Blood Metabolites As Markers for the Nutritional Status in Ethiopian Livestock

Blood metabolites as markers for the nutritional status in Ethiopian livestock

Word count: 13.021

Floortje van de Meulengraaf Student number: 01611842

Supervisor: Prof. Dr. ir. Geert Janssens Supervisor: Ketema Worku

A dissertation submitted to Ghent University in partial fulfilment of the requirements for the degree of Master of Veterinary Medicine

Academic year: 2018 - 2019

Ghent University, its employees and/or students, give no warranty that the information provided in this thesis is accurate or exhaustive, nor that the content of this thesis will not constitute or result in any infringement of third-party rights. Ghent University, its employees and/or students do not accept any liability or responsibility for any use which may be made of the content or information given in the thesis, nor for any reliance which may be placed on any advice or information provided in this thesis.

Acknowledgements

This thesis would not have been possible without the help and support of several people, and therefore I would like to include a few words of thanks.

Since my first visit, Africa has a special place in my heart, so I can only say that I am extremely happy that I had the chance to conduct my research in Arba Minch, Ethiopia. For this I would like to first of all thank my promoter Prof. Dr. Ir. Geert Janssens. You were a great help during the writing process, without your feedback and our discussions I would never have remained so sharp. I would also like to thank Dr. Donna Vanhauteghem very much for her distant support when I was in Ethiopia. It was very nice that you were able to help us, time after time, with our frustration in the research. Ketema Worku, as co-promoter, I would like to thank him for his help in Ethiopia. You did not only help with the research but also took us into the Ethiopian culture, which was fantastic. I would like to thank Yisehak Kechero Kebede for his help in Ethiopia itself and to welcome us at the Kulfo campus (College of agricultural sciences).

Then I would also like to thank my companion in Ethiopia. Annet also called Alex, I thought it was great to go on this adventure with you, even if it was sometimes "crying with the cap on" during our research. I wouldn't have wanted to beat anyone else at checkers. While waiting, until the playing monkeys on the roof were gone and we had power again so we could work with "ferry" the spectrophotometer again.

Lisette thanks that you, despite your own busy schedule, could make time to upgrade my master's thesis in the English language. Finally, I would like to thank my parents, family and friends for their support and encouragement during my years of study. I promise not to miss any birthday parties or other special moments from now on.

A part of the financial costs was covered by the VLIR-UOS travel grant 2018.

Table of contents

I Abstract ______6 II Samenvatting ______7 III Introduction ______8 IV Literature survey ______10 IV.1 The “normal” digestion and metabolism of ruminants ______10 IV.1.1 Digestion and metabolism of carbohydrates ______11 IV.1.2 Digestion and metabolism of protein ______11 IV.1.3 Digestion and metabolism of lipids ______12 IV.2 Metabolic interaction in ruminants ______13 IV.3 Metabolic adaptation in tissue in times of negative energy balance. ______16 V Research aims ______19 VI Material and methods ______20 VI.1 Description of the study area ______20 VI.2 Animals ______21 VI.3 Feed ______21 VI.4 Blood sample collection and preparation ______22 VI.5 Analysis ______22 VI.5.1 Spectrophotometer ______22 VI.5.2 Acylcarnitines ______25 VI.5.3 Statistics ______25 VII Results ______26 VII.1 Body condition score ______26 VII.2 Milk yield ______27 VII.3. Spectrophotometer______28 VII.4 Bloodspots ______29 VIII Discussion ______34 IV Conclusion ______36 V References ______37

List of abbreviations

3OHC4 3-hydroxybutyrylcarnitine Acetyl-CoA Acetyl-coenzyme A BCS Body condition score BHBA: Β-hydroxybutyrate C2 Acetylcarnitine C3 Propionylcarnitine masl Meters above sea level NEFA: Non esterified fatty acids SNNPR: Southern Nations, Nationalities, and Peoples’ Region VFA: Volatile fatty acids VLDL: Very low density lipoprotein

I Abstract

Ethiopia has the fifth largest cattle population in the world, with an estimated population of 59.5 million cattle compared to the estimated human population of 107.5 million. Seventy percent of the rural households make a living from livestock farming, mainly pastoral nomadism, from which it can be concluded that livestock farming is of great economic and social importance in the countryside. Due to the lack of pasture management, there is overgrazing and soil erosion, and the land still has to deal with extremely dry periods. All this has a negative effect on livestock productivity. This creates a conflict with the increasing population growth in developing countries and the additional demand for livestock products. If the nutritional status of the cattle and their corresponding deficits are identified, these shortages can be solved, which will have a positive impact on the country's livestock sector and economy. For this research we focused on the region around Arba Minch, located in Southern Nations, Nationalities, and Peoples’ Region (SNNPR). The aim of this research was to evaluate if the approach can indicate nutritional imbalances, of dairy cattle, and the relationship with environmental factors, such as altitude and season, in the Arba Minch region. Blood samples were collected from 128 local dairy cows in 6 different districts (A/zuria, Bonke, Boreda, Chencha, Dereshe and M/abaya), along a transect extending from the lowlands to the highlands, in both seasons (dry and rainy). The body condition score and milk yield of all cows was also determined for both seasons. A spectrophotometer was used to measure the following metabolites: urea, creatinine, triglycerides and non-esterified fatty acids. Dried Serumspots was used to measure the following markers: valine, leucine, acetylcarnitine, free carnitine, propionylcarnitine and 3-hydroxybutyryl-carnitine. The research showed that there are nutritional imbalances, and that these were influenced by the examined environmental factors such as altitude, season and geographical region, in the Arba Minch region. It can concluded that the “simpler” spectrophotometric analyses can be used to estimate the nutritional status of ranging dairy cows, even when compared with more detailed metabolite analyses such as the acylcarnitine profile.

Keywoords: Blood metabolites - Dairy cattle - Ethiopia - Nutritional status

II Samenvatting

Ethiopië heeft de vijfde grootste vee populatie ter wereld, met een geschatte populatie van 59,5 miljoen stuks vee, vergeleken met de geschatte bevolkingsomvang van 107,5 miljoen mensen. Zeventig procent van de plattelandshuishoudens leeft van de veeteelt, vooral van pastoraal nomadisme, waaruit kan worden geconcludeerd dat de veeteelt van groot economisch en sociaal belang is op het platteland. Door het gebrek aan weidebeheer is er sprake van overbegrazing en bodemerosie en heeft het land nog steeds te kampen met extreem droge periodes. Dit alles heeft een negatief effect op de productiviteit van de veestapel. Dit leidt tot een conflict met de toenemende bevolkingsgroei in ontwikkelingslanden en de extra vraag naar dierlijke producten. Als de voedingstoestand van het vee en de bijbehorende tekorten worden vastgesteld, kunnen deze tekorten worden opgelost, wat een positief effect zal hebben op de veehouderijsector en -economie van het land. Voor dit onderzoek hebben we ons gericht op de regio rond Arba Minch, gelegen in de Zuidelijke Naties, Nationaliteiten en Volkerenregio (SNNPR). Het doel van dit onderzoek was om te evalueren of de aanpak kan wijzen op een onevenwichtige voeding van melkvee en de relatie met omgevingsfactoren, zoals hoogte en seizoen, in de Arba Minch regio. Van 128 lokale melkkoeien in 6 verschillende districten (A/Zurië, Bonke, Boreda, Chencha, Dereshe en M/abaya) werden in beide seizoenen (droog en regenachtig) bloedmonsters genomen langs een doorsnede die zich uitstrekt van de laaglanden tot de hooglanden. De body condition score en de melkopbrengst van alle koeien werd ook bepaald voor beide seizoenen. Een spectrofotometer werd gebruikt om de volgende metabolieten te meten: ureum, creatinine, triglyceriden en niet veresterde vetzuren. gedroogde serumspots werden gebruikt om de volgende markers te meten: valine, leucine, acetylcarnitine, vrije carnitine, propionylcarnitine en 3-hydroxybutyryl-carnitine. Het onderzoek toonde aan dat er sprake is van een onevenwichtige voeding, en dat deze wordt beïnvloed door de onderzochte omgevingsfactoren zoals hoogte, seizoen en woreda, in de Arba Minch regio. Het besluit is dat “eenvoudige” spectrofotometrische analyses een goed beeld kunnen geven van de voedingsstatus van vrijgrazend melkvee, zelfs in vergelijking met meer gedetailleerde analyses zoals de bepaling van metabolieten via het acylcarnitineprofiel.

Sleutelwoorden: Bloedmetabolieten - Melkvee - Ethiopië - Voedingsstatus

III Introduction Ethiopia has an estimated population of 107.5 million (Population Reference Bureau, 2018). The total cattle population in Ethiopia is estimated at 59.5 million (CSA, 2017). Almost all cattle are local zebu breeds (Bos indicus); only 1.3% of the national cattle herd are crossbreeds with Jerseys and Holstein- Friesian (Mayberry et al., 2017). They have the fifth largest cattle population in the world (Cook, 2015), and the highest livestock population in Africa (Tolera, 2012). Seventy percent of the rural households make a living from livestock farming, from which it can be concluded that livestock farming is of great economic and social importance in the countryside (MoA and ILRI, 2013; Tolera et al., 2012a). The average milk production of cows is about 1.5 liters per day, with a lactation period of six months on average (CSA, 2008).

In Ethiopia, pastoral nomadism is a common way of life, because it is the cheapest and easiest system to feed animals. Most of the time the same routes are used year after year with the result that vegetation along these routes changes. It is trampled and overgrazing takes place (Alemayehu, 2006b). In addition, there is increased soil erosion. According to Yisehak et al. (2013) there is an association between soil erosion and reduced feed sources in free-grazing cattle and a link with altitude variation. The reduced feed sources have a negative impact on the productivity of cattle (EARO, 2003). Land degradation can have several detrimental consequences: it reduces soil fertility, decreases agricultural productivity and causes a depletion in soil quality and nutrients (Abebayehu, 2010). Apart from soil erosion, there are extremely dry periods that have a negative effect on livestock. During a dry period, households can lose a large number of their animals due to an inadequate feed supply that leads to starvation of the animals (PLI, 2007). These droughts have a great impact on the food supply and economy in Ethiopia.

A general rise in population density, income and increased urbanisation can be seen in developing countries. This will result in an increased demand for livestock products. It is necessary that the global food system improves resource efficiency and environmental performance to ensure sustainability of global food production and consumption (Herrero and Thornton, 2013). This conflicts with the degeneration of land and the consequences it entails. According to Mayberry et al. (2017) there are yield gaps in dairy production in areas in Ethiopia: “But the scale of the yield gaps indicates that there are opportunities to increase production within the constraints of current production systems. It also appears possible to increase production past currently attainable yields. Household modelling showed that milk yields, reproduction, growth rates and survival can be improved through better nutrition and genetics, but the biggest increases will be realised when multiple strategies are combined.” (Mayberry et al., 2017).

