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Section 1 - Module 7: Animal nutrition

 


Part A: Concepts
Part B: Purposes
Part C: Types of data
Part D: Methods of data collection
References


This module provides a framework for the diagnosis of nutritional problems in traditional African livestock production systems. The discussion is confined to the main ruminant species (cattle, sheep and goats),1 because of their relative importance in an African context2 and because of the emphasis given to ruminants in ILCA's research work. The module follows the format used elsewhere in this section but it also includes definitions of some of the basic concepts used in the literature.

1 The anatomy and physiology of the ruminant is not discussed in this module. It is assumed that the reader is familiar with the basic characteristics of ruminant digestion, which are discussed in several textbooks (e.g. Van Soest, 1982; Church and Pond, 1982).

2 Ruminants and camels (also known as pseudo-ruminants) comprise approximate y 90% of domestic livestock units in sub-Saharan Africa (FAO, 1986).

The reader is encouraged to use the support references given at the end of this module to ensure that an adequate background on the topic is obtained. Butterworth's (1985) book is a useful complement in that it provides a comprehensive review of research on animal nutrition in the tropics and includes an extensive reference list. Other references such as Van Soest (1982), Church and Pond (1982) and McDowell et al (1986) are useful basic texts on the theory of ruminant nutrition.

Part A: Concepts


Feed-related concepts


In any discussion of the principles of animal nutrition, the concepts most commonly used relate either to the animal (as the user of feed) or the feed (as the source of nutrients). The concepts defined below are grouped accordingly into animal- and feed-related concepts.

Concepts related to animal productivity

The term 'productivity' refers to the ability of an animal to grow, reproduce and produce outputs such as milk, wool, draught power and transport.3

3 Liveweight growth can be negative (through a loss of weight), while the production of other outputs such as milk and draught continues. rut in another way, the requirements for maintenance need not always be met in order for production to continue, e.g. feed intake needs to fall substantially below maintenance requirements before wool production actually ceases (Davies, 1982).

In order to perform these functions on a sustained basis, essential nutrients in the form of energy, proteins, minerals, vitamins and water (above those necessary for the maintenance of normal body functions), must be provided. For a given animal species, the level of production achieved will, in turn, depend on the quantity and nutritive value of feed available, breed, genetic potential, sex, age and management.

Below are some of the basic concepts related to animal productivity and their definitions.

Maintenance. When an animal is not reproducing or producing any other output, and when body weight and condition are stable (i.e. the ratio between fat and muscle), it is said to be in maintenance condition (McDonald et al, 1973, p. 261),4 with its energy requirements in 'balance' or 'equilibrium.'5

4 The use of body weight as the sole criterion for assessing maintenance condition is not reliable since an animal can maintain weight by an increase of water in body tissues, while losing condition (fat and/or muscle). For a discussion of condition and body weight refer to page 152 of this module.

5 The same applies to other essential nutrients. If, for instance, an animal is fed a diet lacking protein, it will continue to lose nitrogen in its faeces and urine and will be in a state of negative nitrogen balance. The concept of maintenance, therefore, implies that all nutrient requirements are in balance, with nutrient inputs being exactly offset by nutrient losses. It is more common, however, to refer to maintenance in terms of the energy requirements of the animal.

However, this definition is complicated by the fact that animals can adapt to sub-maintenance energy levels by lowering their requirements in order to stabilise their body weight and condition. This phenomenon has been observed in African cattle in Kenya (Ledger and Sayers, 1977).

The ability to adapt to lower energy levels has important implications for feeding requirements on tropical African grasslands, where animals spend long periods in a state of maintenance or near maintenance. The fact that Bos indicus cattle appear to be more efficient in this respect (Butterworth, 1985) is also of interest. Thus, the standards for cattle maintenance and growth, used in the northern hemisphere, may not be applicable in the context of African tropical grasslands.6

6 Standards have been devised in the USA, by the National Research Council (NRC), and in Britain, by the Agricultural Research Council (ARC), which relate to the daily nutritional needs for growth and production (energy, protein and minerals) of different species of livestock. The standards used in the United States are summarised in a series of booklets published by the NRC (1976) under the general title Nutrient requirements of domestic animals. ARC (1965; 1980) gives similar tables. The standards adopted by ARC (1980) are likely to be closer to the animal requirements of tropical livestock.

Metabolism. Metabolism is the sum of all the physical and chemical processes taking place in living organisms. Some of these processes involve the degradation or decomposition of complex compounds to simpler materials (catabolism) and others involve the synthesis of simpler materials into complex compounds (anabolism). The excretion of waste products from the body is part of the metabolic process.

Fasting metabolism. The amount -of energy used for the maintenance of an animal is known as fasting metabolism, and it is estimated as follows:

Fasting metabolism (kcal of NE/day) = 70 W0.75

or

Fasting metabolism (kJ of NE/day) = 293 W0.75

where:

NE = net energy (see page 154 of this module)
W = the animal's liveweight in kilograms, and
W0.75 = the so-called 'metabolic weight' of the animal.

This relationship between the liveweight of a ruminant animal and the amount of energy it uses for fasting metabolism is applicable to all ruminant species, though variations occur between species as well as within species (e.g. on the basis of age and sex). The equation can be used to estimate whether the energy intake of an animal is sufficient to meet its energy requirements for maintenance and/or production (see Part D of this module).

Compensatory growth. This concept refers to the ability of an animal to recuperate or recover growth after periods of underfeeding. Recovery following underfeeding has often been associated with higher than normal rates of growth (see Figure 1) and has been observed in cattle and small ruminants.

As a general rule, the earlier in life nutritional stress occurs and the longer the period of feed deprivation, the less the compensatory growth will be. In the African rangelands, periods of nutritional stress are common because of long dry seasons and frequent droughts.

Condition. The condition of an animal is reflected in the proportion of body fat and muscle on its carcass. It is generally a more reliable indicator of an animal's nutritional status than body weight since variations in the latter may merely result from changes in gut fill, body water, parturition etc.

Condition measurement has, therefore, been used to monitor changes in animal body reserves over time (Nicholson and Sayers, 1987), and rapid appraisal methods have been devised to 'condition score' African cattle for this purpose (Module 5) (Pullan, 1978; Nicholson and Butterworth, 1986).

Figure 1. Patterns of growth.

Source: Davies (1982, p. 14).

Intake. Intake is the amount of feed voluntarily consumed by an animal. It is determined by:

· the availability, palatability and digestibility of feed

· the nutrient content of the feed

For instance, feed intake is depressed when a diet contains inadequate amounts of minerals, vitamins and various sources of nitrogen (Davies, 1982), or when it is poorly digestible.

· bite size and frequency which, in turn, is influenced by plant structure and feed availability

For instance, Stobbs (1973) found that the amount consumed per bite tends to increase with the amount of green leafy material in the sward.

