TEDESCHI Luis's profile
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TEDESCHI Luis

  • Ruminant Nutrition, Texas A&M University , College Station, United States of America
  • Agricultural sustainability, Animal nutrition modelling, Bioinformatics, Cattle production, Ecology, Farming systems, Grazing management , Gut function, Gut microbiology, Mathematical modelling, Microbial ecology, Microbial fermentation, Physiology, Population dynamics, Precision livestock farming, Rumen microbiology, Rumen microbiome , Ruminant nutrition
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Recommendations:  2

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Educational and work
B.S. in Agronomy Engineer, University of São Paulo, Brazil M.S. in Animal and Forage Sciences, University of São Paulo, Brazil Ph.D. in Animal Science, Cornell University Professor in the Department of Animal Science and Texas A&M AgriLife Research. Tedeschi received his bachelor’s degree in Agronomy Engineer from the University of São Paulo (Brazil) in 1991, his master’s degree in Animal and Forage Sciences from the University of São Paulo (Brazil) in 1996, and his doctorate in Animal Science from Cornell University (NY) in 2001. Prior to joining Texas A&M University in 2005, Dr. Tedeschi was a Research Associate at Cornell University (NY) from 2002 to 2005. Tedeschi teaches ANSC 604 Ruminant Nutrition, ANSC 625 Precision Diet Formulation, and ANSC 415/615 Comparative Ruminant Production for undergraduate and graduate students. His research is focused on the integration of scientific knowledge of ruminant nutrition that has been accumulated over the years to solve contemporary problems. This integration is achieved through mathematical modeling, more specifically by adopting the System Dynamics methodology. This modeling methodology is used to build nutrition models and to understand the structure behind complex systems that is responsible for the behavior of the system under different management policies. These nutrition models are being used as valuable tools for solving current and future needs related to environmental pollution and scarcity of resources (i.e., food) through the development of efficient production systems. His areas of interest are energy and nutrient requirements of grazing and feedlot animals, growth biology and bioenergetics, chemical composition and kinetics of fermentation of feeds, modeling and simulation of decision support systems, and evaluation of models (more information at [https://animalscience.tamu.edu/people/tedeschi-luis/](https://animalscience.tamu.edu/people/tedeschi-luis/)). Tedeschi has been an active developer of submodels and contributor to the Cornell Net Carbohydrate and Protein System (CNCPS; [http://nutritionmodels.tamu.edu](http://nutritionmodels.tamu.edu)) and the Cattle Value Discovery System (CVDS;http://nutritionmodels.tamu.edu/cvds.html). He has published more than 150 manuscripts in peer-reviewed journals and book chapters, and presented in more than 60 conferences and workshops worldwide on modeling nutrition. He is a permanent member of the Modeling Committee of the National Animal Nutrition Program (NANP; [http://nanp-nrsp-9.org/](http://nanp-nrsp-9.org/)), which was created to integrate and provide a systemic approach for sharing, collecting, assembling, synthesizing, and disseminating science-based knowledge, educational tools, and enabling technologies on animal nutrition that facilitate high-priority research across agricultural species. He also served on a committee at the National Research Council of the National Academy of Sciences to revise the nutrient requirements for beef cattle. Professional memberships include the American Society of Animal Science, American Dairy Science Association, Brazilian Society of Animal Science, American Registry of Professional Animal Scientists, and the System Dynamics Society.

Recommendations:  2

2019-12-05
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Effects of feeding treatment on growth rate and performance of primiparous Holstein dairy heifers

Recommended by based on reviews by Emilio Mauricio Ungerfeld and 2 anonymous reviewers

Optimizing growth rate of dairy heifers through nutrition to maximize reproduction and production

The idea of altering the growth rate of replacement heifers to improve reproductive and productive indicators of dairy cattle is not new. In the late 1970s, Gill and Allaire [1] indicated that the first parturition between 22.5 to 23.5 months of age yielded the optimum lifetime performance as long as the heifers had adequate body size [2]. Since 1980s, many studies have been conducted to understand the partitioning of energy between growth and lactation, including the impact of growth rates on the heifer puberty [3] as well as growth and development of the mammary gland [4,5]. The senior author of the recommended study has written previously about this research topic [6].
 