According to Herrero and Thornton (2013), climate change will have an influence on agricultural production and the functioning of ecosystems. Climate change has led to an increase in temperature and reduced precipitation, putting the sustainability of livestock farming at risk (Scholtz et al., 2013). While the current selection is mainly focused on productive capacities, in the future it will have to be based on robustness, efficiency, reduced emissive intensity and adaptability to heat stress (Hayes et al., 2013).

Body condition score (BCS) is a tool to aid in the management of nutritional programs in dairy herds (Waltner et al., 1993; Roche et al., 2009). It will tell if the cow is in negative energy balance, but the underlying reason cannot be identified with just measuring BCS. BCS is a visual inspection with optional palpation of certain areas. A score is assigned depending on the system used. It is highly dependent on the performer and therefore there is a lack of sensitivity and accuracy. In addition, many intensive livestock farms use ration calculation. Based on the group of animals and the management, a feed is composed that provides the most efficient production. In developing

countries such as Ethiopia, where cattle are often kept under pastoral nomadism, rationing is impossible. This is because the ruminants graze on pastures where the exact nutritional value is unknown. As the dry season progresses, the quality of the pastures decreases as a result of a decrease in protein content and digestibility. The pastures are used collectively, which often results in less or no investment by the farmers (Tolera et al., 2012b). Blood analysis of metabolites provides more information on nutritional physiology compared to using the body condition score. For this purpose, UV spectrophotometers can be used as well as dried blood spots.

Shortages and seasonal availability of low quality feed remains a major restriction to livestock production in Ethiopia. If all stakeholders, such as livestock farmers and the government, gain insight into the shortages present, a working solution can be found. Solving these shortages can have a positive effect on livestock and economic performance. If we can increase the production of livestock in Ethiopia, it is possible to raise the income of households and improve food security. For that purpose, we need to identify the shortages that limit current production. As Alemayehu mentioned (2006a), “Sustained, economically-advantageous production must be the goal, and that is now more important than ever, because of the growing human population and increasing demands of meat, milk and other animal products.” It is a challenge to monitor the nutritional status of free-range livestock since the nutritional content of the foraged ration is unknown. Measuring blood metabolites at regional level may provide more direct clues as to how to remediate nutrient and energy provision for the animals. For the region around the city of Arba Minch, this information is absent. Therefore, the present study was initiated to screen the nutritional status of ranging cattle. This information will allow targeted solutions for economically and ecologically sustainable livestock production in the region.

IV Literature survey IV.1 The “normal” digestion and metabolism of ruminants Metabolism is a highly coordinated cellular activity that takes place in living organisms (David and Michael, 2008a; McDonald et al., 2011b). Although metabolism embraces hundreds of different enzyme-catalysed reactions, we will focus on the central metabolic pathway, on understanding how the cows’ metabolism works and aim to grasp the significance of the metabolites we are researching. As mentioned by David and Micael (2008a) there are catabolic and anabolic phases in metabolism. Catabolism is the degradative phase, in which organic nutrient molecules are processed into smaller products and during which energy is made. Anabolism or also called biosynthesis, involves converting small precursors into larger more complex molecules and requires energy. In general, catabolic pathways are convergent and anabolic pathways are divergent (fig. 1) But there are also some cyclic pathways as acetate acid cycle (David and Michael, 2008a; McDonald et al., 2011b ).

Figure 1: illustration of the three types of metabolic pathways: catabolic, anabolic and cyclic pathways. (from: David and Michael, 2008a)

Ruminants eat mainly forage and fibrous roughage, which consist of β-linked polysaccharides. In order to process these, they need the microbiota of the rumen (McDonald et al., 2011a). The rumen has its own microflora that uses complex carbohydrates and produces volatile fatty acids (VFA) as well as energy during the process of fermentation. The most important substrate for hepatic gluconeogenesis is propionate, one of the volatile fatty acids produced during ruminal and hindgut fermentation Amino acids also contribute to ruminant gluconeogenesis. With the exception of the ketogenic amino acids, leucine and lysine, all amino acids contribute to gluconeogenesis (Drackley et al., 2001). Alanine and glutamine generally make the greatest contribution (Bergman and Heitmann, 1978), but the branched-chain amino acid valine is even more important as it can be used as a marker for glucogenic amino acid use (Geda, 2016). Valine tells us something about the glucogenic amino acids, while leucine says something about ketogenic amino acids. The valine/leucine ratio says more about the use of the different amino acids. If the ratio increases, the amount of glucogenic amino acids has increased compared to the ketogenic amino acids, this also applies the other way around.

IV.1.1 Digestion and metabolism of carbohydrates Carbohydrates are the body’s most important fuel, but can only be stored in limited amounts. Especially in cows, the rumen will destruct carbohydrates by the process of fermentation resulting in a limited absorption of carbohydrates in the gut (Rice, 1991). Two different ruminal stages are required to metabolize carbohydrates. In the first stage, complex carbohydrates are converted into the intermediate metabolite, pyruvate, by extracellular microbial enzymes. In the second stage, pyruvate is converted into volatile fatty acids (fig. 2)(McDonald et al., 2011a).

Figure 2: Conversion of pyruvate to volatile fatty acids in the rumen. (From McDonald et al., 2011a)

As can be seen in figure 2, methane, acetate, butyrate, propionate, and carbon dioxide are formed during the digestion of carbohydrates. From butyric acid, β-hydroxybutyric acid (BHBA) is formed during transport through the rumen wall. This is then transported along with acetate to various organs and tissues, where they are used as an energy source by being converted into acetyl-CoA. In the liver propionate is converted to glucose (McDonald et al., 2011b). The first step is the transformation into succinyl-CoA. After this it will be included in the citric acid cycle and is converted into malate. This is transported to the cytosol, where it is converted into oxaloacetate and where eventually glucose is formed (McDonald et al., 2011b). The excess of carbohydrates can be converted to fat for storage (Rice, 1991). When there is a shortage of carbohydrates in the diet, other fuels such as protein have to be converted into carbohydrates, or alternatively the body has to switch to another pathway and metabolize her fat reserve.

IV.1.2 Digestion and metabolism of protein Ingested proteins will be catabolized and resynthesized as microbial protein by the microbial fermentation in the rumen. Meeting protein requirements is essential for the animal as well as for its ruminal microflora. If the rumens microflora does not receive enough protein, it will not be able to fulfil its task in providing enough energy for the cow’s metabolism. By supplementing proteins in the ration there may still be an energy deficiency, and if the feed is not adjusted, cows will use body fat for energy and eventually use protein as an energy source (Rice, 1991). The proteins will be hydrolysed to smaller peptides and amino acids, and are transported to the liver. Some amino acids

undergo a further conversion to organic acids, ammonia and carbon dioxide. For example valine, is converted to isobutyric acid (McDonald et al., 2011a). In the rumen amino acids can be converted into ammonia, which can be used together with some small peptides and free-form amino acids as the building blocks of microbial protein. When the degradation of protein is greater than the build- up, ammonia circulates in the blood and is converted to the metabolite urea in the liver. Urea can recirculate back to the rumen if protein intake in the diet is low and can be reused and converted back into ammonia (McDonald et al., 2011a).

Because the concentration of urea can serve as a marker for nutritional status, we look a little further. Since 1991, the DVE-OEB system has been used in the Netherlands and Belgium to evaluate protein uptake and nutrition. The term DVE stands for small intestine digestible protein; this is the protein that is effectively available in the small intestine for absorption. The term OEB stands for unstable protein balance, which represents the balance between microbial protein production from nitrogen and from fermentable organic matter. To minimise nitrogen losses, the OEB should not be too high (Shepers and Meijer, 1998; ILVO 2012). Urea is formed in the liver as a result of a surplus of OEB, and results in an excess DVE and gluconeogenesis of amino acids. (Oltner et al., 1985; Oltner and Wiktorsson, 1983). 70 to 80% of nitrogen losses are excreted as urea in the urine (Bristow et al., 1992). Plasma urea can be used as an indicator of the status of protein metabolism it is a reflection of the amino acid catabolism of protein derived from food. A high concentration of urea can be toxic, according to Butler et al. (1996) a urea-nitrogen concentration higher than 19 mg/dl in the plasma is associated with a reduced pregnancy rate.

IV.1.3 Digestion and metabolism of lipids Triglycerides, from food, has to be hydrolysed to form glycerol and fatty acids. The rumen microbiota can only digest lipids in very limited numbers (McDonald et al., 2011a). Therefore there is no point in adding fat in large quantities to the ration. Triglyceride in serum can be used as a marker for hepatic resynthesis of triglyceride. Additional fatty acids are also formed in the rumen, generally in small quantities, by deamination of amino acids; these are isobutyric acid from valine, valeric acid from proline, 2-methyl butyric acid from isoleucine and 3-methyl butyric acid from leucine (McDonald et al., 2011a). Βeta-oxidation is the pathway for degradation of fatty acids. Long-chain fatty acids are metabolized to acetyl-CoA, which is a substrate for the citric acid cycle (McDonald et al., 2011b). Acetyl-CoA can also be converted into ketone bodies in the liver, which can serve as an alternative source of energy (David and Michael, 2008d).

Most fats form chylomicrons that are transported through the venous blood system. Another part of the fat is hydrolysed to glycerol and low-molecular-weight acids, which can be absorbed directly in the blood. The liver absorbs the chylomicrons and hydrolyses them to form fatty acids. These fatty acids are used for energy production or triglycerides are formed again. These triglycerides are bound to a lipoprotein, forming very low density lipoproteins (VLDL) which are then transported to the various organs and tissues where they can serve as a source of energy (McDonald et al., 2011b). Ruminants have limited ability to secrete Triglycerides as part of VLDL, which can result in a faster accumulation of Triglycerides (Emery et al., 1992; Drackley, 1999). An accumulation of lipids in the liver, mainly triglycerides causes a fatty liver syndrome (Bobe et al.,2004). Several studies have shown that cows with a high triglyceride level in the liver mobilise more body tissue in early lactation.

This is shown by higher NEFA plasma concentrations and the tendency to lower feed intake (Ingvartsen and Andersen, 2000; Sejersen et al., 2012).

IV.2 Metabolic interaction in ruminants Glucose plays an important and central role in metabolism because it is a good energy source (David and Michael, 2008b). Acetate, BHBA and triglycerides can also be a source of energy (fig. 3).

Figure 3: summary of the sources of the major metabolites available to the body. (From: McDonald et al., 2011b). BHBA= β-hydroxybutyric acid; NADPH (+H+)= reduced nicotinamide adenine dinucleotide phosphate.