· the physiological status of an animal

For instance, pregnant animals have different intake requirements according to litter size and stage of gestation.

· environmental conditions

For instance, the availability of water will affect the amount of feed an animal consumes, as will temperature and humidity.

· infectious, parasitic and metabolic diseases, which may depress intake.

The measurement of intake is discussed in detail in Part D of this module.

Feed selection and palatability. Animals show distinct preferences for particular types of feed. The animals' feed preferences are influenced by feed availability, plant structure, nutrient deficiencies (e.g. salt), appetite and, of course, different species of animals prefer different types of feed (Chacon et al, 1978; Gammon and Roberts, 1980; Van Soest, 1982).

The term palatability is a subjective concept and refers to the assumed reason behind an animal's choice of one source of feed over another (e.g. the choice between different parts of a plant or the choice between different plants). Selection, on the other hand, is an objective term, referring to the actual choice that is made. The ability of an animal to select feed of an adequate quantity and nutritive value affects its productivity.

Grazing time. This is the amount of time a ruminant spends consuming feed. While generally applied to actual grazing on pasture, the definition can be widened to include time spent browsing, consuming stover etc. Grazing time is determined by the availability and nutritive value of feed and by the management system used (Gammon and Roberts, 1980; Lambourne et al, 1983). There is often an inverse relationship between grazing time per day and the quantity and quality of feed available (Butterworth, 1985).

Feed-related concepts

These concepts include:

Digestibility. The digestibility of a feed determines the amount that is actually absorbed by an animal and therefore the availability of nutrients for growth, reproduction etc.

Apparent digestibility is estimated by subtracting nutrients contained in the faeces from nutrients contained in the dietary intake. Therefore, it does not account for nutrients lost as methane gas or as metabolic waste products excreted in the faeces.

True digestibility is estimated by correcting for the endogenous and microbial amount of a nutrient actually lost in the faeces.

The measurement of apparent digestibility is less complex than measuring true digestibility and, therefore, more suited to the requirements of diagnostic livestock systems research.

The amount of energy in (or the energy content of) feed potentially utilisable by animals can be expressed in the form of gross energy (GE), digestible energy (DE), metabolisable energy (ME) or net energy (NE) for maintenance and production. The relationships between them are as follows:

DE = GE - energy lost in faeces
ME = DE - energy lost in urine and gases
NE = ME - heat loss (heat increment)

Gross energy is the total heat of combustion of a feed substance measured in calories or Joules per unit weight of dry matter (DM) or organic matter (OM).7 Because it takes no account of energy losses, gross energy provides no real indication of the energy value of a feed.

7 Dry-matter weight is determined by drying the feed in the oven at 105°C for 12-15 hours and weighing. Dry organic matter (DOM) is determined by weighing the dry matter, then burning its organic matter in a furnace at 550°C for eight hours. The difference between the dry-matter weight and the weight of the ash remaining is the DOM weight of the feed. In dry tropical pastures, dry organic matter usually lies in the range of 90 92% (by weight) of its parent dry-matter material.

Net energy is the energy actually available for maintenance and production (after all losses have been accounted for). It is the most precise estimate of a feed's energy value, but, because of the complexities involved, net energy is rarely measured.

Digestible energy is commonly taken as an indicator of a feed's energy value because faecal losses are relatively easy to measure. Metabolisable energy can be approximated by multiplying digestible energy by a factor of 0.82 (ARC, 1965; 1980).

Crude protein. Protein is the basic structural material from which all body tissues (e.g. muscles, nerves, blood cells) are formed. It is, therefore, essential for production and maintenance and cannot be replaced by other nutrients in the feed.

Ruminants are able to synthesise protein from non-protein nitrogen sources (e.g. urea) by microbial action in the rumen. The nitrogen content of a feed is, therefore, often used to estimate the amount of protein available to the ruminant, which is expressed as the crude protein (CP) content of a feed and calculated as:

% CP = % nitrogen content x 6.25

where the figure 6.25 is based on the assumption that feed protein contains, on average, 16% nitrogen.

Fibre. This fraction refers to the cell-wall content of feeds and consists of carbohydrates (hemicellulose and cellulose) and lignin. Carbohydrates are partially available for digestion by rumen micro-organisms and represent a major source of energy for ruminants. The lignin component of the fibre fraction limits the digestibility of cell-wall carbohydrates.

Crude fibre (which is used in the Wende system of feed analysis) is a poor estimate of cell-wall content because it does not recover lignin and hemicellulose. Instead, the detergent system of analysis (described in Part D below) should be used where feasible, although there are other methods for estimating total fibre (Van Soest, 1982).

Minerals and vitamins. Minerals are required for tissue growth and the regulation of body functions. They are normally categorised as macro-minerals (when required in the order of g/day) or as micro-minerals (when required in mg/day or less). So far, 22 mineral elements have been shown to be essential to animal nutrition (Little, 1985) (Table 1).

Table 1. Essential mineral nutrients.

Macro-minerals:

Ca

P

Na

K

Mg

S

Cl


Micro-minerals:

Cu

Zn

Ma

Mo

Se

I

Fe

Co


F

V

Sn

Ni

Cr

Si

As


In tropical feeds, deficiencies of phosphorus (P), sodium (Na) and copper (Cu) are those most likely to occur, while deficiencies of potassium (K) and chorine (CL) and of the micro-minerals listed in the bottom row of the table are most unlikely in the field.

Vitamins are organic substances required by animals in very small amounts for the regulation of various body processes which ensure normal health and production. Under most conditions, the ruminant is able to synthesise most of its vitamin requirements.8

8 Ruminants do not synthesise vitamin. A which can be deficient in tropical pastures and crop residues. The synthesis of vitamin B12 requires Co which may also be deficient in these feeds. The specific functions of the different minerals and vitamins are discussed in any text on ruminant nutrition.

Part B: Purposes


Diagnostic research on animal nutrition problems
The nature of nutritional constraints
Scope for improvement


Diagnostic research on animal nutrition problems

During the descriptive phase of livestock systems research, data obtained from informal surveys, secondary data sources and other diagnostic studies can be used to determine the need for further diagnostic research on animal nutrition issues. The following types of data will often be useful in this respect:

· production data

Production performance (i.e. mortalities, birth rates, milk production, condition/liveweight gain) may point to nutritional problems in the target area.

· environmental data

Soil surveys may indicate mineral deficiencies. Also, the vegetation characteristics of an area (e.g. plant composition, density, biomass) can be used to identify probable deficiencies in dietary energy and crude protein.9

· management data

Information about management systems can be useful with regard to the use and availability of crop residues, communal grazing practices, stocking rates etc. Evidence of overgrazing on a wide scale will indicate nutrition problems, particularly during the dry season when feed quantity and nutritive value are lowest.

