BUTSER ANCIENT FARM ARCHIVE 1973-2007 Archivist Christine Shaw
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Potential Yields of Prehistoric Cereals

This was the longest running of the Butser programmes and has International equivalents run by the Farm. It was perhaps the most all-embracing area of work associated with the Butser programmes .

Over the years, results for a number of sites were obtained and published in Butser Ancient Farm Year Books (currently out of print), in lectures and in the paper: Crop Yields of Prehistoric Cereal Types Emmer & Spelt

Similar programmes were set up outside the UK. One was in co-operation with Fundacio de Recerca, L'Esquerda, Roda de Ter, Catalonia, Spain, and still continues.  The early data (which can only be indicative but shows the principles involved) has been published.  Later data is can be found in the Research Reports published by the Foundation.

Images of cereals


In his war commentaries, Caesar refers to the export of grain and leather to the continent from Britain in the first century BC. Given the regular recovery of carbonised cereal grains (Provenance of Carbonised Seeds) from excavations of Iron Age sites, a logical line of enquiry for the prehistorian is to attempt to quantify potential yields from this period, in order to understand the implications of international commerce at this time. The long term cereal yield experiments at Butser have shown that British Iron Age men and women were far from the brink of starvation, in fact quite the contrary. Through having a grain surplus, a thriving export trade could secure the import of all the artefacts known from excavation and the presence of which would otherwise be hard to explain. On the social and cultural front, effort could therefore be released to allow development of specialised skills, the artisanal infrastructure and the cultural superstructure.

From the inception of the Ancient Farm, a major research programme was devoted to exploring present day yields of the typical cereal species of the Iron Age, namely Emmer (Triticum dicoccum), Spelt (Tr. spelta), Einkorn (Tr. monococcum), Club Wheat (Tr. aestivo-compactum) and Barley (Hordeum vulgare). From these yields, obtained under a range of closely recorded and controlled conditions, it was possible to project likely outcomes in the Iron Age environment.

The critical uncontrolled variables of this programme were local climate, weather and soil type, bearing in mind that any results are necessarily location dependent. Thus recording of the weather (Climate) was crucial to any meaningful projections. As far as soil type is concerned, the approach was to study yields on as wide a range of soil types as practicable. Initial work on the original site at Little Butser was on a shallow (100mm depth) friable redzina over an underlying rock of Middle Chalk. The second site at Hillhampton Down (BAFDA) had the same underlying geology but with a greater soil depth (300mm), while being a mixture of a similar redzina with clay and flint. The third site, at Bascomb, has a more complex soil of increased depth (400mm). The underlying rock is Upper Chalk. The upper layers are a mixture of hill wash and valley bottom soils, on top of a horizon of clay mixed with chalk particles, itself atop a horizon of clay with large flints, all above the rock level. A rather limited amount of data was obtained on a rich deep Brick Earth soil at Fishbourne but its value was constrained by the short duration of the trials, 3 years only. Since most of these sites are on less than preferable soils and in climatic zones which are, if anything, rather severe, it could be argued that the yields obtained are more likely to represent the lower bounds of Iron Age production, taken as a whole across the available agricultural land and climatic zones.

The managed variables comprised the choice of species, sowing rate and planting time (autumn or spring), manuring or non-manuring, and crop rotation against continuous cropping, along with fallowing or not. This last highlights a supplementary uncontrolled factor that differs from other uncontrolled factors, in that it is subject to modification by management practices such as hoeing and weeding, the only methods available until herbicides (not just modern petrochemically based materials) were found. That factor is the nature of the background weed community. Earlier studies have included the effects of Ploughing and Hoeing and Weed Control as agricultural practices.

Ploughing with replicated prehistoric ards (Ploughing) has provided additional insights into the efficacy of prehistoric farming techniques (for example the Donnerupland ard survives into the present day in the form of the multi-tined chisel plough). The same work provided data on the likely movement of sherds under prehistoric farming regimes. This led to the long term study of the impact of the modern multi-furrow turn-over plough (Artefact Movement Within the Plough Zone).

The area of cereal studies afforded opportunities for supplementary research projects including Pollen Rain and its Environmental Significance and short and long-term cereal storage (Storage of Grain in Underground Silos). Another experiment compared yields on burned and unburned plots within an artificial clearing (Slash & Burn Experiment). The contribution of manuring practices, or their absence, allowed studies from magnetic susceptibility surveys and the use of survival indicators, such as lipids, to be used as indicators of agricultural activity.

Experiment Design Philosophy

That different cereal grain plants have emerged naturally during, and perhaps before, the period of human farming activity is undisputed. The exact timing and location when different types arose is less firmly established. The manner in which knowledge of their existence and how seeds came to be translocated is a matter for anthropology and cultural study, aided by the biological sciences. Growing trials can never give insight into any of this.

Principally, experiments can only show how each species behaves in a range of circumstances set to illuminate particular physically based questions, the results of which may give insight into the economic benefits and sustainability of each crop plant. This may inspire discussion on wider aspects of farming communities and their livelihoods, extending the anthropological and cultural debate but providing no proofs as such.