In order to get energy from glucose, glucose is converted into pyruvate. This reaction is called glycolysis and takes place in the cytoplasm of cells. When reversed and glucose is formed from pyruvate, this reaction is called gluconeogenesis (David and Michael, 2008b; McDonald et al., 2011b). The pyruvate formed can be further metabolized in two ways. It can be converted into acetyl- coenzyme A (acetyl-CoA) which can be processed in the citric acid cycle and takes place in the mitochondria. The second possibility is that pyruvate is reduced to lactate via lactic acid fermentation into lactic acid and take place in muscle cells (David and Michael, 2008b; McDonald et al., 2011b). Another way to metabolize glucose is the pentose phosphate pathway, where glucose is oxidized to pentose ribose 5-phosphates. This can be used to make RNA, DNA, nucleotides and coenzymes (David and Michael, 2008b; McDonald et al., 2011b). Milk production requires the synthesis of lactose from glucose. Glucose is formed via gluconeogenesis, an important substrate for this is propionic acid. Propionic acid is a volatile fatty acid that is formed during rumen fermentation. In addition to propionic acid, acetic and butyric acid are also produced during rumen fermentation, but these volatile fatty acids cannot support gluconeogenesis (Herdt, 2000).

If the blood glucose concentration is sufficiently high, there is more lipogenesis than lipolysis. This suppresses the NEFA release from tissue, causing the blood to have low NEFA concentrations. This is regulated by insulin but also by the direct effect of glucose on fat tissue (Bally et al., 1965; Metz and

Bergh, 1977). The synthesis of triglycerides requires a constant source of glycerol, so glucose is needed. Increased availability of glucose generates more glycerol and triggers lipogenesis. When blood glucose concentrations decrease, which happens during NEB, the source of glycerol is lacking and the mobilisation of NEFA from adipose tissue is stimulated (Herdt, 2000). This results in an increased NEFA concentration in the blood. So the concentration of NEFA in serum tells something about mobilisation of body fat. NEFAs inhibit the use of glucose in peripheral tissues, because NEFA is offered as an alternative fuel source (Boden, 1998).

In the hepatocytes you have cytosolic and mitochondrial cycles. For example, the citric acid cycle and ketogenesis take place in the mitochondria. If there is enough glucose available, this is used in the citric acid cycle. In this situation more glucose is available than is needed for the generation of energy. Tis energy surplus ensures that the citric acid cycle slows down. This results in the intramitochondrial accumulation of intermediate products from the citric acid cycle such as citrate (Herdt, 2000). The excess citrate is transported from the mitochondria and is converted into malonyl CoA. Malonyl CoA inhibits the activity of the enzyme carnitine palmitoyl transferase I (CPTI), which is necessary for the transport of NEFA to the mitochondria for the synthesis of ketone bodies (McGarry and Foster,1980). CPT I therefore has control over the NEFA imported into the mitochondria in cattle and other species (Aiello et al., 1984; Jesse et al, 1986). CPT I therefore provides a link between the carbohydrate status and the synthesis of NEFA in ketone bodies (Cadorniga-Valino et al., 1997). During a NEB, when there is an insufficient amount of glucose present, little glucose flows into the citric acid cycle. As a result, hardly any citrate comes out of the mitochondria for the production of malonyl-CoA. Due to the low concentrations of malonyl-CoA, the activation of CPT-I takes place, with the result that transport of NEFA to the mitochondria is activated (Herdt, 2000). Both the production of glucose and ketone bodies is stimulated by the mitochondrial metabolism of NEFAs (Chow and Jesse, 1992). Acetyl-CoA, a precursor of ketone bodies, stimulates gluconeogenesis by suppressing glucose consumption. Acetyl-CoA is metabolized into the ketone body acetoacetate, which takes place in the mitochondria (Herdt, 2000). Acetoacetate is converted into β-hydroxybutyrate in the cytosol and then leaves the liver. The ketone bodies serve as an extra fuel source for the muscles among other things, This means that less glucose is used as an energy source (Webber et al., 1994) and stimulates blood glucose concentration. Ketone bodies suppress lipolysis and trigger the release of NEFA’s (Metz and Bergh, 1977; Rukkwamsuk et al., 1998).

Carnitine transports activated long-chain fatty acids, released during fat breakdown, from the cytosol to the mitochondria through the formation of acylcarnitines by CPT I (David and Michael ,2008c; Schooneman et al., 2013). In the mitochondrion, acylcarnitines are converted back into free carnitine (C0) and long-chain acylcarnitines that can be oxidised (Ramsay et al., 2001). Acylcarnitines can be measured in serum. Where, from a physiological point of view, diets and fasts influence the acylcarnitine profile of the serum because they reflect the change in flux via the fatty acid oxidation (Soeters et al., 2009). The ratio acetylcarnitine (C2) to free carnitine (C0) in serum tells something about the total metabolic activity. Free carnitine is the balance of de novo synthesis in the body and the esterification degree to acylcarnitines. It can be assumed that de novo synthesis is not too much different between the animals from different groups, so the main explanation for differences will be the different degree of esterification, which is reflected in the fact that low C0 should then correspond with increased C2. If the ratio C2 to C0 is increased, there is a higher metabolic rate. The ratio Propionylcarnitine to acetylcarnitine is a marker for fermentative production of the glucogenic

substrate. The ratio 3-hydroxybutylrylcarnitine to acetylcarnitine reflects the production of ketone bodies per unit of acetyl-CoA.

Figure 4 gives an overview of the possible precursors for the citric acid cycle, which have been discussed earlier.

Figure 4: The citric acid cycle and its precursors (Toward: David and Michael, 2008c)

The urea cycle is used to process ammonia derived from amino acids and can be seen as the detoxification step in metabolism. The carbon skeleton, derived from amino acids, is further processed in the citric acid cycle as we can see in figure 5 (David and Michael, 2008e).

Figure 5: degradation of amino acids. (from David and Michael, 2008e)

The link between these two cycles, as can be seen in figure 6, is important because it is necessary for a complete degradation of amino acids. In the urea cycle the production of arginine from arginino- succinate takes place. This arginino-succinate can also be used via fumarate which is converted into malate, as a malate in the citric acid cycle. The aspartate formed in the citric acid cycle can be included in the urea cycle for the formation of arginino-succinate (McDonald et al., 2011b).

Figure 6: The link between the urea cycle and the citric acid cycle, known as the aspartate-argininosuccinate shunt. (from David and Michael, 2008e)

IV.3 Metabolic adaptation in tissue in times of negative energy balance. During negative energy balance (NEB) there is an increased mobilization of energy reserves, needed to meet the demands of a high milk production. In other words, the energy intake is lower than energy consumption, the cow’s energy requirement is met by hypoglycaemia lipolysis and proteolysis (Roberts et al., 1981) and finally the production of ketone bodies (Herdt, 2000). Whereby lipolysis results in an increased non-esterified fatty acids (NEFA) concentration in the blood, because in the breakdown of triglycerides the ester bond is used and NEFA are formed (Herdt, 2000) The NEB is mostly seen in the first week of lactation, were the cows energy intake obtained from the diet is lower than the energy demands for milk production (Barletta et al., 2017; Ingvartsen and Andersen, 2000; Hammon et al.,2009). The energy reserves are fat and amino acids (Barletta et al., 2017).

When a cow is in NEB it starts to break down body proteins to synthesize as carbohydrates, so important structural proteins and enzymes can become depleted. To counteract this depletion there are adaptive mechanisms, namely the mobilisation of the fat reserve that can serve as an energy source (Herdt, 2000). Fats can easily be converted back to carbohydrates to reach energy requirements when necessary. It can be inferred that body condition score is an important marker and that the associated fat storage is an important source of energy (Rice, 1991).

Fatty tissue consists of adipocyte cells that are filled with triglycerides that are continuously broken down and re-synthesised. Triglycerides are composed of three long chain fatty acids esterified on a glycerol molecule. When triglycerides are broken down, by the process of lipolysis, the ester compound is split and NEFA’s are produced (Herdt, 2000), NEFA’s will be able to serve as an energy source (Opsina et al, 2010). Due to the continuous lipolysis and lipogenesis in the adipocytes, NEFA’s are continuously available for transport. Increased NEFA release occurs as lipolysis increases and there is a decrease in lipogenesis (Herdt, 2000). The increased NEFA concentration in the blood will result in a reduced functioning of the immune system (Mallard et al., 1998), making the cows more susceptible to infections. Metabolic diseases such as ketosis, milk fever and abdominal displacement are then more common (Herdt, 2000; Rukkwamsuk, 1999). So it is associated with negative effects on animal health and production (Hammon et al., 2006; Scalia et al., 2006). In addition, it has been shown that increased NEFA concentrations during the transition period are associated with a reduced pregnancy rate (Ospina, 2010). It has also been described that there is a negative relationship between postpartum NEFA production and the of BCS and fertility (Carvalho et all., 2014; Chapinal et al., 2014; López-Gatius et al., 2003). Barletta et al. (2017) showed that when changes in body condition occur during the transition period, changes in the concentration of NEFA, BHBA follow and fertility is affected. NEFA plasma concentrations in ruminants are influenced by the availability of different energy sources and are a sensitive indicator for fat mobilisation during malnutrition (Reid & Hinks, 1962). Increased NEFA concentration in the blood means that the energy intake from feed is insufficient for the nutritional needs of the cow and therefore inadequate (Drackley, 2000; O’Kelly, 1972). BHBA and NEFA in the blood can be used as indicators for NEB and ketosis (Opsina et al, 2010; Katoh, 2002; Anderson et al. 2002; Herdt, 2000).

The liver is responsible for ensuring that tissues receive a continuous supply of fuel during the fluctuation of absorbed nutrients. The liver determines the distribution of all important body fuels such as glucose, amino acids, propionic acid, butyric acid, NEFA, lactic acid and ketone bodies. In this way, the liver tries to keep the blood glucose concentration stable. It is necessary that the liver can adapt very quickly in times of hypoglycaemia, to process NEFA’s (Drackley et al., 2001). Gluconeogenesis takes place in the liver. If the supply of glucose precursors such as propionic acid and amino acids is high, the excess glucose is stored in the liver in the form of glycogen, however the storage of glycogen is not sufficient to meet the metabolic requirements of the cow (Herdt, 2000). Glycogen reserves indicate the carbohydrate status of the cow (Baird, 1981). If necessary, this glycogen can be mobilised again and converted into glucose. When the glycogen reserves are exhausted in combination with an increased concentration of triglycerides in the liver, ketosis develops (Drackley et al., 1992). As mentioned earlier, during the NEB, large quantities of NEFA are released from fat tissue. These NEFA will circulate in the blood and are available as fuel for most tissues, however the liver will remove a large proportion of them (Bergman, 1971). In the liver, NEFA are re-esterified for triglyceride production or metabolised to ketone bodies. The formation of ketone bodies from NEFA takes place in the mitochondria. Large amounts of triglycerides can be synthesized in the liver during fat mobilisation when NEFA concentrations are high (Herdt et al., 1988). Ketone synthesis can be seen as a way of compensating for the inefficient uptake of glucose precursors. Ketone bodies can be used by the heart, kidneys, skeletal muscles, udder tissue and gastrointestinal tract of ruminants (Heitmann et al., 1987). To remove triglycerides from the liver, lipoproteins, the carriers of triglycerides in the blood, must be synthesized and secreted.