· producers' opinions

Local opinions about particular problem should be taken into account, after having weighed them against evidence available from other sources.

9 Plant composition may also indicate the likelihood of mineral deficiencies. For instance, a high proportion of fortes in the diet can usually be taken as an indication that minerals, in particular phosphorus, may not be deficient.

The nature of nutritional constraints

If solutions are to be identified, the nature of nutritional problems must be clearly defined. Studying the relationships between nutrition on the one hand and performance, management and grazing conditions on the other hand, as well as other nutritional relationships, might be useful in this context.

Relationships between nutrition and animal performance. By using techniques such as linear regression analysis, the relative importance of the different factors affecting production performance can be compared simultaneously. Table 2 shows how performance could be related to different variables of which nutrition is only one.

Example:

Table 2. Relationships determining the effects of animal nutrition on production performance.

Dependent variable (production performance)

Independent (influencing) variables

1. Liveweight/condition

DM intake, breed, type of birth, sex, parity, disease, management system

2. Fertility rate

Seasonal conditions, breed, parity, disease, type of birth, sex of progeny

3. Milk production

DM intake,10 breed, parity, weaning period, disease, lactation length

10 When making comparisons between animals of different size to determine the importance of nutrition as a constraint, DM intake should be expressed in relation to the liveweight (and preferably the metabolic weight, i.e. LW0.75) of the animal. When comparing animals of different species, the preferred exponent is LW0.9 (Graham, 1972).

Various indicators or measures (e.g. digestibility, DM intake, crude protein) can be used to determine the effects of nutrition on production performance. Surrogate or substitute variables for feed availability or intake can be used, as well.

For instance, seasonal rainfall is often assumed to be an indicator of feed conditions while stocking rate has been used as a substitute for feed intake (Abel et al, 1987).

Relationships between nutrition and management. The link between management practices and animal nutrition is often pronounced and needs to be understood. Examples of the relationships which might be studied are:

· the relationship between stocking rate and intake

· the relationship between animal feeding practices and herd size (as an indicator of wealth)

For instance, the use of supplements (salt, bonemeal etc) may vary with herd size (Bailey, 1982).

· the relationship between crop stover utilisation (intake) and oxen condition at ploughing time

· the relationship between stock movement to feed or mineral sources and animal productivity

In other words, is the performance of herds which are moved to these sources superior to that of herds which are not? (Dahl and Sandford, 1978; Sandford, 1983).

In mixed production systems, an understanding of crop/livestock linkages may point to potential areas for improvement. Crop residues can, for instance, have an important bearing on animal nutrition (Bayer and Otchere, 1985), by providing energy to carry stock through the dry season when feed quantity and nutritive value from grazing are low. The availability of energy from stover will, therefore, influence mortalities and birth rates (Powell and Waters-Bayer, 1985; Reed and Goe, 1989).

Figure 2 gives a schematic representation of some of the linkages which commonly affect both crop and livestock performance. Diagrams of this kind are useful in that they force the researcher to think through the system and identify some of the important linkages which exist. From this information, it is often possible to identify the data needs of research more precisely.

Figure 2. Example of negative linkages between crop and livestock production in a mixed farming system.

Relationships between nutrition and grazing conditions. These include the relationships between:

· the amount of intake and the nutritive value of feed (measured in terms of energy or crude protein content)

· selection and the nutritive value of feed, and

· grazing time and animal production performance

For instance, Smith (1961) found that liveweight gains of cattle grazing seven hours per day were only half those of cattle grazed for 11 or 24 hours a day. Bayer and Otchere (1985) also suggest that grazing time affects calving and weaning percentages for cattle owned by pastoralists in the Nigerian subhumid zone.

Other nutritional relationships. This includes the relationships between digestibility end feed quality, and between seasonal conditions (rainfall) and the nutritive value of feed consumed (measured in terms of energy or crude protein content). Such relationships need to be adequately understood if problems are to be correctly identified.

For instance, a positive correlation between digestible energy or dry-matter intake and liveweight gain is commonly observed (Ademosun et al, 1985; Zemmelink et al, 1985) (Figure 3). While this correlation may correctly imply that energy is a limiting factor in the diet, the availability of energy may itself be limited by some other factor (e.g. intake and, therefore, the amount of energy available could be limited by mineral, vitamin or protein deficiencies). Effective diagnosis thus depends on the identification of the primary limiting nutrient (Little, 1985).

Figure 3. Relationship between intake and liveweight gain in cattle, Mali, 1980.

Source: Lambourne et al (1983).

Scope for improvement

The scope for alleviating nutritional problems will depend very much on the characteristics of the system being studied. In pastoral systems, where the range vegetation is the major source of feed, improvements in animal nutrition may be virtually impossible without first addressing issues related to land tenure (communal grazing)11 and management (e.g. stocking rates). While in mixed cropping systems, technologies which increase the quantity and nutritive value of stover fed to animals at the end of the cropping season might be applicable (Powell 1985).

11 Work by ILCA in Nigeria on fodder-bank use by Fulani pastoralists suggests that there is scope for improvement in pastoral systems, despite overgrazing on communal lands.

It should be remembered that in livestock systems research, the solution to a particular problem may not always be technological. (For instance, it may be more important to correct particular aspects of policy before significant improvements in production can be achieved). Any technology studied should, in any event, be consistent with farmer/pastoralist objectives and circumstances (Module 1, Section 1; Module 2, Section 2).

Feasible technological solutions to improve animal nutrition may come through one or more of the following pathways:

· crop improvement
· changes in livestock management
· pasture improvement, and
· feed supplementation.

Crop improvement strategies. In mixed systems of production, livestock nutrition may be enhanced by improving the quantity and nutritive value of crop residues used by stock through:

· the selection for crop varieties which yield residues of higher nutritive value or quantity

For instance, strong positive correlations between crop yield and stover production and nutritive value have been observed in Nigeria (and elsewhere) for sorghum and millet (Grove, 1979; Powell, 1985).

· changing crop combinations so as to produce residues favoured by livestock

For instance, Powell (1985) found in Nigeria that livestock preferred millet (which had a higher nutritive value) to sorghum residues. However, the change from sorghum to millet would need to be consistent with farmers' crop preferences and/or income-earning objectives to be adopted.

· changing the time of planting, which affects stover production

For instance in northern Nigeria, sorghum stover yields were observed to decline by 1700 kg/ha for each week's delay in planting beyond the optimum date (Kassam and Andrews, 1975).

Livestock management strategies. This involves changing livestock management strategies to match feed availability with livestock feed requirements.

For instance, Wagenaar et al (1986) and Wilson and Sayers (1987) have shown that change in the timing of births (to match feed demands with feed supplies) can have significant effects on conception rates and parturition number in sheep and goats.

