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Optimal dietary arginine levels in modern broiler chickens

Published: June 18, 2019
Summary
Introduction Dietary arginine supplementation higher than the recommended levels was shown to improve broiler performance (Murakami et al. 2012; Xu et al., 2018; Zampiga et al., 2018). It suggests that arginine levels needed for maximum performance could be higher in modern broilers, which is probably related to the several functions of arginine on animal metabolism. Besides, arginine enhances...
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Authors:
Iván Camilo Ospina-Rojas
CJ Bio
Ramalho Rodrigueiro
CJ Bio
Lyssa Otani
CJ Bio
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George Entz
19 de septiembre de 2020

The ideal Arg:Lysine Ratio can not always be obtained in some situations.

For example: When the grower Diet is reduced below 20% Crude protein due to feeding program (RWA + VGF birds vaccinated with coccivac B52 to control coccidiosis) and having to use 16 % crude protein wheat with SBM as the main ingredients with no L-arginine to supplement.

So my question is what can be done to reduce some of the negative effects then of a low Arg level in a diet (dig 0.90%)? This problem would be for days 14-26 of age. After that, the CP can be raised.

Looking forward to your comments.

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Iván Camilo Ospina-Rojas
CJ Bio
28 de septiembre de 2020

George Entz, thanks for your question and sorry for my late response.
Recently, it was launched Arg commercially available for feed grade. That´s why I don't see any reason to work with low Arg levels even more in challenged or vaccinated birds. Arginine supplementation has shown to increase antibody titer against some diseases and enhance the antigen-specif immune response. Also, supplemental Arg can help to overcome retarded growth in coccidia-challenged birds.

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George Entz
28 de septiembre de 2020

Thank you for your response. I can't seem to find any commercially available Arginine in western Canada, so far.
If it's not available, Is there a way to reduce the negative effects, of a low arginine:lysine ratio.

Some research is suggesting DEB levels and Methionine source could be factors looking into it.

My thoughts are this, it would be great to use L-Arginine or even feeding a Corn-SBM diet (versus a Wheat-SBM) but cost restriction on both corn and L-arginine makes it so that's it's a hard ROI to use them here.

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Iván Camilo Ospina-Rojas
CJ Bio
30 de septiembre de 2020

I might ask the person in charge of your region about the Arg in feed grade. Pls, feel free to contact me (camilo.ospina@cj.net) to keep you updated. When there is a low Arg/Lys ratio is recommended to avoid high Cl levels, which can increase arginase activity increasing the Arg degradation. As Arg cannot be synthesized by poultry (essential AA), I don't recommend using a low Arg/Lys ratio. The performance improvement in Arg-supplemented diets increases the ROI.

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Juarez Donzele
Universidade Federal de Viçosa - UFV
29 de septiembre de 2020

Iván Camilo Ospina-Rojas, good article, with an enlightening focus. I take advantage of the material presented here, which somehow comes to consolidate some information that we publish, right here at ENGORMIX with the title; Digestible lysine levels obtained by two methods of formulation of diets for 22-to-42-day-old broilers, with a focus on differentiating diets with or without the use of industrial amino acids (Aas). In this study, it was evidenced that diets in which the levels of digestible lysine (LD) (0.90-1.00-1.10 and 1.20%) were obtained by varying corn and soybean meal (full protein) provided better performance of chickens compared to those fed diets in which LD levels, from the baseline level of 0.90%, were achieved using Aas. It should also be considered that in diets supplemented with Aas, because they contain a lower level of CP, they will consequently contain lower levels of amino acids considered non-essential and a reduction in the amount of arginine, which corresponds to that above the ratio arginine x lysine proposed in the protein. ideal for the category of birds being studied. Just as this study showed that the level of arginine can limit the growth of chickens, despite being at the established requirement level, several studies have also shown that some non-essential Aas such as; glutamine, glycine, aspartate can also compromise the performance chickens when using diets with low LD levels. It is concluded, finally, that the practice of reducing CP of the diet with supplementation of Aas must be carried out with great discretion.









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Dr. Andreas Lemme
Evonik Animal Nutrition
15 de octubre de 2020

Dear Camilo, it is always a challenge to compare literature data from different institutes produced under different conditions and to extract conclusions and/or recommendations. However, compiling the data is one issue and you determined (modeled) the SID Arg requirement accordingly. Indeed, changing production conditions might influence optimal concentrations.
You also explained how you determined the optimal SID Arg:Lys ratio and I would have two questions in this context:
1) why did you chose the Brazil tables for SID Lys? There are many more sources/recommendations available globally. However, my point is that the recommended ratio is highly dependent on the Lys level of the reference and thus to a large degree independent from the Arg-research - not considering Lys level of the individual studies considered.
2) you analysed the dose-response by three models and finally averaged the results. Why didn't you decide for one? The outcome of the different models would have tremendous impact on practical feed formulation.
Best regards
Andreas

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Iván Camilo Ospina-Rojas
CJ Bio
20 de octubre de 2020

