GHENT UNIVERSITY

FACULTY OF VETERINARY MEDICINE

Academic year 2016 – 2017

MINERAL STATUS OF ZEBU CATTLE (BOS INDICUS) IN THE ETHIOPIAN RIFT VALLEY

By

Kaat NECKERMANN

Promoters: Prof. dr. ir. Geert Janssens Research Report

Prof. dr. Yisehak Kechero as part of the Master’s Dissertation

© 2017 Kaat Neckermann

Disclaimer 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.

GHENT UNIVERSITY

FACULTY OF VETERINARY MEDICINE

Academic year 2016 – 2017

MINERAL STATUS OF ZEBU CATTLE (BOS INDICUS) IN THE ETHIOPIAN RIFT VALLEY

By

Kaat NECKERMANN

Promoters: Prof. dr. ir. Geert Janssens Research Report

Prof. dr. Yisehak Kechero as part of the Master’s Dissertation

© 2017 Kaat Neckermann

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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.

Firstly, I would like to thank prof. Janssens and prof. Kechero for giving me this once in a lifetime

opportunity to execute the fieldwork for my thesis in Arba Minch, Ethiopia. Without their support and

ideas, I would not have been able to complete this work. Living this African adventure was eye-opening

and full of challenges, providing me with a true hands-on experience. I am very grateful for Seifu, the

assistant of prof. Kechero, for all the effort and work he put into preparing the lab as well as getting me

in touch with all the farmers. Of course, I would also like to thank him for his friendship and the time

taken to guide me around Arba Minch.

I would like to express my gratitude to the Arba Minch University (AMU), and all its staff who assisted

me in this work. I could always count on Ayalo, the veterinary assistant, to accompany me to the farmers

and help me with the translation and sample collection. Also a word of thanks goes out to all the

interviewed farmers, for their hospitality, cooperation and participation on the farms. Without them, I

would not have been able to perform my field work. Additionally, I appreciate the financial support

provided by the VLIR-UOS given in the form of a travel grant.

I am very thankful to Gregor, my soulmate, for always being there and supporting me throughout some,

at times, rather hard and stressful moments and for always believing in me. Thank you for everything!

Last but not least, my parents, my brothers, Wout, Dieter, Tom and Hannes, and my doggies, Hakuna

and Myos, for their unconditional support and love. Not only during this thesis, but throughout my studies

and life.

በጣም አመሰግናለሁ

“Betam ameseginalehu”

Thank you very much!

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TABLE OF CONTENTS

I ABSTRACT ....................................................................................................................................... 1

II SAMENVATTING .............................................................................................................................. 2

III INTRODUCTION ........................................................................................................................... 4

IV LITERATURE SURVEY ................................................................................................................. 6

IV.1 Dairy production in Ethiopia ............................................................................................ 6

IV.2 Introduction to minerals ................................................................................................... 9

IV.3 Functions of minerals in dairy cattle .............................................................................. 10

IV.4 Mineral intake requirements for dairy cattle .................................................................. 13

IV.5 Mineral interactions ....................................................................................................... 14

IV.6 Mineral status assessment of dairy cattle ..................................................................... 15

IV.7 Mineral deficiencies known in zebu cattle ..................................................................... 16

IV.8 Minerals and milk production ........................................................................................ 19

V RESEARCH PROJECT ............................................................................................................... 22

V.1 Materials and methods .................................................................................................. 22

V.1.1 Study area, animals and samples ................................................................................. 22

V.1.2 Farms and diets ............................................................................................................. 26

V.1.3 Mineral analysis ............................................................................................................. 27

V.2 Results .......................................................................................................................... 29

V.2.1 Serum mineral concentration vs lactation stage ........................................................... 29

V.2.2 Correlation of serum mineral concentrations ................................................................ 29

V.2.3 Serum mineral concentration vs body condition score (BCS) ...................................... 31

V.2.4 Serum mineral concentrations vs reference values ...................................................... 32

V.2.5 Milk production vs serum mineral concentrations ......................................................... 33

V.2.6 Milk production vs total dry matter intake (TDMI) and body condition score (BCS) ..... 34

V.2.7 Body condition score vs total dry matter intake (TDMI) ................................................ 35

V.2.8 Effects of parity .............................................................................................................. 35

V.2.9 Mineral intake vs requirements and maximal tolerable limits (MTL) ............................. 36

V.2.10 Effects of body weight (BW) .......................................................................................... 38

V.2.11 List of feed types ........................................................................................................... 39

V.3 Discussion ..................................................................................................................... 41

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V.4 Conclusion ..................................................................................................................... 45

VI REFERENCES ............................................................................................................................ 46

VII APPENDIX ................................................................................................................................... 52

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I ABSTRACT

In Ethiopia, mineral deficiencies in dairy cattle due to poor quantity and quality feed, are believed to

lead to a suboptimal milk production in the local zebu (Bos indicus) cattle. This research was conducted

in urban dairy farms in Arba Minch, Ethiopia, to examine the mineral status of zebu cattle, the mineral

content in their feed, and the relationship with milk production. A survey was taken, to obtain an idea of

the management on a total of 37 farms in 4 districts. Samples, including blood, faeces, milk and hair,

were collected from 49 cows. The administered feed quantity, to calculate the dry matter intake, as well

as the body condition score were recorded on farm level. Besides the animal samples, feed samples

were also gathered on each farm. Apart from the hair, all samples were oven dried and ashed. For this

thesis, only the feed and serum samples were analysed for B, Ca, Cu, Fe, K, Mg, Mn, Na, P and Zn

using ICP-OES. Additionally, Mo was also determined in the feed samples.

In the serum samples, a Na deficiency (2.75 ± 0.22 < 3.10 g l-1) was observed, and Ca and Mg

concentrations were below the reference values for a healthy animal (95 ± 15 < 110 and

26.1 ± 2.2 < 40.0 mg l-1 respectively). Na was also found deficient in the feed, and therefore below the

mineral intake requirement, with 3.18 ± 0.83 g day-1 (p < 0.001). Yet, Ca and Mg intake was above the

mineral intake requirement (p < 0.001). Low Ca and Mg concentrations in the serum could be explained

through a lower absorption from the feed. In any case, more feed rich in Na, Ca and Mg, must be

supplied. Frushika is put forward as a Na and Ca source (4 ± 1.5 and 10.6 ± 4.2 g kg-1 dry matter,

respectively), whereas banana stem is relatively high in Mg (4.8 ± 3.4 g kg-1 DM). An alternative source

of Na is salt, and an advised amount of 20 g day-1 extra is necessary to reach the Na intake requirement.

There was an increasing trend for milk production with increasing total dry matter intake (p = 0.052) and

a significant correlation between milk production and body condition score (p = 0.0087). No significant

difference in milk yield was found between the lactation stages, the mean remained around 1.44 l day-1.

However, there was no significant correlation between the mineral concentrations and milk production

(p > 0.05). Therefore, we can assume that factors, other than mineral deficiencies, are also limiting milk

production in zebu cattle. These factors may include farm management, the provision of qualitative feed

and the genetic potential, and these should be addressed before one can attempt to increase milk

production through mineral supplementation.

Key words: Ethiopia – Feed types – Milk production – Mineral deficiency – Zebu cattle

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II SAMENVATTING

Deze thesis onderzoekt de mineralenstatus van de lokale zeboe (Bos indicus) in de Grote Riftvallei, in

het zuiden van Ethiopië, meer bepaald in het stadje Arba Minch. In Ethiopië ligt de lage kwaliteit en

kwantiteit van het voeder heel waarschijnlijk aan de basis van suboptimale melkproductie van de zeboe.

Het doel van dit onderzoek is enerzijds nagaan of er mineralendeficiënties aanwezig zijn bij zeboe in

deze regio. Anderzijds wordt onderzocht wat de mineralenconcentraties in het voeder zijn. Uiteindelijk

is het de bedoeling een verband te leggen tussen melkproductie en mineralenconcentraties in serum

en voeder.

In deze studie werden melkveeboerderijen gekozen met vaak minder dan drie zeboemelkkoeien, in vier

verschillende wijken van Arba Minch. Een enquête werd afgenomen in 37 boerderijen, aan de hand

van een vragenlijst met betrekking tot het management. Verschillende metingen werden op de

boerderijen uitgevoerd: de hoeveelheid voeder die per dag werd gegeven aan de zeboes, de

borstomtrek – om een schatting van het gewicht te maken – en de lichaamsconditiescore werden

bepaald. Daarnaast werden ook bloed-, faeces-, melk- en haarstalen genomen van 49 zeboes. Naast

de dierlijke stalen werden ook voederstalen verzameld. Op deze manier werd ook een inschatting

gemaakt van de dagelijkse droge stofinname. Alle stalen, behalve de haarstalen, werden in de oven

gedroogd voor droge stofbepaling. Nadien werden de stalen verast in een moffeloven. Voor deze

masterproef werden enkel voeder- en serumstalen geanalyseerd via inductief gekoppeld plasma -

optische emissiespectrometrie (ICP-OES). Zo werden de concentraties van B, Ca, Cu, Fe, K, Mg, Mn,

Na, P en Zn in voeder en serum achterhaald. Van de voederstalen werd ook de Mo-concentratie

bepaald.

De masterthesis is opgedeeld in drie grote luiken. In Hoofdstuk III wordt het probleem van een te lage

Ethiopische melkproductie geschetst en wordt beschreven hoe er vanuit onderzoek en overheid

aandacht aan wordt besteed. Hoofdstuk IV gaat vervolgens dieper in op de achterliggende theorie van

mineralen en diens deficiënties bij melkvee, via een grondig literatuuronderzoek. Tot slot wordt de thesis

afgerond in Hoofdstuk V met de beschrijving van het onderzoek (Paragraaf V.1), de gevonden

resultaten met bespreking (Paragraaf V.2 en V.3) en besluittrekkingen (Paragraaf V.4).

Omdat er geen referentiewaarden bestaan, specifiek voor zeboes, werden de referentiewaarden voor

hoogproductieve koeien gebruikt. In deze studie hebben we aangetoond dat de volledige steekproef

gemiddeld niet koperdeficiënt is. Desondanks had 20% van de onderzochte koeien een deficiënte

serumconcentratie. Natriumdeficiëntie is daarentegen wel algemeen voorkomend, meer dan 80% van

de koeien had een tekort (2,75 ± 0,22 < 3,10 g l-1). Natriumtekorten werden ook geobserveerd in de

inname met 3,18 ± 0,83 g dag-1 (lager dan de referentie, p < 0,001), daarom wordt geadviseerd om

zeboes te suppleren met 20 g zout (NaCl) per dag. Tevens hadden de dieren een lager dan gezonde

Ca en Mg serumconcentratie (respectievelijk 95 ± 15 < 110 en 26,1 ± 2,2 < 40 mg l-1), de inname was

echter hoger dan de aangewezen inname (p < 0,001). Mogelijks werd de absorptiecoëfficiënt voor Ca

en Mg te hoog ingeschat. Frushika, een mengsel van zemelen, is een bron van Na en Ca

(respectievelijk 4,0 ± 1,5 en 10,6 ± 4,2 g kg-1 droge stof) en dit voeder zou dus (zout)supplementen

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deels kunnen vervangen. Voorts is de schijnstam van banaan rijk aan Mg (4,8 ± 3,4 g kg-1 droge stof).

