By Robin B Matthews, William Stephens
This ebook, in keeping with paintings backed through the average assets structures Programme of the united kingdom division for foreign improvement, stories growth in crop-soil simulation modelling and assesses its software to agriculture in constructing international locations. The books is split into sections in accordance with a class of types with various capabilities: these used as instruments by means of researchers; these used as instruments by way of decision-makers; and people utilized in schooling, education and know-how move. The examples used are in most cases from functions of crop versions in constructing international locations, supplemented by means of reviews with tropical vegetation in Australia. the ultimate sections of the booklet talk about even if crop versions have proved necessary and think about the best way ahead in crop modelling and alertness. to be had In Print
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Additional info for Crop-soil simulation models: applications in developing countries
1996, 1997) used the ORYZA1 model for investigating effects on grain yield of various traits such as developmental rates during juvenile and grain-filling periods, leaf area growth, leaf N content, shoot/root ratio, leaf/stem ratio, and 1000-grain weight. Because of the lack of feed-backs built into this model, however, changing any one of these parameters generally changed yields in the expected way, with the exception of the phenological parameters, which interacted with year-to-year variability in weather.
1991). Similarly, many applications of crop models relating to water management have been incorporated into decision support systems for scheduling of irrigation, which are discussed in more detail in Chapters 9 and 10. The following are some examples of how crop models have been used as tools to aid research in water management. Matthews and Stephens (1997) used the CUPPA-TEA model to provide initial evaluations of different irrigation options in terms of yields and 38 R. Matthews profitability for tea growing in Tanzania.
1989) used a model to simulate identification of the factors limiting maize yields for the main land-units, and found that rainfall was limiting only if it was less than 800 mm. At higher levels of rainfall, the main constraint to higher yields was nutrients, indicating that there would be a response to fertilizer. It is not known if the results from this work had any impact. An interesting use of a crop model to evaluate possible causes for change in crop yields over time in a given region is provided by Bell and Fischer (1994).