Pasture improvement strategies. These involve ranching schemes which aim to improve the management of the range and raise productivity, principally through increasing in the amount of available forage. The available evidence suggests, however, that such schemes have mostly been unsuccessful in Africa (Danckwerts, 1975; Behnke, 1984). The redistribution of water points to better utilise grazing resources is another example of a pasture improvement strategy.

Feed supplementation strategies. These involve the use of fodder banks, fodder trees, byproducts such as oilseed cakes and meals, and urea/molasses licks to supplement crude protein shortages.

Fodder banks are concentrated stands of forage, often legumes, sown either on natural grass or fallows to provide dry-season supplementary grazing (Bayer, 1986; Mohamed-Saleem, 1986; Taylor-Powell and Ingawa, 1986). Those tested by ILCA in Nigeria are mainly Stylosanthes spp and have been shown to be viable. However, widespread adoption of forage legumes is constrained by competition for land with food crops, labour shortages during crop operations and lack of adapted species (Reed and Goe, 1989).

Among fodder trees, leucaena and sesbania have been shown to be suitable for animal feed supplementation by the ILCA alley farming programme in Nigeria (Atta-Krah, 1986). Browse gardens and multipurpose trees have also been tried (Reed and Soller, 1987).

Part C: Types of data


Animal data
Feed data


Animal data

The objectives of data collection in this case are to (Table 3):

· examine the effect of nutrition on production
· determine the amount of feed consumed, and
· determine the composition of the feed consumed.

With some of these data (e.g. intake, grazing behaviour, liveweight gains) it may also be necessary to differentiate on the basis of age, sex, breed, productive activity, species, season and/or management system.12

12 Dab on animals' nutrient requirements have not been included since the methods used to collect such data are not discussed in this module. It is recommended that, when such dab are required, the ARC (1980) standards should be used.

Table 3. Types of animal data used to diagnose animal nutrition problems.

Objective

Types of data

Production effects

Liveweight gain, condition scores, traction power, milk production, wool production

Amount of feed consumed

Feed intake

Composition of feed consumed

Oesophageal or rumen fistula samples, faecal samples, grazing behaviour studies (selection data)

Feed data

The principle objective, in this case, is to determine the nutritive value of the feed consumed and digested by the animal. This may also involve an assessment of sources of feed as yet unutilised but with the potential for introduction into the diet.

In particular, data will be collected on digestibility, the energy value of feed (dry matter, dry organic matter, digestible energy and metabolisable energy), and crude protein content When assessing the nutritive value of feed, differentiation on the basis of season or system of production (which affect feed sources and feed availability) will often tee useful. Under certain circumstances (see Part D below), data on the mineral content and fibre composition of a diet may be necessary. When determining mineral content, samples of the feed consumed and of blood or bone may be needed.

Part D: Methods of data collection


Effects of nutrition on animal production performance
Composition of consumed feed
Feed digestibility
Nutritive value of feed


The discussion in Module 11 of different methods of data collection is generally applicable to all types of diagnostic research, and the user is encouraged to read it before embarking on studies of animal nutrition. The emphasis here is on those methods which have been tested by ILCA staff.

Following the format adopted in Part C of this module, these methods have been grouped into methods used to measure:

· the effects of nutrition on animal production
· the amount of feed consumed (i.e. feed intake)
· the composition of feed consumed
· the digestibility of feed, and
· the nutritive value of feed.

Effects of nutrition on animal production performance

The production performance of an animal often reflects its nutritional status. Liveweight and body condition, for instance, provide a measure of the nutritional response, integrated over weeks or months (Lambourne et al, 1983).

Studies which attempt to isolate the key factors influencing animal production performance may, therefore, be the first step in the diagnosis of animal nutrition problems (see Part B above). If nutrition is identified as the critical constraint to performance, further studies on specific aspects of nutrition (related to the animal or the feed) may be needed.

The various methods used to assess animal production performance are discussed in Module 5, and the reader should refer to it if detailed diagnosis of production performance is envisaged.13

13 Prior evidence may be available which removes the need for such studies. For instance, there may be data available from range evaluation and animal production studies and farm management surveys, which specifically identify nutrition as the critical constraint to production.

Feed intake

Intake, or the amount of feed an animal consumes, can be estimated by using either digestibility data or 'markers'.

Digestibility data. When such data are available, intake can be estimated by multiplying the dry-matter weight of faeces by a digestibility factor. The factor is known as the feed:faeces ratio and is expressed as:

DM intake = 100/(100 - digestibility) x DM weight of faeces where digestibility is in per cent.

Example: If the dry-matter weight of faeces of an animal is 870 g/d and the percentage digestibility of the feed consumed is 60%, then the amount of dry feed consumed would be:

DM intake (g/day) = (100/40) x 870 = 2175

The methods used to determine intake and to measure faecal output are discussed below.

Markers. Digestibility and intake data can be derived from the indigestible components of a diet, known as 'markers'. Markers are classified as internal, if they are ordinarily present in the diet (e.g. lignin), or as external, if they are added to the diet (e.g. chromic oxide).14 They are used when the measurement of feed intake and faecal output is difficult.

14 Other markers used include iron oxide, barium sulphate, titanium oxide, and radioactive tracers (Dicko-Touré, 1980). Synthetic organic substances such as beads, rubber and ribbon have also been used, since they can be easily separated from the feed. Van Soest (1982) provides a detailed account of the various markers used to estimate intake and digestibility, and of their advantages and disadvantages. The term 'indicator' is sometimes used instead of 'marker' (Dicko-Touré, 1980, Church and Pond, 1982; Lambourne et al, 1983).

The formula to estimate faecal output is:

Example: An animal is dosed with 50 g of chromic oxide per day to determine its daily faecal output. The concentration (proportion) of marker in the dry-faeces sample is 5.75%, and the dry-matter weight of the faecal output is:

Faecal output = 50/0.0575 = 870 g/d

Let us now take the estimated dry-matter weight of the faecal output and the concentrations of the marker in the diet and in the dry faeces, and calculate intake by using the following formulae:

Example: The dry-matter weight of faeces excreted per day is 870 g and 5.75% of this is the marker. The proportion of the marker in the diet is 3.4%. Calculate the DM intake of the animal.

DM intake (g/day) = 870 x (5.75/3.4)

Different intake rates can be calculated for animals classified on the basis of age, sex, weight or productive activity. These can then be related to such variables as seasonal rainfall, stocking rate, management practices or plant composition to isolate its main determinants.