Dear Andreas, thank you for your comments. Most of the studies used in the review were marginally deficient in Lys levels ensuring that Lys was the second-limiting AA. It has been well known that Lys should be the second-limiting AA in the diet after the investigated AA (Arg) for establishing the optimal ratio between a specific AA and Lys (AA:Lys ratio). This practice improves the validity of the obtained results on AA requirements related to Lys. In the second approach, Lys levels from the individual studies were considered and used to plot the Arg/Lys ratio with the relative BW gain.
I agree with you of comparing literature data under different conditions might influence optimal levels. Even studies done by the same research group using the same facilities might not have the same results. When taking into account many studies into consideration at once, the statistical significance established is much greater than with one study alone. This increases the reliability of the information.
We did not evaluate the goodness of fit, accuracy, and deviation of the models because it was not the objective for this preliminary review we shared in Engormix. Just the R2 is not enough to select the better model. Thus, we decided to use the average result from the three models at this time.
I have the same concern as you about using the AA coef. to estimate SID AA levels from total AAs. That´s why we are preparing a manuscript just using SID AA levels, adding new data recently published, and including non-linear models and artificial neural networks to be published in a peer-reviewed journal. In this case, we will choose the better model using the adjusted coefficient of determination (??2??????), the root-mean-square error (RMSE), the bias, and Akaike's information to evaluate the goodness of fit, accuracy, deviation, and quality of the fitted models, respectively. I will be happy to share it with you when the publication is done. Thanks for your considerations, we will consider them in our paper.
Regards, Camilo

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Juarez Donzele
Universidade Federal de Viçosa - UFV
15 de octubre de 2020
Iván Camilo Ospina-Rojas, I believe that Dr Andreas' considerations are pertinent. As for the information used to obtain the digestible arginine (ARGD): digestible lysine (L D) ratio, I think it should be used only from studies where this determination was made using a diet with a sub-optimal level of LD. This is because in fact the birds demand is Aas gram per day not percentage. In this way, using the diet with suboptimal level of LD, the ARGD: LD ratio would be more accurately determined, since it would avoid the possibility of birds consuming LD above the requirement, which would reflect on the determination of the ideal relationship between these two amino acids. Thus, the use of this methodology, a diet with a sub-optimal level of LD, is more appropriate when compared to the determination of the diet in which the LD level was in the requirement of the birds.
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Alvaro Dubois
Cargill
16 de octubre de 2020
Dear Ospina-Rojas. Congratulation for the very good review and discussion on the importance of arginine in general metabolism. About the mathematical analysis of the data, besides the importance of taking into account lysine levels used in the trials, as mentioned in the other comments, I would like to point that in the regression calculated in fig. 2, a large part of the difference in weight gain and arginine intake comes from the difference in age between the different sets of data and not due to difference in arginine levels used in each paper. In this way, there's a large degree of confounding between the two factors (age and arginine intake). For this reason, although you can establish a large correlation between the two factors, you can not properly define a cause:effect relation. The second approach (fig. 3) is a more proper way of analyzing the results but today mixed models analysis is considered the best way to do it. Still on fig. 3. I couldn't quite figure out what is the regression in red ((LRP+QR). Considering that you would have only one value for it in each study, what is exactly the regression meaning? Thank you.
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Iván Camilo Ospina-Rojas
CJ Bio
20 de octubre de 2020
Dear Alvaro, thank you for your positive feedback. I totally agree with your comment about the age effect. That´s why we run the second approach to standardize and compare performance data from broilers at different ages. However, as I mentioned before, I peer-reviewed journal is being prepared from this preliminary review. More fixed or random factors have been considered to fit multivariate polynomial models. The LRP + QR is the adjustment of data by the quadratic model associated with the linear response plateau (LRP) or broken line. The requirement is estimated by establishing the first point of intersection of the quadratic curve with the broken line plateau. The value of the x-intercept is calculated by matching the quadratic equation with the value of the plateau (y) established by the broken line using the next equation: x = -b ± v b2 – 4a (c-y)/2a, where: X = optimum level; y=plateau; c is the intercept, and a and b2 are the linear and quadratic coefficients, respectively. Please find more information about the calculation of LRP+QR in 2002 Poultry Science 81:485–494. Thank you.
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Juarez Donzele
Universidade Federal de Viçosa - UFV
17 de octubre de 2020

The different considerations that have been made on this matter seem relevant to us. Now regarding my placement, which would be more coherent to use only the works in which diets with sub-optimal level of digestible lysine (LD) were used, I do it because I understand that this is the most accurate methodology for determining the ratio of any amino acid (Aas ) with LD. When I use a diet with a sub-optimal LD level, in addition to the advantage of avoiding a possible excess of LD consumption, which would result in underestimating the relationship, there is also a second advantage that would be related to the fact that, with the use of a sub-optimal level of LD, the accuracy to determine the deficiency of a second Aas, in this case arginine, would be increased. Just check the quadratic regression to see that it is more sensitive to determine the relationship with the LD in the ascendant than at the inflection point of the curve, which represents the animal's requirement. I tried to focus on aspects related to the methodology used in the choice of works.

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Alvaro Dubois
Cargill
23 de octubre de 2020
Dear Ospina-Rojas. Thanks for the reply but my doubt is really about the regression generated with this LRP-QR (97.53= 9.069+1.4213x-0.0056*x2) which is presented in fig. 3. With just one value per paper, regressing it against Arg:Lys ratio sounds a bit odd. Not saying it’s necessarily wrong, but considering that both weight gain and Arg:Lys were standardized based on the point of maximum response, in theory you are setting your requirement as 100% or very close to it. The fact that the quadractic model gave you a much larger requirement is by itself a testimony of the problem of setting requirements based on quadractic curves. LRP model predicted 104% which is much closer to the expected value of 100%. Having this average between the two models diminish but still maintain the problem. Thank you.
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