Er werd geen correlatie gevonden tussen mineralenconcentraties in het serum en melkproductie

(p > 0,05), maar wel een positieve correlatie tussen melkproductie en lichaamsconditiescore

(p = 0,0087) enerzijds en lichaamsconditiescore en droge stofinname (p = 0,035) anderzijds. Er werd

een stijgende melkproductietrend bij stijgende droge stofinname teruggevonden (p = 0,052). Deze

studie toonde geen verschil in melkproductie tussen de drie lactatiestadia; deze was gemiddeld

1,44 l dag-1. Naast de nadelige invloed van mineralendeficiënties, spelen nog tal van andere factoren,

zoals boerderijmanagement en genetische eigenschappen, een belangrijke rol bij melkproductie van

de zeboerunderen in de Grote Riftvallei in Ethiopië.

Sleutelwoorden: Ethiopië – Melkproductie – Mineralendeficiëntie – Voeder – Zeboe

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III INTRODUCTION

With an estimated population of 101.7 million, Ethiopia is the second most populous nation in Africa

(Population Reference Bureau, 2016). In the past decennia, it ranked as one of the poorest countries

in the world, but over the last decennium, an impressive overall economic growth and poverty reduction

has been recorded, placing it amongst the world’s fastest-growing economies. National official data

show that agriculture has grown on average by 7.6 percent per year in the period 2004-2014; which

has been a major contributor to the important poverty reductions observed in the last decade in Ethiopia

(Bachewe et al., 2015). The second five-year Growth and Transformation Plan (GTPII) sets a key goal

for Ethiopia to become a lower middle-income country by 2025 (Moller, 2016).

The agricultural sector accounts for 77% of total employment and 47% of GDP (Martins, 2014). The

livestock sector plays a key role in Ethiopia’s economy; Ethiopia has the largest cattle population in

Africa, but its productivity and commercialisation remain low. Almost all cattle are local zebu breeds

(Bos indicus), with crossbreeds and exotic breeds comprising only 1.3% of the national cattle herd

(Mayberry et al., 2017).

Ethiopia has 10.6 million dairy cattle, but average milk production per cow is low, with 1.4 l day-1 over a

6-month lactation. Cross-bred cattle have a higher level of production estimated at an average of

10 l day-1 (O’Lakes, 2010). Of all milk produced, 97% originates from the agro-pastoral and pastoral

regions, from multipurpose indigenous livestock that also provide draught and beef, and the remaining

3% comes from improved exotic crosses (Felleke et al., 2010).

The demand for dairy and other livestock products increases with the rise in human population, income

and urbanisation, while at the same time there is a decrease in the amount of land and water available

for agriculture, and many grazing lands become more and more degraded (Mayberry et al., 2017).

As most research in Ethiopia points out, major constraints limiting dairy productivity on cow level are

the inadequate supply of quality feed and the low productivity of the native cattle breeds (Ahmed et al.,

2004). In the tropics, mineral shortage is a frequent problem regarding cattle nutrition, and it is

responsible for large economic losses in livestock production (McDowell and Arthington, 2005).

According to Grant (1992), dairy cattle must be provided with a balanced diet containing at least

seventeen minerals for optimal milk production, reproductive performance, and overall health.

Before milk production responses of dairy cattle to mineral supplementation can be investigated, local

research is necessary to assess the mineral status of forages and grazing animals. Most studies

performed in Ethiopia were executed in the north of the country. However, differences in mineral

concentrations in the feed and in the animals were already seen to vary between altitudes and seasons

in the north. Therefore the mineral status in the south is still unknown, although we can assume that it

will be along the same lines of the mineral concentrations of the north. It is assumed that Cu deficiency

in the serum (Khalili et al., 1993b; Abdelrahman et al., 1998; Gizachew et al., 2002; Dermauw, 2013a)

and Na and P shortage in the feed cause the biggest nutritional problems in Ethiopia (Khalili et al.,

1993a; Abdelrahman et al., 1998; Tsegahun et al., 2006; McDonald et al., 2011). Only when it is

5

established that certain minerals are lacking in the diet and in the cattle’s mineral status, can feed supply

and management be adapted accordingly. Furthermore, a link between mineral status and milk yield

should be examined before trying to increase milk production by mineral supplementation. The question

remains if mineral deficiencies alone lie at the bottom of this suboptimal milk production. The objectives

of this study are (1) to determine the mineral deficiencies in the serum of zebu dairy cattle in Arba

Minch, (2) to assess the mineral composition of the provided feed types, and (3) to demonstrate the link

of mineral deficiencies with milk production.

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IV LITERATURE SURVEY

IV.1 DAIRY PRODUCTION IN ETHIOPIA

According to Cook (2015), Ethiopia has the fifth largest cattle inventory in the world, behind Brazil, India,

China and the United States, and ahead of Argentina. It is ranked tenth in the world for population of

ruminant livestock; the Central Statistical Agency of Ethiopia estimates totals of 56.7 million cattle, 29.3

million sheep, 29.1 million goats and 1.16 million camels. These estimates exclude livestock populations

in the non-sedentary (nomadic) areas of Afar and Somali regions (CSA, 2015).

Geographically, Ethiopia is divided into a highland (> 1,500 m above sea level) and a lowland (< 1,500 m

above sea level). The highland comprises 39% of the land area of the country, 88% of human

population, and 74% of the livestock units, while the remainder is in the lowlands (Hassen et al., 2007).

The Ministry of Agriculture (MoA) has officially categorized three major production typology zones in

Ethiopia: lowland grazing (LG), which includes both pastoral and agro-pastoral systems, highland mixed

crop-livestock rainfall deficient (MRD) and highland mixed crop-livestock rainfall sufficient (MRS) zone

(Shapiro et al., 2015).

For 2013, the Livestock Sector Analysis results show around 11.4 million livestock producing

households in Ethiopia (CSA, 2012). Cattle were found to be the dominant species in 70% to 90% of

these households, dominating smallholder income generation and meat-milk production in both lowland

and highland (MRS, MRD and LG), as well as in commercial settings (Shapiro et al., 2015).

A variety of breeds can be distinguished, as the cattle population has evolved continuously over time,

resulting in a mosaic of genetically diverse population from the purest Bos taurus to the nearly pure

B. indicus. They are found across the continent; from the rift valley highlands to below sea level in the

Afar depression. Mwai et al. (2015) alert that these unique livestock genetic resources are in danger if

uncontrolled crossbreeding and breed replacements with exotic breeds would take place, and their

unique adaptive traits might be lost.

Dadi et al. (2008) studied ten cattle populations belonging to four major groups of Ethiopian cattle: the

humpless taurine, thoracic humped zebu, cervicothoracic humped Sanga, and zebu-Sanga, and the

Holstein breed. They found cattle populations in Ethiopia to be highly mixed but distinct from pure

B. taurus and B. indicus breeds, and conclude that this high genetic diversity makes Ethiopian cattle

populations suitable for future genetic improvement and utilisation under a wide range of agro-ecologies

in Ethiopia.

Studies have indicated that zebu cattle utilise forages more efficiently, allowing them to survive on

forages of low quality and in adverse conditions, are more resistant to parasites as ticks and nematodes,

to tick-borne diseases, and infection with Brucella abortus (Macedo et al., 2013). However, zebu cattle

have a slower growth, mature later, are lower in reproduction, and produce lower beef quality compared

to B. taurus. To combine the advantages of both breeds, zebu cattle and B. taurus, cattle are often

7

crossbred, resulting in a breed which is well adapted under local (sub)tropical conditions, and displays

a heterosis effect in production and reproduction (Haile et al., 2008).

In 1984, the MoA established the National Artificial Insemination Centre in the capital of Ethiopia. To

improve dairy cattle’s genetics, the government started promoting the crossbreeding of local breeds

with exotic Holstein Friesian, Brown Swiss and Jersey (Ahmed et al., 2004; Gebre Medhin et al., 2007).

Although the genetic improvement of the zebu breed through crossbreeding may seem promising, the

overall success rate on the production level in Ethiopia has remained low, due to poor cattle nutrition

and management (Haile et al., 2007).

As of today, only 1.3% of the national cattle herd consists of crossbreeds and exotic breeds. Crossbred

cattle are mostly used in commercial milk production, and are concentrated in the highland mixed

crop-livestock region. In the agro-pastoral and pastoral lowland regions, most milk is produced by

multi-purpose indigenous livestock that also provide draught and beef (Mayberry et al., 2017).

Ethiopia has 10.6 million dairy cattle, but productivity per cow is low, averaging milk yield of

1.30-1.54 l day-1 for an average lactation period of 180-210 days. Crossbred cows produce an average

of 10 l day-1 (O’Lakes, 2010).

In the 2014/2015 fiscal year, 3.07 billion litres of cow milk and 233.85 million litres of camel milk were

produced (CSA, 2015). The livestock management system is predominated by extensive production

systems where indigenous breeds are kept under low-input/low-output husbandry practices. Green

pasture (56.23%) and crop residues (30.06%) are the main feed types available in the country (CSA,

2015).

Milk is an important source of proteins and micronutrients, which play a crucial role in children’s’ growth

and development (Bhutta et al., 2013). In the lowlands, farmers nearly completely rely on milk and

livestock for food supply. They trade livestock and its products for food grains and other necessities

(FAO, 2003). Many Ethiopians regularly consume milk products such as fresh milk, fermented soured

whole milk (ergo), butter (kibe), buttermilk (arera), cottage cheese (ayib), whey (aguat), and ghee (nitir

kibe). The United States Agency for International Development indicates that most milk, approximately

95.31%, is consumed and processed at home, while only 4.69% is supplied to formal and informal

markets (USAID, 2016). In the last decade, the number of milk processing plants has been increasing;

where milk is pasteurised, and yoghurt, cheese, and other products for the domestic market are

produced (MoA, 2013).

Due to economic and cultural differences, Ethiopian annual consumption of dairy products is low:

19 l year-1 person-1, which is about half the average African consumption, and well below the world

average of 105 l (USAID, 2013). This relatively low demand for dairy products is partly due to the fact

that Orthodox Christians, comprising about 40% of the Ethiopian population, abstain from consuming

dairy and other animal products for about 200 days a year (Staal et al., 2008). In recent years, milk

demand has been rising as a result of urbanisation, higher incomes and population growth (Ahmed et

al., 2004; Duns and Willems, 2014). The country is a net importer of dairy products with import values

significantly exceeding export values (Yilma et al., 2011). Therefore, improvements in the dairy

8

production sector and a more market-oriented milk production could create employment opportunities

and benefit the smallholder farmers. This could empower people to invest in their welfare, even in higher

education (Njwe et al., 2001). According to FAO, livestock represent a lifetime of savings. It is crucial

to salvage the breeding stock in drought-affected areas such as Ethiopia so that, when conditions

improve, livelihoods will be restored (FAO, 2017).

Reasons for the poor development of the dairy sector in Ethiopia are various and complex. Rural

farmers have difficulties accessing the market due to transport problems and a lack of market outlets

for milk and dairy products. Milk processing technologies are basic, inefficient or inadequate (Redda,

2001).

Of all cattle in Ethiopia, 98.7% are local breeds (Mayberry et al., 2017). The use of more crossbreed

heifers would increase the amount of milk. Poor quality semen and inefficient or poor timing of artificial

insemination contribute to a reduced reproduction and milk production. Forage production is a major

constraint for the improvement of the dairy sector; poor quality feed, shortage of agro-industrial

by-products, and long lasting droughts contribute to the current situation (Duns and Willems, 2014).

