No abstract

Crop models and decision support systems can be very useful tools for scientists, extension educators, teachers, planners and policy makers to help with the evaluation of alternative management practices. Many of the current crop models respond to differences in local weather conditions, soil characteristics, crop management practices and genetics. However, computer-based tools require inputs in order to provide reliable results. Especially for those new to crop modeling, the data requirements are sometimes somewhat overwhelming. In this chapter we provide a clear and concise summary of the input data requirements for crop modeling. We differentiate between requirements for model evaluation, model application and model development and improvement. For model inputs we defi ne daily weather data, soil surface and profi le characteristics, and crop management. For model evaluation and improvement we defi ne crop performance data as it relates to growth, development, yield and yield components, as well as additional observations. We expect that this chapter will make the use and application of crop models and decision support systems easier for beginning modelers as well as for the more advanced users.

Gene flow between domesticated plants and their wild relatives is one of the major evolutionary processes acting to shape their structure of genetic diversity. Earlier literature, in the 1970s, reported on the interfertility and the sympatry of wild, weedy and cultivated sorghum belonging to the species Sorghum bicolor in most regions of sub-Saharan Africa. However, only a few recent surveys have addressed the geographical and ecological distribution of sorghum wild relatives and their genetic structure. These features are poorly documented, especially in western Africa, a centre of diversity for this crop. We report here on an exhaustive in situ collection of wild, weedy and cultivated sorghum assembled in Mali and in Guinea. The extent and pattern of genetic diversity were assessed with 15 SSRs within the cultivated pool (455 accessions), the wild pool (91 wild and weedy forms) and between them. F (ST) and R (ST) statistics, distance-based trees, Bayesian clustering methods, as well as isolation by distance models, were used to infer evolutionary relationships within the wild-weedy-crop complex. Firstly, our analyses highlighted a strong racial structure of genetic diversity within cultivated sorghum (F (ST) = 0.40). Secondly, clustering analyses highlighted the introgressed nature of most of the wild and weedy sorghum and grouped them into two eco-geographical groups. Such closeness between wild and crop sorghum could be the result of both sorghum's domestication history and preferential post-domestication crop-to-wild gene flow enhanced by farmers' practices. Finally, isolation by distance analyses showed strong spatial genetic structure within each pool, due to spatially limited dispersal, and suggested consequent gene flow between the wild and the crop pools, also supported by R (ST) analyses. Our findings thus revealed important features for the collection, conservation and biosafety of domesticated and wild sorghum in their centre of diversity.

2016-12-23T18:49:38

The study quantified rainfall variability for March-May (MAM) and October-December (OND) seasons in Tharaka district, Kenya. The parameters analysed were inter-annual variability of seasonal rainfall, onset and cessation using daily rainfall data in three agro-ecological zones' stations. Percentage mean cumulative method was used to determine onset and cessation, and seasonal variability was estimated using rainfall variability indices. Although both seasons are highly variable, OND has been persistently below mean over time while MAM shows high within-season variability. Despite the near uniformity in the mean onset and cessation dates, the former is highly variable on an inter-annual scale. The two rainfall seasons are inherently dissimilar and therefore require specific cropping in agro-ecological zone LM4 and LM4-5. It is possible that farmers in IL5 are missing an opportunity by under-utilising MAM rainfall. The results should be incorporated in implications of climate variability and vulnerability assessment in semi-arid Tharaka district.