Triglycerides bound to lipoproteins form VLDL (Drackley et al., 2001). VLDL can be used by different tissues for energy or used in the udder for synthesis of milk fat.

Skeletal muscles are the most important site where fuel consumption takes place. During NEB, muscles can use fat in the form of NEFA and ketones as fuel (Boden, 1998). Ruminants are less efficient in using NEFA than other animal species (Palmquist, 1994). Skeletal muscle protein can be mobilised during NEB to support gluconeogenesis. Creatinine in serum comes from catabolism of creatine in muscle tissue as an energy source in the form of phosphocreatine.

The mammary gland and the fetal-placental unit can only use glucose and amino acids as fuel supply. In the mammary gland, glucose is used for lactose synthesis and amino acids for milk protein synthesis. These tissues are therefore not sensitive to insulin (Herdt, 2000).

V Research aims The aim of this research was to identify the nutritional status of dairy cattle in the Arba Minch region in Ethiopia. Blood samples were collected from dairy cattle along a transect extending from the lowlands to the highlands. The blood samples were analysed for nutritional status markers. With the results, the aim was to evaluate if this approach can indicate nutritional imbalances, and the relationship with environmental factors, such as altitude and season, are evaluated. This will be the first step in finding solutions to improve dairy performance in a sustainable way.

VI Material and methods VI.1 Description of the study area This study was conducted in Arba Minch (Amharic for “forty springs”). This is located in Southern Nations, Nationalities, and Peoples’ Region (SNNPR) that is one of the nine regions of Ethiopia (Figure 7). Arba Minch is a 435 kilometres drive from Addis Ababa, the capital of Ethiopia (Google Maps, 2019). More specific it was conducted in five districts (Woredas) of Gamo zone (Chencha, Bonke, Boreda, M/Abaya and Arba Minch Zuria district) and Dereshe special district. These six districts are part of the South Ethiopian Rift Valley.

Figure 7: Study area of Arba Minch (Toward: Girma et al.,2013)

There are three agro-ecological regions in these districts: lowland (Kolla) region, which is within 500- 1500 meters above sea level (masl), middle land (Woyna dega) within 1501-2500 masl and highland (Dega) at above 2500 masl. It receives 600–1600 mm rainfall per annum and the annual temperature ranges from 10°C to 34°C according to (CSA, 2007). The highlands are densely populated and have a high grazing pressure because eighty percent of the cattle population is kept there (Daniel, 1988). In the highlands, better soil is used for cultivation and the steep slopes are used for grazing the animals (Alemayehu, 2004; Tolera et al., 2012b). The midlands have few grazing possibilities and the lowlands therefore have a high grazing pressure and an increased outflow of minerals and nutrients. Each area has their own reasons for specific nutrient and metabolite deficiencies and will therefore differ in the shortages seen in cattle.

65% of the feed is from natural meadows, the rest comes from crop residues and agro-industrial by- products (Birhan and Adugna, 2014; Jahnke and Asemenew, 1983). The crop residues, like cereal straws, are more important in the dry season (Keftasa, 1988). In order to get an impression of what the ruminants are consuming, it is important to focus on the natural pasture. The three agro- ecological regions have different types of forage. The structure of the pastureland is mainly influenced by the user pressure, the topography and the amount and distribution of rainfall (Tolera et al., 2012b). As the altitude increases, the proportion of legumes also increases. Trifolium spp. And Medicago spp. Grow above 2,200 metres. In the lowlands, mainly browse and shrubs can be found (Alemayehu, 2004).

According to Tolera (2012b) this region is mainly overgrown with Acacia commiphora bush land with subdued, perennial grass. The grasses are of good grazing value and include Cenchrus, Chloris, Chrysopogon and Themeda spp. This environment is also rich in tasty forbs and browse, including Blepharis, Tribulus, Acacia, Balanites, Olea, Erythrina, Boswellia, Combrethem, Commiphora and many other species. Bcause the quality of the natural meadow decreases, most tasty grasses have disappeared and have been replaced by indigestible and undesirable species such as Aristida and Sporobolus spp. and poisonous plant species.

VI.2 Animals For this study 128 local dairy cows reared under an extensive production system in one of the six districts, were randomly selected. The cows in each district were selected and grouped into the three agro-ecological conditions: lowland, midland and highland. Table 1 shows an overview of the cows participating in the survey. Most cows were housed in a sheltered area, and were allowed to graze during the day. The animals stayed with their owner during the study. Milk yield of every cow in both seasons are write down. Body condition of the animals was scored from one to nine based on the criteria set by Richard et al. (1986). Body Condition Score (BCS) is a cheap, quick and easy method to compare cattle under different management systems and in different seasons (van Niekerk, 1982; Nicholson and Butterworth, 1986). The score should be performed in the morning when the animals have not had access to food or water during the night (Nicholson and Butterworth. 1986). Reed et al. (1974) demonstrated that there is a positive correlation between the BCS of the animal and the available resources in terms of finance, management skills and grazing opportunities.

Table 1: overview of different study areas and the number of cows that participate. Woreda Number of cows Agro ecology Number of cows High land 1 M/ Abaya 22 Middle land 10 Lowland 11 High land 14 Boreda 43 Middle land 15 Lowland 14 High land 20 Dereshe 60 Middle land 20 Lowland 20 High land 16 A/zuria Woreda 48 Middle land 12 Lowland 20 High land 12 Bonke 36 Middle land 12 Lowland 12 High land 18 Checha 44 Middle land 14 Lowland 12

VI.3 Feed Throughout the whole study, all animals consumed the feed obtained by grazing and what they received from the owner. The main feed consisted of hay or straw as roughage and brewers by- products, or grain residues as concentrate and kitchen waste. It was assumed that animals from the

same district ingested similar diets. It must however be taken into account that the availability of feed resources varies in amount and composition. The free-grazing cattle drank water from the river.

VI.4 Blood sample collection and preparation Blood samples were collected from each animal in both seasons (dry and rainy). The samples were collected preferably in the morning before feeding. The blood was collected from the jugular vein, wearing gloves, using a vacutainer combined with a clot activator serum tube. Each tube contained five to ten ml of blood. The blood was transported to the laboratory in a cool box. The samples in the clot activator serum tubes were centrifuged at 1500 rpm for 10 min to obtain serum and stored at - 20°C until further analysis.

Figure 8: taking blood samples from the jugular vein

Serum samples were analysed for urea, creatinine and triglyceride concentrations by means of a UV spectrophotometer using commercially available kits. The dried bloodspots were transported to Ghent University for acylcarnitine profile analysis.

VI.5 Analysis VI.5.1 Spectrophotometer A spectrophotometer was used to measure the following metabolites: urea, creatinine, triglycerides and non-esterified fatty acids (NEFA). UV-3100PC (VWR) spectrophotometry has been used. Every morning and afternoon, a calibration curve was made to compensate for environmental temperature differences. Kits from Jourilabs (Addis Ababa, Ethiopia) were used for urea, creatinine, triglycerides. Kit from FUJIFILM (California, USA) is used for NEFA.

Creatinine Creatinine forms a coloured complex if it is combined with picric acid in an alkaline solution. The concentration of creatinine is directly proportional with the amount of the complex formed. The absorbant of the samples needs to be measured at 500 nm. For making the calibration curve to follow reagents have been used: R1 Sodium hydroxide, R2 picric acid and R3 standard.

Table 2: calibration curve creatinine Calibrator Prepation Remark

Blank dH2O Add 50 µl of dH2O to cuvette R3 ¼ 50 µl R3 + 150 µl dH2O in Eppendorf Add 50 µl of this mix to cuvette R3 ½ 100 µl R3 + 100 µl dH2O in Eppendorf Add 50 µl of this mix to cuvette R3 R3 Add 50 µl of R3 to cuvette R3 *2 R3 Add 100 µl of R3 to cuvette To measure the serum samples 50 µl of sample was mixed with 500 µl of working reagent in a cuvette. The absorption was measured after 30 (A1) seconds and 90 (A2) seconds. The difference between these 2 absorbance values (ΔA = A2 – A1) was used to calculate the concentration based on the absorbance values of the blank and calibrator. It was calculated as follows: ΔAsample / ΔAR3 x R3 concentration = sample concentration.

Triglycerides The triglycerides were determined after enzymatic hydrolysis with lipases. The indicator is a quinoneimine formed from hydrogen peroxide, 4-aminophenazone and 4-chlorophenol under the catalytic influence of peroxidase (fig. 9)

Figure 9: principle of the assay triglycerides

The absorbance of the samples was measured at 520nm. For making the calibration curve the following reagents were used: R1 reagent, R2 Standard.

Table 3: calibration curve triglycerides Calibrator Prepation Remark

Blank dH2O Add 5 µl of dH2O to cuvette

R21/4 50 µl R2 + 150 µl dH2O in eppendorf Add 5 µl of this mix to cuvette R21/2 100 µl R2 + 100 µl dH2O in eppendorf Add 5 µl of this mix to cuvette R2 R2 Add 5 µl of R2 to cuvette R2*2 R2 Add 10 µl of R2 to cuvette

To measure the serum samples 5 µl of sample was mixed with 500 µl of working reagent in a cuvette. The absorption was measured after incubating for 5 minutes at 37 °C within 1 hour.

Urea Urea is hydrolysed by water and the enzyme urease into ammonia and carbon dioxide. The ammonia produced further reacts with ketoglutarate and NADH in the presence of GLDH to reproduce glutamate and NAD (fig. 10).

Figure 10: principle of the assay urea

The absorbance of the samples was measured at 340 nm. For making the calibration curve the following reagents were used: R1 reagent 1, R2 reagent 2 and R3 standard. Mixing R1 and R2 (4 R1: 1 R2) together forms the working reagent.

Table 4: calibration curve for urea Calibrator Prepation Remark

Blank dH2O Add 5 µl of dH2O to cuvette R3 ¼ 50 µl R3 + 150 µl dH2O in eppendorf Add 5 µl of this mix to cuvette R3 ½ 100 µl R3 + 100 µl dH2O in eppendorf Add 5 µl of this mix to cuvette R3 R3 Add 5 µl of R3 to cuvette R3 *2 R3 Add 10 µl of R3 to cuvette

To measure the serum samples 5 µl of sample was mixed with 500 µl of working reagent in a cuvette. The absorption was measured after 30 seconds and 90 seconds. The difference between these 2 absorbance values (ΔA = A2 – A1) was used to calculate the concentration based on the absorbance values of the blank and calibrator. It was calculated as follows. ΔAsample / ΔAR3 x R3 concentration = sample concentration.

