Supplementation of ruminants on winter pastures

Supplementation of ruminants on winter pastures

Industry Sector: Cattle and Small Stock

Research focus area: Livestock production with global competitiveness

Research Institute: University of Pretoria

Researcher: Prof Willem.A. van Niekerk PhD (Agric) Animal Science

Research Team:

TitleInitialsSurnameHighest Qualification
ProfLourens. J.ErasmusPhD (Agric) Animal Science
DrA.Hassan
PhD (Agric) Animal Science
MrR.J.Coetzer
MSc (Agric) Animal Science
MrHMynhardtMSc (Agric) Animal Science

Final report approved: 2016

Aims of the project

  • To develop a cost-effective supplementation strategy for ruminants under low quality winter forage conditions
  • To maintain body weight during the wineter season by assessing different sources and levels of nutrients that enhances poor quality roughage utilisation
  • To investigate intake, fiber degradation and microbial protein production when various types and levels of nutrients are supplemented to ruminants kept at maintenance under extensive conditions

Executive Summary

A series of studies was conducted to evaluate differential energy and nitrogen (N) sources as supplemental feed to sheep grazing low quality winter grazing in the High veldt. Knowledge on supplementation under local conditions are limiting as the majority of supplementation studies are funded and performed in the more temperate areas. Results indicated that higher N and energy inclusion levels are necessary to optimize ruminant production under local conditions compared to temperate areas. In addition, the ratio of fermentable energy to available protein is an important parameter in optimizing supplementation programs. It is concluded that the supplementary recommendations from the current feeding tables does not describe the requirements and nutrient quality of the tropical grasses satisfactorily and as such, cannot be used to predict supplementation responses by the tropical forage fed ruminant.  del can be used for further sensitivity analyses and “what if” scenarios as well as a database to answer specific questions.

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SUPPLEMENTATION OF SHEEP GRAZING LOW QUALITY GRASSES WITH UREA AND STARCH

BY:  *H. MYNHARDT, W. A. VAN NIEKERK AND L. J. ERASMUS, UNIVERSITY OF PRETORIA

Every year sheep might lose up to 30% of their summer body weight gain during the dry winter periods in the high veldt.  While these weight losses have an economic impact on its own, it also is associated with an increased susceptibility for diseases and parasitic infestations and decreased reproductive performances. It generally is considered that protein or non-protein nitrogen (NPN) supplementation is necessary to limit these weight losses during these periods. However, due to the type of grass found in the High veldt area of Southern Africa, data is limiting on the effects of supplementation of ruminants grazing these types of grasses (See box: Differences between C4 and C3 grasses). As such, supplementations recommendations derived from current feeding tables seldom satisfy the needs of the grazing ruminant in Southern Africa. Therefore, a series of studies was conducted at the University of Pretoria to determine and quantify the requirements of the ruminant grazing low quality Eragrostis curvula hay commonly found in the Southern Africa High veldt.

* References and correspondence can be obtained from the author: hermanmynhardt@yahoo.com


Box 1: Differences between C4 and C3 Grasses

The acronyms C3 and C4 refer to the first product of the photosynthetic processes in the respective grasses with the first product of photosynthesis in the C3 grass being phosphoglycerate (a 3 carbon structure) while for the C4 plant, the corresponding molecule is a 4 carbon molecule (oxaloacetate). C3 grasses are temperate grasses and are adapted to the temperate regions of the world where rainfall is more constant with maximum temperatures seldom topping 22 OC. In contrast, C4 grasses are more adapted to the subtropical and tropical climates with temperatures frequently topping 25oC during the growth period. These areas also are associated with seasonal droughts and the occasional frost. Due to these extremes in temperatures and seasonal droughts, C4 grasses contain more bundle sheath cells and less available nutrients compared to C3 grasses during all maturity stages. Ruminant production therefore in general is significantly lower in ruminants grazing C4 grasses compared to temperate C3 grasses, especially during the dormant stage of the grass where lignification of the C4 grasses reduces the availability of the nutrients even further. As such, supplementation requirements and responses differ between ruminants grazing these grasses. However, the majority of supplementation studies in the past have been conducted on C3 grasses as it is found more in the European countries where research funding is more available. As such, as more studies conducted on low quality C3 grasses are incorporated in the current feeding tables, supplementation requirements derived from these tables to the low quality tropical forage fed ruminant are not always accurate. As such, the need was established to conduct research through the financial support of the **RMRD-SA on the nutritional requirements of the low quality tropical forage fed ruminant in order to improve ruminant production in Southern Africa.


