniques of fish

production, including diet design and manufacture

(FAO 2011). Many forms and compositions of fish

diets have been developed, but few studies correlate

the mechanisms of digestion and the requirements of

different species to their eating and social behaviors.

The search for the optimal management and determi-

nation of the ‘‘ideal’’ and economically viable food is

ongoing (Pereira-da-Silva et al. 2004). According to

those authors, there are many benefits to offering the

animals a free choice of food, which is considered the

most natural and gentle way of feeding fish.

Feeding methodologies, such as demand feeders

and encapsulated diets, are being used to investigate

food intake regulation and dietary preferences. With

the development of demand feeders, the research on

feeding behavior and nutrition has advanced

enormously, and the following questions can be now

answered: When should food be offered? What type

should be offered? and Howmuch should be offered to

fish? The most relevant issues in aquaculture feed can

be solved with less investment of time and in

conjunction with the study of multiple variables that

operate in the nutrition of fish (Madrid et al. 2009).

It would be ideal, in terms of nutritional and

economic practices, for fish diets to be established on

the basis of experiments in which the fish themselves

self-select the type and quantity of food being

consumed (Rubio et al. 2003; Pereira-Da-Silva et al.

2004; Sanchez-Vazquez et al. 1994; Fortes-Silva et al.

2010). The concept of animals ‘‘nutritional wisdom’’

emerged after the pioneering studies of Richter (1943),

who showed that rats choose among different food

sources to obtain a nutritionally balanced diet. Dietary

selection involves the existence of ‘‘specific hungers’’:

that is, the animal is able to sense nutrients in the diet

and choose a diet with the required elements. In

addition to economic issues, regulation or food pref-

erence of a particular food, the concept of welfare of

the fish is implicit. Identification of the internal state of

welfare is still a challenge, particularly on farms where

fish are exposed to food challenges regarding the type

of feed and feeding schedule. A sick fish is certainly

not in a state of welfare, but a healthy fish may not

necessarily be feeling well. The state of wellness could

be considered when the fish is in a position to exercise

the option of free choice (Volpato 2007).

This paper provides a review on recent research on

dietary selection of fish and useful information on new

technologies used to investigate feeding nutrition. We

begin with an overview of the feeding behavior and

learning. To conclude, we discuss avenues for future

research.

Behavioral mechanisms of nutrient intake

regulation

Animals do not eat all food items encountered but

actively choose food that contains dozens of different

types of molecules that provide the right nutrients for

the animal’s survival, growth and reproduction. Thus,

animals have evolved from an extraordinary diversity

of means and challenges, acquiring mechanisms of

intake regulation, such as the perception of the

energetic content of a particular food, the ability to

40 Rev Fish Biol Fisheries (2016) 26:39–51

123

sense nutrients and the existence of ‘‘specific hunger’’

to regulate the intake of specific nutrients.

On one hand, an animal adapted to feed on a single

type of food (specialist) of invariant nutrient compo-

sition needs only to regulate the amount of food to be

eaten to ensure nutritional regulation, for example,

using stretch receptors of the stomach and intestine

(Simpson and Raubenheimer 2001). On the other

hand, an animal that has evolved in an environment

that is spatially and temporally heterogeneous, with

numerous types of foods that vary greatly in their

composition (generalist), has to feed on a combination

of diets, regulating the total amount of each food or

nutrient consumed over time. In these cases, the

animal requires specific regulatory systems for each

nutrient to achieve a balanced diet (Simpson and

Raubenheimer 2001). Some authors prefer the term

‘‘nutritional wisdom,’’ for the ability of the fish to

regulate nutrient intake (Sanchez-Vazquez et al. 1994,

1995a, b; Simpson and Raubenheimer 2001; Fortes-

Silva et al. 2010; Fortes-Silva et al. 2011a, b). This

term was first used in the first half of the last century

and refers to the ability of animals to ingest specific

substances to maintain homeostasis, such as the

appetite of cattle for sodium (Katz 1937).