Non esterified fatty accids Non-esterified fatty acids (NEFA) are treated with acyl-CoA synthetase (ACS) in the presence of adenosine triphosphate (ATP) and Coenzyme A (CoA). Thiol esters of CoA then form as acyl-CoA along with by-products adenosine monophosphate (AMP) and pyro-phosphate (PPi). In the second portion of the procedure, the acyl-CoA is oxidized by added acyl-CoA oxidase (ACOD) to produce hydrogen peroxide. In the presence of added peroxidase (POD), this allows for the oxidative condensation of 3-methyl-N-ethyl-N-(ß- hydroxyethyl)-aniline (MEHA) with 4-aminoantipyrine to form a purple colored (Figure 11).

Figure 11: principle of the assay non esterified fatty acids.

The absorbance of the samples was measured at 550nm. For making the calibration curve the following reagents were used: R1a buufer, R1b enzyme, R2a enzyme diluent, R2b maleimide and R2c enzyme reagent. Whereby reagent R1 is formed of 1 vial R1b with 10ml of R1a, and reagent R2 is formed out 1 vial R2b with the entire content of a vial of R2a.

Table 5: calibration curve non esterified fatty acids Calibrator Prepation Remark

Blank dH2O Add 10 µl of dH2O to cuvette CAL 1/4 50 µl CAL + 150 µl dH2O in eppendorf Add 10 µl of this mix to cuvette CAL 1/2 100 µl CAL + 100 µl dH2O in eppendorf Add 10 µl of this mix to cuvette CAL CAL Add 10 µl of CAL to cuvette CAL *2 CAL Add 20 µl of CAL to cuvette

To measure the serum samples 10 µl of sample was mixed with 200 µl of working R1 in a cuvette and incubate at 37 °C for 10 minutes. After 10 minutes add 400 µl of working R2. The absorption was measured after incubating for 10 minutes at 37 °C.

VI.5.2 Acylcarnitines Using dried bloodspots to get information about biomarkers is a relatively cheap and automated method (Demirev, 2013). 35 µL drops of serum were collected on filter paper. Most of the analytes remain stable at room temperature for one week or more, In laboratory freezers the analytes remain stable for long periods of time (Mcdade et al., 2007). Samples were subjected to tandem-mass spectrometry according to the method of Zytkovicz et al. (2001) at the Department of Clinical Biology at Ghent University Hospital. For this research the focus is on the following markers: valine, leucine, acetylcarnitine (C2), free carnitine (C0), propionylcarnitine (C3) and 3-hydroxybutyryl-carnitine (3OHC4).

VI.5.3 Statistics A three-factorial variance of analysis was performed, with woreda (six regions), agro-ecological zone (lowland, midland and highland) and season (dry versus rainy) as independent factors. The model used was a full model, hence including all interactions between the factors. To indicate pairwise differences in case of overall significant effects, a Tukey post-hoc test was performed. All analyses were performed in SPSS version 25.

VII Results Only the significant results are discussed where the significance threshold P≤0.05 is used.

VII.1 Body condition score The BCS of all cows are scored from 1 to 9 in both seasons. The BCS is different between the woredas (P=0.001) and between altitude (P=0.001), but not independently because significant interactions were present between woreda and agro-ecology (P=0.001) and between agroecology and season (P=0.023). The latter interaction appears because the increase in BCS with increasing altitude become more distinct from dry season to rainy season (Figure 12).

7 BCS of the cows 6 5

4 dry season BCS 3 rainy season 2 1 0 lowland middle land high land a b c Agro-ecological zonel Figure 12: Body condition score (BCS) of ranging dairy cows in the Arba Minch region in both seasons at different agro-ecological zones.

Between some woredas there is a difference (P=0.001) this is indicated by the letters of the woreda. This shows that in Dereshe and M/abaya the BCS is the lowest, and in Chenca the BCS is the highest. The interaction between woreda and agro-ecological zone can be seen, because the increase in BCS in each eco-ecological zone is influenced by differences in the woredas (Figure 13).

7 BCS of the cows 6 5

BCS 3 lowland 2 middle land 1 highland 0 A/zuria Bonke Boreda Chencha Dereshe M/abaya b b ab c a a Woredas

Figure 13: Body condition score (BCS) of ranging dairy cows in the different woredas of Arba Minch region at different agro-ecological zones.

VII.2 Milk yield Milk yield shows a threefold interaction between woreda, agro-ecology, and season (P=0.009). This means that the seasonal effects on milk production are different between woredas, and that this interaction in its turn is affected by agro-ecological zone. It can alternatively be explained as that season modulates the fact that the altitude effect is not constant among woredas. The results are shown in Figure 14. There is also a clear difference in milk yield between the different woredas (P=0.001) with the highest production in Chencha and the lowest production in Dereshe being seen.

6 Milk yield of the cows

4 3

2 Milk Milk (L) yield 1 dry 0

rainy

lowlands lowlands lowlands lowlands lowlands lowlands

highlands highlands highlands highlands highlands highlands

middlelands middlelands middlelands middlelands middlelands middlelands A/zuria Bonke Boreda Chencha Dereshe M/abaya cd d bc e a b woredas

Figure 14: Milk yield of ranging dairy cows in the different woredas of Arba Minch region in both seasons at different agro-ecological zones

The milk yield is different between the seasons (P=0.001) and agro-ecological zone (P=0.001). There interaction between season and agro-ecological zone (P=0.001). There is a higher milk yield during the rainy season then dry season. The increase in milk yield with increasing altitude become more distinct from dry season to rainy season (Figure 15).

Milk yield of the animals 3,5 3

2,5 2 1,5 dry season

Milk Milk yield 1 rainy season 0,5 0 lowland middle land High land a b c Agro-ecological zone Figure 15: Milk yield of ranging dairy cows in the Arba Minch region in both seasons at different agro-ecological zones.

VII.3. Spectrophotometer Creatinine and triglycerides are only different between the two different seasons (P=0.001; P=0.001). NEFA is also different between to two seasons (P=0.001). All three are present in higher concentrations in the dry season compared to the rainy season. Urea is also different between the two seasons (P=0.001), only here you can see that this is the opposite of the two previous metabolites. Because urea is higher in the rainy season and lower in the dry season. It shows that the values of urea more or less match the BCS and milk yield. The results are shown in Figure 16.

Concentration of creatinine, triglycerides, urea and 4 NEFA

3,5

3 Dry season 2,5 Rainy season 2 1,5

1 concentration(mg/dl) 0,5 0 Creatinine Triglycerides Urea NEFA metabolites Figure 16: Creatinine, triglycerides, urea and NEFA concentrations of ranging dairy cows in the Arba Minch region in both of the seasons.

The concentration of urea is also different between the woredas (P=0.018). In addition, there is an interaction between agro-ecological zones and woredas (P=0.037). This may mean that the urea concentration in the different woredas is also determined by the height of the agro-ecological area. The results are shown in Figure 17.

1,6 Concentration of urea

1,4

1,2 1 0,8 lowland 0,6 middle land 0,4

concentration(mg/dl) highland 0,2 0 A/zuria Bonke Boreda Chencha Dereshe M/abaya ab ab ab c ab a woredas

Figure 17: creatinine concentration of ranging dairy cows in the different woredas of Arba Minch region at different agro-ecological zones.

There is a difference in NEFA concentration between the woredas (P=0.001). it is a threefold interaction between woreda, agro-ecology and season (P=0.002). This means that the seasonal effects on urea concentration are different between woredas, and that this interaction in its turn is affected by agro-ecological zone. The results are shown in Figure 18. In Dereshe and M/abaya are the highest concentrations NEFA.

4,5 Concentration of non esterified fatty acids

3,5 3 2,5 2 1,5 1 concentration(mg/dl) dry 0,5

0 rainy

lowlands lowlands lowlands lowlands lowlands lowlands

highlands highlands highlands highlands highlands highlands

middlelands middlelands middlelands middlelands middlelands middlelands A/zuria Bonke Boreda Chencha Dereshe M/abaya b b ab a c c Woredas

Figure 18: NEFA concentration of ranging dairy cows in the different woredas of Arba Minch region in both seasons at different agro-ecological zones VII.4 Bloodspots The ratio Valine to Leucine Valine and Leucine are different between de woredas (P=0.001) and between the seasons (P=0.001). Both values are higher during rainy season (Figure 19). Concentration of valine and leucine

180 160 140 120 Dry 100 Rainy 80 60 40 20 Concentration(mg/dl) 0 Valine leucine Figure 19: values of valine and leucine of ranging dairy cows in Arba Minch region at different seasons.

The ratio is different in the two seasons (P=0.001) and between the woredas (P=0.001). But there is also an interaction between the different agro-ecological and woredas (P=0.001). This means that the valine to leucine ratio in the different woredas is influenced by difference in height (Figure 10).

Bonke and Chencha have the lowest ratio, and will also have a higher ketogenic amino acid mobilization, while Boreda and M/abaya have the highest ratio and thus a mobilization of glucogenic amino acids.

1,6 Ratio valine to leucine 1,4

1,2 1 0,8 lowland 0,6 middle land 0,4 high land

Ratio ofvaline/leucine 0,2 0 A/zuria Bonke Boreda Chencha Dereshe M/abaya ab a c a bc c woredas

Figure 20: Ratio of valine to leucine of ranging dairy cows in the different woredas of Arba Minch region at different agro-ecological zones.

The interaction between the different woredas and seasons means that the ratio valine to leucine that differs between the woredas is influenced by the season (P=0.001) (Figure 21). The ratio is higher during dry season then rainy season in all woredas excepting from M/abaya were the ratio is higher during rainy season.

Ratio valine to leucine 1,6

1,4

1,2 1 0,8 0,6 Dry

0,4 rainy ratio valine/leucine 0,2 0 A/zuria Bonke Boreda Chencha Dereshe M/abaya ab a c a bc c woredas

Figure 21: Ratio of valine to leucine of ranging dairy cows in the different woredas of Arba Minch region at different seasons.

The ratio acetylcarnitine to free carnitine The ratio C2 to C0 is different between the woredas (P=0.001) and between the two seasons (P=0.001). But there is also an interaction between the different agro-ecological and woredas (P=0.001) (Figure 22). This means that the ratio C2 to C0 in the different woredas is influenced by difference in height. Boreda has a higher ratio than the rest.