Summary

The normal procedures to estimate DM digestibility and intake are to:

· identify animals (3-5) for sampling

· sample the feed consumed by these animals (e.g. by the hand-plucking, oesophageal-fistula or rumen cannula methods described below)

· take faecal samples from the animals (as described below) and mix them to eliminate differences between animals

· determine the proportion of the marker in the (mixed) faecal sample

· determine the weight and proportion of the marker in the feed sample taken, using standard laboratory techniques15

· calculate digestibility of the feed as the ratio of feed:faecal marker concentrations (digestibility can also be estimated using in vitro procedures on feed samples see next page) and

· calculate intake from the formula given above. This requires the further estimation of faecal output either by total faecal collection or dosing with known quantities of, for instance, chromic oxide.

15 These techniques are discussed in most texts on animal nutrition. When facilities for laboratory analysis are not available or are inadequate, intake should be calculated on the basis of digestibility. Simple methods to estimate digestibility are given in the text which follows.

Composition of consumed feed

There are various methods used to determine what the animal is eating. Those discussed here are:

· the oesophageal fistula method
· the rumen cannula method
· direct observation of grazing habits
· pasture analysis before and after grazing, and
· faecal samples.

Oesophageal fistula. The botanical composition of feed consumed by an animal can be determined by using a surgical fistula inserted into an animal's oesophagus. The food eaten passes into a collection bag attached to the neck, and samples are taken directly from the bag after allowing the animals to graze for not more than two hours before re-inserting the fistula plug.

The oesophageal fistula method provides an accurate indication of the botanical composition of the feed consumed. An illustration of this type of approach is given by McLean et al (1981). However, because of salivary contamination of the samples, accurate direct estimates of the chemical composition of feed eaten are restricted to nitrogen, neutral detergent solubles, calcium, magnesium, sulphur and copper (Little, 1972; 1975). Dietary phosphorus concentrations can be estimated accurately only from oesophageal extrusa labelled with radioactive P (Little et al, 1977). It also tends to be time-consuming and costly, and farmers are unlikely to cooperate when their own stock is involved. Nevertheless, ILCA research workers have used the method in the field.

In Kenya, for instance, oesophageal fistulae were fitted to cows which had been purchased from Maasai pastoralists and herded with farmers herds during three seasons in several locations (Semenye, 1988a,

b). The data obtained on feed composition were then complemented by studies on grazing behaviour of the type discussed below. ILCA has also used the fistula method with a small sample of cattle in Mali (Dicko-Touré, 1980; Lambourne et al, 1983).

Material collected with the fistula method can be used in the determination of digestibility by in vitro estimation procedures (see page 167).

Rumen cannula. This method is applicable to both cattle and smallstock and allows direct sampling of the contents of the rumen by means of a cannula surgically inserted into the rumen. It involves physically emptying the contents of the rumen by hand before the animal goes to graze and then taking samples from the freshly ingested material two to three hours after the animal started grazing. The method has been used by ILCA field researchers in Ethiopia (Nicholson and Sayers, 1987) and Mali (Dicko-Touré, 1980) but the technique is elaborate, labour-intensive and costly. It is therefore more likely to be applicable to on-farmlon-range experiments described in Section 2.

Direct observation of grazing habits. The content of food consumed by grazing animals can be guesstimated by following selected animals in a herd or flock at distances which are close enough to observe what is being eaten. Each selected animal is observed at regular intervals. Two field examples demonstrate the principles.

Examples:

De Leeuw and Chara (1985) used the technique to compare goat and sheep browse preferences in mixed Maasai flocks in Kenya. Observations were carried out during the dry season with randomly selected animals being followed for periods of one to two hours by one or two observers who were familiar with the local flora. Because the animals were familiar with humans, observations could be made at distances of 2-10 m.

The aim was to obtain an equal number of 'hits' for sheep and goat - a 'hit' occurring each time a particular plant species was eaten. Hits per plant species were then summed and compared with the total number to determine the proportion of each plant eaten. These figures were then used to derive an index of preference or selection. Between 200 and 400 hits were collected for both sheep and goats in each sample flock.

Nyerges (1979) observed the grazing habits of 120 sheep, by following each for a period of 20 minutes (measured by stop watch). Animals were followed at distances of 5-15 m and the shrub and ground species consumed (including ground litter) during the observation period were recorded.

Direct observation can also be applied to other studies of animal grazing behaviour, e.g. time spent eating, walking, resting and watering (Dicko-Touré, 1980). These variables can then be related to such parameters as intake, digestibility, stocking rate and distance to water, to isolate the more important determinants of grazing behaviour (Lambourne et al, 1983, pp. 195-198).

A modification of the direct-observation method was used by Dicko-Touré (1980) in Mali to determine the composition of feed consumed. Selected animals were followed for a period of one minute, and distance walked as well as the number of mouthful taken during this period were recorded.

A sample of forage was then collected by hand from the area grazed during the one-minute observation period. The size of the sample taken was in proportion to the observed number of mouthfuls (one hand-grab for every five mouthful). Similar measurements were made for each selected animal every 45 minutes throughout the day in order to obtain comprehensive data on feeding habits and feed composition.

Lambourne et al (1983) argued that, for most purposes, such rapid-survey techniques provide sufficient detail on diet composition. They are low-cost, require minimal supervision and can be completed in a relatively short time. Observers should, preferably, have a good knowledge of local flora, but it is more important for them to be observant. If hand samples are collected to mimic grazing habits, these can be analysed at a later stage by someone who is thoroughly familiar with the flora.

Data on diet composition can be complemented by opinions obtained from herdsmen in the area. Their knowledge about species differences in terms of selectivity and palatability is often very precise.

Pasture analysis before and after grazing. The 'before' and 'after' method involves the demarcation of quadrats in a paddock before and after animals are released into an area for grazing (Figure 4). Adjacent to each fenced quadrat is an equally sized area, with similar vegetation characteristics. The biomass and vegetation composition of the two 'paired' areas are measured using one of the techniques described in Module 6 and animals are then released into the area to graze (t'Mannetje, 1978).

Figure 4. Schematic representation of the pasture analysis method.

After a prescribed period (e.g. one week) biomass and plant composition in the paired areas adjacent to each fenced quadrat is remeasured and preferences for different species of vegetation are determined. The method will give reasonable estimates provided that the two areas are not highly variable in terms of species composition. When vegetation is highly variable, the number of paired samples required must be increased, making measurement more time-consuming.

Faecal samples. Faecal samples have been used for microscopic analysis of the plant part they contain, to provide an indication of the vegetation consumed by an animal (Stewart, 1967). However, as an indicator of dietary composition such samples tend to be unreliable since the indigestible portion of the diet may bear little relationship to the portion actually consumed. The faeces may, for instance, contain high proportions of woody ligneous material consumed during browsing. This does not necessarily mean that the diet also contains similar proportions of this component.

Feed digestibility

The methods used to assess digestibility are based on:

· the use of markers
· the use of if 'faecal indices'
· in vitro analysis of consumed feed, and
· in vivo analysis of consumed feed.

