close

Вход

Забыли?

вход по аккаунту

?

An experimental analysis of ingestion rates in an omnivorous species.

код для вставкиСкачать
American Journal of Primatology 70:510–513 (2008)
BRIEF REPORT
An Experimental Analysis of Ingestion Rates in an Omnivorous Species
M. STAMMATI1,2, G. SABBATINI1,2, AND E. VISALBERGHI1
1
Unità di Primatologia Cognitiva, Istituto di Scienze e Tecnologie della Cognizione, Consiglio Nazionale delle Ricerche, Rome,
Italy
2
Dipartimento di Biologia Animale e dell’Uomo, Università di Roma ‘‘La Sapienza’’, Rome, Italy
Food intake is difficult to estimate under natural conditions. We investigated ingestion rates of 14
different food types in 26 captive capuchin monkeys (Cebus apella). The procedure consisted in
weighing a piece of food and using a two alternative choice tests to present food to the subject, alone in
its cage. We recorded the food chosen and the time it took the subject to consume the food entirely.
Consumption time was converted into ingestion rates (g/s) for each food type. Ingestion rates of food
types significantly differed, and the difference was significantly higher among foods than among
subjects. In particular, ingestion rates of the fruits were higher than those of human-processed food.
Interestingly, food preferences were significantly related to energy intake rate, i.e., to the amount of
energy ingested per unit of time, but not with ingestion rates or energy content alone. The energy
acquired by eating different types of food cannot be calculated on the basis of the time spent eating
unless a correction factor for each given food (or similar ones) is applied. Future controlled studies
should provide field researchers with such corrections factors, possibly using foods collected in the wild.
Am. J. Primatol. 70:510–513, 2008.
r 2008 Wiley-Liss, Inc.
Key words: ingestion rate; Cebus apella; food preferences; energy intake rate
INTRODUCTION
Food intake (grams of food eaten) is difficult to
estimate because the sources of measuring errors are
numerous, particularly under natural conditions
[Hladik, 1977]. Time spent feeding is often used as
an approximation of actual food intake, but Zinner
[1999] demonstrated that feeding time has to be used
with caution to estimate food intake, and Hladik
[1977] found that time spent feeding on some food
items by Hanuman langurs was 10 times higher than
the proportion of food intake. Therefore, an accurate
estimate of food intake should take into account both
time spent feeding and mass of food eaten.
The ingestion rate (grams of food ingested per
unit of time) depends on many factors, for example,
mastication and chewing patterns. The characteristic breakage of a given food is important for the
sensory feedback it can provide when chewed and, in
turn, mastication patterns depend on the perceived
taste and texture [van der Bilt et al., 2006]. In
humans, the time until swallowing was shorter, and
fewer chews were observed as palatability of the food
increased [Bellisle et al., 2000].
Very recently, Schulke et al. [2006] showed that
ingestion rates have a crucial importance in determining the energy intake rates in two ecologically
different populations of Hanuman langurs (Semnopithecus entellus). The authors calculated the ingestion rate of each monkey by multiplying its bite rate
r 2008 Wiley-Liss, Inc.
by the average bite dry weight. Bite rate was
recorded from a limited number of complete direct
observations of eating, and the weight of a bite was
estimated from a set of food samples having similar
size of that eaten by the monkey. Their complex
calculations, possibly the best obtainable in nature,
are still far from being precise.
Although variation in both ingestion rate and
chemical composition of primate food items has been
investigated [e.g., Laska et al., 2000; Zinner, 1999],
few studies have explored their relation with food
preferences. We studied an omnivorous primate
species, the capuchin monkey, in controlled laboratory conditions in which we could accurately assess
ingestion rates for a variety of familiar foods and
individual preferences toward these foods. For each
food presented we knew its mass and its energetic
Contract grant sponsor: FIRB/MIUR; Contract grant number:
RBNE01SZB4; Contract grant sponsor: ANALOGY: Humans—
the Analogy-Making Species; Contract grant number: 029088.
