Section 2 - Module 1: Definitions, problems and initial considerations in planning livestock on-farm trials

Part A: Definitions and concepts
Part B: Problems confronted
Part C: Justifying the need for on-farm trials
Part D: Choosing the technology to test: the screening process
References

This module defines concepts related to livestock on-farm trials. It also discusses some of the problems which the researcher is likely to confront when livestock on-farm trials are being planned and implemented. It ends by outlining the principles which need to be considered when technologies are being selected for on-farm testing.

Part A: Definitions and concepts

The following terms will be used throughout the remainder of Section 2:

Trial. For the purposes of the discussion in tints section, on-farm trials are classified as¹:

· statistical trials, in which emphasis is given to obtaining statistically analysable results

Statistical trials are designed along conventional statistical lines in order to facilitate the analysis of results (Module 3, Section 2) With livestock, these kinds of trials require relatively high levels of researcher supervision.

· monitoring trials, in which the main intention of the researcher is to observe and monitor farmers' reactions to the technology being tested

With these kinds of trials, farmers control the use of trial inputs and adapt the technology according to their own requirements. The results obtained are not statistically analysable in most cases, but other simple methods of analysis can be used to assess the potential of the technology for the target area in question (e.g. partial budgeting, cash flow budgeting - see Module 3, Section 2).

¹ The range of possible trial types is large and the terminology used here does not correspond with that used in cropping systems research literature (e.g. Stroud, 1985, pp. 23-26). The categories of trials defined above are based on whether trials are likely to be statistically analyzable or not, since this is of major importance in livestock systems research.

Design. This is a stage in the livestock systems research procedure. In the context of livestock on-farm trials, 'design' is defined as that process which starts with an initial screening of the various technological options available and ends when the suitability of a technology for adoption by farmers has been established. The definition thus goes beyond (but includes) the conventional statistical use of the term². The design process is an iterative process which is likely to involve the need to re-design and re-try adapted versions of the original technology (Gilbert et al, 1980).

Test. A test is an informal study which assesses the practical implications and farmers' reactions to a particular trial.

Target population is the population of animals to which we would like to apply the results of a study.

Sampled population is the set of individual animals which would actually have a chance of being chosen for the purposes of the trial.

Sample is the set of animals selected for the purposes of the trial.

Sampling unit is the unit chosen for study (e.g. individual animals, pens of animals, herds).

Experimental variable is the variable whose effect is being examined in the trial (e.g. the effect of feed supplementation on weight gate).

In order to isolate the effect of the experimental variable, conventional research techniques require that the effects of other influencing factors (non-experimental variables) be held constant. In livestock on-farm trials, it can be difficult to measure and control non-experimental effects (e.g. management effects), and this problem increases as the level of control over the trial by the researcher declines (see pages 24-26 of Module 2, Section 2).

Treatment. The effect of an experimental variable can be examined by altering its level of application or the manner in which it is combined with other experimental variables. Each alteration constitutes a treatment. Control treatments are used as a standard against which other treatments can be compared (e.g. animals receiving no supplement in a feeding trial) might be used as a 'control' (i.e. as the basis for comparison with those receiving some supplement).

Replication. Each repetition of a treatment is called a replication. In livestock trials, treatments may be repeated at the level of a pen, herd or individual animal. By increasing the number of replications, there is a better chance of detecting real treatment differences.

² It involves sample selection, treatment specification, treatment layout, replication requirements and the methods of analysis used.

Part B: Problems confronted

Most of the problems confronted in on-farm trials stem from the fact that resources available for research are limited. In particular this affects:

· the supervisory capacity of the research team

i.e. the capacity of the tea' to supervise adequately the farmers and enumerators taking part in the trial so that the data collected are useful.

· sample size

i.e. the ability of the tear to obtain a large enough sample to ensure that statistical analysis of the results is meaningful.

Difficulties with respect to supervision and statistical analysts of the results obtained tend to be more pronounced with livestock than they are with crops, and the reasons for this are discussed in the literature (Bernsten et al, 1984; Sands et al, 1984; Gryseels, 1986; McIntire 1986). In brief, they relate to:

· animal mobility

In systems where livestock are highly mobile or where the quality of grazing resources is highly variable, treatment effects can be confounded by the effects of environmental variation. The more mobile and extensive the system, the "ore difficult it is to account for these sources of variation (McIntire 1986). To compensate, large samples are needed, but the supervision time required and the costs involved may be prohibitive. Options for technological improvement are also likely to be more limited in extensive production systems.

· lifespan

The lifespan of ruminant animals is relatively long. Research aimed at improving breed performance therefore tends to be costly and beyond the scope of most systems research teams. Farmers are also inclined to lose interest in trials which continue for prolonged periods and require more supervision as a result. The risk that experimental animals will die or be sold also increases with the length of the trial period.

· life-cycle synchronisation

Blocking sample animals into uniform classes on the basis of age, sex, weight and parity should always be attempted. This removes potential sources of variation between different sample animals and improves the chances of detecting treatment effects. However, in practice it can be extremely difficult to find large enough samples to 'block' animals in this way, which, in turn, imposes limitations on the ability of the researcher to obtain statistically analyzable results (Module 2, Section 2).