High cost and low availability of good quality animal feed from forage and fodder contribute to

underfeeding and malnutrition, limiting the ability of an animal to reach its genetic potential. Tolera et

al. (2012) reported a milk production increase from 1.7 l on average at peak lactation to 4 l when a Horo

cow is fed and managed properly. Supplementing feeding interventions, along with genetic and health

interventions, are required to realise productivity increases (Shapiro et al., 2015).

Over the last 20 years, the government of Ethiopia has prioritised the transformation of the agricultural

sector. Based on the findings of the 2010-2015 Growth and Transformation Plan (GTP), the Livestock

State Ministry, together with the International Livestock Research Institute (ILRI), have developed a

long-term Livestock Master Plan (LMP) to achieve the GTP. The objectives of the present 2015-2020

GTPII are to reduce poverty, achieve food and nutritional security, contribute to economic growth,

exports and foreign exchange earnings, and climate mitigation and adaptation (MoA and ILRI, 2015).

The livestock technology interventions, which depend upon the biophysical, agro-ecological and market

conditions facing livestock in the three production typology zones (LG, MRD and MRS), include:

Improving dairy cattle through breeding interventions, by combining artificial insemination using

exotic semen with oestrus synchronisation in MRS dairy systems and in peri-urban milk sheds

throughout Ethiopia;

Enhancing productivity of local breeds (cattle, sheep, goats, and camels) for meat and milk, through

genetic selection, improving animal health to reduce young and adult stock mortality, and

implemention of critical vaccinations and parasite control programs;

Increasing public investment in rehabilitating range and pasture lands to improve feeding and

animal management to complement genetic and health improvements (Shapiro et al., 2015).

9

IV.2 INTRODUCTION TO MINERALS

Although minerals are found in all animal tissues, not all play a vital role in the animal’s metabolism.

Only essential minerals are necessary for correct body functioning. This means that deficits of these

minerals in the animals’ diet cause deficiency symptoms; a causal link is proven by alleviation of these

symptoms through supplemention of these minerals to the feed (McDonald et al., 2011).

Essential minerals are classified into two groups depending on dietary or bodily concentration

requirements (McDonald et al., 2011). The major minerals or macrominerals consist of calcium (Ca),

phosphorus (P), magnesium (Mg), potassium (K), sodium (Na), chlorine (Cl) and sulphur (S). Minerals

required in much smaller quantities – less than 100 mg kg-1 in feed and present in the animal body in a

concentration less than 50 mg kg-1 body weight (BW) – are trace minerals or microminerals. These

include iodine (I), iron (Fe), cobalt (Co), copper (Cu), manganese (Mn), zinc (Zn), molybdenum (Mo),

chromium (Cr), fluorine (F) and selenium (Se). Discussion remains about which minerals are truly

essential, the numbers varying per author, especially concerning the trace elements (Grant, 1992;

McDonald et al., 2011).

An important constraint in Ethiopia’s dairy production is the lack of qualitative forage for dairy cattle.

Most animals receive fibrous feeds, crop residues and by-products, and graze on mature pastures,

often herbage that grows on non-arable, natural grazing lands. The fodder is generally deficient in crude

protein, minerals and vitamins and is poorly digestible, limiting the productivity of the cattle (ESGPIP,

2007; Tekeba, 2012). Mineral supplementation is exceptional, apart from the occasional common salt.

Therefore, all mineral intake is through the poor quality feeds, and despite energy and proteins being

the most important factors, mineral deficiencies also seem to limit the cattle’s optimal performance

(Kabaija and Little, 1987). As minerals are required in low concentrations, it is not easy to establish if a

mineral status is deficient or marginally deficient. Only when a severe mineral deficiency is present,

resulting in clinical symptoms, will it be recognised. Consequently, in the tropics, subclinical mineral

deficiencies in grazing animals might be more common than recognised, and may manifest as low

productivity, thus being responsible for large economic losses in livestock production (Mcdowell et al.,

1977; Kabaija and Little, 1987; Gizachew et al., 2002; McDowell and Arthington, 2005). This is also

observed when the cattle are undernourished, or fed a protein deficient diet, or are infested with

parasites (Gizachew et al., 2002; Suttle, 2010).

East African grazing lands are often affected by drought and overgrazing, yet these pastures play a

primary role in the animal’s feed resource. Other than through grazing and crop residues, incidental soil

ingestion may also be an important source of mineral intake, but its mineral contents are highly variable,

depending on location; the same applies for the mineral concentrations of many feeds (Khalili et al.,

1993a; NRC, 2001; Yadessa, 2015). Although water is not a principal source of minerals, almost all

essential minerals are to some extent present in water, albeit in varying concentrations (Yadessa,

2015).

10

Mineral concentrations found in cattle serum in mg l-1 are compared to critical levels, which represent

dietary sufficiency (Abdelrahman et al., 1998). Various studies report East African forages to be low in

Na and P, creating the most common nutritional problems in livestock (Khalili et al., 1993a;

Abdelrahman et al., 1998; Tsegahun et al., 2006; McDonald et al., 2011). A study performed throughout

Ethiopia by Faye et al. (1986) indicates that forages are low in Zn and animals are generally deficient

in Cu. Deficiency in Zn in grazing cattle has also been reported in Sudan by Mahmoud et al. (1983) and

in Malawi by Mtimuni (1982).

IV.3 FUNCTIONS OF MINERALS IN DAIRY CATTLE

Minerals serve different purposes in dairy cattle; a balanced diet should prevent adverse effects on

animal production and health. Both excessive and insufficient amounts of minerals in the diet are

undesirable, as they cause toxicity and deficiency symptoms respectively (NRC, 2001). Most minerals

have more than one task, which makes it difficult to establish a criterion for adequacy; the dietary

mineral level may be sufficient for one body function, yet insufficient for another. They play a role in

catalytic (i.e. enzyme function), physiological (i.e. maintaining osmotic pressure), structural (i.e. bone

strength), and regulatory processes (i.e. cell replication and differentiation) (Suttle, 2010; McDonald et

al., 2011). Table 1 provides an overview of mineral functions in dairy cattle.

11

Table 1 Mineral functions, deficiency and toxicity symptoms in dairy cattle (adapted from the NRC (2001) and McDonald et al. (2011))

Minerals Functions Deficiency Toxicity

Macrominerals

Ca

Constituent of bone and teeth

Nerve impulse transmission

Blood coagulation

Hypocalcaemia

Bone mineralisation problems

Rickets (Vit. D, P)

Growth retardation

Osteoporosis, osteomalacia

Milk fever

P

Constituent of bone and teeth

Component of nucleic acids and phospholipids/proteins

Energy metabolism

Blood buffer

Hypophosphatemia

Bone mineralisation problems

Rickets (Vit. D, Ca)

Osteomalacia

Appetite ↓, pica

(Re)production ↓

Ca metabolism problems

Milk fever

K

Osmoregulation and acid-base balance

Nerve and muscle excitation

Carbohydrate metabolism

Intracellular electrolyte

Hypokalaemia

Feed and water intake ↓

Milk yield ↓

BW ↓

Pica

Cardiac arrest, death

Mg absorption ↓

Na

Osmoregulation and acid-base balance

Constituent of bone

Nerve impulse transmission

Extracellular electrolyte

Sugar and amino acid absorption

Dehydration

Shivering, weakness

Appetite ↓, pica

Feed intake ↓

Milk yield ↓

Anorexia

Anhydremia

BW ↓

Milk yield ↓

Mg

Constituent of bone

Nerve conduction

Cofactor for enzymes in carbohydrate and lipid metabolism

Hypomagnesaemic tetany Feed intake ↓

Diarrhoea

12

Table 1 Continued

Minerals Functions Deficiency Toxicity

Microminerals

Cu

Component of enzymes, e.g.:

ceruloplasmin (transport and absorption Fe);

cytochrome oxidase (electron transport chain);

superoxide dismutase (antioxidant system).

Hair pigmentation

Loss of hair pigmentation

Diarrhoea

Anaemia

Growth ↓

Brain stem & spinal cord lesions

Haemolytic crisis

Jaundice

Necrosis of liver cells

Death from hepatic coma

Fe Component of haemoglobin/myoglobin

Cofactor of enzymes in electron transport chain

Hypochromic microcytic anaemia

(calves)

Oxidative stress (free radicals)

Feed intake ↓

Growth ↓

Diarrhoea

Absorption Cu, P and Zn ↓

Mn Activator of enzymes, e.g.:

glycosyltransferase (bone formation)

Growth ↓

Skeletal deformation

Reproduction ↓

Ataxia of the newborn

Feed intake ↓

Growth ↓

Mo Component of enzymes

Limits Cu (and P) absorption (with 𝑆𝑂42−)

Not observed

Cu deficiency

Zn Component and activator of enzymes

Cell replication, differentiation

Feed intake ↓

Growth ↓

Reproduction ↓

Skin lesions

Feed intake ↓

Absorption Cu ↓

13

IV.4 MINERAL INTAKE REQUIREMENTS FOR DAIRY CATTLE

In ‘Nutrient Requirements for Dairy Cattle’ (NRC, 2001), the mineral requirements for (lactating) dairy

cattle are calculated using a factorial method. This means that the requirement is subdivided into four

components: requirement for maintenance (and work), lactation, pregnancy and growth. The sum of

these four components is the net requirement (NR) for mineral absorption. Since not the complete

mineral amount in feed is available, the factorial method assigns an absorption coefficient (A) to a

specific feed for each mineral. In this way, a gross mineral requirement (GR) is determined (Suttle,

2010), for example for calcium (Ca):

𝐺𝑅𝐶𝑎 =𝑁𝑅𝑚𝑎𝑖𝑡𝑒𝑛𝑎𝑛𝑐𝑒, 𝐶𝑎 + 𝑁𝑅𝑔𝑟𝑜𝑤𝑡ℎ, 𝐶𝑎 + 𝑁𝑅𝑝𝑟𝑒𝑔𝑛𝑎𝑛𝑐𝑦, 𝐶𝑎 + 𝑁𝑅𝑙𝑎𝑐𝑡𝑎𝑡𝑖𝑜𝑛, 𝐶𝑎

𝐴𝐶𝑎

1

Due to absorption differences between feed types, an adequate band of mineral intake is commonly

used, ranging from minimum requirement to safe allowance (Figure 1, Suttle (2010)).

Figure 1 Dose-response curve for feeds A and B. A has a higher mineral absorption coefficient than B. (Suttle, 2010)

The major drawback of the factorial method is that the outcome heavily relies on precisely determined

A-values, which can be difficult to establish. Another method to define mineral requirements are

dose-response experiments (Suttle, 2010; Dermauw, 2013a). However, this method also has its

disadvantages, as it needs trials with a lot of different mineral input levels (Remmenga et al., 1997).

In literature and research papers, (average) mineral requirements vary, depending on the source, as

different criteria for adequacy and safety are used, and various factorial methods apply different

components and absorption coefficients. Therefore it is advisable to use a range, with minimal

requirements to investigate mineral deficiencies (Suttle, 2010). The net requirement for several minerals

is presented in Table 2.