For some time, the consumption of an unbalanced

diet has been known to have metabolic consequences

that can lead the individual to develop a particular

behavior of diet selection. Protein intake in young rats is

not regulated at a constant proportion of total calories

but is controlled between a minimum level that will

support rapid growth through the availability of essen-

tial amino acids and a maximum that, if exceeded, will

cause the animal to suffer some substantial metabolic

consequences (Peters and Harper 1984). Likewise, a

fish that meets its goal of each specific nutrient intake

will provide its tissues with optimal concentrations of

nutrients for proper growth and reproduction (Simpson

and Raubenheimer 2001; Fortes-Silva et al. 2012).

In all vertebrates, the regulation of consumption,

appetite and body weight is a complex phenomenon

that involves elaborate interactions between the brain

and peripheral signals. The brain, especially the

hypothalamus, produces key factors that either stimu-

late (orexigenic) or inhibit (anorexigenic) the intake of

food. These factors can be directly related to the search

for or the rejection of a particular food and, conse-

quently, in feeding behavior. The hypothalamus is

continually informed about nutritional, energetic and

environmental status of the body by anorexigenic and

orexigenic messages of central and peripheral systems.

The peripheral feedback signals include nerve

impulses, peptides, leptin, cortisol, glucose and insulin.

These substances are integrated in the food intake-

regulation centers in the hypothalamus, with monoami-

nes and neuropeptides playing a central role in trans-

mitting signals from the central system (Kulczykowska

and Sanchez-Vazquez 2010). A series of peptides

homologous to mammals have been isolated or their

sequence deduced from cloned cDNA sequences.

These peptides include cholecystokinin (CCK) (Peyon

et al. 1998), bombesin (Volko et al. 1999), neuropeptide

Y (Blomqvist et al. 1992; Cerda-Reverter et al. 2000),

melanin concentrating hormone (Baker et al. 1995),

galanin (Anglade et al. 1994; Unniappan et al. 2002;

Wang and Conlon 1994), proopiomelanocortin (Cerda-

Reverter andPeter 2003), corticotropin-releasing factor

(Bombardelli et al. 2006) and orexins (Kaslin et al.

2004). Information on the role of these neuropeptides in

the control of food intake and its mechanism of action,

as well as the regulation of specific nutrient intake in

fish, is growing but still very limited. In recent years,

mechanisms have been proposed for carbohydrate and

lipid regulation. The food intake can be affected by the

blood levels of glucose, glycogen and glucose 6-phos-

phate, activities and expression of glycogen synthetase

(GSase) and pyruvate kinase (PK), expression of

GLUT2, and expression of the components of the

KATP? channel in parallel with changes in glucose in

agreement with the known model in mammalian

glucosensing (Soengas 2014). With regard to lipids,

an increase in fatty acid (FA) levels in plasma can

induce an increase in malonyl-CoA levels and subse-

quent inhibition of carnitinepalmitoyl transferase 1

(CPT-1) to import FA-CoA into the mitochondria for

oxidation (Lopez et al. 2007).

In other species, such as birds and pigs, several

studies were conducted to quantify the intake of

nutrients such as protein using techniques of self-

selection of diets. In cattle, studies conducted decades

ago showed the importance of feeding behavior and

diet selection in studies of nutrition. Ruminants are

faced with a huge variety of food on pasture with

concentrations of nutrients and toxins that vary by type

of forage, season, etc. (Freeland and Janzen 1974;

Provenza et al. 1998). Despite this challenge, animals

can select diets with adequate levels of nutrients and

fewer toxins, indicating that the food selection is not

Rev Fish Biol Fisheries (2016) 26:39–51 41

123

random in these animals (Newman et al. 1992; Illius

and Gordon 1993). Thus, why not use behavioral

information of self-selection of diets to study the

intake and regulation of nutrients by fish?

The basic mechanism proposed to control the intake

of protein in fish is likely to be similar to that described

in mammals, where protein can be detected by

gastrointestinal receptors during the digestion (Rubio

et al. 2003; Almaida-Pagan et al. 2006; Fortes-Silva

et al. 2011a, b) and where amino acids can be detected

in the liver (Bellinger et al. 1996) after being absorbed.

These receptors would originate signals (neural and

hormonal activity), informing brain centers about the

nutritional properties of food and thus modifying

feeding behavior. With this information, animals learn

to associate eating too much or too little of a particular

nutrient with its metabolic consequences, called ‘‘nu-

tritional reward,’’ at post-ingestive and post-absorptive

levels (Forbes 2001).