Of these, only the first three are relevant to the diagnostic phase of livestock systems research. The in vivo method is more applicable to on-station research and involves intensive laboratory work and careful supervision.

The use of markers. When it is impossible or inconvenient to measure total feed intake or to collect total faeces, markers can be used to determine intake (see pages 161-162) as well as digestibility. The formula used to calculate apparent digestibility16 is:

16 The reciprocal of apparent digestibility is per cent faeces.

Example: A sample of feed contains 13% lignin and a dry-faeces sample taken after the animal consumed the feed contains 22% lignin. Calculate the apparent digestibility of the feed.

Using the above formula,

Apparent digestibility (%) = 100 - 100(13/22) = 41

The formula for feed digestibility can be extended to estimate the apparent digestibility of a given nutrient or component of the diet as follows:

To obtain data for the analysis based on markers, follow this procedure:

· collect 3-5 grab samples of faeces from the area in which the animals are grazing and mix them thoroughly

· collect grab samples of the forage consumed after observing animal behaviour

· determine the percentage of the indicator in the faeces and the feed, using standard laboratory techniques. If you are interested in the estimation of crude protein and energy intake or nutrient digestibility, assess the same samples for nutrient content, and

· determine digestibility (and intake) as shown above.

Note: There are two obvious sources of error in such a methodology. First, lignin may be partly digestible and is thus not always a reliable indicator (marker). Second, the feed samples taken will often be not truly representative of actual intake, particularly when pasture is highly variable, and where the choice of samples is entirely dependent on the enumerator judgement.

There are various methods available to sample faecal output in the field, including:

· taking 'grab samples' from several animals and mixing them thoroughly to ensure that differences between individual animals are eliminated. This method is practical in a range context.

· total collection by bags attached to the animal: The method is generally regarded as being inapplicable to most range/pasture studies because of the cost and supervision involved (e.g. Schneider and Flatt, 1975).

However, (Dicko-Touré, 1980, p. 248), who used a low-cost modification of the method on pastoral male cattle in Mali, reported that this need not necessarily be the case. She argued that the costs of using indicators to estimate faecal output would, in fact, have been more expensive since this method would have involved sending samples to another country at a cost that is at least 10 times higher than the cost actually incurred by using the bag-collection method.

Thus, the methods adopted in any diagnostic study to sample faecal output should be tailored to the particular circumstances of the study, bearing in mind the financial and manpower resources of the research team.

The use of faecal indices. The methods using faecal indices to estimate digestibility are based on established regression relationships between faecal indices and the digestibility of dry or organic matter (Van Soest, 1982). The general model for these relationships is:

Digestibility of forage grazed = f (faecal index)

The faecal indices in this model are calculated on the basis of the nitrogen, lignin or chromogen contents of the faeces, i.e. the components of faeces known to be closely related to digestibility.17

17 The relationship is not causal. The two variables merely happen to go together i.e. they are concomitant (Dicko-Touré, 1980) are only relevant to the site at which data were originally collected or to sites with very similar vegetation and animal species (Dicko-Touré, 1980; Semenye, 1987).

The estimation of digestibility via faecal indices involves the following steps:

· conduct conventional studies to determine, from faeces and feed samples, regression relationships between digestibility and the content of these substances in the faeces (The principles of regression analysis are discussed in Module 11 of this section)

· analyse faecal samples collected in the field to determine the percentage(s) of selected substance(s) in the faeces (The methods used to obtain faecal samples are described above)

· predict digestibility using the faecal indices calculated from these data.

The main advantages of this method are that it is relatively low-cost and results can be obtained fairly quickly. Its chief disadvantage is that it is site-specific, and the derived parameters and relations

In vitro analysis of consumed feed. When digestibility is analysed by in vitro methods, samples of feed ingested are subjected to artificial tests which simulate digestibility under controlled conditions. The more commonly applied methods involve the use of rumen fluids, chemical fermenters and nylon bags (see Church and Pond, 1982).

Rumen fluids. Rumen fluids are extracted from rumen-fistulated animals and used in combination with buffers to simulate the action of saliva. The substances are added to feed taken from the fistula, and the mixture is heated at rumen temperature (39°C) for periods of 24-48 hours (Church and Pond, 1982). The Tilley-Terry (1963) method, which is widely used, involves an additional stage in which the feed is further digested with acid pepsin for another 48 hours. The residual represents the indigestible portion of the feed.

Chemical fermenters added to the feed have been used to predict digestibility. The method is also used to study rumen function and the metabolism of certain compounds, e.g. to determine types of non-protein nitrogen (NPN) that can be utilised by rumen micro-organisms.

The advantage of the two methods is that the analysis is not expensive (if laboratory facilities are available) and that it can be performed fairly quickly. The methods can also be used to assess the digestibility of grab samples of grass or of cut samples of stover and straws taken after crop harvesting.

Nylon bags. These are inserted into the rumen of test animals and removed after a prescribed period. The loss of material from the bag as a result of fermentation is then calculated. The method is more applicable to on-station research, but it can be used together with the rumen cannula method to determine intake.

Nutritive value of feed

This part of the module focuses on the methods and techniques used in estimating the supply of different nutrients to animals in particular situations or systems, in relation to their need for these nutrients. It starts with a general section on estimating the main feed components. It then goes straight to fibre analysis because of the difficulties involved in estimating feed values in very fibrous diets. Finally, it looks at some of the techniques in use for the physical sampling, from stands of different kinds of feed, for laboratory analysis.

Methods to estimate feed components

The feed value of a source of feed can be assessed on the basis of its energy value, crude protein content and mineral content, using methods specifically designed to estimate these components of feed.

Energy. The energy yield of a source of feed (such as natural pasture) can be estimated from its dry-matter weight per unit area. Module 6 discusses the various methods used to estimate biomass or dry-matter weight under rangeland conditions. Many of these methods rely on the use of predictive equations based on the relationship between biomass and the vegetation characteristics (e.g. height, density, crown diameter, stem diameter) of an area in order to extrapolate biomass estimates over larger areas.

Samples can be taken to establish similar predictive relationships for the estimation of dry-matter weight of crop residues. Powell (1985), for instance, used grain yield to predict total stover dry-matter weight and stalk and leaf dry-matter weights for millet and sorghum. The relationships, which were based on data obtained from randomly chosen sites in Kaduna State, Nigeria, were highly significant (Figure 5).

Van Raay and de Leeuw (1971) adopted a similar procedure to determine the DM weight of crop residues in Katsina, Nigeria. They established predictive relationships on the basis of stalk and stand density, plant height and plant edibility (subjectively estimated).

Figure 5. Relationships between sorghum and millet grain yields and stover dry-matter (DM) yields.