*RMRD -SA – Red Meat and Research Development, South Africa



Results and Discussion

Forage intake and digestibility was not influenced by either the level of urea or starch supplementation to the wethers. However, CP-balance, measured as CP intake – CP excretion in the faeces and urine, increased from 12.5 g CP/day in the LU wethers up to 70 g CP/day in the EHU wethers. Based on these observations, only the EHU treatment supplied sufficient protein to potentially satisfy the needs of the 50 kg wethers as they require 65 – 70 g CP for maintenance. These recommendations are significantly higher than the recommendations set in the current feeding standards, however, it is in alignment with the observations and recommendations set out by **Leng (1995) studying ruminants grazing tropical grasses in Australia.

Forage intake and digestibility was not influenced by either the level of urea or starch supplementation to the wethers. However, CP-balance, measured as CP intake – CP excretion in the faeces and urine, increased from 12.5 g CP/day in the LU wethers up to 70 g CP/day in the EHU wethers. Based on these observations, only the EHU treatment supplied sufficient protein to potentially satisfy the needs of the 50 kg wethers as they require 65 – 70 g CP for maintenance. These recommendations are significantly higher than the recommendations set in the current feeding standards, however, it is in alignment with the observations and recommendations set out by **Leng (1995) studying ruminants grazing tropical grasses in Australia.

HIGHER LEVELS OF PROTEIN AND ENERGY SUPPLEMENTATION IS NECCESARY TO OPTIMISE THE GRAZING RUMINANT IN THE S.A. HIGH VELDT DURING THE DRY WINTER MONTHS

An important parameter in ruminant nutrition is microbial protein synthesis (MPS) as it gives an indication of the efficiency of the rumen microbes. During the dry winter months, MPS generally decreases due to the lack of available nutrients in the roughages (Leng, 1990, 1995) which decreases the productivity of the animal which is experienced as weight loss by the farmer.  In this study, MPS increased almost 50% from 78 g MPS to 106 g MPS as the level of starch supplemented was increased from 200 (LS) to 280 (HS) g starch/day. This observation is in agreement with suggestions made by Leng, (1990; 1995) that energy is an important nutrient driving MPS in the tropical forage fed ruminant, provided that the protein requirements of the ruminant have been met. Interestingly, energy supplementation for the temperate forage fed ruminant is not always advocated as these grasses contain higher concentrations of water soluble carbohydrates compared to the tropical grass.

Based on the above results, higher levels of both protein and energy supplementation is necessary to optimise ruminant production during the dry winter months in the High Veldt. The question now was asked whether there was an “ideal” quantity of protein and energy to be supplemented to ruminants grazing low quality “tropical” forages.

Graph 1 is a schematic representation of MPS per unit CP intake (MNS: N intake) while Graph 2 represents the mean rumen ammonia nitrogen (RAN) concentration as influenced by the ratio of starch supplemented to available protein intake.

Graph 1

Urea supplementation across all three starch treatments affected the MPS: CP ratio similarly with the ratio decreasing from almost 3 to below 1 where the wethers were supplemented with the higher urea treatments (HU and EHU). It is important to note that alleviated MPS: CP levels (above 1) could be indicative of CP deficiency as more microbial protein was synthesized in the rumen compared to dietary CP intake. The additional CP required to produce the microbial protein under these circumstances is derived from body protein catabolism which in itself, is an inefficient process, resulting in an excessive body weight loss. As such, in this trial, it is suggested that the protein intake of the wethers supplemented with at least 26.4 g urea/day (HU) was sufficient to meet the requirements of the wethers.