(%)

14

Table 2 Net minimal intake requirements (NRC, 2001) and maximum tolerable level (MTL, from NRC (2005) for dairy cattle for the factorial components maintenance and lactation). DM = dry matter; BW = body weight

Component Unit Ca Cu K Mg Mn Na P Zn

Maintenance g kg-1 BW 0.031 7.1·10-6 0.042 0.003 2·10-6 0.043 0.802 4.5·10-5

Lactation g kg-1 milk 1.37 1.5·10-4 1.5 0.12 3·10-5 0.63 0.9 3.4

MTL mg kg-1 DM 15 40 20 6 2 000 12 7 500

Fe is required in such a small amount that it is negligible in feed requirements. It is recycled in the

animal’s body and reused to synthesize haemoglobin. Only 10% of the mineral escapes this cycle

(McDonald et al., 2011). Likewise, Mo is negligible in feed requirements, as Mo deficiency has only

been observed in laboratory setup, but not under natural conditions, in any species. According to

National Research Council (NRC, 1970), no estimated concentration of boron (B) is required in the feed

for cattle. It is considered a potentially toxic contaminant of water, and only an upper limit concentration

of 5 mg l-1 has been determined (NRC, 2001).

IV.5 MINERAL INTERACTIONS

Mineral deficiencies are not only caused by a deficit in feed intake, but also by the presence of other

elements with antagonistic effects in the diet (Suttle, 2010). Some minerals may interfere with the

absorption, transport, function, storage or excretion of other nutrients. Three ways have been identified

as to how minerals interact: they form unabsorbable compounds, compete for metabolic pathways or

induce metal-binding proteins (McDonald et al., 2011).

According to NRC (2001), an overload of Ca intake reduces the efficiency of absorption of P in the

digestive tract by decreasing the solublility of P. Ruminants are able to tolerate a broader ratio of Ca:P,

either as long as dietary requirements for both minerals are met, or as long as the ratio is not critical

(> 7:1 or < 1:1) (Miller, 1983).

A high intake of K is believed to have a negative influence on the uptake of Mg in the rumen of the

animal. Mg is transported through the ruminal wall by two active transport systems, which are inhibited

by K, especially when present in high concentrations, reducing the absorbability of Mg (McDonald et

al., 2011).

An important Cu-Mo-S correlation has been documented. Concurrent high concentrations of Mo and S

in the feed limit the absorbability of dietary Cu by forming an unabsorbable complex. In the rumen,

microorganisms produce sulphide from sulphate or organic sulfur compounds in the feed. Sulphide then

reacts with molybdate to form thiomolybdate. In turn, thiomolybdate interacts with Cu, rendering Cu

unabsorbable by forming the insoluble copper thiomolybdate. Furthermore, if an excess of

thiomolybdate is formed, it may be absorbed through the ruminal wall, where it will systemically bind to

15

Cu, thus severely affecting the Cu metabolism in the animal. In addition to Mo and S, extreme amounts

of dietary Zn may induce Cu deficiency (McDonald et al., 2011).

Also, chronic Fe toxicity tends to result in P deficiency (McDonald et al., 2011). An excess of Fe forms

insoluble Fe-Cu-S complexes which enhances Cu deficiency by lowering Cu absorption (Gould and

Kendall, 2011).

IV.6 MINERAL STATUS ASSESSMENT OF DAIRY CATTLE

Frequently, the serum mineral concentration of dairy cattle is used as a proxy for mineral deficiency

assessment (Kincaid, 1999; NRC, 2001; Suttle, 2010). However, liver mineral concentration is the best

predictor for mineral deficiency, as the liver acts as a storage organ, and therefore provides a more

accurate mineral status of the animal (Frøslie et al., 1983; Khalili et al., 1993b). The relationship

between liver mineral concentration and serum mineral concentration is strongest when the body

reserves are depleted and the animal has a mineral deficiency (Kincaid, 1999).

In deprivation studies, where a mineral is lacking from the animal’s feed, four stages are observed,

starting with depletion, followed by deficiency and dysfunction, and ultimately a stage of overt disease.

These stages are related to changes in body pools of the mineral that serve the following purposes:

storage (e.g. liver), transport (e.g. plasma) or functional (e.g. muscle enzyme). For all elements, there

is a marginal area where stores are all but exhausted and mineral-dependent functions begin to fail, but

the animal remains outwardly healthy, indicated as a grey area in Figure 2 (Suttle, 2010).

Figure 2 Four stages that occur after mineral deprivation (Suttle, 2010)

16

Similar to the requirement band for mineral intake (Figure 1), a range of serum mineral concentrations

can be defined. Suttle (2010) indicates serum mineral concentrations as normal (stage of depletion),

marginal (stages of dysfunction and deficiency), and abnormal (stage of disease). Serum mineral

concentrations levels for deficiency, adequacy and toxicity are presented in Table 3.

Table 3 Serum mineral concentrations (mg l-1) for dairy cattle for the stages of deficiency, adequacy and toxicity, based on data from several authors

Stage B Ca Cu Fe K Mg Mn Na P Zn

Deficiency / 80a 0.57a 0.6b 152a 17d 0.006e 3 100a 40c 0.2a

Adequacy / 110a 1.20a 6.0e 200c 40d 0.070e 3 450a 80c 1.9f

Toxicitya 19 300 11 25 390 63 1.48 5750 120 15

a Puls (1988); b Suttle (2010); c Bakrie et al. (1996); d McDonald et al. (2011); e Kincaid (1999);

f Herdt and Hoff (2011)

IV.7 MINERAL DEFICIENCIES KNOWN IN ZEBU CATTLE

Khalili et al. (1993a, 1993b) investigated the macromineral and micromineral concentrations in soils,

feed, blood plasma and faeces of local breeds and crossbreeds in the Selale highlands of Ethiopia,

north of Addis Ababa. Results were compared to the recommended dietary mineral levels for lactating

cows according to the NRC (1989).

Studying the macromineral concentrations, soils were analysed for pH, organic matter, Ca, P, Mg, Na

and K. Wide variations were found within all macromineral concentrations. A significant correlation was

found between soil Ca and Mg with pH (Khalili et al., 1993a). Analysis of feed samples showed all feed

types to be deficient in Na. Hay, pasture grass, barley straw, grains and teff straw were also low in P

and Mg (Table 4).

Table 4 Average macromineral content of feed samples in mg kg-1 on dry matter basis. Adapted from Khalili et al. (1993a)

Ca K Mg Na P

Hay 5500 16700 2800 300 2100

Pasture 6300 21700 2200 100 3400

Barley straw 3100 13300 1100 400 1400

Teff straw 3800 9200 1500 200 1100

Grains 900 5800 1300 100 3700

The average P concentration in plasma of the local breeds was found to be higher than the suggested

critical level published by McDowell (1985), although the plasma P of a considerable number of animals

was significantly lower during the rainy season. Grazing animals with no access to adequate extra feed

during the dry season, usually lose weight, and therefore have lower total minimal requirements than

during the rainy season. In the rainy season, cows and calves of both local breeds and crossbreeds

were found to suffer mainly from Na and P deficiency. Khalili et al. (1993a) suggest that P absorption

17

might also be reduced due to higher Ca or Fe intake. Analysis of the faecal samples showed that 80%

of all the cows were deficient in Na, reflecting the Na deficiency of the feeds (Khalili et al., 1993a).

Khalili et al. (1993b) analysed trace elements in soils, feed, blood plasma and faeces and also in fresh

livers collected from the abattoir. The soil samples were analysed by atomic absorption spectroscopy

(AAS) for Fe, Mn, Cu and Zn. Forage, faeces and liver samples were oven dried and analysed for Fe,

Mn, Cu and Zn, while blood plasma was analysed for Fe, Cu and Zn.

In all feeds, Fe content was found extremely high and Mn levels were also higher than the dietary

requirements. Several feed samples had a low content in Cu and Zn, as seen in Table 5, e.g. hay, teff

straw and grains were low in both Cu and Zn, and barley straw was low in Zn.

Table 5 Average micromineral content of feed samples in mg kg-1 on dry matter basis. Adapted from Khalili et al. (1993b)

Cu Fe Mn Zn

Hay 7 610 313 25

Pasture 9 1347 266 36

Barley straw 10 377 59 18

Teff straw 7 211 209 30

Grains 7 473 65 31

In the blood plasma samples, Khalili et al. (1993b) also found low mean levels of Cu (0.62 mg l-1) and

Zn (0.66 mg l-1) based on the critical levels published by McDowell (1985): 0.65 mg l-1 for Cu and 0.60

to 0.80 mg l-1 for Zn. More than half of the animals were found to have low plasma Cu and Zn during

the rainy season. The study was done over two consecutive years, i.e. two rainy seasons and two dry

seasons. A statistically significant seasonal effect, with year to year variations was found for Ca, P, Mg

and K, and for all the trace elements studied (Khalili et al., 1993a, 1993b).

Khalili et al. (1993a, 1993b) found no significant correlation between the plasma micro- and

macromineral concentrations and the soil or pasture mineral concentration. The authors therefore

recommend analysis of bone and blood for Ca and P, blood for Mg, faeces for Na, and liver and blood

for Fe, Cu and Zn, as a more reliable means of assessment for the mineral status of grazing cattle in

the highlands, instead of the analyses of soils and pastures.

The NRC states that mineral deficiencies in herbivores are directly related to soil characteristics; e.g. P

deficiency in grazing cattle is most common when the forages are derived from soils low in P. Besides

the mineral concentration in the soil, soil pH also plays an important role. As the soil pH increases, the

availability and uptake of forage Fe, Mn, Zn, Cu and Co decrease, and the availability and uptake of

forage Mo and Se increase (NRC, 2001).

Abdelrahman et al. (1998) measured minerals in feed samples and in serum of zebu cattle in Sudan,

using AAS. The authors referred to the critical levels of McDowell and Conrad (1977), Underwood

(1981) and Puls (1988). This study also demonstrates a significant seasonal link in mineral

concentrations in serum, for P, Cu, K, Ca, Mg, Na, Co and Zn, as well as in forages.

18

An average serum Cu deficiency of 0.54 mg l-1 throughout the year, with the lowest value 0.35 mg l-1 in

the rainy season, and an average serum Se deficiency, below detection limit of 0.02 mg l-1 were found

(Table 6). Low average serum concentrations of P (58 mg l-1), Ca (103 mg l-1) and Na (3 668 mg l-1)

were also observed, but these were at their lowest during the late dry season; 45, 82 and 2 967

respectively (Abdelrahman et al., 1998).

Table 6 Mean mineral concentrations found by Abdelrahman et al. (1998) in the study of zebu blood serum (mg l-1) in Sudan, compared to critical levels derived from McDowell and Conrad (1977), Underwood (1981) and Puls (1988)

Ca Cu K Mg Na P Zn Co Se

Blood serum 103 0.54 149 26 3 668 58 1.04 0.63 <0.02

Critical level 85 0.68 97.5 20 3 105 45 0.8 0.25 0.03

During the dry season, forages were low in Ca, P, Na and Cu (Table 7). The authors contribute the

critically low levels of Na in the dry season to low Na concentrations in forages on the one hand, and

Na loss by the animals on the other hand. The Na loss is the result of high temperatures, and the

requirement of Na for milk production. Besides Na, also K and Cl are lost from the body through

perspiration (McDonald et al., 2011). Na and Cl can easily be supplemented via salt.

Salt is an important element in the diet of both humans and animals and plays a role in several

physiological processes (see Na in Table 1). However, the signs of salt, most importantly Na, deficiency

are not apparent. Often the symptoms are vague, and many other problems can be the cause, such as

nutrient deficiencies or disease (Underwood, 1981; Johansson, 2008). In tropical countries, common

salt is expensive and is not regularly fed to the animals (Khalili et al., 1993a).