· producers' attitudes to livestock

Producers may be unwilling to divulge information about the livestock they own or hold and to participate in trials because of the high value they attach to individual animals (particularly cattle). When the herds or flocks owned or held are small, the inconvenience (and risk) associated with participation in trials may also be considered too great to "arrant the effort. When animals are jointly owned or held or managed, further complications arise. Full commitment is, however, a pre-requisite to the success of on-farm trials.

· management variability

Producers vary in their ability to manage livestock, and this can confound trial results. Blocking trials on the basis of differences in management can overcome this problem if sufficient animals within the same age, sex and productive class can be obtained on each farm for each treatment. When this is not possible, similar animals have to be obtained from many more farmers. Problems of supervision then tend to increase. The more widely dispersed the population, the more difficult it is to supervise the trial.

· communal land tenure systems

Communal grazing can pose problems in the measurement of the effects of non-experimental variables (e.g. grazing resources and disease). It also limits the potential for certain types of technological improvement (e.g. breed and pasture improvement).

· multiple outputs

Livestock produce multiple outputs (meat, milk, draught, manure and skins) and some of these can be difficult to measure and value. This sometimes complicates data collection.

The implications of each of these problems are discussed in greater detail in Module 2 of this section.

Part C: Justifying the need for on-farm trials

Justifying the need for on-farm research requires consideration of essentially three issues:

· the relevance of technology to the problems identified
· the appropriateness of on-farm trials, and
· the practicality of on-farm trials.

The relevance of technology to the problems identified

Section 1 of this manual emphasised that correct description and diagnosis of the system is critical to the success of any on-farm trial project. It showed that diagnostic research should be directed towards the identification of 'pathways' for the improvement of production and income and that such improvements may come as a result of policy and of infrastructural, institutional or technological change.

On-farm trials may be justified if a technological solution by itself is considered appropriate to the problem(s) identified. In other circumstances, a new policy or an institutional reform may be required before technological solutions are considered (Caldwell, 1984).

The appropriateness of on-farm trials

Having identified the need for a technological solution, the need for on-farm trial work should then be definitely established. In some circumstances, on-station research may be sufficient or all that is possible* This would be true, for instance, if the problem(s) identified required long-term research unsuited to on-farm trial work (see part B above), or if technology suitable for on-farm adoption had not been developed.

There may be other situations in which exploratory on-farm trials are justified. Such trials are essentially diagnostic in intention, the elm being to obtain a better understanding of the system by more intensive contact with farmers. They are likely to be used by researchers who, although convinced of the need for technological change, are still searching for an innovation to try' (Stroud, 1985). Exploratory trials are not discussed in this section.

The practicality of on-farm trials

In certain circumstances' on-farm research directed towards statistical analysis of the results may be justifiable in theory but impractical, because it is too difficult to obtain a large enough sample or because adequate supervision cannot be assured. Alternative courses of action should then be considered (Module 2, Section 2), rather than attempting to conduct on-farm trials.

The research team may not be able to assess the need for and the practicality of on-farm testing immediately after the diagnostic phase. Some issues may only be properly clarified at the design stage, while others may require a preliminary testing stage. A flexible attitude and approach is therefore required at all stages of the research procedure.

Part D: Choosing the technology to test: the screening process

If a technological approach to the problem(s) identified is justified, it is necessary to screen the various options which exist and choose from them the technologies most relevant to the situation which we seek to ameliorate. In many cases, few (or no) options will be available. In others, a range of possibilities may exist and those most appropriate to on-farm testing will need to be selected.

Screening is essentially an on-going process of technology selection directed towards reducing the risk of negative or unproductive research results (Bernsten et al 7 1984). It begins by considering each of the following issues:

· the nature of the problem(s) confronted
· the technological options available to meet the problem(s) identified, and
· the technological options appropriate to the problem(s) identified.

The nature of the problems confronted

The diagnostic techniques described in Section 1 and exploratory trials should give the researcher a reasonably good idea of the constraints limiting production and income in the target area. However, this is not enough: the nature and causes of the problems identified must be specified, by asking the following questions:

· Which particular production parameters are affected (e.g. mortality rates, reproduction rates, growth rates)?

· Which animal species and classes within each species are affected?

· What specifically causes the problem?

For instance, if the problem is a disease problem, we will need to identify the determinants of the disease (Module 8, Section 1). If it is a problem related to the nutritive value of the feed, we will need to determine which components of the diet (energy, protein or minerals) warrant particular attention (Module 7, Section 1). If it is a management problem, then "e will need to find out which aspects of management require attention -watering and herding practices, for instance (Module 10, Section 1).

Available technological options

When the nature and the causes of the problems identified have been specified, the next step is to identify the technological options which are available to solve the problems. Some options may need to be tested in on-farm trials, others may not (see below).

