For generations, agronomic experiments have been the conventional basis for cultivar selection and the evaluation of crop productivity in response to climate, soil and management options. However, agronomy is often limited by the availability of physical and human resources. All agronomic research is restricted to a limited number of sites, seasons and experimental combinations. Nevertheless, general recommendations for appropriate agronomic practices require an assessment of spatial and temporal variability, both within and between locations. This requirement is difficult to satisfy through conventional short-term experimentation on a limited number of sites. For the world's major crops, agronomic recommendations have been based on a long history of experiments and experience across a range of sites, seasons and management practices. By definition, major crops have an international significance and therefore research effort can be directed to long term and broad geographical objectives. In contrast, minor or underutilised crops often have important but regional or local significance. Since many of these crops are grown for subsistence and contribute to the food security of many of the world's poorest people, attempts to improve them rarely attract interest from international agencies or commercial sponsors. As a result, research on underutilised crops cannot afford the luxury of a long-term international effort and to make rapid progress alternatives to conventional agronomic experimentation must be sought. Recent developments in the use of computer-based analytical tools, such as weather data generators, crop simulation models, geographic information systems (GIS) and the Internet, provide exciting new opportunities to complement conventional agronomy and provide practical recommendations for appropriate agronomic practices outside the limited range of experimental conditions. One particular use of these new technologies is to assess the potential productivity of underutilised crops at locations beyond their current distribution.
The objective of this study was to assess the potential productivity of bambara groundnut (Vigna subterranea L. Verdc) - an underutilised African legume - across the world. This global approach had two aims:
Most human food requirements are provided by fewer than 20 crop species. There remains a vast repository of many hundreds of underutilised species that have been grown locally for centuries and which contribute to the food security of the world's poorest people. Many of these crops are cultivated in hostile, tropical environments by small-scale farmers without access to irrigation or fertilisers and with little guidance on improved practices and feasible alternatives. Any attempts to improve their germplasm or management practices depend on local experience and resources since most agricultural scientists and breeders have ignored or actively discouraged the cultivation of indigenous underutilised crops. The few efforts that have been made to evaluate these species by conventional methods have been slow and labour-intensive and research funds have rarely been directed to multidisciplinary research on such crops of unknown potential. Furthermore, because many of these crops are grown for subsistence, little effort has been made to genetically or agronomically improve them or assess their nutritional, processing and economic potential. A major limitation of most research on underutilised crops is that, because of inadequate funding, it is confined to a single aspect, e.g. breeding, of the particular species in question. The lack of a multidisciplinary effort or comprehensive published literature on any particular underutilised species means that any research that is done may duplicate that being done elsewhere with no increase in overall knowledge or understanding of the crop in question. The lack of an overarching strategy for the improvement of different underutilised crops discourages the development of general principles that can be applied across species. This piecemeal approach reduces both the effectiveness of research on each underutilised species and the collective influence of those advocating greater efforts to increase agricultural biodiversity.
If there is to be an increase in agricultural biodiversity and a broader basis to food security policies, there is an urgent need to co-ordinate research on underutilised crops within a general and robust methodology that:
This study, using our experience of bambara groundnut as an example, demonstrates how the integration of physiological principles, field research and crop modelling together with a weather data generator and GIS can provide a general and cost-effective means of rapidly assessing the potential of many underutilised food crops.
Bambara groundnut (Vigna subterranea L. Verdc) is an indigenous grain legume grown mainly by subsistence women farmers in drier parts of sub-saharan Africa. The crop has advantages over more favoured species in terms of nutritional value and tolerance to adverse environmental conditions. In much of Africa, bambara groundnut is the third most important legume after groundnut (Arachis hypogaea) and cowpea (Vigna unguiculata) (Sellschop, 1962). The crop has a number of production advantages in that it can yield on poor soils with little rainfall as well as produce substantial yields under better conditions. It is nutritionally superior to other legumes and is the preferred food crop of many local people (Linnemann, 1990; Brough and Azam-Ali, 1992). Bambara groundnut is a rich source of protein (16-25%) and its seeds are valued both for their nutritional and economic importance. The seeds command a high market price, with demand far outweighing supply in many areas (Coudert, 1982). However, despite these important attributes, the agro-ecological and genetic potential of bambara groundnut have not yet been fully realised nor its full economic significance determined. The crop is still cultivated from local landraces rather than varieties bred specifically for particular agro-ecological conditions or production systems.