Learning and feeding behavior

When considering dietary selection, a basic question

arises: How do animals know what type of food they

should eat? Three states of knowledge are relevant to

feeding behavior: the short-term learning and memory,

buffer via parental effects, and ancestral memory,

which includes the genetic effect on the phenotype.

Thus, an animal is born with a set of expectations, for

example, about what types of foods could be found.

Learning from experience allows the animal to assess

whether a food is satisfactory or not and whether the

supply of nutrientsmeets their nutritional requirements,

thereby allowing the animal to use this learning to

predict future consequences. Three types of learning

associated to nutritional consequences and status have

been reported for insects and vertebrates: (a) learning

frompositive associations (e.g., remembering clues that

lead to placeswhere food is rich in protein), (b) learning

from aversions (e.g., remembering clues that allow the

animal to avoid locations associated with toxic or

nutrient-poor foods), and (c) non-associative responses

(e.g., simplymoving to find new,more attractive foods,

which fulfill a nutritional deficiency) (Simpson and

Raubenheimer 1996; Berthoud and Seeley 2000). State

of knowledge can have a direct effect on the search

strategy used by an organism. For example, in the

absence of relevant local information, individuals may

prefer to wait instead of using a random search strategy

(Viswanathan et al. 1999; Bartumeus et al. 2005). In all

cases, the survival success or failure of any organism is

often closely linked with its ability to detect and

interpret signals or cues within its environment. Signals

may come in a variety of modalities, and it may benefit

an organism to be highly tuned to signals that offer

increased survival or reproductive opportunities (Holt

and Johnston 2011).

What food signals do the animals use to make

dietary selection?

Locusts can develop learned associations between

plant-derived odors and the protein content of foods

(Simpson and White 1990). In the same insect, it is

possible to observe the existence of associative

learning in response to pairing visual cues with protein

and carbohydrate consumption (Raubenheimer and

Tucker 1997). A similar nutrient-specific learning has

also been shown in rats, which learn to associate odors

(Baker et al. 1987) and food texture (Booth and Baker

1990) with specific macronutrients. An alternative

explanation for the exhibition of a preference for

specific types of food items by animals may be

associative learning, which is a phenomenon widely

reported in many different animal species. Evidence

may suggest that animals choose a given food item

because of its orosensorial properties only (taste,

texture, etc.). However, there is compelling evidence

that dietary selection by fish is based only on post-

ingestive signals. European sea bass (Dicentrarchus

labrax) are able, through various nutritional chal-

lenges, to self-compose a balanced diet by choosing

from individual macronutrients encapsulated in gela-

tin capsules (and thus with the same odor and texture),

using only the color of the capsule and the place of

delivery as the clue to select the proper nutrients

(Rubio et al. 2003) (Fig. 1). The same ability of self-

selection of encapsulated diets has been reported in

different fish species, such as the sharpsnout seabream

(Diplodus puntazzo) (Almaida-Pagan et al. 2006) and

Nile tilapia (Oreochromis niloticus) (Fortes-Silva

et al. 2011a, b). When fed encapsulated diets, these

fish are even able to compensate for protein dilution

(adding 50 % cellulose) by increasing protein intake,

indicating that the animals try to sustain a certain level

of consumption of this nutrient.


123

How can we study dietary selection in fish?

To investigate feeding behavior, we need a system that

allows fish to feed freely at any time, consuming any

amount of the different foods, such as with a self-

feeder system, for example. Fish were trained to

activate a trigger to obtain a food reward; thus, feeding

behavior and food preferences were assessed (Aranda

et al. 2000). To obtain data on feeding behavior, a

trigger is connected to a PC and allows continuous

recording (see Fig. 2). Thus, the fish can feed them-

selves or even select among different diets placed in

separate feeders. In the early 1990s, this system was

considered a breakthrough for the study of feeding

(00:00 min) (02:00 min) (04:00 min)

(06:00 min) (08:00 min) (10:00 min)

B

A

Fig. 1 Scheme of dietary selection based on color-coded

capsules and post-ingestive signals [illustration (a) and photo

of tilapia Oreochromis niloticus (b), 10 min. after the feeding].

