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 study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner–Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale. 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