Grain Legumes and Green Manures for Soil Fertility in ... - cimmyt

to the system in such a way that this contributes to
both short- and long-term soil fertility. There is
great potential for integrating livestock and
residue / manure management technologies to
maintain soil fertility, and in particular to make
optimum use of mineral fertilizers. Often it is the
effect of a technology on weeds, pests, diseases or
vermin which makes or breaks ' it. Problems with
rats and snakes make many farmers in Lampung,
Indonesia reluctant to use mulches, and
agroforestry legume fallows at Domboshawa were
found to increase cutworm populations, resulting in
almost complete loss of yield of a subsequent maize
crop..Conversely, Mucuna pruriens can be highly
effective at suppressing weeds in some
environments and this has aided its adoption as a
nitrogen fixing green manure (see Giller, 2001).
Creating a farm system model integrating processes
such as crop rotation, livestock production and
residue management is conceptually simple.
Outputs from a crop model can provide inputs of
crop residue to a decomposition model or stover as
forage to a livestock production model and vice
versa. Budgets can be calculated for calories, carbon,
nutrients and money. Historically, agronomic
model~ have been developed by a research group
extendmg an existing model within the original
software framework. However, developments in
software technology suggest an alternative
approach that allows existing models to
communicate with each other and be linked as
submodels (Muetzelfeldt, 1995). In such a linked
model, each part of the system such as a crop field
or a dairy unit can be simulated by a submodel of
any level of complexity, provided that standard
inputs are required and standard outputs produced.
Quantitative models of pests or weeds could also be
linked. Linking of all of the various components of
the farm system would thus allow the exploration
of opportunities for combing different types of soil
fertili.ty technologies to understand how they can
contnbute to overall improvement of productivity
of the farm as a whole. Optimal farm systems could
then be designed using techniques such as multiple
goal linear programming.
Such biophysically optimal systems might however
remain unadopted if they were poorly adapted to
the specific needs and resources of farmers and in
particular the timing of labour availability. Labour
requirements are notoriously difficult to assess,
particularly for new technologies, and
quantific~t~on of labour supply is complicated by
opportumtles for alternative employment off-farm
and hired labour whether paid or unpaid. External
and internal value judgements about the amount of
time farmers spend working in the fields also make
assessment difficult. Labour constraints are
generally not included in crop models, and labour is
thus effectively and naively seen as a free resource.
T~e nee~ for agro~cological models to be integrated
w~th ~oclOeconomlc models has been identified by
sCientists from both disciplines.
NUANCES (Nutrient Use in ANimal and
Cropping systems - Efficiency and
Scales) .
NUANCES (Nutrient Use in ANimal and Cropping
systems - Efficiency and Scales) is a conceptual
framework for analysis of trade-offs in African
smallholder 'farming systems. Heterogeneity is a
key feature of most farms, as farmers tend to
concentrate resources in small areas where soil
fertility is maintained while the majority of their
fields are effecffvely mined of nutrients. The
efficiency with which nutrient resources are utilized
for crop production is likely to vary strongly
between land of different quality, as will the
potential growth of different crops or indeed of the
potentially soil-improving legumes. Documenting
the extent of variable land qualities within farms is
therefore an important step in understanding the
potential impact of different technologies for soil
fertility improvement. The wealth or resource
endowment of farming households also determines
their capacity to invest labour and other resources
in agriculture as, for example, livestock ownership
IS often regarded as a key indicator of wealth in
rural Africa. Poorer farmers are often only able to
earn income off-farm by selling their labour to the
wealthier farmers which then restricts the labour
they can invest in improving productivity of their
own farms. Farm types will also be identified,
which might correspond to different wealth classes
or production systems, to capture the resource
flows between farms (Figure 1). Resource flows are
often mediated by livestock, and the framework
thus includes livestock productivity and manure
management.
Resource flow mapping approaches have provided
valuable insights into the allocation of crops · and
nutrient resources at various scales, from fields to
farms, from regions to continents. Assembling static
balances for nutrients across different land units
does not however allow for testing of future
scenarios of how farms could be developed in
future. Flows which are difficult to measure, such as
leaching, are generally estimated using simple
transfer functions, but these functions may not give
an appropriate response to changing conditions.
Biophysical models of various degrees of
Grain Legumes and Green Manures for Soil Fertility in Southern Africa
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