All three capsule types have the same chemosensory properties

at the oropharyngeal level, so there are no flavor or texture clues

to their macronutrient content


123

behavior in fish because it allowed the development of

a computer system that provided more accurate

records of the data through chronobiological software

that records the activities (Sanchez-Vazquez et al.

1994). These systems allowed us to perform a more

appropriate management of cultivated species (Ala-

nara and Brannas 1996).

Self-feeding is based on the learning ability of fish

and, therefore, is a technique that can improve

performance and reduce levels of waste because the

food is delivered depending on the appetite (Azzaydi

et al. 1998). In a self-feeding system, fish are assumed

to be able to precisely control the feeding, simply

activating a ‘‘trigger’’ sensor inserted into the water

(Alanara and Brannas 1996). In addition, attachment

of the system of self-demand feeders to a computer

system allows the feeding activity of the fish though

seasons to be quantified, characterizing the annual

feeding circadian rhythms, as well as the nocturnal,

diurnal, crepuscular or even dual feeding habits. This

Fig. 2 Self-feeding by

European sea bass

(Dicentrarchus labrax) with

a stretch sensor or ‘‘trigger.’’

The two feeders enable the

delivery of different diets

separately, enabling fish to

make dietary self-selection

and choose their preferred

time for feeding. a Feeders,

b food delivery, c record of

feeding activity


123

same system has been improved by exchanging the

trigger sensor for infrared photocells (Fig. 2), so the

feeder does not require contact but instead is driven by

the presence of the animal at a given point in the tank;

the fish associates that place with the dispensing of

food, which indicates ‘‘learning associated with

reward’’ (Forbes 2001). This system is used for young

animals or for animals that have a mouth shape that

prevents the fish from reaching past the stretch sensor

to the feeder (Fig. 3).

Ability to compose a balanced diet:

‘‘macronutrient selection’’

Dietary selection is also a powerful tool for investi-

gating the response of fish subjected to nutritional

challenges (e.g., protein or fat deprivation) to inves-

tigate the relative flexibility of the food intake-

regulation mechanism. The development of method-

ology for demand feeders that will allow the study of

the ability of fish to compose a diet balanced in

macronutrients presented a greater challenge. The

option to choose from three pure macronutrients

(protein, lipid and carbohydrate) in three separate

demand feeders was offered to sharpsnout seabream

(Diplodus puntazzo), and the ability of the fish to

compose a balanced diet rich in protein was observed

(Almaida-Pagan et al. 2006). This diet is very similar

to that reported for carnivorous fish, such as rainbow

trout, which selected a diet with 63.8 % protein and

18.5 % lipids (Sanchez-Vazquez et al. 1999) (Fig. 1).

These data were also similar to those of other

carnivorous species, such as the European sea bass,

which selected 58.8 % protein and 19.4 % lipids using

the same demand feeders (Aranda et al. 2000).

However, these data were different from those

obtained with goldfish, which is an omnivorous

species. This fish species selected a diet low in protein

(18.9 %) but high in lipids (33.8 %) (Sanchez-

Vazquez et al. 1998). In all cases, it was necessary

to provide fish a challenge to prove the preference for

selected levels of the diets, so that after exchanging the

diets between feeders, the fish sustained a constant

Fig. 3 Self-feeding with

infrared sensor ‘‘photocell.’’

The feeder is driven by fish

approaching a photocell in

the water. The tube covering

the photocell ensured the

feeder is only triggered by

the presence of the fish

inside, thereby avoiding

accidental activations. The

data are transferred to a data

acquisition board that sends

the signals to a computer for

recording


123

consumption of each macronutrients, resuming the

previous pattern of selection. When the nutrient in

question was diluted, fish responded by increasing the

nutrient demands, showing the ability to regulate its

consumption and ‘‘defend’’ a given nutritional target.