Graph 2

An inverse relationship was observed between RAN and the ratio of starch: digestible protein intake (Graph 2) with RAN decreasing and plateau between 5 and 10 mg RAN/ dL rumen fluid as the ratio increased. An inflexion point was observed where RAN increased exponentially to levels as high as 25 and even 30 mg RAN/dL rumen fluid as the ratio decreased below 2: 1. This graph highlights the importance of supplementation of both rumen available energy sources (starch in this instance) as the supplementation of only RDP sources to the ruminant could lead to an increased risk of ammonia toxicity under these circumstances.

Conclusion

The results from this study suggest that the supplementation requirements of 50 kg wethers grazing low quality tropical forages (2.7% CP) differs to the current feeding standards as:

  • Higher levels of protein (urea supplementation up to 26.4 g urea per day per wether or 3% urea of the total DM intake) is necessary to optimise CP balance in the tropical forage ruminant.
  • Starch supplementation (up to 280 g/wether/day or almost 20% of the total DM intake) in addition to urea supplementation is necessary as tropical grasses not only are deficient in protein, but also in easy available energy.
  • For wethers grazing low quality tropical grasses, the ideal ratio of starch supplemented to digestible protein intake lies between 2 and 3: 1.
  • Additional research is necessary to study the effects of other energy sources and protein sources on rumen environment and the production parameters of the tropical forage fed ruminant as these sources might have different availabilities compared to urea and pure starch within the rumen.

The authors wish to thank the Red Meat Industry and Research Development (RMRD) for their financial support of this study.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project –
Willem van Niekerk on willem.vanniekerk@up.ac.za

Genomics for the South African Beef industry

Establishing genomic selection for the South African beef industry

Industry Sector: Cattle and Small Stock

Focus Area: Livestock production with global competitiveness (2)

Research Institute: Department of Animal & Wildlife Sciences, University of Pretoria (UP) and SA Studbook Association

Researcher: Prof Este van Marle-Köster PhD

Research team:

Title Initials Surname Highest Qualification
Dr Japie van der Westhuizen PhD

Final report approved: 2016

Aims of the Project

  • To use high throughput SNP technology to establish reference populations for the SA beef industry.

Executive Summary

The project titled “Establishing genomic selection for the South African beef industry” was conducted at the University of Pretoria, Department of Animal & Wildlife Sciences in collaboration with South African Stud Book and Animal Improvement Association.

The overall aim was to use high throughput SNP technology to establish reference populations for the SA beef industry. To attain this goal, a process for the identification of high impact animals was established, guidelines for sample collection were compiled and genotyping were performed with the available funding using both 80K SNP and 150K SNP GeneSeek (GeneSeek GGP HD) bead chips at GeneSeek (USA. Population structure analyses were performed and parameters for genetic diversity and inbreeding were calculated.

Results has shown that breeds such as the Bonsmara and SA Hereford formed separate clusters while the other indigenous breeds such as the Tuli, Afrikaner and Drakensberger showed a closer relationship. These results are important for future across-breed analyses. The commercial chips also tended to be less informative for the indigenous breeds with regard to the number of SNPs available for analyses, but still had sufficient numbers for application in genomic selection. A substantial number of genotypes have been generated for Bonsmara cattle that have also been phenotypically recorded for the traits of interest.

In this project, the Bonsmara genotypes are currently being applied as a training set for estimation of Genomic Breeding Values (GEBV’s). After GEBVs have been estimated for these animals, validation will commence followed by the roll-out of routine GEBV estimation. This genomic information will provide breeders with an additional, accurate tool for selection of superior stock.