Correspondence to: Elisabetta Visalberghi, Unit of Cognitive
Primatology and Primate Center, Institute of Cognitive Sciences
and Technologies, CNR, Via Ulisse Aldrovandi, 16/b, 00197
Roma, Italy. E-mail: elisabetta.visalberghi@istc.cnr.it
Received 1 March 2007; revised 12 December 2007; revision
accepted 12 December 2007
DOI 10.1002/ajp.20523
Published online 9 January 2008 in Wiley InterScience (www.
interscience.wiley.com).
An Experimental Analysis of Ingestion Rates / 511
and nutritional characteristics. In this exploratory
study, we aimed to reveal possible variation in
ingestion rates across individuals and/or food types.
If these factors turn out to play a role, it means that
field studies can increase the accuracy of their
estimation of food intake by taking variation in
ingestion rates into account.
frequency of eating behavior was scored with
instantaneous sampling every 5 s. Eating was scored
when the subject bit and masticated the food, licked
or swallowed it, but did not include processing
behaviors (e.g., peeling) occurring outside the mouth.
The experiment was carried out between January
2001 and January 2002.
MATERIALS AND METHODS
Analysis
Subjects
We calculated ingestion rates (g/s) by dividing the
weight of the piece of food (g) by the time (s) taken to
consume it totally. As the assumptions of parametric
statistics were not met, we used non-parametric tests.
To determine whether ingestion rates vary among food
items more than among individuals, we compared
coefficient of variation (standard deviation over the
mean) with Mann–Whitney U test.
To assess whether there was a significant difference between the ingestion rates of the different foods,
we carried out a Friedman analysis of variance test
and Wilcoxon Matched Pairs test to compare pairs of
foods. As many comparisons were made, we applied
Bonferroni’s correction, with the corrected a level set
at 0.00076. We used the Mann–Whitney U test to
assess whether age and sex affected ingestion rates.
Ingestion rates of the three categories of food used
(fruit: tangerine, banana, pear, pineapple, grapefruit,
tomato; leaf-tuber: boiled potato, lettuce; and humanprocessed food: bread, monkey chow, canned meat,
boiled pasta) were compared with the Kruskall–Wallis
test and post hoc analyses were conducted by means
of the Mann–Whitney U test with a corrected a level
set at 0.017.
We obtained the item-specific energy intake rate
(kJ ingested per sec) by multiplying the average
ingestion rate across individuals with the energy
content (kJ per 1 g) of each food item. We carried
out Spearman correlations (with Bonferroni’s correction, a level set at 0.0167) to assess whether food
preferences (i.e., the average number of times in which
each food was chosen) were related with ingestion
rates, item-specific energy intake rate and energy
content of food. To exclude spurious correlations, we
carried out Spearman correlations (with Bonferroni’s
correction, a level set at 0.0167) between item-specific
energy intake rate and ingestion rates, energy content
of food and water content and between ingestion rates
and water content of food.
We tested 26 capuchins belonging to four
groups: 10 males, 16 females; five juveniles (o4
years old), 21 adults (44 years old); the age range
was 2–35; average age was 13. Twenty-one subjects
were laboratory born, whereas five were of unknown
origin (probably wild born). The monkeys were
housed at the Primate Center of the Institute of
Cognitive Sciences and Technologies (CNR) inside
the Bioparco (Rome). Group 1 (N 5 12) had a total of
105 m3, group 2 (N 5 6) had a total of 135 m3, group 3
(N 5 3) had 90 m3 and group 4 (N 5 5) had 70 m3. By
passing through one or more sliding doors, the
subject can be separated from the rest of its group
in the testing cage. Monkey chow (Altromin-A
pellets, Rieper standard diet for primates), fresh
fruits and vegetables were given every afternoon.
Three times a week, monkeys received a mixture of
curd cheese, vitamins, egg, bran, oats and sugar. The
research complied with protocols approved by the
Italian Health Ministry, and all procedures complied
with ASAB guidelines and European law on the
humane care and use of laboratory animals.