The methodology of the demand feeder provides a

means for assessing the feeding preferences of fish and

defining the target of consumption of each nutrient

offered. However, this methodology is not able to

separate the physiological effects of the ingestion of

nutrients and organoleptic properties. Therefore, it

was necessary to develop a new methodology to avoid

the effect of flavor, texture and smell to determine the

extent to which the regulation of nutrients is influ-

enced without oral factors. The intake regulation

involves multiple mechanisms that interact to control

physiology and behavior. Among these control mech-

anisms, the pre-ingestive and post-ingestive signal

provides the animal an anticipatory behavioral

response to food. Thus, the fish learn to relate the

metabolic consequences of food ingestion to a specific

future behavior (Forbes 2001).

The sharpsnout seabream not only established a

pattern of consumption of macronutrients but were

also able to increase the consumption of food provided

to them when the protein was supplied in a smaller

proportion, thereby adjusting the nutrient intake

(Almaida-Pagan et al. 2006). The composition of the

diet selected by the sharpsnout seabream was 62.7 %

protein, 21.3 % carbohydrate and 16.0 % lipids in

terms of percentage of pure macronutrients. These

data were similar to those found by Vivas et al. (2006),

who used the previously described demand feeder

method. Even when the contents of the capsules were

changed (i.e., capsules that previously contained

proteins were filled with carbohydrates, whereas those

that were previously filled with carbohydrates were

filled with lipids), the sharpsnout seabream were able

to perceive this exchange and reestablish their pattern

of consumption for each macronutrient (Almaida-

Pagan et al. 2008). These results strongly suggest a

post-ingestive influence of each macronutrient, which

controls dietary selection and feeding behavior.

When the protein was diluted, the tilapia (Ore-

ochromis niloticus) increased the intake of the encap-

sulated diet to maintain the pattern of consumption of

protein, and when only capsules of carbohydrate and

lipid were it was offered to the animals, the fish kept the

ingestion of these capsules to regulate energy intake.

(Fortes-Silva et al. 2011a, b). This behavior was not

observed in European sea bass (Dicentrarchus labrax)

because this species refused to eat in the absence of

protein, which is a characteristic behavior of strictly

carnivorous fish (Rubio et al. 2005a, b). Thus, the

‘‘omnivorous tilapia’’ was observed to have a greater

tolerance to diets of low protein content, whereas the

‘‘carnivore sea bass’’ stops eating if the protein levels

do not match their nutritional requirements.

The results provided by the methodology of

encapsulated nutrients support the observations made

using self-feeders; that is, fish are able to select a diet

according to their nutritional needs regardless of the

organoleptic characteristics of the food. This valuable

data on diet selection should be used to formulate diets

and discuss issues such as regulation of food intake,

food preferences and fish well-being related to feed-

ing. However, in some cases, fish may have prefer-

ences for capsules colors. The preference for a specific

color implies that self-selection of diet composition

may not be a suitable tool for the feed optimization of

perch (Perca fluviatilis) (Brannas and Strand 2015).

We need to acknowledge that developing optimal diets

based on fish macronutrient requirements requires

years of research. In addition, protocols related to this

subject must take into account the observational skills

of the researcher. The ability of the fish to swallow

whole capsules needs to be accessed, and the fish must

be allowed the time required to exhibit a physiological

response (Table 1).

Self-selection of micronutrients

Dietary selection is a powerful tool to research

preferences for micronutrients, such as vitamins,

minerals, essential amino acids, or food additives.

This technique can also be used to investigate

avoidance behavior of antinutritional factors (e.g.,

phytate). A summary of results on micronutrient

selection is shown in Table 2. European sea bass

(Dicentrarchus labrax) was not only able to select a

balanced diet in methionine, but this fish was also able

to detect levels of an essential amino acid to allow

consumption of the nutrient in an amount considered

adequate for the nutrition of the species (Hidalgo et al.

1988). Rainbow trout were also able to detect adequate

levels of zinc to maintain their nutritional status

(Cuenca et al. 1993). Another fish species, Sparus


123

aurata, detected and selected a diet with added

vitamin C (Paspatis et al. 1997), showing the species

ability to select a nutritionally complete food. All

authors concluded that the method of the demand

feeders is a powerful tool for understanding the

relation between the consumption of a nutrient and

its behavioral effects.

