By D. K. L. Mackerron, A. J. Haverkort
Versions of crop development and improvement have been initially conceived for clinical reasons. generally, they describe the mechanisms of crop construction, improvement from emergence via tuber initiation to senescence made up our minds through temperature and day-length. progress is pushed via sun radiation intercepted by means of the foliage. Yields are more suitable by means of the provision of water and foodstuff and should be lowered by way of pests, ailments and weeds. those clinical versions are leaving the examine institutes and more and more have gotten a method of data move for college kids, and most significantly, to growers and their intermediaries corresponding to extensionists and experts. Many selection aid platforms (DSS) have a mechanistic version middle that assures their robustness and reliability. This publication supplies an summary of model-based DSS in potato construction. determination help structures are utilized by the processing to steer them to promising creation components and through breeders to spot the fitting genotype for such environments. experts and soil laboratories use them in addition to farmers to optimize using nitrogen, water and chemical substances to regulate bugs, nematodes, past due blight and weeds
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Additional info for Decision support systems in potato production: Bringing models to practice
Nct N uptake = NNI . %Nct . Wt The NNI characterises the nitrogen nutritional level %Nct characterises the critical nitrogen content Wt, the dry matter weight of the plant as a whole, characterises the growth level We can thus adapt the evaluation of crop N requirement to: • production objectives, by using the appropriate crop N status (NNI) and • the production duration cycle, by estimating dry matter production (Wt) The dry matter of the plant as a whole can be simulated by a growth model. , 1997) for evaluating the nitrogen requirement corresponding to each biomass level (the CRITIC model by T.
Transactions of the ASAE 39 1869-1875. , 1998. Using precision farming technologies to improve management of soil and fertilizer nitrogen. Australian Journal of Agricultural Science 49 555-564. G. & J. Verhagen, 1997. Using decision support systems to optimize barley management on spatial variable soil. J. Kropff et al. J. M. Oomen, 1997. Environmental and economic effects of site specific and weather adapted nitrogen fertilization for a Dutch field crop rotation. In: Precision agriculture ‘97.
However, the total nitrogen input was about 20% less (Figure 6). So a similar yield was obtained at a lower nitrogen input. However, this difference was not reflected in the residual mineral soil nitrogen (Figure 6). As the nitrogen off-take was also the same (Figure 6), it means that the amount of nitrogen in the senesced foliage was less. Decision support systems in potato production 51 Crop-reflection-based DSS for supplemental nitrogen dressings in potato production 200 160 120 Standard CropScan 80 40 0 N-input N-tuber N-res id.