Table 7 Mean mineral concentrations found by Abdelrahman et al. (1998) in the study of feed samples (in g kg-1 dry matter) in Sudan, compared to critical levels derived from McDowell and Conrad (1977) and Underwood (1981)

Co Ca Cu K Mg Mn Na P Zn Se Co

Feed 0.001 3.8 0.004 6 2 0.02 0.47 0.8 0.03 0.0001 0.001

Critical level 0.001 3 0.01 6 2 0.02 0.6 2.5 0.03 0.0001 0.001

A study performed in western Ethiopia, where grazing is the main source of diet for the zebu cattle,

Gizachew et al. (2002) also identified a significant effect of season on serum mineral concentrations.

Except for P and Mn, serum mineral concentrations dropped sharply during the dry season (Table 8).

For example, the Ca concentration dropped with about 55% from 337 mg l-1 in the wet season to

153 mg l-1 in the dry season, although the concentrations remained above the critical level in both

seasons. Also P, Fe, Mn and Zn concentrations remain above the critical level in both seasons. K, Mg

and Cu are below the critical level during the dry season, but above it during the wet season. All critical

levels were derived from Grace (1983).

19

Table 8 Mean mineral concentrations found by Gizachew et al. (2002) in the study of zebu blood serum (mg l-1) in Western Ethiopia, compared to critical levels derived from Grace (1983)

Ca Cu Fe K Mg Mn P Zn

Dry season 153 0.66 1.36 139 17 0.26 141 0.91

Wet season 337 1.38 3.27 249 23.5 0.11 141 1.45

Critical level 80-120 0.8-1.2 1.1-2.2 180-220 18-30 0.03 40-65 0.8-1.2

Since the energy and protein content in pastures also fall below maintenance requirements in the dry

season, mineral supplementing has a beneficial effect on animal production only if combined with extra

energy and protein rich feed. This will also reinforce rumen microorganisms to degrade dietary

substances that would otherwise impair the absorption of some mineral elements (Gizachew et al.,

2002).

Not only does the season during which the forage was produced influence the mineral concentration in

the grasses, also the altitude seems to play a role. Tsegahun et al. (2006) evaluated different feed types

collected from three altitudinal ranges in the central and western part of Ethiopia, in two different

seasons. The feed samples were found to be low in Ca, P, Mg, Na and K in the mid and higher altitudes;

Na was found to be low in all feeds regardless of the altitude.

IV.8 MINERALS AND MILK PRODUCTION

The mineral composition of milk differs per animal species and varies according to parity, stage of

lactation (colostrum being richer in minerals), nutrition and the presence or absence of disease. Cow

milk is a rich source of Ca, P, K, Cl and Zn and to a lesser extent of Mg, Fe, Cu and Mn, see Table 9

(Suttle, 2010).

Table 9 Representative values for the mineral contents of cow milk, adapted from Suttle (2010)

Ca P Mg K Na Cl Zn Fe Cu Mn

(g l-1) (mg l-1)

1.2 1.0 0.1 1.5 0.5 1.1 4.0 0.5 0.15 0.03

The effect of the cattle’s feed on milk production, as well as on the mineral composition of the milk

varies per mineral. A decrease in milk production is observed when Ca, P, Na, K and Fe deficiencies

are present, but these deficiencies are not reflected in the mineral concentrations of the milk (Suttle,

2010; McDonald et al., 2011). Deficiencies in Cu and I were found to result in a decline in the Cu and I

concentrations in the milk (Suttle, 2010). By augmenting I and Se in the diet, higher concentrations of

these minerals can be found in the milk (Givens et al., 2004; Suttle, 2010). On the contrary, raising the

intake of Cu, Mn and Zn does not increase the concentration of these minerals in the milk (Suttle, 2010).

No differences in milk yield or milk composition are found when dairy cattle are fed diets with variable

20

Ca:P ratios. However, both minerals should be present in adequate concentrations in the feed (NRC,

2001).

In an attempt to increase milk yield, several experimental studies have been performed to determine

the effect of mineral supplementation on milk production. To compensate mineral shortcomings,

supplementing with urea molasses multi-nutrient (UMMN) or multi-mineral blocks could increase

digestibility of fibrous feeds up to 20%, as well as increase the nutrient and feed intake by 25 to 30%

(ESGPIP, 2007). Supplementing with nutrient blocks has been studied in a number of countries, and

positive effects on dry matter (DM) intake, digestibility of nutrients, productive and reproductive

performance have been documented (Sahoo et al., 2009).

UMMN blocks are composed of different ingredients. Urea acts as source of fermentable nitrogen to

form ammonia, with an important role in the rumen. Molasses, by-products of refining sugarcane into

sugar, provide energy and a mixture of minerals and vitamins. These minerals alleviate mineral

deficiencies to obtain a balanced diet. Na and Cl can easily be supplemented by adding salt to these

blocks. Cement is used as binding agent to create and keep the block together. Both nitrogen and

energy reinforce the activity of ruminal microorganisms, boosting cellulose digestion and therefore

increasing roughage fermentation and feed intake. Associated with this increased fibre digestion, high

acetic acid fermentation in the rumen results in a rise in the milk fat production in dairy cows (Upreti et

al., 2010; Tekeba, 2012).

In Vietnam, UMMN blocks and urea-treated rice straw were adopted to successfully increase both the

milk production of dairy cattle by 10.3-11.9% (an increase of 1.3-1.5 kg cow-1, starting from

12.1 ± 5.6 kg cow-1) and the milk quality by increasing milk fat content by 3-5% (from 3.21% in the

control group to 3.32-3.36% in the supplemented groups), and thus the profit for the farmers.

Reproductive performances were significantly positively affected, the intervals shortened: from calving

to onset of ovarian activity from 112 to 91-94 days, to oestrus from 135 to 110-114 days, to conception

from 152 to 121-122 days and calving interval shortened from 14.4 to 13.4-13.6 months, compared to

the control group which was not supplemented. No significant improvements in body condition score

(BCS) and body weight (BW) were observed (Duc Vu et al., 1999).

In north-western Ethiopia, a study was performed in the Andassa Livestock Research Centre (ALRC),

on the use of UMMN blocks on local zebu and crossbred cows in milk production systems. A significant

improvement in milk quantity and quality was determined. The milk available for sale increased

significantly by 24% for the indigenous breed and by 34% for the Holstein crossbreed. The milk fat

content also increased significantly by 12% and 8% respectively, but no change in protein content was

observed. Besides the improved milk production, supplementing with UMMN blocks resulted in an

increase in estimated BW gain in both local and crossbreeds, with 121% and 97% respectively. An

increase in BCS was also observed, with 17% and 9% respectively, compared to the control cows. An

increase in feed (DM) intake was seen for both breeds (Tekeba, 2012). This supplemental feed

resource, rich in carbohydrates, proteins and minerals, is affordable and can easily be manufactured

on the farm. Producers can create and sell blocks as a source of income (Abebe et al., 2015). In

21

addition, the benefit-cost ratio for local and crossbreed cows has been shown to be 2.64 and 5.53

respectively in north-western Ethiopia (Tekeba, 2012). Although many studies report multi-nutrient

blocks to be low in cost and easy-to-use, Dermauw (2013b) states that it is rarely implemented in

developing countries due to high cost and low accessibility.

In other studies, where dairy cattle were supplemented with a mineral mix of Zn, Cu, Se and Co

(Dermauw, 2013b), with Cu (Engle et al., 2001), Se (Juniper et al., 2006) or Zn (Sobhanirad et al.,

2010), no positive effects on milk yield were observed. In another study by Dermauw et al. (2015), trace

element supplementation did not affect milk production nor milk composition.

22

V RESEARCH PROJECT

V.1 MATERIALS AND METHODS

V.1.1 Study area, animals and samples

This study was conducted in Arba Minch (Amharic for ‘Forty Springs’), at the end of the dry season,

between February and April 2017. It is located in the Ethiopian Rift Valley, at the base of the western

side of the Great Rift (Figure 3). This area is part of the Gamo Gofa Zone of the Southern Nations,

Nationalities and Peoples Region, in the south of Ethiopia (Aregu and Demeke, 2006). Arba Minch is a

435 kilometers drive from the country’s capital, Addis Ababa, and lies at an elevation of 1269 m above

sea level (Worldatlas, 2015; Google Maps, 2017). Although founded about forty years ago, Arba Minch

already counts a population of 69622 (World Population Review, 2017), making it one of the fastest

developing cities of Ethiopia, its population having grown from 57223 in 2001 and from 40020 in 1994

(CSA, 1996; Elias, 2003; Aregu and Demeke, 2006). The city is divided into four administrative sub-

cities and eleven kebeles or districts (Dube, 2012).

Figure 3 Left: a kebele, where people live in traditional housing; Right: Ethiopian Rift, Arba Minch is located in the yellow circle (IGG, 2017)

The study was carried out in four of the eleven kebeles of Arba Minch, namely Bere, Weze, Kulfo and

Gurba. These districts were randomly assigned after contacting the officer of agriculture and the kebele

leaders and obtaining their consent. A total of 49 indigenous zebu dairy cows were included in the study.

The criterion of selection was that the cow had calved at least once (parity of at least one), although

one cow of parity zero was also sampled. In Bere kebele 12 farms and 17 cows were sampled. In Weze

kebele 14 farms and 17 cows were sampled. In Kulfo kebele 3 farms and 4 cows were sampled. In

Gurba kebele 8 farms and 11 cows were sampled. See Table 10 for an overview.

All visited farmers were requested to participate in a survey for an assessment of the overall

management on the farm, and to register the amount of feed given for calculating DM and mineral

23

intake. The survey included questions about lactation status, reproductive and productive performance

parameters, feed type and amount, provided water and drug administration. To complete the

questionnaire, the amount of feed given per cow per day was measured in kilograms using a portable

hanging scale (Scales, NTS, capacity 50 kg and precision of 200 g). The stage of lactation and the

amount of milk (with precision of 300 ml) produced per day was recorded. Three stages of lactation

were noted: early from 0 to 3 months, mid from 4 to 6 months and late from 7 to 9 months after calving.

Although the data concerning the age, parity, stage of lactation, lactation length and milk production

were not written down by the farmers, they claimed to know this information by heart as they were in

possession of a few cows only. The questionnaire is included in the appendix.

All cows included in the study were measured using a flexible measuring tape. Their body length (from

the middle of the scapular spine to the tuber ischii), height at withers (with and without hump) and heart

girth (with and without hump) were measured, rounded to the nearest centimetre. The BCS, using the

1 to 9 scale specifically for zebu cattle (based on Nicholson and Butterworth (1986)), was evaluated on

site using plasticised BCS papers. Body condition scoring is a method used to evaluate the energy

reserves or the nutritional status of (dairy) cattle, and has proven useful as a management tool to help

improve the health of livestock (Hady et al., 1994; EBLEX, 2016) (Figure 5).

Feed samples were obtained from each farm, and blood, faeces, milk and

hair samples were collected from all dairy cows. Feed subsamples from

random places in the feed stack were pooled. Dry feed was placed in

envelopes and liquid feed in sealable pots. Wearing gloves, blood was

collected from the jugular vein with a 21G needle, after disinfecting the area

with alcohol (Figure 4). Two serum tubes (2 x 6 ml gel and clot activator

vacuum blood tubes, GongDong Golden VacTM) were filled. These blood

samples were immediately placed on ice in a cooler box.

