No abstract

Meals have long been considered relevant units of feeding behavior. Large data sets of feeding behavior of cattle, pigs, chickens, ducks, turkeys, dolphins, and rats were analyzed with the aims of 1) describing the temporal structure of feeding behavior and 2) developing appropriate methods for estimating meal criteria. Longer (between-meal) intervals were never distributed as the negative exponential assumed by traditional methods, such as log-survivorship analysis, but as a skewed Gaussian, which can be (almost) normalized by log-transformation of interval lengths. Log-transformation can also normalize frequency distributions of within-meal intervals. Meal criteria, i.e., the longest interval considered to occur within meals, can be estimated after fitting models consisting of Gaussian functions alone or of one Weibull and one or more Gaussian functions to the distribution of log-transformed interval lengths. Nonuniform data sets may require disaggregation before this can be achieved. Observations from all species were in conflict with assumptions of random behavior that underlie traditional methods for criteria estimation. Instead, the observed structure of feeding behavior is consistent with 1) a decrease in satiety associated with an increase in the probability of animals starting a meal with time since the last meal and 2) an increase in satiation associated with an increase in the probability of animals ending a meal with the amount of food already consumed. The novel methodology proposed here will avoid biased conclusions from analyses of feeding behavior associated with previous methods and, as demonstrated, can be applied across a range of species to address questions relevant to the control of food intake.

When animals are offered a choice of feeds that are nutritionally complementary, they are able to select a consistent combination of these feeds over long periods of time. Analysis of how such consistent diet choice is achieved, in terms of short-term feeding behavior, may further our knowledge of how animals regulate nutrient intake. Previous work, on meal pattern analysis and on nutrient synchronization, led us to hypothesize that animals may select a consistent diet within a meal. In three experiments cows were offered a choice between high- (H) and low- (L) protein feeds and short-term feeding behavior data were collected using computerized feeders. Feeding behavior was first analyzed in terms of visit characteristics. A greater average daily intake of H, relative to L, was more closely related to the ratio of H visits to L visits than to differences in the intake per visit to feeders supplying H or L. Individual meal criteria were estimated using a mixed-distribution model, and visits were clustered into meals. Cows typically had approximately six meals per day. The observed frequency distribution of meal composition, in terms of the proportion of visits to H feeders, was determined. Subsequently, the observed visits were randomly reclustered into bouts consisting of the same number of visits as were observed in meals, and the frequency distribution of random bout composition was calculated. If frequency distributions of meals and random bouts coincide, then this is evidence that cows do not regulate diet choice within a meal. Comparison of the frequency distributions of meals and random bouts provided no evidence that cows attempted to achieve their long-term average diet composition within a meal. We also investigated whether cows tried to achieve a consistent diet choice within a meal by adjusting their intake per visit, depending on the feed type visited and the proportion of visits to H feeders in a meal. There was no evidence that this occurred. In conclusion, our analyses have shown that cows did not attempt to select within a meal a consistent diet in terms of protein to energy ratio. Indeed, our data and the literature suggest that the timeframe over which the intake of energy and protein is regulated must be greater than a meal in a number of animal species.

The analysis of short-term feeding behaviour may give insights into how food intake is regulated in farm animals. Food intake is often recorded in terms of feeding events, e.g. visits to feeders, which can be clustered into meals. This enables calculation of the probability of cows starting a meal in relation to time since the last meal, which is thought to give insight into intake regulation. Starting probabilities are often calculated after data have been pooled, e.g. across day and night or across individuals. Recent work suggested that such pooling might have strongly affected previously published conclusions. We therefore constructed simulation models to investigate how such pooling affects interpretation of feeding behaviour and consequently the biological significance attached to results.

When cows are offered a choice of foods they are able to select a consistent combination of these foods over long periods of time. Consistent long-term diet choice (DC) is the result of feeding behaviour, which may be regulated in the short-term. The shortest unit of feeding that can be measured is often a visit to a feeder supplying one food type only. These visits are usually clustered into meals, which are the shortest biological unit in which DC can be expressed. Previous work led us to hypothesise that animals may select a consistent diet within meals, thus ensuring nutrient synchronisation in the short-term. Therefore, the aim of this study was to investigate whether long-term average DC was a direct result of cows selecting a consistent diet within meals.

Analysis of short-term feeding behaviour may improve our understanding of food intake regulation and diet choice. Feeding behaviour of animals consists of feeding events separated by non-feeding intervals. Feeding events are often observed to be clustered into bouts that may be called meals. Determining a meal criterion (the longest non-feeding interval which is accepted as part of a meal) allows feeding events to be grouped into meals. Tolkamp & Kyriazakis (1999) presented a model that described three populations of loge-transformed intervals in the form of three normal distributions (Gaussians). These populations represent intervals within meals, with or without drinking, and intervals between meals. This model predicted that the probability of a meal starting, first increased, then decreased, with time since the last meal. This is in contrast to the satiety concept, which predicts that the probability of an animal starting a meal will increase with time since the last meal. This study aims at developing a model that best describes, biologically and statistically, the distribution of non-feeding intervals, thus leading to a more accurate meal criteria.