Recently, scientists in Africa and elsewhere have begun to accumulate agronomic and physiological knowledge about the crop and to link this with the indigenous knowledge and perceptions of farmers and their families. Between 1992 and 1996, the University of Nottingham, UK, co-ordinated a major European Union (EU) project to assess the agro-ecological potential of bambara groundnut. This programme linked field experiments in the United Republic of Tanzania, Botswana and Sierra Leone with experiments and analysis at Nottingham and Wageningen University in the Netherlands. The objectives of the EU Bambara Groundnut Project were to:
A more complete description of the EU project appears in University of Nottingham (1997). A number of associated publications describe the growth and development of the crop (Collinson et al., 1996) its capture and use of solar radiation (Collinson et al., 1999) germination responses of seeds (Kocabas et al., 1999) and yield responses to sowing date (Collinson et al., 2000).
Simulation models are robust tools to guide our understanding of how a system responds to a given set of conditions. Crop simulation models are increasingly being used in agriculture to estimate production potentials, design plant ideotypes, transfer agrotechnologies, assist strategic and tactical decisions, forecast real time yields and establish research priorities (Uehera and Tsuji, 1993; Penning de Vries and Teng, 1993; Bannayan and Crout, 1999). Although there are growth simulation models for a range of major crops, there have been few attempts to develop models for underutilised species for which the factors controlling growth and development are not well understood and the general literature is sparse. The BAMnut crop simulation model was designed as a part of the EU Bambara Groundnut Project to integrate our knowledge about the agro-ecological requirements of bambara groundnut across a range of locations in Africa. BAMnut is the first dynamic simulation model for bambara groundnut and therefore provides the first predictions of its pod yields in response to the use of environmental resources or responses to environmental stress. A major objective for developing BAMnut was to provide a means of integrating our preliminary understanding of the dynamics of crop growth as influenced by soil moisture and environmental variables. This allows the agro-ecological potential and resource requirements of the crop to be established. In particular, because BAMnut is a process-based model, it allows predictions of crop growth and yield to be generated and matched with current and potential production environments beyond those used in the development of the original model.
To develop BAMnut, functional relations were derived from experimental data collected in growth room or glasshouse experiments at the University of Nottingham (UK) in 1995 (Collinson et al., 1993, 1997and1999; Kocabas et al., 1999; Berchie, 1996; Babiker, 1989; Zulu, 1989) and field experiments conducted in Africa (Sesay and Yarmah, 1996; Karikari, et al., 1996;). A set of independent data from Nottingham and two years (1994, 1995) field data from two sites in the United Republic of Tanzania (Morogoro: 6° 49' S, 37° 4' E and Hombolo 5° 54' S, 35° 57' E) were used to evaluate the model.
For the 1995 glasshouse experiments, three contrasting landraces of bambara groundnut were grown as crop stands in controlled-environment glasshouses at the Tropical Crops Research Unit (TCRU), University of Nottingham. Each glasshouse has a cropping area of 35 m2 containing a sandy loam soil overlying a gravely loam subsoil. This area is subdivided into two equal plots within which soil moisture can be independently controlled and monitored. The soil volume is lined to a depth of 1.25 m with butyl rubber to prevent natural water table fluctuations from affecting the rooting zone. The three bambara groundnut landraces were obtained from collaborating institutions in Sierra Leone (`LunT'), the United Republic of Tanzania (`DodR') and Botswana (`DipC'). In each glasshouse, one landrace was grown in each plot and received one of two soil moisture treatments. In the first, the soil was irrigated to 90% field capacity each week. In the second, the soil was irrigated to 60% field capacity until establishment (27 days after sowing (DAS)) with no further irrigation (Collinson et al., 1999). The crops received natural daylight with no supplementary lighting. Fertiliser was applied prior to sowing to achieve approximate soil nutrient contents of; N 150 kg ha-1, P 40 kg ha-1 and K 150 kg ha-1 based on soil analysis. Crop growth measurements were obtained from seven sequential growth analyses taken during the growing period. More details of this experiment can be found in Collinson et al., (1999).
Two of the landraces used in the 1995 glasshouse experiment (DipC and DodR) were also grown in a field study in the United Republic of Tanzania. In the field experiments, the crop was planted at three different dates; 4 January, 4 February and 4 March in 1994 and 1995 on a sandy loam soil. Experiments were arranged as a randomised complete block design with four replicates each containing six plots. Individual plot size was 5.6 x 5.6 m, each plot containing 16 rows 35 cm apart. Fertiliser was applied prior to sowing at a rate of 40 Kg N ha-1 using NPK compound fertiliser (25:5:5). Sequential growth analyses were carried out on six plants per plot on eight occasions throughout the season.