No efficient experiment in agriculture could ever assess the response of factors one at a time. Thus test designs must be established, from the outset, with the aid of a statistician or a sound appreciation of statistical design AND data analysis (including an understanding of the underlying assumptions in statistical methodology). This applies both to plot and factor allocation and to data collection protocols, which should all be carefully documented before a single action is taken. It is often overlooked that experimenters should have their own individual instructions about procedures. There is a misguided belief that telling someone to do something "randomly" is both meaningful and achievable. There are numerous studies to show that even experienced workers are incapable of doing anything "at random" without a specific procedure being advanced in clear detail.

It is a necessary caution in all multifactorial work to know that the methods used presume linear responses and additivity, including any interactions between variables that may exist. There are many reasons for supposing this may not be true. A simple example is that of sowing rates. Continuous increases in sowing rate will not give proportionate and ever increasing yields. Light, food and water will become less and less available for each increment, up to the point of failure. There is therefore a need to understand the range of each variable for which linearity might be a reasonable supposition.

One reason why such analyses give the impression of meaningfulness is that, even where non-linearity is known or reasonably expected to exist, a disproportionate amount of data may be needed to prove it. Thus the methods tend to be self-fulfilling, insofar as the standard cross-checks do not indicate anything may be awry. It is only when attempts are made to predict outside the original data range (another simple concept too readily forgotten!) that things may go amiss.

Another important feature of agricultural experiments is the wide range of variables experienced, no less so than in the weather and its effects. To meet this, especially in view of the great uncertainties in projecting back to the putative conditions of past millennia, results for anything less than trial periods of up to 10 years merely add uncertainty upon uncertainty. Results from work covering only a few can at best be described as indicative, at worst valueless and potentially misleading. This time constraint inevitably restricts our ability to study the outcomes for a wide range of climatic zones and soil types.

An essential point from modern agricultural research practice, that cannot be sidestepped, relates to plot size. It is routine to have a 1 metre planted strip along each side of a trial plot with no samples collected from it. This is to avoid "edge effects" i.e. distortion of any target outcomes because of differing influences from the surrounding community compared with the test community. Thus it is easily seen that the MINIMUM overall plot size must be 3 metres by 3 metres.

The Butser test fields were 30 metres by 30 metres, in line with the size of Iron Age fields.

It is a reality that most, if not all, crop cereals have a maximum vital period of seven years, after which most of the seed is dead. Studies of farming practice around the globe show that grain for planting is routinely retained for only three years, by which time germinability has fallen from about 95% to around 75%. It is therefore essential to incorporate this into any test protocol, checking and recording both the history and germinability of source seed.

Output Data Selection

The cardinal rule is that the likely type of analysis of the data should be considered at the outset, so that the data may be collected in such a way as to be appropriate. This particularly includes the methods of sampling, sub-sampling (if necessary) and the numbers of replicates and duplicates (they are different!), which may be appropriate.

A factor worthy of contemplation is the time of emergence which relates to minimum ground temperature at which a given cereal will germinate. Naturally, too early a germination may expose the tender young plant to subsequent frost damage, so early emergence is not the be-all and end-all it might seem, so that one cereal may be favoured over another according to the local climatic pattern. The conventional input variable measures used are the ground surface temperature and the soil temperature at both 50 mm and 100 mm depth.

Further issues of plant survivability and ability to compete with weeds merit study before one may be able to test meaningful propositions about choice in a given climatic and soil zone.

An obvious question relates to the tillering property of cereal plants, that is the tendency or ability to throw up side shoots separate from the principal germination stem(s). This property may compensate for poor germination, frost damage, disease or early drought which lead to low plant populations. A word of caution for the researcher is that it is an exceedingly difficult characteristic for which to define a recording protocol and exceedingly time consuming in practice.

There are several other measures after emergence and ripening that are relevant to the cereal's behaviour under different conditions. It will be recognised that many of them are inter-related, so that a clear purpose in collecting each element of the data should be set at the outset.

Stand height, which varies in response to the input variables of weather, especially rainfall and temperature, and soil fertility and manuring, as a minimum, is also a character of a given cereal type. Greater height may lead to lodging as the stems tend to be weaker but could also be regarded as a competitive advantage in outgrowing weeds, since a better access to light should ensue. However, weeds themselves may respond differently in different circumstances, so it is relative response that is crucial. To this end it is necessary to check the relevant input variable by undertaking a survey of the background weed community on an annual basis.

There is an ancillary issue that relates to plant height wherein modern demands differ from the past. Straw has many uses, but especially for thatching. Local demands in the past might have put a premium on this quality, thereby biassing the decision to use one cereal against another.

Cereal plants exhibit great adaptability in grain production. The number of fruiting ears per plant, the number of spikelets per ear, the number of grains per spikelet and the weight of individual grains are all measurements that should be considered.

Finally, it is often instructive to incorporate the issues of nutrition or food value. The commonest measures are protein and gluten content.