In the present manuscript, Le Cozler et al. studied the effect of feeding programs to increase the growth rate of late-born heifers to catch up with the growth of those born earlier in the calving season on their reproductive and productive performance. The authors analyzed 217 heifers for three consecutive years, split into three dietary treatments: control (C), accelerated growth rate from birth to 6 months of age (ID1), or accelerated growth rate from birth to 12 months of age (ID2). In this study, the late-born heifers receiving the ID2 treatment were able to partially reach the bodyweight of the early-born heifers at 24 months of age. In part, the incomplete understanding of the prioritization of the use of energy (and other nutrients) for different physiological stages (e.g., maintenance, growth, lactation, and pregnancy) of the dairy animal [7] undercuts the development of more robust feeding strategies to improve the reproductive and productive performance of the animal. In the recommended study by Le Cozler et al., although there was no impact on reproductive performance among groups, heifers in the group ID2 produced less milk (about 400 kg for the whole first lactation) than heifers in the groups C and ID1, apparently suggesting that energy allocation for growth had priority over that needed for lactation. The question then becomes what would have happened with energy partitioning if energy intake was restricted. Studies like this one are important to shed some light on the prioritization of the use of energy and other nutrients in support of growth, pregnancy, and lactation of dairy animals, and how compensatory growth differs between meat versus dairy growing animals, both physiologically and energetically.

References

[1] Gill, G. S., & Allaire, F. R. (1976). Relationship of Age at First Calving, Days Open, Days Dry, and Herdlife to a Profit function for Dairy Cattle1. Journal of Dairy Science, 59(6), 1131–1139. doi: 10.3168/jds.S0022-0302(76)84333-0
[2] Hoffman, P. C. (1997). Optimum body size of Holstein replacement heifers. Journal of Animal Science, 75(3), 836–845. doi: 10.2527/1997.753836x
[3] Cardoso, R. C., Alves, B. R. C., Prezotto, L. D., Thorson, J. F., Tedeschi, L. O., Keisler, D. H., … Williams, G. L. (2014). Use of a stair-step compensatory gain nutritional regimen to program the onset of puberty in beef heifers. Journal of Animal Science, 92(7), 2942–2949. doi: 10.2527/jas.2014-7713
[4] Sejrsen, K., Huber, J. T., Tucker, H. A., & Akers, R. M. (1982). Influence of Nutrition on Mammary Development in Pre- and Postpubertal Heifers1. Journal of Dairy Science, 65(5), 793–800. doi: 10.3168/jds.S0022-0302(82)82268-6
[5] Sejrsen, K., & Purup, S. (1997). Influence of prepubertal feeding level on milk yield potential of dairy heifers: a review. Journal of Animal Science, 75(3), 828–835. doi: 10.2527/1997.753828x
[6] Le Cozler, Y. L., Lollivier, V., Lacasse, P., & Disenhaus, C. (2008). Rearing strategy and optimizing first-calving targets in dairy heifers: a review. Animal, 2(9), 1393–1404. doi: 10.1017/S1751731108002498
[7] Tedeschi, L. O., and D. G. Fox. 2018. The Ruminant Nutrition System: An Applied Model for Predicting Nutrient Requirements and Feed Utilization in Ruminants. (2nd ed.). XanEdu, Acton, MA."

2019-09-06
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Lactation curve model with explicit representation of perturbations as a phenotyping tool for dairy livestock precision farming.

Recommended by based on reviews by Alberto Atzori, Jennifer Spencer and 1 anonymous reviewer

Developing smart fitting algorithms to identify random perturbations in time-series data

The ability to adequately characterize the lactation curve of livestock is important not only to ensure proper nutrition of the lactating animal but, among many other benefits, it can assist in diagnosing the incidence of diseases, predicting the quantity of milk production, and comparing animals within the herd for managerial strategies such as culling. Eventually, such smart fitting algorithms can lead to improved genetic selection of more productive animals after genetic-unrelated noises are removed from the data, systematically.
The manuscript by Ben Abdelkrim et al. developed and explained an algorithm to detect perturbations in lactation curves of dairy goats. Researchers have been interested in accurately describing lactation curves since the early-1960s. Johansson [1] proposed a nonlinear decay function, Nelder [2] described an inverse polynomial, and Wood [3] proposed the incomplete gamma function to describe milk production of dairy cows. Unfortunately, many of the lactating animals that yielded lactation curves that did not comply with the typical, expected pattern of milk production were usually discarded and, until then, efforts to address this lack of adherence were not conducted. The recommended manuscript provides a different perspective in which rather than discarding the lactation profile, one can model the perturbations of the lactation curve as an attempt to identify possible problems (e.g., mastitis) and minimize their occurrence. Such an algorithm is important to separate females that show resilient attributes from those females that show sustainable attributes, as per existing definitions proposed by Tedeschi et al. [4].
The recommended manuscript proposes the Perturbed Lactation Model to explicitly account for multiple perturbations in the time-series milk production in dairy goats. When perturbations occur in biological processes, a typical negative impact is observed in the animal’s response, but on rare occasions, positive impacts can occur. In this case, the animal responds positively to the perturbation (i.e., responsive), and as a result, there is an increase in their output when compared to unperturbed animals. The recommended manuscript only considered negative impacts due to perturbations in the lactation curve of dairy goats. Future modifications should include positive responses due to perturbations. In this case, animals would be “positively responsive” to perturbations, and examples of such behavior include feed intake and growth curves.

