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ENVIRONMENT, WELL-BEING, AND BEHAVIOR |
Catholic University of Leuven, Faculty of Bioscience Engineering, Biosystems Department, Division Measure, Model & Manage Bioresponses: M3-BIORES, Kasteelpark Arenberg 30, B-3001 Heverlee, Belgium
1 Corresponding author: daniel.berckmans{at}biw.kuleuven.be
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONREFERENCES |
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Key Words: model-based control • broiler growth • growth trajectory
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONREFERENCES |
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Feed restriction in broiler growth as a method for decreasing health problems has been studied comprehensively by researchers (Parks, 1982). It has been proven through the years that body weights of birds that were restricted in the early stage of their growth period reached slightly greater values than those of the ad libitum-fed ones. Broiler chickens that were undergoing compensatory growth exhibited a feed intake greater than normal, and some associated digestive adaptation was observed. Food conversion efficiency and meat yield were improved by early age food restriction (Plavnik and Hurwitz, 1991; Plavnik, and Balnave, 1992; Zubair and Leeson, 1996a,b). In his study, Santoso (2002) suggested that to achieve a complete compensatory growth and better feed conversion ratio, broilers should be restricted at 25% ad libitum for 6 d.
In addition to management advantages, early feed restriction has proven to decrease mortality from all causes, while maintaining optimum body weight and feed conversion (Shlosberg et al., 1991; McGovern et al., 1999; Urdaneta-Rincon and Leeson, 2002; Demir et al., 2004; Salinas-Garcia et al., 2004). Lowered mortality and less leg problems were confirmed by the increased activity levels of the restricted birds (Savory and Maros, 1993; Nielsen et al. 2003). It has been suggested by Lippens et al. (2000) that a mild restriction may offer economic advantages by decreasing mortality. Not only the end weight and mortality but also the meat characteristics of the restricted birds were greatly investigated (Scheideler and Baughman, 1993; Zubair and Leeson, 1994; Palo et al., 1995). It has been shown that feed restriction resulted in alterations of organs and activities of digestive enzymes, confirming a functional adaptation to feed restriction.
Aerts et al. (2003a) introduced a procedure that modeled and predicted the dynamic growth response of broiler chickens to feed intake in real time. This approach allowed the prediction of broiler growth without any prior knowledge of the system and took into account the time-variant nature of the growth process of each flock of birds. Subsequently, they integrated this procedure in a control strategy in which the growth trajectory of broiler chickens during the production process was controlled online. Instead of restricting the birds using a fixed feed quantity during a fixed amount of time, this new strategy was able to alter the growth of birds by letting them follow a previously defined target growth trajectory. The mean relative error between the different predefined target growth trajectories and the realized growth trajectories ranged from 3.7 to 6.0% in 4 trials (Aerts et al., 2003b).
The modern process control techniques in livestock production have been extended in an integrated management system in which not only growth but pollutant emissions and heat production could be controlled (Aerts et al., 2003c; Frost et al., 2003). Being highly advantageous in favor of broiler welfare, this paper aimed to test the growth control strategy in livestock production developed by Aerts et al. in real-time farming conditions using several different target weight trajectories. Another objective was to study the effects of different target trajectories on broiler performance in growth control.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONREFERENCES |
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The experiments were conducted with Ross 308 broilers, mixed sex, obtained from local hatchery (Belgabroed N.V., Merksplas, Belgium). The female breeders were 37 wk old. The birds were vaccinated in the hatchery using a spray administration technique against Newcastle disease (NDW, Poulvac, Fort Dodge Animal Health, Southampton, UK) and infectious bronchitis (IB Primer, Poulvac, Fort Dodge Animal Health). On d 23, they were vaccinated additionally in the stables using a drink water vaccination technique against Gumboro (Bursine 2, Poulvac, Fort Dodge Animal Health) and Newcastle disease (Hipraviar-NDV-clon, Codifar NV, Antwerp, Belgium).
