In a six-year crop rotation trial organically and integrated grown vegetables were produced according to current good agricultural practices, taking quality and quantity aspects into consideration. The raw materials assessed focussed on materials used for industrial food production. Nutritional, sensory and agricultural aspects were evaluated. Carrot, cabbage, onion, pea and potato are possible to grow organically for industrial purposes. Depending on crop, the yield was lower (65-90%) for organically grown compared to integrated grown. Cultivation of organic spinach and dill turned out to be difficult due to problems with weed and discoloration. The chemical analyses included pesticide residues, nitrate, glycoalkaloid, dry matter, vitamin C and 25 different minerals and trace elements. Overall, the organically grown crops had higher dry matter content than the integrated grown. However, when examining the data for the different crops contradictory results were noted. No significant differences due to growing system were noticed for vitamin C and the other nutrients except for 4 of the trace elements. The growing system did not influence the sensory properties. 相似文献
This paper describes the development of a systems based model to characterise farmers’ decision-making process in information-intensive practices, and its evaluation in the context of Precision Agriculture (PA). A participative methodology was developed in which farm managers decomposed their process of decision-making into brief decision statements along with associated information requirements. The methodology was first developed on a university research farm in Denmark and further revised during testing on a number of research and commercial farms in Indiana, USA. Twenty-one decision-analysis factors were identified to characterise a farm manager’s decision-making process. Then, a general data flow diagram (DFD) was constructed that describes the information flows “from data to decision”. Illustrative examples of the model in the form of DFDs are presented for a strategic, a tactical and an operational decision. The model was validated for a range of decisions related to operations by three university farm managers and by five commercial farmers practicing PA for cereal, corn and soybean production in Denmark and in Indiana, USA. 相似文献
It is assumed that Agent-Based Modeling is a useful technique for water management issues. In particular, it may provide a suitable framework for representing irrigated systems. The objective of this paper is to demonstrate its potential for a specific use: research on irrigated systems’ viability in the Senegal River Valley. The main assumption to be verified is that Multi-Agent Systems constitute a suitable architecture to study theoretically irrigated systems’ viability using simulations. By using Multi-Agent Systems, virtual irrigated systems can be designed that might then be used as virtual laboratories. These virtual labs constitute an alternative when real labs cannot exist for some reason.
In this paper we report on experiments we have conducted using such virtual labs for exploring an Agent-Based Model through the simulation of scenarios. A scenario is defined as a triplet: an environment, a set of individual rules, a set of collective rules. It is evaluated according to the longevity of the irrigated system. An index is defined, based on the ratio of long-enduring simulations among a set of repetitions of a given scenario. Even if simulation results display significant diversity for a given scenario due to random factors in the processes simulated, the ratio of long-enduring simulations is repeatable. This entails to explore the overall behavior of the virtual irrigated system and to build theories concerning the viability of Senegalese irrigated systems. An example is given showing the need for strong coherence for a given environment among individual rules and collective rules. 相似文献
The objective of this study is to present a new application of optical and radar remote sensing with high spatial (∼10 m) and temporal (a few days) resolutions for the detection of tillage and irrigation operations. The analysis was performed for irrigated wheat crops in the semi-arid Tensift/Marrakech plain (Central Morocco) using three FORMOSAT-2 images and two ASAR images acquired within one week at the beginning of the 2005/2006 agricultural season.The approach we developed uses simple mapping algorithms (band thresholding and decision tree) for the characterisation of soil surface states. The first images acquired by FORMOSAT and ASAR were processed to classify fields into three main categories: ploughed (in depth), prepared to be sown (harrowed), and not ploughed-not harrowed. This information was combined with a change detection analysis based on multitemporal images to identify harrowing and irrigation operations which occurred between two satellite observations.The performance of the algorithm was evaluated using data related to land use and agricultural practices collected on 124 fields. The analysis shows that drastic changes of surface states caused by ploughing or irrigation are detected without ambiguity (consistency index of 96%). This study provided evidence that optical and radar data contain complementary information for the detection of agricultural operations at the beginning of agricultural season. This information could be useful in regional decision support systems to refine crop calendars and to improve prediction of crop water needs over large areas. 相似文献