Agriculture Reference
In-Depth Information
assessed for high quality wheat production (Germeyer 1999, Holle and Untiedt 1999, Becker
and Leithold 2001, Richter and Debruck 2001) and for other crops drilled in line (Becker and
Leithold 2003). Depending on the cultivars tested, grain yield losses can differ between negli-
gible to substantial, particularly under the competition of living mulch systems (Germeyer
1999). Interestingly, increases in the protein content of grains were also observed, as in research
in Northern Germany where a considerable increase in the glutene content that was higher
than 2.0% of normally sown wheat (Holle and Untiedt 1999). Spring wheat was more respon-
sive to that drilling design compared to winter wheat cultivars. The lower level of seeds used
provided attractive economic figures, gain in lower seed costs combined with higher payments
for better grain quality. Due to the wider spacing, undersowing should be integrated, at least at
suitable sites. Reduced erodability was measured by Becker and Leithold (2003). The apparent
increase of biodiversity in such an undersowing-oriented system (more space, more light,
better growing factors for the undersown species) has to be paid for with higher labour input
in terms of multiple mulching passes and costs for labour and the initial investment. However,
very aggressive regulation of weeds is possible.
Weed management itself is important in determining crop densities and planting configu-
rations. Wider rows are advantageous for weeding to allow access for tillage and hand-weeding
implements, particularly under heavier weed loads (van Elzakker and Caldas 1999, Tillett and
Home 2002, Rasmussen 2004). However, higher crop densities along the row achieved through
closer transplant distances for seedling-grown crops or higher sowing rates for seed-grown
crops are used to maximise resource capture and competition against weeds (Bulson
et al.
1997, Grevsen 2000).
Timing of operations
The deliberate scheduling of farming activities is an important cultural strategy used by
organic growers to manage resources efficiently and improve their effectiveness. The main
factors for which timing can be manipulated include sowing, tillage, applying inputs and har-
vesting. Farmers' decisions about timing may be inf luenced by agronomic considerations such
as crop phenology, the quantity and growth stage of weed seedlings, environmental factors
such as climate and soil condition, and by marketing needs and opportunities.
Nitrate leaching can be an undesirable impact of organic crop production. Losses of mobile
N of 100 kg ha
-1
or more have been reported (Faßbender 1998), posing a serious economic and
ecological problem, especially if continuous leakages within the rotation cannot be avoided.
However, careful timing of farming operations such as fertiliser applications and green manure
management to match availability with demand can be achieved. Conventional 'best practice' is
designed to minimise nitrate leaching by improving the N use efficiency of crops, as well as pro-
tecting soil N from leaching during higher rainfall. Crop management factors affecting N
dynamics include the selection of an appropriate crop variety, maintenance of a green cover for
as much of the year as is practicable, and drilling crops early. Fertiliser management considera-
tions include the calculation of fertiliser requirements using a recommendation system (and
allowing for soil mineral N and any manures applied), spreading fertilisers evenly with a
properly calibrated spreader (possibly with split applications) and using banding where appro-
priate. Irrigation water should also be applied carefully according to scheduling requirements.
Research is now focusing on the study of whole farm systems and the interactions between
N losses and other pollutants to the environment, with the aim of minimising total environ-
mental impact. In addition, increasingly sophisticated and reliable computer models are being
developed to provide predictive capabilities for farm management tasks. Decision making
about the timing of tasks within crop rotations is a process with many possible options and is,
therefore, well suited to a modelling approach. Computer models have been developed and