References

[1] Johansson, I. (1961). Genetic Aspects of Dairy Cattle Breeding. University of Illinois Press, Urbana, IL.

[2] Nelder, J. A. (1966). Inverse polynomials, a useful group of multi-factor response functions. Biometrics. 22 (1):128-141. doi: 10.2307/2528220
[3] Wood, P. D. P. (1967). Algebraic model of the lactation curve in cattle. Nature. 216 (5111):164-165. doi: 10.1038/216164a0
[4] Tedeschi, L. O., J. P. Muir, D. G. Riley, and D. G. Fox. (2015). The role of ruminant animals in sustainable livestock intensification programs. Int. J. Sustainable Dev. World Ecol. 22 (5):452-465. doi: 10.1080/13504509.2015.1075441

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TEDESCHI Luis

  • Ruminant Nutrition, Texas A&M University , College Station, United States of America
  • Agricultural sustainability, Animal nutrition modelling, Bioinformatics, Cattle production, Ecology, Farming systems, Grazing management , Gut function, Gut microbiology, Mathematical modelling, Microbial ecology, Microbial fermentation, Physiology, Population dynamics, Precision livestock farming, Rumen microbiology, Rumen microbiome , Ruminant nutrition
  • recommender, manager

Recommendations:  2

Reviews:  0

Educational and work
B.S. in Agronomy Engineer, University of São Paulo, Brazil M.S. in Animal and Forage Sciences, University of São Paulo, Brazil Ph.D. in Animal Science, Cornell University Professor in the Department of Animal Science and Texas A&M AgriLife Research. Tedeschi received his bachelor’s degree in Agronomy Engineer from the University of São Paulo (Brazil) in 1991, his master’s degree in Animal and Forage Sciences from the University of São Paulo (Brazil) in 1996, and his doctorate in Animal Science from Cornell University (NY) in 2001. Prior to joining Texas A&M University in 2005, Dr. Tedeschi was a Research Associate at Cornell University (NY) from 2002 to 2005. Tedeschi teaches ANSC 604 Ruminant Nutrition, ANSC 625 Precision Diet Formulation, and ANSC 415/615 Comparative Ruminant Production for undergraduate and graduate students. His research is focused on the integration of scientific knowledge of ruminant nutrition that has been accumulated over the years to solve contemporary problems. This integration is achieved through mathematical modeling, more specifically by adopting the System Dynamics methodology. This modeling methodology is used to build nutrition models and to understand the structure behind complex systems that is responsible for the behavior of the system under different management policies. These nutrition models are being used as valuable tools for solving current and future needs related to environmental pollution and scarcity of resources (i.e., food) through the development of efficient production systems. His areas of interest are energy and nutrient requirements of grazing and feedlot animals, growth biology and bioenergetics, chemical composition and kinetics of fermentation of feeds, modeling and simulation of decision support systems, and evaluation of models (more information at [https://animalscience.tamu.edu/people/tedeschi-luis/](https://animalscience.tamu.edu/people/tedeschi-luis/)). Tedeschi has been an active developer of submodels and contributor to the Cornell Net Carbohydrate and Protein System (CNCPS; [http://nutritionmodels.tamu.edu](http://nutritionmodels.tamu.edu)) and the Cattle Value Discovery System (CVDS;http://nutritionmodels.tamu.edu/cvds.html). He has published more than 150 manuscripts in peer-reviewed journals and book chapters, and presented in more than 60 conferences and workshops worldwide on modeling nutrition. He is a permanent member of the Modeling Committee of the National Animal Nutrition Program (NANP; [http://nanp-nrsp-9.org/](http://nanp-nrsp-9.org/)), which was created to integrate and provide a systemic approach for sharing, collecting, assembling, synthesizing, and disseminating science-based knowledge, educational tools, and enabling technologies on animal nutrition that facilitate high-priority research across agricultural species. He also served on a committee at the National Research Council of the National Academy of Sciences to revise the nutrient requirements for beef cattle. Professional memberships include the American Society of Animal Science, American Dairy Science Association, Brazilian Society of Animal Science, American Registry of Professional Animal Scientists, and the System Dynamics Society.