0,2 Ratio of acetylcarnitine to free carnitine 0,18 0,16

0,14

0,12 0,1 lowland 0,08 Ratio C2 /C0 middle land 0,06 high land 0,04 0,02 0 A/zuria Bonke Boreda Chencha Dereshe M/abaya a a b a a a Woreda

Figure 22: Ratio of acetylcarnitine (C2) to free carnitine (C0) of ranging dairy cows in the different woredas of Arba Minch region at different agro-ecological zones

The interaction between the different woredas and seasons means that the ratio C2 to C0 that differs between the woredas is influenced by the season (P=0.001). During the rainy season, a higher ratio is visible, which means that the animals have a higher metabolic rate during this period (Figure 23).

0,25 Ratio of acetylcarnitine to free carnitine

0,2

0,15

0,1 Dry Ratio C2 toC0 rainy 0,05

0 A/zuria Bonke Boreda Chencha Dereshe M/abaya a a b a a a Woreda

Figure 23: Ratio of acetylcarnitine(C2) to free carnitine(C0) of ranging dairy cows in the different woredas of Arba Minch region at different seasons.

The ratio 3-hydroxybutyrylcarnitine to acetylcarnitine 3-hydroxybutyrylcarnitine (3OHC4) is a marker for ketone synthesis. 3-hydroxybutyrylcarnitine is different between woredas (P=0.001), but not significantly different between seasons (Figure 24).

values of 3OHC4

0,05 0,04 0,03 0,02 0,01 3OHC4 0 A/Zuria Bonke Boreda Chencha Dereshe M/Abaya

Concentration (mg/dl) ab a b a b ab Woredas

Figure 24: 3-hydroxybutyrylcarnitine(3OHC4) of ranging dairy cows in the different woredas of Arba Minch region.

The ratio is different between de woredas (P=0.016) and season (P=0.001), but there is also an interaction between the agro-ecological zone and the woredas (P=0.011). This means that the difference in ratio between the different woredas is influenced by the difference in ecological zone (Figure 25).

0,06 Ratio 3-hydroxybutyrylcarnitine to acetylcarnitine

0,05

0,04

0,03 lowland middle land

Ratio 3OHC4/C2 0,02 high land 0,01

0 A/zuria Bonke Boreda Chencha Dereshe M/abaya b ab a ab ab ab Woredas

Figure 25: Ratio 3-hydroxybutyrylcarnitine(3OHC4) to acetylcarnitine(C2) of ranging dairy cows in the different woredas of Arba Minch region at different agro-ecological zones

The ratio ratio 3-hydroxybutylrylcarnitine to acetylcarnitine is different in the seasons (P=0.001) In the rainy season is the lower than in the dry season (Figure 26)

Ratio 3-hydroxybutyrylcarnitine to acetylcarnitine

0,06

0,04

0,02 Ratio 3OHC4/C2

Ratio 3OHC4 Ratio 3OHC4 toC2 dry rainy season Figure 26: Ratio 3-hydroxybutyrylcarnitine(3OHC4) to acetylcarnitine(C2) of ranging dairy cows in Arba Minch region at different seasons.

The ratio propionylcarnitine to acetylcarnitine. Acetylcarnitine (C2) and propionylcarnitine(C3) are both different between the two seasons (P=0,001; P=0.006). The concentrations are higher during the rainy seasons (Figure 27)

Values of acetylcarnitine and propionylcarnitine 1,4

1,2 1 0,8 dry 0,6 rainy 0,4

concentration(mg/dl) 0,2 0 Acetylcarnitine Propionylcarnintine Figure 27: Values of propionylcarnitine(C3) to acetylcarnitine(C2) of ranging dairy cows in Arba Minch region in different seasons.

The ratio propionylcarnitine to acetylcarnitine is different between the woredas (P=0.001. Boreda is lower than A/zuria, Bonke and Chencha and Dereshe is lower than Bonke (Figure 28)

Ratio propionylcarnitine to acetylcarnitine 0,15 0,1 0,05

0 3OHC4 RatioC3/C2 A/zuria Bonke Boreda Chencha Dereshe M/abaya bc c a bc ab abc Woredas

Figure 28: Ratio of propionylcarnitine(C3) to acetylcarnitine(C2) of ranging dairy cows in the different woredas of Arba Minch region.

VIII Discussion The aim of this research is to evaluate if this approach can indicate nutritional imbalances, of dairy cattle, and the relationship with environmental factors, such as altitude and season, in the Arba Minch region.

The condition and milk yield are better in the rainy season than in the dry season, and they increase as the altitude increases. The altitude effect is obviously not because of altitude per se, but because the highlands seem to be more fertile than the lowlands. So we can say that cows with better condition having the ability to produce more milk. This is different from northern scenarios, were almost all cows have a good condition, and loose BCS when producing a lot of milk. NEFA is higher in the lowlands, pointing to more body fat mobilisation, because milk production is actually lowest in the lowlands means that shortage of feed supply is the main driver for this effect. Creatinine, triglycerides and NEFA are distinctly lower in rainy season, whereas urea is higher. The difference between creatinine and urea is remarkable, as they are both markers of protein metabolism. The difference is that creatinine is specific for the degradation of body proteins, while urea can also reflect the amino acid metabolism of protein in the diet. A logical explanation for the difference is that lack of dietary protein in the dry season urges the cattle to break down body protein to enable milk production, whereas in the rainy season, there is the “luxury” of using dietary protein as energy source. The latter may be relatively more needed because of ranging on tropical pasture without additional concentrate feeding as in northern settings. Indeed, tropical pasture does not contain high amounts of fast-fermentable carbohydrates, meaning that propionic acid production is expected to be low. Because direct absorption of glucose is low because of the low dietary content of sugars and starch, and because those carbohydrates would be fermented to volatile fatty acids anyhow, the main glucogenic source would be propionic acid. Propionic acid is likely not produced at high amounts, and then the only possible glucogenic source left, are glucogenic amino acids (e.g. alanine, glycine, valine, isoleucine). Therefore, the high urea concentration in the rainy season may actually mean that amino acids can serve as glucogenic substrate in the citric acid cycle, hence avoiding the development of ketonemie. This agrees with the lower ratio of 3-hydroxybutyrylcarnitine to acetylcarnitine, during rainy season, that reflects the lower production of ketone bodies per unit of acetyl CoA. Both free valine and leucine are also higher in blood from cows in the rainy season. Valine tells us something about the glucogenic amino acids, while leucine says something about ketogenic amino acids. The ratio of valine to leucine shows that the ratio increases in the dry season, likely because valine, as glucogenic amino acid, is relatively more needed to come to the rescue to avoid ketone body synthesis from the mobilized body fat. The latter is demonstrated by the higher concentrations of NEFA, as marker for body fat mobilization, and triglycerides, as marker for hepatic resynthesis of triglycerides in the absence of sufficient glucogenic substrate. In general, it is clear that energy production rates are higher in the rainy season, as demonstrated by the higher concentrations of acetyl carnitine and propionyl carnitine. Also the ratio of acetyl carnitine to free carnitine increased for the same reason. Because the ratio is higher during rainy season what means that there is a higher metabolic rate. The ratio of propionyl carnitine to acetyl carnitine does not change with season, which supports the hypothesis that the fermentability of the rainy season is not substantially higher than that of the dry season, hence urging the cattle to use amino acids as a glucogenic source.

If we look at the different between the woredas, the following parameters are significantly different between the different woredas: BCS, Milk yield, urea, NEFA, Ratio valine to leucine, ratio C2 to C0, Ratio C3 to C2 and ratio 3OHC4 to C2. These values are shown in the table 6 below, where they are arranged from low to high. Each woreda is indicated by its own colour

Table 6: The significant different parameters between the woredas of Arba Minch region. Where woredas are arranged from low to high value. Wored BCS (1 till Milk Urea NEFA Ratio Ratio Ratio Ratio as 9) yield (L) (mg/dl) (mg/dl) valine/ C2/C0 C3/C2 3OHC4/ leucine C2 Lowest Dereshe Dereshe M/abaya Chencha Bonke Chencha Boreda Boreda value M/abaya M/abaya Boreda Boreda Chencha Bonke Dereshe M/abaya Boreda Boreda Bonke A/zuria A/zuria Dereshe M/abaya Bonke Bonke A/zuria Dereshe Bonke Dereshe A/zuria Chencha Chencha A/zuria Bonke A/zuria M/abaya Boreda M/abaya A/zuria Dereshe Highest Chencha Chencha Chencha Dereshe M/abaya Boreda Bonke A/zuria value

It can be seen that in Chencha the highest condition and milk production was obtained. Dereshe had the lowest condition and milk production. This would be in line with the above conclusion that cows in better condition are capable of producing more milk. The NEFA concentration was the highest in Dereshe, indicating more body fat mobilisation, in this region milk production was the lowest which could mean that a lack of food supply was a major cause of this effect. The urea concentration, which reflects the amino acid metabolism of the digestion of proteins from food, was the highest Chencha which may indicate that they can make use of proteins in the diet as an energy source here. With the ratio 3OHC4 to C2 Boreda had the lowest ratio values, which means there was the lowest production of ketone bodies per unit of acetyl-CoA. This would mean that few ketone bodies were produced and therefore the animals were not in negative energy balance; this would be more likely to be the case with animals with the higher condition score and milk production. The ratio C2 to C0 was the highest in Boreda so it is expected that the animals here had a higher metabolic rate. The ratio C3 to C2 was lowest in Boreda, which can be expected to be high because, just like the ratio C2 to C0, it says something about the metabolic rate. The ratio valine to leucine was highest in M/abaya, which would mean that valine in this region was relatively more needed to save the ketone body synthesis from the mobilized fat. Broadly speaking, this is in line with the explanation above; there are minor exceptions that maybe can be explained by the fact that the values in the woredas are often influenced by the season and the altitude.

It can therefore be said that the selected metabolites and metabolite ratios studied in this study seem to change with the three factors examined: season, agro-ecological zone and woreda (district). From which we can conclude that changes in metabolism occur due to season, agro-ecological and woredas. It would therefore be justified to carry out further research into the explanation behind these differences.

We must keep in mind that BCS is a subjective measurement and is therefore subject to personal interpretation. Looking at all the data, some of the average BCS per district were higher in the dry

season than in the rainy season, which is unlikely. In addition, in this research BCS of the animals was scored from one to nine based on the criteria set by Richard et al. (1986). These criteria are designed for beef cattle. It would have been better to determine the BCS with the criteria set by Nicolson and Butterwordt (1986), where the BCS define for the Bos indicus is described. It can also be assumed that the milk yield data is potentially biased, because some farmers do not measure the milk yield and this is done on the basis of an estimate. In addition, the milk yield is a snapshot, which does not take into account where the animal is in the lactation curve, although this does make a real difference.