The testing facility contained 2 houses with 8 compartments each, making a total of 16 compartments. Each compartment contained 1,500 birds with a stocking density of 20 birds/m2. In one house, birds were kept on floor pens of wood shavings, and in the other house, birds were kept on peat. Each of the 16 compartments was equipped with 1 weighing platform, and all weighing platforms were connected to an automatic weighing computer (F47, Fancom B.V., Panningen, the Netherlands). All 16 compartments were connected to an automatic feeding system (Minimax, Roxell N.V., Maldegem, Belgium) in which the daily feed intakes of the different compartments were recorded. Water was freely available to all birds.
Mean air temperature was set at 34°C during d 1. Temperature was decreased gradually until 18.4°C was reached at the end of the growth period. Except for the first 5 and the last 4 d, birds were subjected to 18 h of light and 6 h of darkness, in which the intensity of light changed from 5 to 20 lx. One hour of light period was applied to the birds for the first 5 and the last 4 d. The growth periods were carried out for 42 d (August-September, 2005 and October-November, 2005) in the Provincial Centre for Applied Poultry Research, Province Antwerp, Geel, Belgium.
Diets
For the first 9 d, a prestarter diet with 23% protein and 12,106 kJ of AMEn/kg (metabolizable energy) was given. From d 10 until 13, a starter diet with 22% protein and 11,704 kJ of AMEn/kg, and from d 14 to 35, a grower diet with 20% protein and 12,144 kJ of AMEn/kg was offered. The finisher diet, from d 36 to 42, consisted of 19,021% protein and 12,412 kJ of AMEn/kg.
Experimental Design
There were 3 experiments performed during 2 growth periods (42 d). The first one was during August-September 2005, the second during October-November 2005, and the third one during February-March 2006. Each experiment was performed in 2 broiler houses simultaneously. Each house contained 8 compartments, and each compartment housed 1,500 birds.
As seen in Figure 1
, in the first 2 experiments, each house of 8 compartments had 2 ad libitum-fed control groups and 2 replicates of 3 different restricted growth trajectories. Making a 4 x 4 design, each trajectory, including the control group, had 4 repetitions. For these experiments, only Ross 308 birds (mixed sex) were used. For the third experiment, to test responses of different strains in growth control, in addition to the Ross 308 bird, Cobb 500 birds were used. In this experiment, due to organizational reasons, 15 out of 16 compartments were used for experimentation. With a total of 8 compartments for Ross and 7 compartments for Cobb, each strain contained 2 repetitions of ad libitum-fed control group and 2 restricted trajectories. With Ross birds, the third trajectory was repeated twice, whereas with Cobb birds, it could be tested only once.
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The target weight trajectories were some percentage less than the ad libitum weights during the days called maximum restriction days. Because it was almost impossible to expect any chicken to lower its weight suddenly to, for example, to 90% in 1 d (no matter how much it was forced to starve), the depart from the ad libitum curve started at a certain start day, and the target weight decreased linearly and reached the desired percentage of the ad libitum weight during the maximum restriction days. It linearly increased again and reached and followed the ad libitum weight from the end day on. Some trajectories were a bit ambitious, in which 5% more weight was expected at the slaughter age. The restriction strategy in terms of offered amount of feed every day depended on the calculations of the controller and varied even in between different trials with the same target trajectory to grow the birds accurately on target.
In the first experiment, birds were restricted in such a way that they are intended to weigh 1) 90, 2) 85, and 3) 80% of the birds given ad libitum feed with maximum restriction days between 22 and 29. Start day was d 9, and the birds were aimed to reach comparable weights of the ad libitum-fed birds at 41 d of age (Table 1 and Figure 2).
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and Figure 3).
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and Figure 4a and b).
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A graphical user interface was prepared for the user to register every day at 1000 h during the growth period the weight of the birds, the feed intake of the last 24 h, and the mortality of the birds. Weight recorded by the weighing scale and the feed intake measured via the feeding system were given as inputs to the control algorithm, and it calculated the feed advice for the following 24 h. This amount was registered to a feeding computer and offered to the birds for the next 24 h. The number of birds, feed conversion ratio, and cumulative feed intake were calculated and displayed daily in the interface as additional information.
Until the day in which restriction started in both experiments, all the birds, including the control and reference groups, were fed ad libitum. Seventy-five birds randomly chosen from each compartment were weighed manually once every week. The results were compared from the readings of the automatic weighing scale. The mortality rates of all experiments were evaluated starting from d 10 to eliminate any other effects on mortality than feeding regimens. Experiments were done under the norms of the ethical commission of the Catholic University of Leuven.