Note: The three relationships shown are between grain yield and, respectively, stover DM weight (A), stalk DM weight (B) and leaf DM weight (C).

Source: Powell (1985, p. 79).

Having obtained an estimate of dry-matter yield, an estimate of digestibility is then required before the desired approximation of the energy yield can be calculated. The fibrous portions of a feed must, therefore, be considered before more accurate estimates of nutritive value can be made.

Feeds with a high biomass per unit area are often low in energy since they also contain a high proportion of indigestible fibrous matter. Methods of fibre analysis have been devised to separate those portions of fibre which can be utilised by the ruminant from those which are essentially indigestible.18 These methods are briefly discussed.

18 The digestible portion of the fibrous fraction of crop residues and agro-industrial byproducts is a major source of energy for ruminant animals. Fibre analysis is thus particularly important in the assessment of the nutritive value of these feeds.

For the purposes of illustration, however, the following average relationships can be used:19

GE (gross energy) = 18.0 MJ/kg DM of feed intake
DE (digestible energy) = 0.50 (for example), and
ME (metabolisable energy) = 0.81 DE.
So in this illustration, ME = 7.3 MJ/kg DM of feed intake.

19 The average relationships used in the text which follows are feed energy supply and requirements derived principally from King (1983) to whom reference should be made for all supporting details.

The metabolisable energy available in the feed intake can then be related to energy requirements for maintenance and/or production to provide an indication of the energy status of the animal.

Example: Let us calculate the feed energy requirements of a 300 kg (liveweight) ox for maintenance, foraging and production, and compare these with the availability of energy to that animal from its feed supply.

The maintenance (fasting metabolism) requirement is determined as follows:
Daily maintenance requirement (Em) = 0.293 W0.75 MJ of NE where:

MJ = megajoules
NE = net energy, and
W = liveweight in kilogrammes.

In this case, W = 300 kg, so
Em = 0.293 (300)0.75 MJ of NE = 21.12

To convert this figure into metabolisable energy (ME), we need to divide it by the efficiency of conversion (Km) of ME to NE for maintenance.

Km tends to lie in the range 0.64 to 0.70, and here it is assumed to be 0.67. So,

Em = 21.12/0.67 = 31.52 ME

To obtain its energy needs for maintenance (fasting metabolism), an animal needs to walk while grazing and trekking to water. We can call this 'foraging'. The energy requirement for foraging (Ef) are given by the formula:

Ef (in MJ of ME) = 1.8/1000 x W x distance walked in km

On the assumption that our ox walks 18 km daily at a speed of 3 kph:

Ef = 1.8/1000 x 300 x 18 = 9.72 MJ of ME daily

so its daily energy requirement for living (El), i.e. fasting metabolism and foraging, is:

El = Em + Ef = 31.52 + 9.72 = 41.24 MJ of ME

If the daily energy intake of our ox is greater than 41.24 MJ of ME, it will be able to put on weight. To gain weight, an animal needs between 12 and 27 MJ of ME per kg liveweight, depending on the percentage that fat constitutes in the meat accumulated. Under African conditions, the average figure may be about 16 MJ of ME/kg LW gain (derived from Ledger and Sayers, 1977).

Assume now that we are conducting our study in a region where the remaining stock of standing hay in the early dry season (three months or 90 days before rain will bring fresh growth) is estimated at 200 kg DM/ha. Assume also that the stocking rate in the area is the equivalent of three ha/ox. We can now compare supply and requirements of feed energy per ox for the 90 days of the dry season as follows:

Supply

3 (ha) x 200 (kg DM/ha) x 7.3 (MJ ME/kg DM) = 4380 MJ ME/ox

Requirement for living

90 (days) x 41.24 (E/days) = 3712 MJ ME/ox

Balance available for liveweight gain

Supply - requirements for living = 4380 - 3712 = 668 MJ ME/ox or the equivalent of about 42 kg of liveweight gain at the rate of:

42/90 = 0.47/head/day.

Crude protein. The standard laboratory method for the estimation of crude protein is the Kjeldahl method which is described in most texts on animal nutrition (e.g. McDonald et al, 1973; Church and Pond, 1982). The analysis is used to determine the crude protein content of a sample of grass or stover, and the results can then be used to establish predictive regression equations similar to those illustrated in Figure 5.

Powell (1985), for instance, found that the relationship between grain yield at the time of harvest and total crude protein (CP), and between grain yield and leaf CP/ha were highly significant. Such relationships can be used to indicate the availability of crude protein from different sources and/or at different stages of plant growth.

When estimating the crude protein content of browse plants and crop residues, it should be borne in mind that the presence of certain phenolics (tannins) in these feeds can affect the availability of nitrogen to the ruminant. This is particularly true of feeds high in insoluble polyphenolics, for which the calculated crude protein content may overestimate the amount of nitrogen which can actually be synthesised into protein (e.g. Woodward and Reed, 1989).

Minerals. Analysis should only be attempted if mineral deficiencies are clearly evident. Even then, if other nutrients such as energy or crude protein are more limiting (as is likely to be the case on African rangelands), the mineral constraint should be dealt with only after the primary deficiencies have been rectified (Little, 1985).

The methods used by ILCA researchers to diagnose the more common deficiencies involve blood, bone, liver, milk and faecal samples and are discussed in general terms below. All the methods outlined rely on adequate laboratory facilities. For a more detailed account of symptoms of mineral deficiency and the role of minerals in animal nutrition, the user is referred to basic nutrition texts, e.g. Cullison (1982) and Church and Pond (1982).

Blood samples. Whole blood, blood serum and blood plasma samples have been used to diagnose mineral deficiencies (particularly phosphorous and magnesium) in livestock. Values significantly below 'normal' concentrations (or ranges) indicate the nutritional status of an animal with respect to a particular mineral, but the evidence is not always conclusive (McDowell et al, 1986).

Precautions must, for instance, be taken when samples are taken in less than optimum conditions since exercise, stress, temperature and other factors can alter mineral concentrations. Such factors are often difficult to control in African conditions (Mtimuni, 1982) and have resulted in high concentrations of phosphorous in serum when the concentration in forages consumed was, in fact, extremely low.

Little et al (1971) described a method for obtaining accurate estimates of blood inorganic P concentrations, but the difficulties of interpretation of such data were noted by Gartner et al (1980). Basically, only low blood inorganic P values have any diagnostic value.

Bone samples. Because of the problems just described, tests using bone samples have been developed to test for phosphorus deficiency in livestock. Samples of rib bone can be obtained by simple surgery. For FSR diagnostic work, simple measurements that can be made on certain long bones at slaughter can provide results which are generally more reliable than those obtained from blood samples. These methods have been described by Little (1984).

Liver samples. Liver samples have been used to diagnose for copper, cobalt and vitamin A deficiencies in African livestock (Tartour, 1975; van Niekerk, 1978).