For instance, if labour is identified as the factor limiting watering frequency and hence production in a pastoral system (Module 11, Section 1), the options available for technological improvement (e.g more evenly distributed water points) are likely to be fairly limited, offering little scope for trial work within the community.

For instance, if seasonal feed shortages are identified as limiting in a sedentary system, a wide range of options is likely to be available (e.g. various feed supplementation strategies, crop improvement strategies to increase stover production, pasture improvement schemes) (Module 1, Section 1) and the scope for on-farm testing is also likely to be greater.

Obtaining information about the various options available can be more difficult than expected. To overcome this problem, as many sources of information as possible should be used, including:

· farmers/pastoralists

If consulted, farmers and pastoralists will often provide useful information about the nature of their production constraints and the solutions they consider appropriate. Their opinions should always be given full consideration but should be cross-checked against the opinions of others (e.g. extension officers).

· between and within-system comparisons

An examination of the management practices adopted in the target area may point to potential solutions. Similarly, comparisons between similar systems might indicate suitable options for improvement (Shaner et al, 1982). For instance, if lambing percentages in one production system are consistently lower than those in an adjacent but similar production system, reasons for these differences should be examined. Producers in the latter area may, for instance, time the mating of ewes to coincide better with seasonally available feed supplies.

· other sources, such as non-governmental organisations, extension officers and researchers, and

· secondary data sources (Module 1, Section 1).

Appropriate technological options

While the constraints confronted by small farmers and pastoralists are often similar (e.g. in terms of animal nutrition or health), the relevant solutions are often 'site-specific' because of cultural, institutional, economic, infrastructural and political influences. Available technologies should, therefore, be screened, using the following criteria (Peterson and Hayani, 1977; Dillon, 1979; Zandstra, 1980; De Boer, 1982):

· potential costs and benefits

Low-cost innovations which generate obvious cash returns within a relatively short time period are likely to be attractive. If access to credit enables the farmer to 'spread' the capital costs of an investment (in equipment or livestock), longer-term options may also be attractive.

· Farmers' objectives/perspectives

Farmers' and researchers' perceptions about the value of an innovation can differ quite markedly. Farmers, for instance, may be more interested in the survival of their livestock than in improved calving performance, milk production or weight gain, and this may affect their reactions to a technology and the manner in which it is applied (Behnke, 1984; Waters-Bayer and Bayer, 1981).

· risk

Farmers will not adopt a technology if the risks involved are considered too great (Dillon and Scandizzo, 1978; Anderson et al, 1985).

· interactions

Production decisions are influenced by various exogenous and endogenous factors which need to be carefully considered (see Parts A and B of this module).

· accessibility/availability of inputs

Technologies requiring the use of purchased inputs will be inappropriate if those inputs are not available or accessible on a continuing basis.

In addition, the broader social implications of adoption should be considered on the basis of:

· equity

For instance, what effect will adoption have on the distribution of income in the target area?

· gender

For instance, what effect will the adoption of a technology have on labour inputs required from women and on the distribution of benefits within the family. Will adoption be practical and will the overall welfare effects within the family be positive?

· environment

What impact will adoption have on the environment (e.g. in terms of range stability and sustainability)? (Module 6, Section 1) (Conway, 1985).

· replicability

For instance, is the technology likely to be applicable outside the target group? Within the group itself, will it be widely adopted? (Norman and Collinson, 1985).

A decision matrix can be a useful means of checking technologies against such criteria (Steiner, 1987). An example is given below. Module 1 in Section 1 describes an alternative but complementary approach suggested by CIMMYT (1986) for the screening of technological options.

Example: Assume there are three technological options available (A, B and C). Rate these in a decision matrix on the basis of the criteria given above using the symbols:

(+) = fair to good
(-) = poor
(*) = fairly certain of effect
(?) = uncertain of effect

Decision matrix

Criterion	Technological option
	A	B	C
Costs/benefits	-/*	+/*	+/*
Farmers' objectives	-/*	+/?	+/?
Risk	-/*	+/*	+/*
Interactions	+/?	+/?	+/?
Accessibility/availability	-/?	+/*	+/*
Equity	-/*	+/?	+/?
Gender	+/?	-/*	-/?
Environment	+/*	-/*	+/*
Replicability	-/*	+/?	+/?

Of the three options considered available, option A is obviously inappropriate on the basis of the criteria used. Options B and C are very similar but option B would be ruled out on the grounds of environment and gender. With option C, uncertainty about farmers' objectives, on-farm resource interactions and equity effects would strongly suggest the need for on-farm trials.

After screening, it is important to decide whether an on-farm trial approach is relevant to the circumstances. Technologies identified as 'appropriate' will normally need to be adapted or refined before wide adoption can be envisaged (e.g. Gilbert et al, 1980; Norman and Collinson, 1985; Mutsaers et al, 1986). This may involve the need for on-farm trials or on-station research work.

If on-farm trials are considered relevant to the circumstances, the research team will need to decide whether 'statistical' or 'monitoring' trials should be carried out. Module 2 (Section 2) outlines the factors which need to be considered when this is done. It also suggests when on-station research is perhaps the more relevant approach to adopt.

References

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