Statistical Analysis
The error between the reference trajectory and the measured weight was calculated by using mean relative error (MRE) defined as:
where MRE = a percentage; w(t) = the weight measured with the automatic weighing systems at time t (g); r(t) = the reference weight at time t (g); and N = the number of samples (Aerts et al., 2003a,b). The significance of differences in mean values of different variables such as mortality or feed conversion ratio in different groups was tested using the ANOVA method.
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONREFERENCES |
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To be able to follow the 3 target trajectories, in the first experiment, birds were repetitively restricted until d 33. As seen in Figure 5, from reference trajectory 1 (90%, d 22 to 29), the restrictions from d 10 to 22 resulted in accelerated compensatory growth during the consecutive periods of increased feed intake. Weight gain, or in other words the slope of the weight curve, was considerably greater than the ad libitum group (Figure 6) during the same period. Weight gain (%) during d 23 to 26, which corresponds to the compensatory growth period, was for compartment 6 (reference trajectory 1, 90%, d 22 to 29) 30.9%, whereas for compartment 3, it stayed at 24.1%. After d 26, because the restricted birds were above their reference trajectory in compartment 6, they were restricted again one more time during d 27 to 31. Even though another catch-up growth was expected as it was after the first restriction, it has been seen that the birds could not recover from the second restriction and that their weight stayed always lower than the reference trajectory.
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and 8 illustrate that in compartment 7 (reference trajectory 2, 85%, d 22 to 29) and compartment 2 (reference trajectory 3, 80%, d 22 to 29), birds that were restricted in a later phase until d 33 could not exhibit the same catch-up growth, although they were fed ad libitum afterwards. The same pattern in all 3 experiments proved that restrictions after the third week of growth resulted in a decreased growth and significantly lower end weight.
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, it has been shown that as the level of restriction in the reference trajectory increased, the mean relative error between the weight measurements and the reference trajectory increased from 6.9 to 9.2%. However, this increase was not statistically significant (P = 0.02). Cumulative feed consumption (P = 0) and end weight (P = 0) of the restricted groups were significantly lower than the ad libitum group. Although not significant, feed conversion ratios for reference trajectories 1 (90%, d 22 to 29) and 3 (80%, d 22 to 29) were lower than that of the control group (P = 0.69). Average uniformity indexes of the different groups, on the other hand, did not show a significant difference (P = 0.79).
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When the restriction period exceeded d 23, in the second experiment, birds again could not catch up afterwards, and they had lower end weights. Figure 9 demonstrates that due to the fact that the restriction was mild, in compartment 5 (reference trajectory 2, 90%, d 21), birds could follow the target trajectory better than other groups. Because the growth retardation in the trajectories of the second experiment was not lower than 90% of the ad libitum growth, end weights of this experiment were greater than the first one. However, the end weights of the 3 trajectories were, respectively, 13.8, 13.9, and 12% less than the target end weight, indicating that the restrictions were still too severe or in a wrong time period in the growth of the birds (Figure 9, 10, 11, and 12).
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, mean relative error (%) was greater than the first experiment, signifying that the target trajectories were not yet well optimized. Total mortality in the second round was also greater than the first round. Because this was true for the ad libitum group, it could be suggested that the greater mortality was not dependent on the choice of target trajectories, but most was probably caused by environmental factors that affected the growth of all the birds in the farm. Although, it was found that the restricted feed intake in the trajectories enhanced the mortality. Feed conversion ratio of reference trajectory 1 (90%, d 22 to 28) and 3 (90% + 5%, d 19) was lower than the ad libitum group (although not significant, P = 0.57) but did not exhibit an advantage to the feed conversion ratios of the first experiment. Average uniformity index (%) of controlled groups was not significantly different (P = 0.33) from each other but slightly (less than 10%) less than that of the first experiment.
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The third experiment was valuable in getting insight into the response of different strains to the same growth control process. Choice of target trajectories in this round was more delicate. Maximum restriction was limited up to d 16, and standard ad libitum curves and consequently the target trajectories were based on data of 6 growth periods of the 2 strains in the same experimental farm. This was performed with the intention of having more realistic curves that take into account the environmental limitations of the installation on the bird.