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Genomic selection: a new tool for genetic improvement of SA Livestock

Este van Marle-Köster (PhD Pr.Anim. Sci.) & Carina Visser (PhD Pr.Anim. Sci)

Department of Animal & Wildlife Sciences, University of Pretoria

Introduction

Over the past two decades major discoveries and technological developments in the field of molecular genetics opened up new opportunities for genetic improvement in farm animals that were previously beyond the reach of animal breeders. The bovine genome has been mapped and sequenced and several DNA-marker types were discovered. The discovery of Single Nucleotide Polymorphism (SNP) markers and the concurrent development of appropriate high through-put technology gave rise to commercial SNP chips available for generating genomic information.

SNP markers and genomic selection

The DNA markers used for generating genomic information for genomic selection are single nucleotide polymorphisms (SNP) commonly referred to as “SNIPS”. Each of these markers has two alleles and they occur very frequently across the genome. The Bos Taurus genome has an estimated total of nearly 4 million SNPs. It is currently estimated that a trait of economic importance (i.e. weaning weight, carcass weight, feed conversion ratio etc.) is governed by between 100 and 300 genes. Each of these genes contributes only a small amount to the phenotype that is expressed. In the past, individual genes and markers associated with genes were identified and thus only a very small portion of the phenotypic variation could be explained. By using a very dense SNP panel to genotype animals with, it is assumed that each individual SNP will be associated with at least one gene contributing to the trait of interest. When all the SNP effects are added, they should thus explain the total phenotypic variance that is expressed.

If a number of animals of a specific breed have been genotyped, and their phenotypic records are available, it is possible to draw a correlation between a SNP combination and the level of performance associated with it. This correlation is commonly referred to as the “prediction equation” or “SNP key”. Genomic selection is therefore based upon the basic principle of using the information of many DNA markers and accurate and complete phenotypic records. In practical breeding, the genotypic information (Direct Genomic Value) will be included in the Estimated Breeding Value (EBV) of an animal. In this way, genomic data will be included as an additional source of information together with pedigree and performance records used in routine quantitative analyses. This process is referred to as blending and will result in providing a genomic estimated breeding value (GEBV) for each individual.

Prerequisites for implementation

The implementation of genomic selection is not a simple process and each phase requires careful planning to ensure that the end result will be accurate, useful and cost effective. The first step is the selection of the bulls to form the reference or training population. These bulls should represent the specific breed and include bulls with low, medium and high breeding values with accuracies above 60%. It is important that the traits recorded on these bulls will be the traits that breeders would like to include in selection programs and which form part of the breeding objectives for the breed. A biological sample of these animals should be available and this could be a hair, blood, semen or tissue sample for extraction of DNA.

Once the DNA is available the samples will be analyzed using an appropriate high density commercial chip. In this step the SNP effects based on high density chips and their correlation with the animals’ known performance (EBV values) are established, in order to calculate the prediction equation.

Application of SNP technology

There is no doubt that genomic selection has significant advantages for improvement of farm animal genetics. Dairy cattle thus far have led the way and have experienced some of the advantages of having an added source of information. GEBVs can be obtained in a relative short period after birth compared to a 6-7 year period of progeny testing before a progeny-based EBV becomes available. GEBVs have distinct advantages for dairy cattle with regard to reducing costs on progeny testing and decreasing the generation interval. Genomic technology has been well received by dairy cattle breeders in the USA and Canada and indications are that genomic evaluations will replace traditional evaluations in these countries. The use of genomic selection in selection programs holds the most potential for sex-limited traits, traits that are expressed late in life and traits with low heritability.

In South Africa we are fortunate to have a long history of animal recording for a large number of cattle breeds. This data has routinely been used for EBV calculations and are widely used by South African stud breeders. The current challenge is to ensure the banking of biological samples of animals with desired traits and phenotypes, in order to obtain both molecular and phenotypic records from individuals. Application of GS globally in both the dairy and beef industries has become inevitable and smaller countries with fewer resources, like South Africa, will have to collaborate and carefully plan genetic programs to remain part of the international arena.