Procedure
The subjects were presented with all possible
binary combinations of 14 foods (tangerine, banana,
pear, boiled potato, bread, monkey chow, lettuce,
pineapple, canned meat, boiled pasta, grapefruit,
tomato, boiled string beans and savoy cabbage) using
a two-alternative choice test [see Addessi et al.,
2005; Visalberghi et al., 2003]. This procedure was
repeated three times and led to a data set in which
the tested foods were not evenly represented because
during a single trial subjects could choose between
two pieces of food, and most preferred foods were
chosen a higher number of times than least preferred
ones. Given this, string beans and cabbage could not
be used for ingestion rate analyses as these items
were entirely eaten only a few times. The foods were
cut into pieces of similar sizes (about 1 cm3), and
each piece was weighed with a digital scale (AND
compact scale, CA; 0.1 g accuracy, 200 g capacity)
before testing. Note that similar size leads to weight
that depends on the type of food. The trial started
when the subject took the food and ended once the
food was totally consumed. To calculate the average
time spent by each subject eating each food type, the
RESULTS
Coefficient of variation of ingestion rate was
significantly higher across foods (Mean7SEM 5
0.8670.04) than across individuals (Mean7SEM 5
0.4570.04; U 5 29.00, Z 5 4.39, nf 5 26, ns 5 14,
P 5 0.000002).
The ingestion rates were significantly different
across foods (Friedman analysis of variance
w2 5 84.44; Po0.0001). Mean ingestion rates of foods
Am. J. Primatol.
512 / Stammati et al.
TABLE I. Post Hoc Comparisons Between the Foods
Bread
Lettuce
Pear
Monkey chow
Potato
Tangerine
Grapefruit
Meat
Pasta
Pineapple
Tomato
Banana
Bread
Lettuce
Pear
0.00001
0.00028
0.00002
0.00001
0.00001
0.00001
n.s.
0.00003
0.00001
0.00016
n.s.
0.00029
0.00001
0.00004
0.00002
0.00001
0.00004
0.00029
0.00023
0.00001
0.00004
0.00039
0.00023
n.s.
0.00046
0.00064
0.00044
0.00029
n.s.
0.00081
0.00001
0.00002
n.s.
n.s.
0.00003
0.00001
n.s.
n.s.
Monkey chow Potato Tangerine Grapefruit
0.00001
0.00001
0.00003
n.s.
n.s.
0.00001
0.00003
0.00002
0.00005
0.00004
0.00002
0.00010
0.00004
n.s.
0.00003
0.00001
n.s.
n.s.
0.00009
0.00004
n.s.
n.s.
Meat
Pasta
n.s.
0.00003 0.00001
0.00009 0.00004
Pineapple
n.s.
P-values are reported only for significant comparisons; n.s., not significant.
(7SEM) from the highest to the lower value were
the following: banana 0.52 (70.04), grapefruit 0.39
(70.03); tomato 0.37 (70.03), pear 0.34 (70.02),
pineapple 0.32 (70.02), tangerine 0.30 (70.02),
potato 0.16 (70.02), lettuce 0.14 (70.01), string
bean 0.14 (70.01), savoy cabbage 0.12 (70.01),
monkey chow 0.04 (70.00), pasta 0.03 (70.00),
canned meat 0.03 (70.00) and bread 0.02 (70.00).
Table I reports P-values for the post hoc comparisons. The ingestion rates differed across food
categories (H (2, 12) 5 9.23; Po0.01), and post hoc
comparisons revealed a significant difference between fruit and artificial food categories (U 5 0.00;
Z 5 2.56; n1 5 6, n2 5 4; P 5 0.009), but not between
fruit and leaf-tuber categories (U 5 0.00; Z 5 2.00;
n1 5 6, n2 5 2; P 5 0.07), and between leaf-tuber and
human-processed food categories (U 5 0.00; Z 5 1.85;
n1 5 2, n2 5 4; P 5 0.13). Nevertheless, potato and
lettuce had significantly lower ingestion rates than
fruits, if considered one at a time (see Table I).
Ingestion rates were not affected by age and sex.