As illustrated in Figure 13a and b, there was a big difference between the standard ad libitum growth trajectories of the 2 strains, Ross and Cobb. It was estimated that the Cobb bird would grow 7% more than the Ross bird in the end weight when fed ad libitum. The Cobb bird would grow faster in the beginning, slow down toward the end, but still be heavier than the Ross bird in end weight. In developing the target trajectories, percentage of restrictions or overgrowth was identical but based on the individual ad libitum growth characteristics of the strain. Therefore, each strain had 3 target trajectories.
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, 15, and 16 prove that this performance was repeated in the controlled trajectories. Even though the 3 growth trajectories of the Cobb bird were, respectively, 7, 7, and 11% greater in end weight in favor of Cobb birds, Ross birds resulted in greater (1, 3, 10%) end weights (P = 0.66). Ross birds seemed to be more resistant to feed restrictions, and they could exhibit an accelerated catch-up growth when fed ad libitum afterwards, whereas Cobb birds could not reveal acceleration in growth after a restriction, hence resulting in a lower end weight. This was especially apparent in the severe restriction (80% from ad libitum) of target trajectory 2 (80%, d 12 to 16; Figure 15).
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were lower for Ross birds than those of the previous experiments, indicating that the choice of target trajectories was considerably better. Between 2 strains, mean relative error of Cobb was significantly better (P = 0.0) for trajectories 1 (90%, d 12 to 16) and 3 (90% + 5%, d 12 to 16), where restrictions were milder. Total mortality of ad libitum-fed Cobb birds was slightly greater, but for the controlled groups, it was hard to draw any conclusions as to whether the target trajectory had a significant effect on mortality for each strain.
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Conclusion
In realizing broiler growth control in real time in field conditions, the experiments demonstrated that a great deal of challenge lies not only in choosing the target trajectories but also the accuracy of the sensors and actuators in the control process. These were namely the automatic weighing scale and the feeding system. The difficulty of weighing the birds with an automatic weighing system under farm conditions, in which the scale registered only a sample of birds voluntarily jumping on the scale, reflected much on the results. It could be seen from the hand-weighing that the accuracy of the weighing scale varied, showing less accuracy toward the last week of growth. The mean relative errors of the weighing scale (compared with hand-weighing) were, on average, 6.2, 3.9, and 4.8% for the first, second, and third experiments consequently. The feed given to the birds was regulated by an automatic feeding system, which distributed the fixed amount dependent on the sensors in the feeding pens. The amount of feed left in, not eaten, in the pens as well as in the piping system could not be determined. Therefore, there was occasionally an error of more than 10% in daily measured feed input. These 2 factors resulted in a delayed measurement of the weight response of the bird. Indeed, when the results are compared with previous tests under ideal circumstances (high accuracy) or in laboratory conditions (Aerts et. al, 2003b), it could be seen that the delay, not incorporated in the control, causes difficulties for the system.
In controlling the growth of birds, the choice of the target growth trajectory is crucial; hence, a wrong choice can decrease bird health and production. These tests also demonstrated that the growth control algorithm should also take into account information on the health status of the birds and not only feed and body weight.
Unachievable target trajectories caused the birds to be restricted for an extensive time period. It has been seen from the 3 experiments that the broiler chickens had potential to exhibit a highly accelerated compensatory growth if they were restricted during the first 3 wk of their growth period. Target trajectories, which lead to restrictions after the third week, retarded the growth and resulted in a considerably lower end weight.
It could be clearly concluded that, for Ross-type birds, reference trajectory 3 in the third experiment (90% of ad libitum growth between d 12 to 16 and 5% supplement in end weight; with an end weight of 2,616 g and feed conversion ratio of 1.54) was best in terms of growth control. For Cobb-type birds, reference trajectory 1 in the third experiment (90%, d 12 to 16) was optimum, with an end weight of 2,472 g and a feed conversion ratio of 1.67. Even though the results were also promising for Cobb birds, it would be wiser to carry out more experiments and validate the results accordingly. Growth control offered an innovative management system in the broiler industry, especially in the case of integrated processes in which rearing could be automatically controlled online, resulting in decreased costs of labor.
Received for publication March 13, 2008. Accepted for publication June 13, 2008.
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REFERENCES |
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