Nile tilapia (Oreochromis niloticus) that were fed

three diets with three different sources of lipids (i.e.,

soybean oil, linseed oil and fish oil), and thus different

profiles of fatty acids, showed a clear preference for oil

source (Fortes-Silva et al. (2010). To this end, three

demand feeders were installed containing the different

diets in terms of lipids. Fish established a clear

preference for the diet containing linseed oil. To

impose a challenge to the fish, the diets were

exchanged between the feeders. After a few days,

the fish reestablished their initial preference for the

diet of linseed. Despite the tilapia’s preference for the

diet with linseed oil, there was a relatively constant

consumption of the other diets, which suggests that the

fish have established levels of consumption of each

diet containing the different oils.

Some of the main concerns about food used in

aquaculture are the antinutritional effects, such as phytic

acid or phytate, which are present in vegetable flours.

Table 1 Summary of the results of studies on macronutrient selection using different fish species and ‘‘self-feeders or encapsulated

diets’’ methods

Species Habitat Method Macronutrient (protein,

P; fat, F; carbohydrate, C)

Authors

Name Scientific

name

Salt

water

Freshwater Self-

feeder

Capsules

Goldfish Carassius auratus X X 18.9 % P; 33.8 % F; 47.4 % C Sanchez-Vazquez

et al. (1998)

Rainbow

trout

Oncorhynchus mykiss X X 63.8 % P, 18.5 % F, 17.7 %C Sanchez-Vazquez

et al. (1999)

Sea bass Dicentrarchus labrax X X 58.8 % P; 19.4 % F; 21.8 % C Aranda et al. (2000)

Sea bass Dicentrarchus labrax X 51 % P, 32.5 % F, 16.5 % C Aranda et al. (2001)

Common

carp

Cyprinus carpio X X 55 %HP, 21 %HF, 24 %HCa Yamamoto et al.

(2003)

Sea bass Dicentrarchus labrax X X 55 % P, 23 % CH and 22 % F Rubio et al. (2003)

Sea bass Dicentrarchus labrax X X 66.1 % P, 21.2 % F, 8.2 % C Vivas et al. (2006)

Sharpsnout

seabream

Diplodus puntazzo X X 47 % P, 10 % F Atienza et al.

(2004)

Sea bass Dicentrarchus labrax X X 37 % P, 44 % F, 19 % C Rubio et al. (2005a)

Sea bass Dicentrarchus labrax X X 3.5 P, 1.7 F, 2.7 Cb Rubio et al. (2005b)

Sea bass Dicentrarchus labrax X X 46 % P, 34 % F, 20 % C Rubio et al. (2006a)

Sea bass Dicentrarchus labrax X X 43 % P, 40 % F, 17 % C Rubio et al. (2006b)

Sharpsnout

seabream

Diplodus puntazzo X X 63 % P, 19 % F, 18 % C Vivas et al. (2006)

Sharpsnout

seabream

Diplodus puntazzo X X 62.7 % P, 16.0 % F, 21.3 % C Almaida-Pagan

et al. (2006)

Sharpsnout

seabream

Diplodus puntazzo X X 67.3 % P, 13.5 % F, 19.0 % C Almaida-Pagan

et al. (2008)

Senegalese

sole

Solea senegalensis X X 68.0 % P, 15.7 % F, 16.3 % C Rubio et al. (2009)

Tilapia Oreochromis

niloticus

X X 45.4 %P, 22.4 % L, 32.2 % C Fortes-Silva

et al. (2011a, b)

Tilapia Oreochromis

niloticus

X X 41.7 % P, 23.5 %F, 34.8 %C Fortes-Silva

et al. (2012)

a HP (diet with 63 of P), HF (diet with % 30 of F), HC (diet with 60 % of C)b capsules/100 g BW/day


123

The presence of this component in the diet can cause a

decrease in food consumption and consequently a loss in

body weight. A substantial preference of Nile tilapia

(Oreochromis niloticus) for the soy diet with added

phytase, compared to the samedietwithout phytase,was

observed (Fortes-Silva et al. 2010). This enzyme is

capable of hydrolyzing phytic acid and promotes the

release of chelated minerals in the diet. In addition,

when the exogenous phytic acid was added to increase

the concentration of this compound in the diet, therewas

a progressive decrease in food consumption. This

response was also observed in European sea bass

(Dicentrarchus labrax), which significantly decreased

the demands on feeders, when they had a diet with 30 %

soy flour with no added phytase (Fortes-Silva et al.

