Agriculture Reference
In-Depth Information
are relevant for the particular farms considered but are sometimes diffi-
cult to extrapolate because of the peculiarities of the individual farmer's
management. This procedure not only includes characterization of existing
conditions, as in the Zimbabwe Arenosol case study, but may also involve
experimentation with applied manure or inclusion of legumes. This on-farm
approach offers opportunities to discover “lighthouse” examples of farmer
innovations. When applying organic fertilizers, e.g., manure, it is important
to recognize that nutrients are delivered beyond the year of application.
This supports the idea that land use history should be taken into account
when developing appropriate fertilization strategies within a farm context.
4. Awareness about the possible impact of fertilization on environmental
quality has, starting in the 1980s, resulted in a broad system analysis by
modeling and monitoring that not only considers nutrient uptake by plants
and resulting plant growth, but also leaching of excess nutrients to ground-
water and surface waters and production of various gases adversely affect-
ing environmental quality (e.g., Sonneveld et al. 2008). Now, the dynamics
of the entire soil are characterized rather than a static fertility sample for
surface soil only. This procedure also includes innovative, modern methods
to measure soil conditions with, e.g., in situ or proximal sensors.
5. A development of approach 4 is precision agriculture where fertilization
in a given farmer's field is “fine-tuned” by applying it differently in space
and time, depending on different soil conditions in the field and changing
weather and crop demand during the growing season. Dynamic modeling
of crop growth, based on the nutrient regime of the soil and weather condi-
tions, allows fine-tuning of fertilization rates and times. A field study in the
Netherlands showed that precision procedures resulted in a 30% reduction
of fertilizer use as compared with the traditional procedures, while yields
did not decrease. This not only represented a considerable savings for the
farmer but also a more efficient use of natural resources (Van Alphen and
Stoorvogel 2001; Van Alphen 2002; Bouma et al. 2012). Note that only
dynamic modeling can provide signals of soil nutrient stocks in the rootzone
becoming critically low. The highly promoted use of remote sensing for
precision agriculture can indicate nitrogen shortage in crop leaves; however,
this signal comes too late as crop growth retardation has already occurred.
This is avoided by the dynamic modeling approach. Precision agriculture is
the procedure of the future anywhere in the world as it most closely matches
the needs of the plants, on the one hand, and fertilizer applications, on the
other, taking into account solute fluxes in the soil-plant-atmosphere sys-
tem. Thus, ecological intensification becomes more feasible, also in devel-
oping countries (e.g., Cassman 1999; Tittonell and Giller 2012).
Institutional arrangements have, for a long time, been rather top-down, where
fertilizer rates, as determined on experimental stations, were communicated to
farmers through extension services. This has been quite successful in both devel-
oped and developing countries as long as the focus was on production. As attention
shifted since the 1980s to sustainable development and environmental concerns in