Preferences were the following, from the most to
the least preferred food: tangerine, banana, boiled
potato, pear, pineapple, canned meat, bread, grapefruit, boiled pasta, tomato, monkey chow, savoy
cabbage, boiled string beans and lettuce. Neither
ingestion rates (rs 5 0.39; ns) nor energy content
(rs 5 0.40; ns) correlated with food preferences. In
contrast, item-specific energy intake rate (kJ
ingested per sec) significantly correlated with food
preferences (rs 5 0.83; Po0.001). Item-specific
energy intake rate did not correlate with ingestion
rates (rs 5 0.53; ns), energy content of food
(rs 5 0.50; ns) and water content (rs 5 0.36; ns).
Moreover, water content did not correlate with
ingestion rates (rs 5 0.50; ns).
DISCUSSION
As reported by Schulke et al. [2006] for langurs,
the ingestion rates of capuchin monkeys differed
more across food items than across individuals.
Am. J. Primatol.
In particular, there were marked differences in
ingestion rates between the most pairs of foods.
Moreover, although water could facilitate mastication, ingestion rates were not significantly influenced
by water content of food. Ingestion rates of humanprocessed foods were lower than those of fruits. It is
interesting to note that as the human-processed
foods had higher energy content than fruits and
vegetables, their slow ingestion rate still resulted in a
high energy intake. Our foods reflected a sufficiently
broad range of mechanical properties [Lucas, 2004;
see Fig. 5 in Williams et al., 2005], but unfortunately
we did not measure them. Tufted capuchins exhibit
craniofacial features and a broad face associated with
powerful masticatory muscles that anteriorly can
produce and dissipate high masticatory forces. In the
wild, Cebus apella open palm nuts using the canines
and the premolars [Izawa, 1979]. Moreover, Wright
[2005] found that plant tissues processed by C. apella
are tougher than those processed by C. olivaceus and
suggested that to adapt to a hard diet C. apella has
exaggerated the ancestral condition for capuchins by
increasing the robusticity of canine size. This
adaptation allows the monkey to break hard fruits
with the anterior dentition without precluding
consumption of pulpy fruits that are easier and
quicker to process and ingest. The decreased size of
the more distal molars characterizing C. apella can
account for the lower values of ingestion rates for
leaves, tubers and human-processed foods. In fact,
this feature reduces the ability to perform higher
magnitude and repetitive loadings with the posterior
dentition required for eating foods such as leaves,
tubers and human-processed food [Spencer, 2003].
Future studies will benefit from combining data on
ingestion rates with those on the food mechanical
properties and primate mastication.
A novel and important finding that comes from
our data is that food preferences are significantly
related to energy intake rate (i.e., the amount of
energy ingested per unit of time), but not with
ingestion rates (grams of food ingested per unit of
An Experimental Analysis of Ingestion Rates / 513
time) or food energy content alone (kJ per g). This
result reinforces the previous results of Nakagawa
[1997] and Barton and Whiten [1994] that primates
optimize their energy intake according to food
availability and patch use. There is increasing
knowledge about how primates perceive and represent food [Rolls, 1999]. Food perception begins
externally with visual, auditory, olfactory and tactile
cues and proceeds in the mouth with texture and
taste stimuli [Dominy et al., 2001]. Finally, the
primate orbitofrontal cortex is an important site for
the convergence of representations of these stimuli
and for their non-linear combination with visceral
and satiety-related signals and with previously
learned associations [Rolls, 2005]. This entire system
acts on food acceptance and preferences. Future
studies should investigate how primates integrate
mechanical and chemical properties of food to
establish preferences.
We demonstrated that the same period of time
spent eating corresponds to different amounts of
food eaten, for example, 1 sec spent eating lettuce
corresponds to 0.10 g ingested and 1 sec spent eating
banana corresponds to 0.52 g ingested. As previously
pointed out by Hladik [1977], this result challenges
the common view that the time spent feeding reflects
the same amount of food eaten, regardless of food.