IV Conclusion It can concluded that the “simpler” spectrophotometric analyses can be used to estimate the nutritional status of ranging dairy cows, even when compared with more detailed metabolite analyses such as the acylcarnitine profile. The research shows that there are nutritional imbalances, and that these are influenced by the examined environmental factors such as altitude, season and woreda, in the Arba Minch region. Further research would be needed in which, for example, the difference in feed in the different areas is also researched because these can explain the difference in metabolic status. It can be concluded that the mapping of metabolite status can be used as a tool to develop targeted nutritional interventions to improve the productivity and health of cows.

V References Abebayehu A., 2010. Soil Fertility Management and Nutrient Balance in Farm Components and Socio- economic Groups: in the selected sites of Gilgel Gibe Catchment of Southwest Ethiopia, p. 75. An MSc thesis Submitted to School of Graduate Studies of Hawassa University Ahmed M., Ehui S., Assefa Y., 2004. Dairy development in Ethiopia. International Food Policy Research Institute, 123 Aiello R. J., Kenna T. M., Herbein J. H., 1984. Hepatic gluconeogenic and ketogenic interrelationships in the lactating cow. Journal of Dairy Science 67:1707-1715

Alemayehu M., 2004. Feed Resources base of Ethiopia: status, limitations and opportunities for integrated development. In: Participatory Innovation and Research: Lessons for Livestock Development, Proceedings of the 12th annual conference of the Ethiopian Society of Animal Production (ESAP) held in Addis Ababa, Ethiopia, August 12-14, 2004

Alemayehu M., 2006a. Introduction. In Range Management for Eastern Africa: Concepts and Practices. RPSUD, Addis Ababa University Press, Addis Ababa, Ethiopia, pp 1-6 Alemayehu M., 2006b. Primary production and cycling. In Range Management for Eastern Africa: Concepts and Practices. RPSUD, Addis Ababa University Press, Addis Ababa, Ethiopia, pp 15-19 Andersen J. B., Mashek D. G., Larsen T., Nielsen M. O., Ingvartsen K. L., 2002. Effects of hyperinsulinaemia under euglycaemic condition on liver fat metabolism in dairy cows in early and mid- lactation. Journal Veterinary Medicine A Physiology Pathology, Clinical Medicine. 49:65–71

Baird G.D., 1981. Metabolic modes indicative of carbohydrate status in the dairy cow. Federation Proceedings 40:2530

Bally P.R., Kappeler H., Froesch E.R., 1965. Effect of glucose on spontaneous stimulation of lipolysis in isolated adipose tissue. A potential regulatory mechanism. Annals of the New York Academy of Sciences 131:143-156

Barletta R.V., Maturana Filho M., Carvalho P.D., Del Valle T.A., Netto A.S., Rennó F.P., Mingoti R.D., Gandra J.R., Mourão G.B., Fricke P.M., Sartori R., Madureira E.H., Wiltbank M.C., 2017. Association of changes among body condition score during the transition period with NEFA and BHBA concentrations, milk production, fertility, and health of Holstein cows. Theriogenology 104, 30–36

Bergman E.N., 1971. Hyperketonemia, ketogenesis and ketone body metabolism. Journal of Dairy Science 54:936-940

Bergmann E.N., Heitmann R.N., 1978. Metabolism of amino acids by the gut, liver, kidneys and peripheral tissues. Federation Proceedings, 37:1228-1232

Birhan M., Adugna T., 2014. Livestock Feed Resources Assessment, Constraints and Improvement Strategies in Ethiopia. Middle-East Journal of Scientific Research 21:616-622

Bobe, G., Young J. W., Beitz D. C., 2004. Invited review: Pathology, etiology, prevention, and treatment of fatty liver in dairy cows. Journal of Dairy Science 87:3105–3124

Boden G., 1998. Free fatty acids (FFA), a link between obesity and insulin resistance. Frontiers in Bioscience 3:D169-175

Bristow A.W., Whitehead D.C., Cockburn J.E., 1992. Nitrogenous constituents in the urine of cattle, sheep and goats. Journal of the Science of Food Agriculture. 59:387–394

Butler, W.R., Calaman, J.J., Beam, S.W., 1996. Plasma and milk urea nitrogen in relation to pregnancy rate in lactating dairy cattle. Journal of Animal Science 74, 858–865

Cadorniga-Valino C., Grummer R.R., Armentano L.E., Donkin S.S., Bertics S.J., 1997. Effects of fatty acids and hormones on fatty acid metabolism and gluconeogenesis in bovine hepatocytes. Journal of Dairy Science 80:646-656

Carvalho P.D., Souza A.H., Amundson M.C., Hackbart K.S., Fuenzalida M.J., Herlihy M.M., Ayres H., Dresch A.R., Vieira L.M., Guenther J.N., Grummer R.R., Fricke P.M., Shaver R.D., Wiltbank M.C., 2014. Relationships between fertility and postpartum changes in body condition and body weight in lactating dairy cows. Journal of Dairy Science 97: 3666-3683

Chapinal N, LeBlanc SJ, Carson ME, Leslie KE, Godden S, Capel M, et al.2012. Herd- level association of serum metabolites in the transition period with disease, milk production, and early lactation reproductive performance. Journal of dairy science, 95:5676-5682

Chow J. C., Jesse B. W. 1992.Interactions between gluconeogenesis and fatty acid oxidation in isolated sheep hepatocytes. Journal of Dairy Science 75:2142-2148

Cook R., 2015. World Cattle Inventory: Ranking of countries. Farm Journal. Available at: www.cattlenetwork.com/world-cattle-inventory-ranking-countries-fao (laatst geconsulteerd op 10 augustus 2018) CSA (Central Statistical Agency), 2007. Federal Democratic Republic of Ethiopia, Agricultural sample Survey, Report on livestock and livestock holding characteristics. Statistical Bulletin No. 388, Addis Ababa Ethiopia (2):12-16 CSA (Central Statistical Agency), 2008. Agricultural sample survey 2007/08. Volume II. Report on livestock and livestock characteristics (private peasant holdings). CSA, Addis Ababa, Ethiopia CSA (Central Statistical Agency), 2017. Agricultural sample survey, report on livestock and livestock characteristics (private peasant holdings) 2 Reported by USAID Daniel, K. 1988 Role of crop residue as livestock feed in Ethiopian highlands. In: African Forage Plant Genetic Resources , Evaluation of Forage Germplasm and Extensive Livestock Production Systems. Production System. Proc. Third Workshop at International Conference Centre, Arusha, Tanzania, pp. 430-439 David L.N., Michael M.C.,2008a. Bioenergetics and metabolism. In: Principles of Biochemistry, fifth edition.W. H. Freeman and company, NY, USA, pp 485-488 David L.N., Michael M.C.,2008b. Glycolysis, Gluconeogenesis and the pentose phosphate pathway. In: Principles of Biochemistry, fifth edition.W. H. Freeman and company, NY, USA, pp 527-568 David L.N., Michael M.C.,2008c. The citric acid cycle. In: Principles of Biochemistry, fifth edition.W. H. Freeman and company, NY, USA, pp 615-646 David L.N., Michael M.C.,2008d. Fatty acid catabolism. In: Principles of Biochemistry, fifth edition.W. H. Freeman and company, NY, USA, pp 647-672

David L.N., Michael M.C.,2008e. Amino acid oxidation and the production of Urea. In: Principles of Biochemistry, fifth edition.W. H. Freeman and company, NY, USA, pp 673-706 Demirev P. 2013. Dried blood spots: analysis and applications. Analytical Chemistry, 85, 779−789 Drackley J.K, Overton T.R., Douglas G.N., 2001. Adaptations of glucose and long-chain fatty acid metabolism in liver of dairy cows during the periparturient period. Journal of Dairy Science ;84:E100- 112 Drackley J.K., 2000. Use of NEFA as a tool to monitor energy balance in transition dairy cows. Illinois Dairy Days. Drackley J.K., Richard M.J., Beitz D.C., 1992. Metabolic changes in dairy cows with ketonemia in response to feed restriction and dietary 1,3-butanediol. Journal of Dairy Science 75:1622-1634 Drackley J.K., 1999. ADSA Foundation Scholar Award. Biology of dairy cows during the transition period: The final frontier?. Journal of Dairy Science, 82:2259–2273 EARO (Ethiopian Agricultural Research Institute), 2003. National Pastoral and Agro- pastoral Strategic Research Planning Document. Addis Ababa, Ethiopia. Emery, R.S., Liesman J.S., Herdt T.H., 1992. Metabolism of long chain fatty acids by ruminant liver. Journal of Nutritrion. 122:832–837 Geda, 2016. Nutritional Strategies to Cope with Mildly Elevated Water Temperature in Fish. PhD thesis, Faculty of Veterinary Medicine, Ghent University Girma M., Yaya Y., Gebrehanna E., Berhane Y., Lindtjorn B., 2013. Lifesaving emergency obstetric services are inadequate in south-west Ethiopia: A formidable challenge to reducing maternal mortality in Ethiopia. BMC health services research. 13. 459 Google Maps (2019) Googlemaps. Available at: https://www.google.nl/maps/dir/Addis+Ababa,+Ethiopië/Arba+Minch,+Ethiopië/@7.5040197,37.22 89991,8z/data=!3m1!4b1!4m14!4m13!1m5!1m1!1s0x164b85cef5ab402d:0x8467b6b037a24d49!2m 2!1d38.7577605!2d8.9806034!1m5!1m1!1s0x17babc91df1c1f4b:0x192439451e905b6a!2m2!1d37.5 641095!2d6.0206054!3e0(Accesed: 12 july 2019) Hammon D.S, Evjen I.M, Dhiman T.R, Goff J.P, Walters J.L. 2006. Neutrophil function and energy status in Holstein cows with uterine health disorders. Veterinary Immunology and Immunopathology ;113:21-29 Hammon, H.M., Stürmer G., Schneider F., Tuchscherer A., Blum H., Engelhard T., Genzel A., Staufenbie R.l., Kanitz W., 2009. Performance and metabolic and endocrine changes with emphasis on glucose metabolism in high-yielding dairy cows with high and low fat content in liver after calving. Journal of Dairy Science. 92:1554–1566 Hansen, P.J., 2004. Physiological and cellular adaptations of zebu cattle to thermal stress. Animal Reproduction Science. 82, 349–360 Hayes, B.J., Lewin, H.A., Goddard, M.E., 2013. The future of livestock breeding: genomic selection for efficiency, reduced emissions intensity, and adaptation. Trends Genetics 29, 206–214. Heitmann R.N., Dawes D.J., Sensenig S.C. 1987. Hepatic ketogenesis and peripheral ketone body utilization in the ruminant. Journal of Nutrition 117:1174-1180