2011a, b). The positive effect of phytase in improving

phosphorus and calcium in the bones of sea bass was

noted by the authors.

A thorough study on the ability of tilapia for diet

self-supplementation with essential amino acids was

developed (Fortes-Silva et al. 2012). Two different

diets were provided: (a) a gelatin-based diet that was

free of tryptophan and low inmethionine, threonine and

isoleucine, and (b) a diet covering the estimated

essential amino acids requirements for tilapia, which

was based on a diet supplemented with L-tryptophane,

L-methionine, and L-threonine. Tilapia showed a sig-

nificant preference for the diet supplemented with the

three essential amino acids. Moreover, food selection

was not based on the orosensorial properties of the diets

because the fish fed the capsules sustained their

preference for the diet with essential amino acids.

Finally, fish were capable of self-supplementation of

essential amino acids when the three amino acids were

provided separately from the diet. These results further

support the working hypothesis that fish possess

‘‘nutritional wisdom,’’ so they avoid a protein-imbal-

anced diet and choose a diet containing essential amino

acids that best match their nutritional requirements.

Concluding remarks and future direction

This review presents a new approach to the study of

nutrition and highlights the importance of fish behav-

ior in relation to the endogenous effects provided by

food. Using the animal as our ‘‘guide’’ to formulate

diets, we can use the vast complexity of nutritional

space to reach optimized solutions of ration formula-

tion, consumption regulation and welfare in fish. Our

review reveals that the two groups of fish ‘‘carnivorous

and omnivorous’’ have a number of key characteristics

of their biology for future study on feeding behavior.

The influence of foods and physiology on the feeding

behavior of the fish generally remains little under-

stood, but fish may offer unique opportunities for

Table 2 Synopsis of selected micronutrients by different species using the self-feeder method

Species Habitat Substance (method:

self-feeder)

Authors

Name Scientific name Saltwater Freshwater

Sea bass Dicentrarchus labrax X Methionine Hidalgo et al. (1988)

Trout Oncorhynchus mykiss X Zinc Cuenca et al. (1993)

Sea bass Dicentrarchus labrax X Taurine Martinez et al. (2004)

Trout Oncorhynchus mykiss X Vitamin C Paspatis et al. (1997)

Trout Oncorhynchus mykiss X Fluoroquinolone Boujard and Le Gouvello (1997)

Trout Oncorhynchus mykiss X Methionine/lysine Yamamoto et al. (2001)

Trout Oncorhynchus mykiss X Dietary oil Geurden et al. (2005)

Trout Oncorhynchus mykiss X Dietary oil Geurden et al. (2007)

Tilapia Oreochromis niloticus X Dietary oil Fortes-Silva et al. (2010)

Tilapia Oreochromis niloticus X Phytase Fortes-Silva et al. (2010)

Gilthead seabream Sparus aurata X Oil versus

oxidized oil

Montoya et al. (2011)

Sea bass Dicentrarchus labrax X Phytase Fortes-Silva et al. (2011a, b)

Tilapia Oreochromis niloticus X Methionine/threonine/

tryptophan

Fortes-Silva et al. (2012)


123

comparative studies of intimate interplay between

welfare and growth. Future work needs to be under-

taken in different fish species, as has been conducted

in several other species, such as dogs (Heberlein and

Turner 2009), mice (Rymer et al. 2008), swine (Owen

et al. 1994), sheep (Favreau et al. 2010) and chickens

(Siegel et al. 2011). Previous work has mostly focused

on a few fish species; this needs to be extended to other

fish. This group of vertebrates offers a unique oppor-

tunity because fish are extraordinarily varied and

inhabit very different environments. The study of fish

feeding behavior therefore has great potential to

provide important and spectacular insights into the

interplay of food preferences and food requirements

for the improvement of the aquaculture environment.

Acknowledgments Developing the report that led to this review

was primarily sponsored by the Spanish Ministry of Science and

Innovation (MICINN) by projects (AGL2010-22139-C03-01 and

AQUAGENOMICS) to FJSV and (CNPq, Pesquisador Visitante

Especial/PVE, 401416/2014-3) to R. Fortes-Silva, although the

material has been updated since that report.

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