If you have any queries, please contact the researcher Prof Este van Marle-Köster PhD on Este.vanMarle-Koster@up.ac.za

Agri Benchmark beef and sheep

Agri Benchmark beef and sheep local and international network

Industry Sector: Cattle and Small Stock

Research focus area: Livestock production with global competitiveness

Research Institute: University of the Free State, Department of Agricultural Economics, Thünen Institute of Farm Economics (Braunschweig, Germany)

Researcher: Mr H.N. van Niekerk MSc

Research Team:

Title Initials Surname Highest Qualification
Mr JF Henning Mcom
Mnr FA Maré MSc
Dr DB Strydom PhD

Final report approved: 2017

Aims of the project

  • To uphold and maintain the Agri Benchmark international and local networks. We established a fully functional local Agri Benchmark network for sheep and beef in South Africa. We are now able to simulate “what if” scenarios and compare beef and sheep farms locally. This is however an ongoing project and will continue to grow as time proceeds and industries develops.
  • To include small scale farmers in the local network and to develop the Agri Benchmark model to be more inclusive. Over time the inclusion of small-scale farmers became unsustainable. This is mainly due to government subsidies differ too much between parties assisting small-scale farmers. The inclusion of 2 beef and 2 sheep farms per year will help the network to grow stronger over time to be more inclusive and representative of South Africa

Executive Summary

The Agri Benchmark initiative refers to international comparisons and benchmarking of productivity, costs and income pertaining to livestock production, especially beef and sheep. This concept can also be applied to South African conditions by establishing a local network for local comparisons and to feed the international model with up to date data for international comparisons.

The local comparisons can also be used to benchmark local farms with each other. The farms are selected according to specific regions and then calculated as typical farms. The modelling and analyses have various features that can be used by beef and sheep producers. The results within the model can be used for further sensitivity analyses and “what if” scenarios as well as a database to answer specific questions.

The Agri Benchmark and UFS project comprises of beef and sheep networks where the aim was to establish a local beef and sheep network. This in turn could feed the international model for comparisons. In 2014, we started data collection for our local beef and sheep network. A total of 17 typical usable farms were included into the local network for comparisons for beef and sheep. In 2015, we had a number of strategic sessions with various roll player to discusses the way forward and how Agri Benchmark can contribute more within the agricultural sector.

It was concluded that there is a need for a local network for beef and sheep. In 2015, we will start with the local beef network to be reprehensive in South Africa. The local network plans to grow each year by 2 to 3 farms, so in due time a well-established network will be in place in South Africa. Benchmarking can play a tremendous role in developing farmers. Once the benchmarking process is started we can benchmark farmers on various productivity levels, this will show where the shortcomings or problems occur within the farming scenario. For example; If we are benchmarking two or more commercial and one of the farms returns in lower then, the other the investigation can start quick and easy. Is it in terms of cost structures, management etc., by this meaning; if there is a low lambing percentage what is wrong? It can be above normal losses; more must be spent on animal medicine or problems with heard composition.

The inclusion of the “what if” scenarios contributed tremendously to the livestock industry, these scenarios include increases in farm level labour costs, increases in production cost and risks in livestock farming (drought, predation, changes in input and output prices). Agri Benchmark helped the livestock industry in obtaining reliable and relevant information and answers to burning questions within the livestock sector. All repots can be seen in the appendixes of this report.

We would like to thank the RMRDT for helping us in achieving our goals and making a difference in South African agriculture. Agri benchmark still remains a project in the Unit of livestock Economics at the University of the Free State. We hope to submit future projects to the RMRDT as the networks grow over time.

To conclude, Agri benchmark is a divers project with a large variety of outcomes as illustrated in the appendixes. Agriculture in South Africa will in the future become more challenging and Agri benchmark can help illuminate champagnes by comparing farming bossiness and running “what if” scenarios to improve agriculture in South Africa.

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Please contact the Primary Researcher if you need a copy of the comprehensive report of this project –
HN van Niekerk on vnierkhn@ufs.ac.za