Herdt T.H. 2000. Ruminant adaptation to negative energy balance. Veterinary Clinics of North America: Food animal practice;16:215-30 Herdt T.H., Wensing T., Haagsman H.P., et al., 1988. Hepatic triacylglycerol synthesis during a period of fatty liver development in sheep. Journal Animal Science 66:1997-2013 Herrero M., Thornton P.K., 2013. Livestock and global change: emerging issues for sustainable food systems. Proceedings of the National Academy of Sciences, 110, 20878–20881 ILVO, 2012. Eiwit. In: Melkveevoeding, derde druk. Department landbouw en visserij, Brussel, België. pp 9-14 Ingvartsen K.L., Andersen J.B., 2000. Integration of metabolism and intake regulation: A review focusing on periparturient animals. Journal of Dairy Science. 83:1573–1597 Jahnke, H.E., Asemenew G., 1983. Ethiopian highlands reclamation study. An assessment of the recent past and present livestock situation in the Ethiopian highlands. Land Use Planning and Regulatory Department, Ministry of Agriculture and Food and Agriculture Organization. Addis Ababa, Working Paper 8 Jesse B. W., Emery R. S., Thomas J. W. 1986. Control of bovine hepatic fatty acid oxidation. Journal of Dairy Science 69:2290-2297 Katoh, N,. 2002. Relevance of apolipoproteins in the development of fatty liver and fatty liver-related peripartum diseases in dairy cows. Journal of Dairy Science. 64:293–307 Keftasa D., 1988. Role of crop residues as livestock feed. In Ethiopian highlands in Pasture Network for Eastern and Southern Africa (PANESA) . African forage plant genetic resources, evaluation of forage germplasm and extensive livestock production systems. Proceedings of the Third Workshop held at the International Conference Centre, Arusha, Tanzania, 27-30 April 1987. ILCA, Addis Ababa. López-Gatius F, Yániz J, Madriles-Helm D., 2003. Effects of body condition score and score change on the reproductive performance of dairy cows: a meta-analysis. Theriogenology;59:801-812 Mallard B.A., Dekkers J.C., Ireland M.J., Leslie K.E., Sharif S., Lacey Vankampen C., Wagter L., Wilkie B.N., 1998. Alteration in immune responsiveness during the peripartum period and its ramification on dairy cow and calf health. Journal of dairy science;81:585-595 Mayberry D., Ash A., Prestwidge D., Godde C.M., Henderson B., Duncan A., Blummel M., Ramana Reddy Y., Herrero M., 2017. Yield gap analyses to estimate attainable bovine milk yields and evaluate options to increase production in Ethiopia and India. Agricultural Systems. 155, 43–51. Mcdade T.W., Williams S., Snodgrass J. J., 2007. What a drop can do: dried blood spots as a minimally invasive method for integrating biomarkers into population-based research. Demography. 444(4), 899–925 McDonald P., Edwards R.A, Greenhalgh J.F.D., Morgan C.A., Sinclair L.A., Wilkinson R.G., 2011a. Digestion. In Animal nutrition, seventh edition. Pearson, Amsterdam, Nederland. pp 156-191 McDonald P., Edwards R.A, Greenhalgh J.F.D., Morgan C.A., Sinclair L.A., Wilkinson R.G., 2011b. Metabolism. In Animal nutrition, seventh edition. Pearson, Amsterdam, Nederland. pp 192-234 McGarry J.D., Foster D.W., 1980. Regulation of hepatic fatty acid oxidation and ketone body production. Annual Review of Biochemistry, 49:395-420

Metz S.H.M., Bergh-S.G., 1977. Regulation of fat mobilization in adipose tissue of dairy cows in the period around parturition. Netherlands Journal of Agricultural Science 25:198-211 MoA and ILRI, 2013. Review of past policies and strategies for livestock in Ethiopia. Addis Ababa, Ethiopia, Ministry of Agriculture and International Livestock Research Institute MOARD (Ministry of Agriculture and Rural Development), 2007. Crop development department, crop variety register. Issue No. 10. MOARD, Addis Ababa, Ethiopia. pp 167-169 Nicholson M.J., Butterworth M.H., 1986. a Guide To Body Condition Scoring of Zebu Cattle. International livestock centre for Africa, Addis Ababa O’Kelly J. 1968. Comparative studies of lipid metabolism in Zebu and British cattle in a tropical environment. I. Plasma lipid levels of grazing cattle. Australian journal of biological sciences 21, 1013- 1024 O'Kelly J.C. 1972. Seasonal variations in the plasma lipids of genetically different types of cattle: grazing steers. Comparative Biochemistry and Physiology Part B: Comparative Biochemistry. 43, 283- 394 Oltner R., Emanuelson M., Wiktorsson H., 1985. Urea concentrations in milk in relation to milk yield, live weight, lactation number and amount and composition of feed given to dairy cows. Livestock Production Science 12, 47–57 Oltner R., Wiktorsson H., 1983. Urea concentrations in milk and blood as influenced by feeding varying amounts of protein and energy to dairy cows. Livestock Production Science 10, 457–467 Ospina P.A., Nydam D.V., Stokol T., Overton T.R., 2010. Associations of elevated nonesterified fatty acids and b-hydroxybutyrate concentrations with early lactation reproductive performance and milk production in transition dairy cattle in the northeastern United States. Journal of Dairy Science;93:1596-603 Palmquist D.L., 1994. The role of dietary fats in efficiency of ruminants. Journal of Nutrition 124:1377S-1382S Pereira A.M.F., Titto E.L., Infante P., Geraldo A.M., Alves A., Leme T.M., Baccari Jr. F., Almeida J.A., 2014. Evaporative heat loss in Bos taurus: do different cattle breeds cope with heat stress in the same way? Journal of Thermal Biology. 45, 87–95 PLI. 2007. Impact Assessments of Livelihoods-based Drought Interventions in Moyale and Dire Woredas. A Pastoralist Livelihoods Initiatives report produced by Feinstein International Center with CARE and Save the Children USA, Tufts University, pp 58 Population Reference Bureau, 2018. World Population Data Sheet. p.18 Ramsay R.R., Gandour R.D., van der Leij F.R., 2001. Molecular enzymology of carnitine transfer and transport. Biochimica et Biophysica Acta 1546:21–43 Reed J.B.H., Doxey D.L., Forbes A.B., Finlay R.S., Geering I.W., Smith S.D. and wright J.D., 1974. Productive performance of cattle in Botswana. Tropical Animal Health and Production 6: 23-29 Reid R.L. and Hinks N.T., 1962. The metabolism of glucose, free fatty acids, ketones and amino acids in late pregnancy and lactation. Australian journal of agricultural research, 13, 1112-1123 Rice L.E., 1991. The effects of nutrition on reproductive performance of beef cattle. Veterinary Clinics of North America: Food Animal Practice. 7(1), 1-26

Richards M.W., Spitzer J.C. and Warner, M.B., 1986. Effect of varying levels of postpartum nutrition and body condition at calving on subsequent reproductive performance in beef cattle. Journal of Animal Science, 62: 300-306 Roberts C. J., Reid I. M., Rowlands G. J., Patterson A., 1981. A fat mobilization syndrome in dairy cows in early lactation. Veterinary Record, 108:7–9 Roche J.R., Friggens N.C., Kay J.K., Fisher M.W., Stafford K.J., Berry D.P., 2009 Invited review: body condition score and its association with dairy cow productivity, health, and welfare. Journal of Dairy Science;92:5769-5801 Rukkwamsuk T., Wensing T., Geelen MJ.. 1998. Effect of overfeeding during the dry period on regulation of adipose tissue metabolism in dairy cows during the periparturient period. Journal of Dairy Science 81:2904-2911 Rukkwamsuk T., Wensing T., Kruip T.A.M., 1999. Relationship between overfeeding and overconditioning in the dry period and the problems of high producing dairy cows during the postparturient period. Veterinary Quarterly 21, 71–77 Scalia D, Lacetera N, Bernabucci U, Demeyere K, Duchateau L, Burvenich C., 2006. In vitro effects of nonesterified fatty acids on bovine neutrophils oxidative burst and Viability. Journal of Dairy Science;89:147-154 Schepers A.J., Meijer R.G.M., 1998. Evaluation of the Utilization of Dietary Nitrogen by Dairy Cows Based on Urea Concentration in Milk. Journal of Dairy Science 81, 579–584 Scholtz M.M., McManus C., Leeuw K.-J., Louvandini H., Seixas L., Melo C.B., Theunissen A., Neser F.W.C., 2013. The effect of global warming on beef production in developing countries of the southern hemisphere. Nature and Science 5, 1–14 Schoonemand M.G., Vas F.M., Houten S.M. Soeters M.R., 2013. Acylcarnitines, reflecting of inflicting insulin resistance? Diabetes 62(1), 1-8 Sejersen H., Sørensen M.T., Larsen T., Bendixen E., Ingvartsen K.L., 2012. Liver protein expression in dairy cows with high liver triglycerides in early lactation. Journal of Dairy Science. 95 :2409–2421 Soeters M.R., Sauerwein H.p., Duran M., Wanders R.J., Ackermans M.T., Fillers E., Houten S.M., Serlie M.J., 2009. Muscle acylcarnitines during short term fasting in lean healthy men. Clinical science 116(7), 585-592 Tolera A., 2012. Feed resources Availability and quality vs. animal productivity. In: Livestock Feed Resources in Ethiopia. Ethiopian animal feeds industry association, Ethiopia, pp 36-45 Tolera A., Assefa G., Geleti D., Gizachew L., Mengistu A., 2012b. Major feed resources. In: Livestock Feed Resources in Ethiopia. Ethiopian animal feeds industry association, Ethiopia, pp 14-36 Tolera A., Mengistu A., Geleti, D., Yami, A., Woldesemayat Y. 2012a. The need for transforming the Ethiopian feed sector. In: Livestock Feed Resources in Ethiopia. Ethiopian animal feeds industry association, Ethiopia, pp 1-3 van Niekerk A., 1982. The effect of body condition as influenced by winter nutrition, on the reproductive performance of the beef cow. South African Journal of Animal Science, 12, 383–387 Waltner S.S., McNamara J.P., Hillers J.K., 1993. Relationships of body condition score to production variables in high producing Holstein dairy Cattle1. Journal of Dairy Science;76:3410-3419

Webber J., Simpson E., Parkin H., Macdonald I.A., 1994. Metabolic effects of acute hyperketonaemia in man before and during an hyperinsulinaemic euglycaemic clamp. Clinical Science, 86:677 Yisehak K., Belay D., Taye T., Janssens G.P.J., 2013. Impact of soil erosion associated factors on available feed resources for free-ranging cattle at three altitude regions: Measurements and perceptions. Journal of Arid Environments 98, 70–78 Zytkovicz T.H., Fitzgerald E.F., Marsden D., Larson C A., Shih V.E., Johnson D.M., Strauss A.W., Comeau A.M., Eaton R.B., Grady G.F., 2001. Tandem mass spectrometric analysis for amino, organic, and fatty acid disorders in newborn dried blood spots: A two-year summary from the New England newborn screening program. Clinical Chemistry 47:11,1945-1955