Figure 4 Collecting blood from the jugular vein

Figure 5 Extremes in BCS (the cow on the right was not included in this study)

To avoid dirt contamination, rectal manure was taken, using gloves, and placed in a Ziploc bag.

24

The farmer was asked to collect milk directly from the udder after washing hands (Figure 6). The milk

samples were collected in 15 ml milk tubes with a screw cap and were also placed on ice.

Figure 6 Left: farmer milking her cow; Right: the material taken to the field

Switch hair (tuft of hair at the end of the tail) and poll hair (hair between the ears) free of visible

contamination were collected, using clean scissors, and stored in Ziploc bags. In total 47 blood samples,

49 faeces samples, 44 milk samples, 49 hair samples and 95 feed samples were collected. We were

unable to collect blood from two cows due to aggression. One cow was dry and one was a heifer, and

three cows were too aggressive to collect milk samples from. An overview is given in Table 10.

Within 4 hours, all specimens were transported to the laboratory at the campus of agriculture of the

Arba Minch University (AMU), for further processing (Figure 7).

Figure 7 Left: the College of Agriculture, partly under construction; Right: the lab and instruments

Table 10 Number of farms, cows and samples included in this study, grouped per district (kebele)

Kebele # farms # cows # blood # faeces # milk # hair # feed

Bere 12 17 17 17 13 17 43

Weze 14 17 17 17 17 17 27

Kulfo 3 4 2 4 3 4 8

Gurba 8 11 11 11 11 11 17

Total 37 49 47 49 44 49 95

From the heart girth measurement, individual BW was estimated using the regression formula

developed at the Andassa Livestock Research Center (ALRC) (Addisu, 2010; Tekeba et al., 2013):

25

𝐸𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑑 𝑏𝑜𝑑𝑦 𝑤𝑒𝑖𝑔ℎ𝑡 (𝑘𝑔) = 2.126 ∙ ℎ𝑒𝑎𝑟𝑡 𝑔𝑖𝑟𝑡ℎ (𝑐𝑚) − 87.39 2

After acclimatisation to room temperature, serum was obtained through centrifugation at 3000 rpm for

15 min.

All samples, except the hair samples, were transferred into weighed coffee cups and then reweighed.

Next, they were oven-dried at 65°C for at least 72 h, after which dry weight was attained and noted. All

used materials and instruments were washed using soap and rinsed three times with deionised water

before re-use. Dry plant samples were ground with mortar and pestle, passed through a sieve and

weighed. In the laboratory, an analytical and precision balance (Ohaus Pioneer PA124C Analytical &

Precision Balance) was used to weigh all samples (Figures 8 and 9).

Figure 8 Left: weighing the samples; Right: samples in the drying oven

Figure 9 Left: grinding the feed samples; Middle top: dry serum; Middle bottom and Right: ashed samples

Due to time constraints, all samples had to be analysed at UGent. To comply with the safety regulations

of the Federal Agency for the Safety of the Food Chain, all livestock samples had to be treated to be

pathogen free. Hence, all samples, apart from the hair, were ashed in a muffle furnace at 550°C for 8 h.

The temperature was increased gradually. Specimens were weighed before and after ashing (Figures

8 and 9).

Due to complications and circumstances, 2 of the 47 taken serum samples were lost during processing.

26

V.1.2 Farms and diets

All farms included in the study are located in Arba Minch city. The visited farmers owned a maximum

of five cows, with one to three dairy cows only. Most cows are housed in a sheltered area, and the

majority of the indigenous breeds are allowed to graze freely during the day (Figure 10). They are

released in the morning before 8 am to join the herd and head out to a grazing area under the guidance

of some shepherds. Around 5 pm the livestock return to their home (Figure 11).

Figure 10 Housing of the cattle

On the farm, the main feed types of the dairy cattle consist of hay or straw as roughage and brewage

by-products, or grain residues as concentrates and kitchen wastes. Table 11 gives an overview.

However, feed composition and amounts vary, depending on the availability of the feed. The animals

that graze freely drink water from the river, the ones that stay on the farm are either supplied with water

or taken to the river twice a day. Many animals (n = 29) were treated intramuscularly with

trypanosomiasis-prophylaxis.

Figure 11 Cattle returning home from the grazing area

27

V.1.3 Mineral analysis

Mineral analysis of all feed and serum samples was performed using inductively coupled plasma-optical

emission spectrometry (ICP-OES). The minerals analysed in feed and serum consisted of B, Ca, Cu,

Fe, K, Mg, Mn, Na, P and Zn. Additionally, Mo was determined in all feed samples using ICP-OES

(detection limit of 12 ppb in solution). All statistical analysis is performed with the software package

RStudio (R 3.3.1). Prior to analysis, as well as afterwards, all data was inserted into Excel spreadsheets.

Faeces, milk and hair samples were not yet analysed due to time and financial constraints.

Data was analysed using ANOVA statistical models. Each analysis was tested for significant

interactions of factors, such as lactation stage, BCS and parity. The level of significance used in this

study is 0.05. Where possible, results are presented with a 95% confidence interval for the mean.

For all minerals, values above toxic levels were treated as outliers as these values were physiologically

unrealistic.

In this study, the calculation for the net requirement for mineral intake consisted of two parts: one for

maintenance and one for milk production. The first part is expressed in g kg-1 BW while the second is

expressed in g kg-1 milk produced.

28

Table 11 Main feed types of the dairy cattle on the farms in Arba Minch

Farm

Ingredient 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37

Hay + + + + + + + + + + + + + + + + + + + + + + + + + + +

Atelaa + + + + + + + + + + + + + + + + + +

Frushikab + + + + + + + + + + + + + + + +

Maize + + + + + + +

Teff + + +

Vegetablec + + + + + + + + + + +

Grassd + + + + + + + +

Fruit e + + + + + +

Harag + + + + + + + + + + + + + + + +

Bananaf + + + + + + + +

Brewageg + + +

Barley + + +

Enjerah + + + +

Sugarcanei +

Moringaj +

Sweet potato +

a Local liquid brewing by-product of alcoholic beverage made from maize or sorghum; b Bran; an industrial by-product of milling in the production of refined grains (maize, wheat, barley, and

millet); c Kitchen waste of cabbage, onion and/or carrots; d Savanah or elephant grass; e Kitchen waste of banana, papaya and/or avocado; f Banana/Enset leaves or stem; g Waste of brewing by-

products such as borde; h Flat bread made from teff flour, usually dried for the cattle; i Leaf; j Stem

29

V.2 RESULTS

V.2.1 Serum mineral concentration vs lactation stage

For each mineral, serum mineral concentrations per lactation stage were statistically analysed using

ANOVA. Only serum mineral concentrations for Na were different between the lactation stages

(p = 0.031). The Na serum concentration, with a 95% confidence interval, is 3.02 ± 0.38; 2.31 ± 0.19

and 2.70 ± 0.40 g l-1 for the early, mid and late lactation stages respectively.

V.2.2 Correlation of serum mineral concentrations

Because of the lack of significant differences between the lactation stages in the serum mineral

concentrations, the lactation stages were pooled. Table 12 displays the correlation coefficients of the

serum mineral concentrations; Figures 12 and 13 display some of these correlations graphically.

Table 12 Correlation coefficients of the serum mineral concentrations, bold if significant (p < 0.05)

Ca Cu Fe K Mg Mn Na P Zn

Ca 1

Cu 0.70 1

Fe 0.82 0.80 1

K 0.10 0.22 0.13 1

Mg 0.81 0.43 0.60 0.14 1

Mn 0.00 0.23 0.14 0.36 0.03 1

Na 0.78 0.22 0.35 0.36 0.71 -0.13 1

P 0.52 0.09 0.51 0.38 0.68 0.00 0.67 1

Zn 0.63 0.44 0.56 0.15 0.18 0.19 0.25 0.25 1

Figure 12 Linear regression between serum K and Mg concentration; with 95% confidence band

30

Figure 13 Linear regressions between serum Cu and Fe concentration; Cu and Zn; Ca and P, all with 95% confidence band

31

V.2.3 Serum mineral concentration vs body condition score (BCS)

In this analysis, we have focused on the body condition score (BCS) ranging from 1 to 6. The mean

values of the serum mineral concentration per BCS are presented in Figures 14 and 15. No significant

differences in serum mineral concentrations were found between the BCS.

Figure 14 Mean serum macromineral concentrations in function of the body condition score. [Na]·10-1 for a better representation

Figure 15 Mean serum micromineral concentrations in function of the body condition score

32

V.2.4 Serum mineral concentrations vs reference values

Two types of serum reference mineral concentration values were adopted. The first is a limit for

deficiency, below which deficiency symptoms occur. The second is the concentration found in healthy

animals.

From the former results we concluded that generally there were no effects of lactation stage and BCS

on serum mineral concentration. Hence it was acceptable to pool the data. In this section, serum mineral

concentrations of all cows were compared with the two types of reference values, with two-sided one

sample t-tests. The mean serum concentrations of all minerals, except for Na (2.75 ± 0.22 < 3.10 g l-1),

were higher than the limit for deficiency. However, Ca and Mg serum concentrations were significantly

lower than the reference value for a healthy animal (95 ± 15 < 110 and 26.1 ± 2.2 < 40 mg l-1

respectively). The other elements are equally high or higher than the reference value for a healthy

mineral status. The results are presented in Figure 17. In Figure 16, the percentage of lactating cows

with adequate and deficient serum mineral concentration levels are graphically displayed.

Figure 16 Percentage of lactating cows with adequate, intermediate and deficient serum mineral concentration levels

0

20

40

60

80

100

Na Ca Cu Mg K Mn P Fe Zn

% o

f co

ws

Deficient Intermediate Adequate

33

Figure 17 Boxplots of the serum mineral concentrations (mg l-1) for all the cows (n = 47). The red solid line (bottom) is the lower limit for mineral deficiency, the green dashed line (middle) is the reference value for a healthy mineral status and the blue dashed-dotted line (top) is the reference value for toxicity

V.2.5 Milk production vs serum mineral concentrations

In this study, the milk production does not significantly differ between the three lactation stages

(p = 0.24), with a production of 1.62 ± 0.24, 1.24 ± 0.42 and 1.33 ± 0.42 l day-1 for the early, mid and

late lactation stage respectively (Figure 18). Of all the minerals analysed, no correlations exist between

the mineral concentrations and milk production.

34

Figure 18 Milk production in function of the lactation month. The bigger the circle, the more cows producing the same amount of milk at the same point in time of lactation

V.2.6 Milk production vs total dry matter intake (TDMI) and body condition score (BCS)

An important factor in milk production is the total dry matter intake (TDMI) of the cows. In this study, no

significant differences were found concerning TDMI between the different lactation stages (p = 0.82),

with 5.52 ± 0.93, 5.46 ± 1.30, 5.94 ± 1.34 kg dry matter day-1 for the early, mid and late lactation stages

respectively. There was only a weak link between TDMI and milk production, as is shown in Figure 19.

The linear model shows that only 8.2% of the milk production variation was explained by TDMI. An

increase of TDMI of 5.8 ± 3.4 kg day-1 would result in a milk production increase of 0.5 l day-1. A positive

relation exists between BCS and milk production (Figure 20).

Figure 19 Linear regression between milk production and total dry matter intake of all lactation stages, with 95% confidence band

35

Figure 20 Linear regression between body condition score and milk production of all lactation stages, with 95% confidence band

V.2.7 Body condition score vs total dry matter intake (TDMI)

Figure 21 examines the relation between BCS and TDMI, all cows (n = 49) are included. The linear

regression only explains 8.4% of the total variance observed in the BCS. For an increase of one BCS

point, a cow should eat 6.7 ± 4.1 kg of dry matter extra.