This means that the energy acquired by eating
different types of food cannot be calculated on the
basis of the time spent eating unless a correction
factor for each given food (or similar ones) is applied.
Future controlled studies should provide field
researchers with such correction factors possibly
using foods collected in the wild, and not foods from
the grocery stores as we used.
ACKNOWLEDGMENTS
We thank F. Natale and E. Addessi for statistical
advice and the two anonymous referees for their
useful comments. We are also grateful to the
Bioparco Foundation for hosting the laboratory
where the experiment was carried out and our
keepers M. Bianchi and S. Catarinacci for their help.
This research complied with ASAB guidelines and
the European law on the humane care and use of
laboratory animals.
REFERENCES
Addessi E, Stammati M, Sabbatini G., Visalberghi E. 2005.
How tufted capuchin monkeys (Cebus apella) rank monkey
chow in relation to other foods. Anim Welf 14:215–222.
Barton RA, Whiten A. 1994. Reducing complex diets to simple
rules: food selection by olive baboons. Behav Ecol Sociobiol
35:283–293.
Bellisle F, Guy-Grand B, Le Magnen J. 2000. Chewing and
swallowing as indices of the stimulation to eat during meals
in humans: effects revealed by the edogram method and
video recordings. Neurosci Biobehav Rev 24:223–228.
Dominy NJ, Lucas PW, Osorio D, Yamashita N. 2001. The
sensory ecology of primate food perception. Evol Anthropol
10:171–186.
Hladik CM. 1977. A comparative study of the feeding
strategies of two sympatric species of leaf monkeys:
Presbytis senex and Presbytis entellus. In: Clutton-Brock
TH, editor. Primate ecology. Studies of feeding and ranging
behaviour in lemurs, monkeys and apes. London: Academic
Press. p 324–353.
Izawa K. 1979. Foods and feeding behavior of wild blackcapped capuchin (Cebus apella). Primates 20:57–76.
Laska M, Hernandez Salazar LT, Rodriguez Luna E. 2000.
Food preferences and nutrient composition in captive spider
monkeys, Ateles geoffroy. Int J Primatol 21:671–683.
Lucas PW. 2004. Dental functional morphology: how teeth
work. Cambridge: Cambridge University Press. 355p.
Nakagawa N. 1997. Determinants of the dramatic seasonal
changes in the intake of energy and protein by Japanese
monkeys in a cool temperate forest. Am J Primatol 41:
267–288.
Rolls ET. 1999. The brain and emotion. Oxford: Oxford
University Press. 367p.
Rolls ET. 2005. Taste, olfactory, and food texture processing in
the brain, and the control of food intake. Physiol Behav
85:45–56.
Schulke O, Chalise MK, Koenig A. 2006. The importance of
ingestion rates for estimating food quality and energy
intake. Am J Primatol 68:951–965.
Spencer MA. 2003. Tooth-root form and function in platyrrhine seed-eaters. Am J Phys Anthropol 122:325–335.
van der Bilt A, Engelen L, Pereira LJ, van der Glas HW,
Abbink JH. 2006. Oral physiology and mastication. Physiol
Behav 89:22–27.
Visalberghi E, Sabbatini G, Stammati M, Addessi E. 2003.
Preferences towards novel foods in Cebus apella: the role of
nutrients and social influences. Physiol Behav 80:341–349.
Williams SH, Wright BW, Truong VD, Daubert CR, Vinyard
CJ. 2005. Mechanical properties of foods used in experimental studies of primate masticatory function. Am J
Primatol 67:329–346.
Wright BW. 2005. Craniodental biomechanics and dietary
toughness in the genus Cebus. J Hum Evol 48:473–492.
Zinner D. 1999. Relationship between feeding time and food
intake in hamadryas baboons (Papio hamadryas) and the
value of feeding time as predictor of food intake. Zoo Biol
18:495–505.
Am. J. Primatol.
Документ
Категория
Без категории
Просмотров
1
Размер файла
66 Кб
Теги
species, experimentov, rate, analysis, ingestion, omnivorous
1/--страниц
Пожаловаться на содержимое документа