Browsing by Subject "Crop Modeling"

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Designing, modeling, and evaluation of improved cropping strategies and multi-level interactions in intercropping systems in the North China Plain
(2010) Knörzer, Heike; Claupein, Wilhelm
Adjusting cropping systems in order to increase their efficiency is a global issue. High yield and sustainability are the catchphrases of production in the 21st century, and agricultural production has to solve the balancing act between ecology and economy. Therefore, the requests for farmers, consultants and researchers are rising, and production modes are changing. Nevertheless, solutions have to be detected spatially explicit and locally adapted and accepted in order to be implemented successfully. Taking the North China Plain as an example, the productivity of arable land needs to be further increased by applying strategies to reduce or avoid negative environmental effects. Further yield increases are not possible by increasing input factors like N-fertilizer or irrigation water as N-fertilizer rates are extremely high and irrigation water is limited. However, yield increases might be possible by developing improved cropping strategies operated by cropping designs. Taking modeling and simulation tools into account back up the acceleration of research attainments and the understanding of cropping systems. The present thesis embraces the designing and modeling of such a potential cropping system, to wit strip intercropping. Thus, the main goals of the study were to analyze, design, evaluate, and in the end model intercropping. Intercropping systems are complex systems which strongly need to be designed and evaluated carefully in order to fulfill the premises of ecological and economical efficiency as well as sustainability. Multi-level interactions have to be weighted and taken into regard for evaluating datasets applicative for modeling and simulating intercropping. The main results of the study indicated, that traditional cropping systems like intercropping are widespread in China, where approximately one third of arable land is under intercropping. Reviewing cereal intercropping systems in China, the four agro-ecological regions ?Northeast and North?, the ?Northwest?, the ?Yellow-Huai River Valley? and the ?Southwest? could be classified, distinguished and described. Intercropping offers a great variation of species combination, benefits as well as challenges for cropping systems design and farmers. Carefully balanced between facilitation and competition, intercropping bears the potential of increased yield and yield stability, income security, resource use efficiency and biodiversity. Intercropping gives evidence about traditional cropping systems with the potential for future production systems under the paradigm of sustainability. Further, results from conducted field experiments indicated that border effects are the key component of intercropping performance. Nevertheless, analyzing strip intercropping statistically has peculiarities as they lack in randomization because the cropping system imposes alternating strips. Thus, spatial variability and its effect on yield were regarded differently within a geo-statistical analysis. In addition to the geo-statistical analysis, the crop growth modeling approach paid tribute to monocropping effects as well as to field border effects occurring in strip intercropping systems. Further on a model-based approach was tested to quantify multi-level interactions with special regard to changing microclimatic conditions and to optimize intercropping systems from an agronomical point of view. In comparison to other interspecific competition modeling approaches, a shading algorithm was evaluated and implemented into the process-oriented crop growth model DSSAT in order to simulate competition for solar radiation. More common in modeling mixed intercropping, a modified Beer?s law subroutine has been used instead, e.g. in APSIM. APSIM and DSSAT were compared by modeling the conducted field trials. As a result, the Beer?s law approach was not capable to model strip intercropping. In contrast, the modeling with a changed DSSAT model showed that applying a simple shading algorithm that estimated the proportion of shading in comparison to the monocropping situation and in dependency from neighboring plant height seems to be a promising approach. The results indicated that competition for solar radiation in those systems is a driving force for crop productivity but neither the most dominant nor the one and only. Resource distribution and allocation in space and time seems to be more important than the total amount of resources. Those effects have to be taken into account when simulating interspecific competition.