Figure 21 Linear regression between total dry matter intake and body condition score, all cows included, with 95% confidence band

V.2.8 Effects of parity

In this section, the effect of parity on the parameters milk production, BCS and TDMI is investigated.

None of these parameters were affected by parity (r = -0.27; -0.098; -0.015; p = 0.067, 0.49, 0.92

respectively). There was also no effect of parity on the serum mineral concentrations (all p-values above

0.18).

36

V.2.9 Mineral intake vs requirements and maximal tolerable limits (MTL)

V.2.9.1 Net mineral requirement

With a paired t-test, differences between the required intake and the effective intake were examined.

Minerals excluded from analysis are B and Fe.

Only Na was present in limited amounts in the feed, with 3.18 ± 0.83 g day-1 (p < 0.001). Ca, K, Mg, Mn,

P and Zn were sufficiently present in the feed and the intake was well above the net mineral requirement

(p < 0.001) as well as the Cu intake (p = 0.015). Mo intake did not differ from the requirement (p = 0.43).

The daily mineral intake was lower than the maximum tolerable level (MTL) for the minerals Ca, K, Mg,

Mn, Na, P, Zn and Mo (p < 0.001). Cu intake was not lower than the MTL (p = 0.098).

For all elements except P (r = 0.39; p = 0.0060) there was no significant correlation between serum

mineral concentration and daily mineral intake. No correlations were found between the intake of Zn,

Mo and Fe on the one hand and the serum concentration of Cu on the other hand. For the Ca:P feed

intake ratio, there was a significant negative correlation with the serum P concentration (Figure 22).

Figure 22 Linear regression between the Ca:P ratio in the feed intake and serum P concentration, with 95% confidence band

37

V.2.9.2 Gross mineral requirement

As the gross mineral intake requirement takes into account that minerals are not always completely

available in feedstuffs, the absorption coefficients are presented in Table 13, together with the daily

mineral intake, requirement and maximum tolerable level (MTL).

Table 13 Absorption coefficients, mean value for all feedstuffs (from NRC (2001)). The mean mineral intake and requirement for all the cows (n = 49) is presented with 95% confidence interval. Intake in bold is significantly lower (p < 0.05) than the gross requirement. The maximum tolerable level (MTL, from NRC (2005)) is bold when not significantly higher than the mineral intake

Mineral Absorption coefficient Intake Requirement MTL

(%) (g day-1) (g day-1) (g day-1)

Ca 33 33.5 ± 6.6 26.0 ± 1.2 84.3 ± 9.3

Cu 3 0.66 ± 0.53 0.0577 ± 0.0019 0.225 ± 0.025

K 93 45.6 ± 9.4 11.90 ± 0.48 113 ± 12

Mg 16 11.8 ± 2.0 5.02 ± 0.21 338 ± 37

Mn 3 0.358 ± 0.051 0.01887 ± 0.00054 11.3 ± 1.2

Na 90 3.18 ± 0.83 11.25 ± 0.32 66.4 ± 7.4

P 60 13.7 ± 2.1 9.4 ± 1.0 39.4 ± 4.4

Zn 15 0.190 ± 0.036 0.0937 ± 0.0056 2.81 ± 0.31

In Figure 23 the amounts of daily mineral intake and gross daily mineral intake requirements, as well

as the MTLs are presented.

38

Figure 23 Boxplots of daily mineral intake (g day-1). Green dotted lines represent the 95% confidence band of the gross requirement for all cows. Red dashed lines represent the 95% confidence band of the maximum tolerable level. No gross requirement for B and Mo

V.2.10 Effects of body weight (BW)

Several factors can be influenced by BW. In this section, the effects of estimated BW on parity, milk

production, BCS, and TDMI are presented.

Between the different parities (1 to 5), differences were found regarding BW (p = 0.010). The estimated

BW for parity 1 to 5 was respectively 204.1 ± 8.6; 226.0 ± 6.8; 223 ± 14; 216 ± 11 and 220 ± 37 kg.

There was an almost significant positive correlation between milk production and estimated BW

(r = 0.27; p = 0.066). There was a positive effect of estimated BW on BCS (Figure 24). Finally, there

was no significant correlation between BW and TDMI (r = 0.15; p = 0.27).

39

Figure 24 Linear regression between body condition score and estimated body weight, for all cows, with 95% confidence band

V.2.11 List of feed types

Several types of animal feed were analysed in this study to reveal the mineral concentrations. These

values are presented in Table 14. The percentages of dry matter intake of the most common feedstuffs

in Arba Minch are presented in Figure 25.

When the different feed types were grouped in roughages on the one hand and concentrates on the

other, we found a significantly higher K, Mg, Na, P and Zn content in concentrates (respectively

11.9 ± 3.5; 2.87 ± 0.56;1.27 ± 0.69; 4.92 ± 0.92 g kg-1 DM and 48 ± 11 mg kg-1 DM) compared to the

concentration in roughages (respectively 5.6 ± 3.1; 1.66 ± 0.62; 0.174 ± 0.056; 1.04 ± 0.43 g kg-1 DM

and 24 ± 11 mg kg-1 DM).

Figure 25 Percentage of dry matter intake of the most common feedstuffs

0 10 20 30 40 50

Other

Banana stem

Maize

Teff

Frushika

Atela

Harag

Hay

% of dry matter intake

40

Table 14 Common feedstuffs in Arba Minch and their respective mineral concentrations (mg kg-1 dry matter (DM)), sample size n is given, significantly higher concentrations (p < 0.05) than the other feedstuffs are bold, almost significantly higher concentrations are italic, with 95% confidence intervals

n %DM B Ca (·103) Cu Fe (·103) K (·103)

Roughages

Harag 6 5 40.0 ± 6.6 13.9 ± 4.4 9.1 ± 3.0 3.6 ± 2.5 19.0 ± 11.1

Hay 22 92 3.6 ± 2.3 3.6 ± 1.3 4.1 ± 2.8 1.7 ± 1.6 2.05 ± 0.74

Concentrates

Atela 15 20 7.3 ± 1.6 4.6 ± 1.4 6.3 ± 1.6 1.08 ± 0.27 9.6 ± 2.2

Banana stem 4 54 8.5 ± 3.0 8.3 ± 7.0 3.4 ± 2.8 1.6 ± 2.7 28 ± 32

Frushika 8 92 7.4 ± 1.6 10.6 ± 4.2 9.7 ± 2.1 0.691 ± 0.085 11.1 ± 1.8

Maize 4 94 3.3 ± 2.9 0.47 ± 0.55 4.5 ± 3.5 1.6 ± 2.1 6.3 ± 4.2

Table 14 Continued

Mg (·103) Mn Na P (·103) Zn Mo

Roughages

Harag 4.4 ± 1.2 111 ± 55 328 ± 154 3.0 ± 1.3 27 ± 7.0 7.6 ± 13.3

Hay 0.98 ± 0.38 63 ± 49 140 ± 59 0.50 ± 0.14 18 ± 10 0.75 ± 0.42

Concentrates

Atela 2.88 ± 0.73 37.9 ± 8.4 375 ± 105 5.7 ± 1.4 56 ± 16 0.54 ± 0.22

Banana stem 4.8 ± 3.4 89 ± 78 346 ± 345 2.3 ± 2.7 22 ± 30 0.47 ± 0.33

Frushika 2.83 ± 0.53 89 ± 14 4000 ± 1500 6.3 ± 1.0 60 ± 20 0.74 ± 0.18

Maize 0.98 ± 0.40 31 ± 28 49 ± 51 1.99 ± 0.94 21.0 ± 7.7 0.42 ± 0.64

41

V.3 DISCUSSION

From the results obtained, the mean serum mineral concentrations of 45 zebu dairy cows in this study

were higher than the limit under which deficiency symptoms would occur, except for Na (Figure 17).

The serum concentrations of Mg and Ca were significantly lower compared to the reference values

used for a healthy animal, but not deficient. On individual cow level, 80% of the cows were deficient in

Na (n = 35). A Na shortage was also found in the feed, which confirms what is seen around the world

(Khalili et al., 1993a; Abdelrahman et al., 1998; Tsegahun et al., 2006; McDonald et al., 2011).

As indicated in ESGPIP (2007) and Tekeba (2012), most animals are confined to grazing on poor quality

rangelands, while on the farm they are fed fibrous feeds, crop residues, and brewing or industrial by-

products. This study confirms that the grazing dairy cattle of Arba Minch, like in other parts of the world,

are unable to take in enough Na from the feed and need salt supplementation to compensate for this

Na shortage. Compared to the requirement presented in NRC (2001), the cows lack 7.82 ± 0.90 g Na

day-1. Although it is possible that the animals take up Na from other sources, such as drinking water

and soil, an advised extra amount of 19.9 ± 2.3 g salt day-1 should be added to the diet to reach the Na

intake requirement.

Na is necessary for milk production (Suttle, 2010; McDonald et al., 2011), which was found to be low

(mean of 1.44 ± 0.21 l day-1) among the studied animals. However, in this study, no significant

correlation between the serum Na and milk yield was established. Yet, the Na concentration was found

to be significantly higher in the early stage compared to the mid lactation stage. Contrarily to the zebus,

high milk producing cattle experience a milk peak in the early lactation stage, which was not observed

in this study. However, as Na is needed for milk production, we would expect the Na serum

concentration to be lower in the early lactation stage, which is the opposite of what was found in this

study. But, contrarily to high milk yielding cattle, no significant differences in milk yield were observed

between the three lactation stages for these zebu cows. The question remains if the reference values

given in NRC (2001) (for B. taurus) are valid for the zebu cattle (B. indicus), as no clinical symptoms of

Na deficiency are mentioned in studies performed in Ethiopia. Perhaps this suggests that the deficient

serum concentration values in high milk yielding cattle is not deficient for a zebu as they are known to

cope under harsher conditions (Macedo et al., 2013).

Although Cu deficiency is very common in Ethiopian cattle (Dermauw et al., 2014), this study found no

evidence of Cu deficiency in the serum of the cattle in Arba Minch. According to Suttle (2010) and Khalili

et al. (1993a) blood is an inaccurate indicator of the current mineral status of the animal. Although the

serum mineral concentration is frequently used to assess mineral deficiency, it is the liver mineral

concentration that is the most accurate (Frøslie et al., 1983; Khalili et al., 1993b; Kincaid, 1999; NRC,

2001; Suttle, 2010). However, blood collection is the least invasive and the easiest way to determine

the mineral status of the animals on the farms; various studies adopt this technique.

From literature, we expect mineral interactions in the feed absorption, where one mineral reduces the

absorbability of another. It was assumed that these would be reflected in the serum, and therefore linear

42

regressions were performed. However, this study cannot confirm the Cu-Fe, Cu-Zn, and K-Mg

correlations. A positive correlation was found between serum Cu-Fe and Cu-Zn, yet the importance of

the Cu-Zn association can be doubted (R² = 0.20). As for K-Mg, no significant correlation was

demonstrated, and the wide variation is clearly visible in Figure 12. In the feed analysed for the purpose

of this study, only one feed intake Ca:P ratio was found to be as high as 6:1. Nevertheless, this does

not exceed the the critical ratio of 7:1 (Miller, 1983). However, high Ca intake reduces P absorption,

which is indeed seen in Figure 22. As a low Ca concentration was observed in the serum and rather

low in the feedstuffs, there was no reduced P absorption and therefore no P serum deficiency was

found.