Milk samples. ILCA has used samples of milk to diagnose mineral deficiencies in cattle in Ethiopia. However, since milk composition is influenced by such factors as cow age, stage of lactation and genetic potential, milk sampling tends to be unreliable. The 'let-down' problem associated with zebu cattle (Module 5) also means that it is cliff cut to obtain representative samples in field studies. Large variations in butterfat content between successive milkings of the same cow reflect this problem (Lambourne et al, 1983). However, milk samples are very useful in the diagnosis of iodine deficiency (Committee on Mineral Nutrition, 1973).

Faecal samples. Apart from their use in digestibility and intake studies, faecal samples have been used to diagnose for phosphorus and sodium deficiencies (Little, 1987). Sodium problems are diagnosed more accurately, but with more difficulty, from saliva samples.

However, the analysis of mineral deficiencies is probably best done by feed analysis at the diagnostic phase of farming systems research. The methods described above are more applicable to specific problems requiring more sensitive analysis (Little, 1987). A knowledge of the symptoms involved will provide further confirmatory evidence (e.g. bone chewing is an indication of phosphorus deficiency). The opinions of traditional herders will also be useful in identifying mineral deficiencies (particularly the need for salt), as will be the movement of stock over large distances to natural sources of minerals.

Fibre analysis

The crude-fibre (Weende) method is described in most texts on animal nutrition. The method has been widely used to determine the fibre content of feed, but it has two serious shortcomings, particularly with respect to highly fibrous feeds such as crop residues, straws etc. These are:

· The method treats all fibre components (cellulose, hemicelluose and lignin) as uniformly digestible. Ruminants can, however, utilise some cellulose and hemicelluose though lignin is essentially indigestible. The digestibility of a feed therefore tends to be underestimated.

· Not all of the lignin and hemicelluose is extracted by the crude-fibre method. As a result, a portion of these components is included in the nitrogen-tree extract (sugars and starches) and is, therefore, assumed to be highly digestible. The digestibility of a feed therefore tends to be overestimated.

Because of these shortcomings, Van Soest (1988) devised a method which separates feed dry matter into two fractions - one of high or uniform digestibility and the other of low or non-uniform digestibility. Feed samples are boiled in a neutral-detergent solution and components are separated as follows:

· neutral-detergent solubles (NDS), consisting mainly of lipids, sugars, starches and protein with a digestibility of about 98%, and

· neutral-detergent fibre (NDF), consisting of plant cell wall components (lignin, silica, hemicelluose and some protein). This fraction more closely corresponds to the true fibre fraction than the estimate of the Weende crude-fibre analysis.

However, NDF is not a uniform chemical entity, its overall nutritive value is considerably influenced by the amount of lignin present. To determine this amount, the feed is treated by acid detergent, and the procedure is known as the acid-detergent fibre (ADF) analysis. By heating the NDF in acid detergent, the presence of tannins can also be detected.

The detergent analysis and its different procedures are discussed in greater detail by Van Soest (1988) and Reed and Van Soest (1985). Because of the high costs of reagents and apparatus used in detergent analysis, developing countries have been slow to adopt the method. ILCA's Animal Nutrition Section has recently developed a low-cost micro-fibre apparatus which uses one tenth of the amount of reagent used in conventional detergent analysis experiments. This method is described by Reed (1984), and the specifications of the apparatus can be obtained from ILCA, Addis Ababa, Ethiopia.

Feed sampling for laboratory analysis

The types of feed usually sampled for laboratory analysis are crop residues and hays, grains and fresh forage or silage.

Crop residues and hays. Most African farmers store crop residues and hays in stacks, and the nutritive value of the feed tends to be highly variable both within and between stacks. This increases sampling requirements and complicates the procedures involved.

Because of the variability in the nutritive value of crop residues and hay commonly encountered, it is useful to make a visual estimate of the variation in a selected stack before sampling begins, and to interview the farmer about the time of harvesting, the methods of stacking used and the composition of the stack (i.e. whether it contains material from more than one source or crop).

Sampling may be done with a coring device or by hand. Samples should always be taken from a cross-section of each chosen stack. When large stacks are encountered, dismantling may be necessary to ensure that samples from the less accessible parts are obtained.

When the coring device is used, at least 10 samples should be taken per stack. The material gathered should be properly mixed, weighed and stored in a dry place before dispatching it to the laboratory. The combined dry weight of corings taken per stack should not be less than 2 kg. The samples should be clean and stored in a porous paper or a piece of cloth to avoid moisture contamination. Relevant information (date, feed type, sample weight, identification) should be recorded in duplicate.

When samples are taken by hand, several visits are normally required to ensure that the nutritive value of the stack is properly assessed. At each visit, 12-15 grab samples should be taken from the face of the stack and mixed. They should be taken at every 50-75 an, as the farmer makes use of the stack. If the farmer finishes one stack and starts another, or alternates between different stacks, new samples should be taken following the same procedure.

Although hand-sampling is tedious, changes in feed quality over time (e.g. resulting from storage or environmental effects) can be monitored at the same time. With coring, several return trips would be required if specific information on quality change over time was needed.

Grains. Grain samples are usually taken with a grain probe. Between 5-7 cores should be taken at random from the storage bin. The samples should then be mixed and separated into subsamples of about 450 g. Each sub-sample should be placed in a porous paper or cloth sack and properly labelled before dispatch or storage.

Wet feeds. These are usually fresh forage or silage.

Fresh forage should be weighed immediately after sampling and put in a porous paper or cloth sack for dispatch to the laboratory, where it should be dried at 65°C to a constant weight and weighed again (Van Soest and Robertson, 1985).

If it is not possible to weigh the sample when it is taken, one half should be placed in a sealed plastic bag to retain moisture and then weighed after returning from the field. This fresh weight is needed to calculate dry-matter content after drying. The other half of the sample should be kept in a porous paper or cloth sack for other analyses than dry-matter content.

In the event that samples cannot be transported to the laboratory the same day, they should be dried either by hanging under cover or by spreading them out on paper in a dry and protected place. Alternatively, samples can be hung in sacks above the coil of a kerosene refrigerator. If drying is delayed, samples should be kept in plastic bags out of direct sunlight to avoid spoilage, or they should be stored frozen.

Silage. Cored samples should be taken from the pit using the procedure outlined above for stacked hay and crop residues. If sampling is done by hand, about 20 grab samples should be taken from the freshly cut face and mixed thoroughly. A subsample of 2 kg is required for analysis. The procedure should be repeated every third or fourth face cut to account for within-pit variability.

After weighing, samples should be placed in sealed plastic bags, frozen or dried at 65°C and sent immediately to the laboratory. If oven-drying is not possible, one of the drying methods given for fresh forage will suffice.

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