In this study, no significant correlations were found between the serum mineral concentrations and the

BCS. In a mineral supplementation study (Cu, Zn, Se, Co and I) of Dermauw et al. (2015), a fall in BCS

was detected in the mineral supplemented group, whereas in a study by Tekeba (2012), using a UMMB,

an increase of 15% in BCS was registered for the local cattle. The effect of mineral supplementation on

the BCS is unclear, as UMMBs contain more than just minerals. Therefore, further research is

necessary to determine the effect of certain serum mineral concentrations on BCS. Nevertheless, this

could prove difficult as that more than one factor affects BCS such as parity, age, DMI and milk

production (Roche et al., 2009).

As the growing population demands more land for crop production, a reduction in grazing land results

in shortage of feed and land degradation through overgrazing. Enhancing agricultural productivity in a

sustainable way is key to sustain livelihood for the dairy farmers in the region. It is therefore important

to establish mineral concentration status mainly of the indigenous dairy cattle, to optimise feed

production, whereby crop residues and agro-industrial by-products could be adequately utilised, with

cultivation of forage and development of the necessary commercial feed production. This could

generate income and employment and thus improve welfare on an economically sustainable basis

(Shapiro et al., 2015).

From Figure 25 can be deduced that the most prominent cattle feed types are hay, harag, atela and

frushika. When the mineral composition of the hay in Ethiopia and the hay in Europe and North America

were compared, there were quite some differences regarding its quality. Ca, Mg and Cu concentrations

of Arba Minch were similar to the poor quality hay in Europe (see Table 15 in the appendix). However,

Na and P were present in much lower concentrations (five and two times lower, respectively) than even

the poor quality hay in Europe. This confirms the many studies reporting East African forages to be low

in Na and P (Khalili et al., 1993a; Abdelrahman et al., 1998; Tsegahun et al., 2006; McDonald et al.,

2011). In contrast with other studies performed throughout Ethiopia (Faye et al., 1986), the main feed

types in Arba Minch were in general not low in Zn when compared to the feed in Europe and North

America. Even between the north and south of Ethiopia, differences in mineral composition were

observed for the same feed types. When compared to data presented by Khalili et al. (1993a, 1993b),

the hay in Arba Minch seemed to be, on average, poorer in all minerals (except for Fe) than the hay in

the north of Ethiopia. This study was performed in the dry season, which implies that most mineral

concentrations in the feed were at their lowest, so the effect of season, which was established in several

43

studies (Khalili et al., 1993a, 1993b; Abdelrahman et al., 1998; Gizachew et al., 2002; Tsegahun et al.,

2006) must be borne in mind.

From all the feed samples analysed, we found harag to be richer in certain minerals than the other

forages. It was significantly higher in B, and nearly so for Ca, K, Mg and Mo. As Mo is an antagonist of

Cu, an excess of harag can suppress Cu absorption and lead to copper deficiency. Cu was marginally

deficient in all forages, which corresponds to other studies performed in Ethiopia (Khalili et al., 1993b;

Gizachew et al., 2002; Dermauw, 2013a). Fe was present in high concentrations in all feed samples,

and can therefore act as an additional antagonist of Cu. Like Fe and Mo, Zn will also have a negative

impact on the Cu absorbability. However, this study cannot confirm these correlations.

Interestingly, frushika was found to be rich in minerals, without containing high levels of minerals that

interfere with Cu absorption, such as Fe and Mo. It was also found to be rich in Na and Ca, which is

useful considering that low Na and Ca serum concentrations were established. Somewhere in the

production process of frushika, a mixture of bran, probably salt must have been added, as the Na

concentration is much higher than that of grains. Additionally, banana stem was found rich in Mg. On

the contrary, maize and atela presented low Ca values and are therefore not suitable to compensate

for this low serum level. Atela is a brewing by-product of local beer made from maize or sorghum. The

diet for dairy cows needs to be diverse, while too much of one feed, such as harag, must be avoided.

Frushika seems to be a promising alternative, but as it is an industrial by-product, it needs to be imported

from the bigger cities to Arba Minch. Therefore, the quantity and quality of the cattle’s feed depends on

their availability on the market.

Considering the net requirements for mineral intake, this study indicates that Na intake was too low for

the studied zebu cattle of Arba Minch. This can be attributed to the low Na concentration in the supplied

feeds, and reflected as a Na deficiency in the serum. However, no correlation can be determined

between serum mineral concentration of Na and the daily mineral intake. This absence of significance

is possible if the mineral status is in a homeostatic phase, in which case increase or decrease of a

mineral supply will not make a difference in the animal’s serum concentration. This would imply that the

homeostatic phase of a zebu (2.75 ± 0.23 g l-1) is lower than that of the Holstein (3.45 g l-1, NRC (2001)),

again raising the question of the reference values used for this study. Considering that no energy is

invested in growth during the dry season (when this study was conducted), these values would be

negligible, therefore requirements for growth were not considered.

Unlike the net mineral intake, the gross mineral requirement takes into account that minerals are not

readily available in a feed. As stated earlier, the present study neglects the absorption differences

between feed types, and employs one absorption factor per mineral, a simplification based on the model

by NRC (2001). A better calculation of the gross requirement would be using the absorption coefficients

for each feed individually. The Na intake was also significantly below the gross requirement. For Mg

and Ca, the intake was above the requirements, yet the absorption appeared to be lower than expected,

resulting in low serum concentrations.

44

For milk production, there was only a weak link with TDMI (p = 0.052), as shown in Figure 19. So any

link between TDMI and milk production cannot be substantiated by these data. If feed intake barely has

an effect on milk production, other factors such as the animal’s genes and farm management, are the

more important limiting factors. The Ethiopian government is already trying to improve the milk yield by

crossing the indigenous breeds with highly productive breeds. Only when the limiting factors are dealt

with, can mineral supplementation have an effect on the milk yield. Duc Vu et al. (1999) and Tekeba

(2012) identified an increase in milk yield when supplementing with UMMBs, which contain several

minerals but also energy. Other studies found mineral supplementation to not have an effect on milk

yield. This was the case for Zn, Cu, Se, Co and I in Dermauw (2013b; 2015), Cu in Engle et al. (2001),

Se in Juniper et al. (2006), and Zn in Sobhanirad (2010). Additionally, no effect of lactation stage on the

milk production, nor on the serum mineral concentration, was found.

The use of “body condition scoring”, as a method for evaluating the energy reserves or the nutritional

status of (dairy) cattle, was confirmed in this study, as a positive correlation was found between the

BCS and the TDMI. However, there was a wide variation for TDMI in each BCS (R2 = 0.082, p = 0.052)

(Figure 21). In Figure 20, a positive link between BCS and milk production is shown (R2 = 0.14,

p = 0.0087). There was also a positive correlation between the BCS and the estimated BW. When the

feed of Holsteins is reduced, the high milk producing cows tend to keep their high milk production, at

the cost of their BCS. Low milk producing Holsteins tend to lower their milk yield and upkeep their BCS.

Zebu cattle could be classified as and compared to a low producing dairy cow. However, from the data

collected in this study, it can be assumed that zebu cattle reduce their milk production as well as their

BW and BCS when fed a suboptimal diet.

45

V.4 CONCLUSION

In this thesis, blood samples were collected to assess the mineral status of zebu dairy cattle in Arba

Minch, and feed samples were analysed to evaluate the mineral composition. Despite the findings of

several studies in Ethiopia, a general Cu deficiency it could not be established, although 20% of the

animals were Cu deficient. In the serum, the zebus were deficient in Na (>80% of the animals), and

were below the reference value for a healthy animal for Mg and Ca. For a more accurate view of the

mineral status, an additional study could sample and analyse livers from a local abattoir.

The most common feed types in this study were of poor quality; hay was low in Ca, Mg and Cu, and

deficient in Na and P, whereas harag was rich in B, Ca, K, Mg and Mo. Although the intake of Mg and

Ca was above the requirement, the absorption seemed to be lower than expected. This suggests that

extra Na, Mg and Ca should be supplied in the feed. Frushika seems to be the most interesting product

to include in a more diverse diet, as it was found rich in Ca and Na, and banana stem could be added

as a source of Mg. A more obvious alternative feed supplement rich in Na would be salt. This can be

added to the diet with an advised amount of 20 g extra day-1. Yet, caution must be advised, as this salt

requirement is based on numbers established for high milk producing cattle. For future studies, new

serum reference concentrations and intake requirements specifically for the tropical (zebu) breeds

should be investigated. In addition, the use of absorption coefficients per feed type would be more

accurate.

This study was unable to demonstrate a link between mineral deficiencies and milk production.

However, a higher milk production was associated with a higher body condition score, and the latter

increased with a higher total dry matter intake. No difference in milk yield was found between the

lactation stages. The total average milk yield remained constant (1.44 l day-1) independent from serum

mineral concentrations. This suggests that before one can attempt to increase milk production through

mineral supplementation, limiting factors should be addressed first, including farm management, the

provision of qualitative feed and the genetic selection.

46

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52

VII APPENDIX

Questionnaire on smallholder dairy farm management

Kebele name: Date:

Name of farmer:

1. Cow identification and lactation status

2. Reproductive and productive performance parameters

Cow

number

Age at first

calving (years)

Calving interval

(months)

Lactation length

(months)

Milk production

per day per cow

(litres)

3. Are the calves weaned? If yes, at what age (in weeks)?

4. Type, amount and frequency (once/twice a day) of feeding

Type and amount (in kg) per day

Cow

number

Hay Atela2 Frushika3 Dried

banana

stem

Free

grazing

(yes/no)

2 Local brewing by-product of alcoholic beverage

3 In pellet form = industrial by-products of grains (such as sorghum)

Cow

number

Age (years) Parity (0-7) Early-, Mid-, Late

Lactation or Dry1

1E=Early (0-3m after calving), M=Mid (4-6m), L=Late (7-9m) lactation and D=Dry

53

5. How much (litres per day) and how frequently do you provide water for your cattle on the farm?

Cow

number

Water source Ad libitum Once a day Twice a day Other

6. When was the last time drugs (for parasites, bacteria etc.) were administered to the cows? To

which cows, how frequently and at what dose?

7. Measurements and Scoring

Cow

number

Body length4

(cm)

Height at

withers (cm)

Heart girth (cm) Estimated

weight (kg)

BCS5

4 Scapular-ischial length

5 For local breeds (1-9)

54

Table 15 Mineral composition of feed types in Europe and North America (adapted from McDonald et al. (2011)

Ca Mg Na P Cu Mn Zn

Fresh grass 4800 1700 1700 2800 7 16 5

Grass silage 3000-8000 900-3000 1000-3000 2000-4000 3-11 90-94 25-30

Grass hay 2500-7000 800-2500 1000-2500 1500-3500 2-9 70-100 17-21

Clover 15300 4300 1900 2500 11 73 17

Maize 300 1100 200 2700 2.5 6 16

Lucerne 21000 2700 2100 3300 11 41 /

Cereal silage 4000 1000 1800 2700 6 80 25

Barley 4500 800 1100 700 3.2 84 16

Wheat 500-1100 1200-3300 100-400 8000-13600 5-17.5 42-143 50-189

Sugar beet pulp 5700 2400 2500 800 11 51 32

Soya bean meal 3500 3000 400 6800 25 32 61