In spite of the economic importance and extensive agronomic literature on cocoa, no physiological production model has been developed for cocoa so far. Such a model would be very useful to compare yields in different climates and cropping systems, and to set the agenda for future agronomic research. Here, we present and apply such a physiological growth and production model for cocoa (SUCROS-Cocoa), based on the SUCROS-family of physiological crop growth models. Our model calculates light interception, photosynthesis, maintenance respiration, evapotranspiration, biomass production and bean yield for cocoa trees grown under shade trees. It can cope with both potential and water-limited situations, and is parameterised using existing information on cocoa physiology and morphology. A validation study showed that the model produces realistic output for bean yield, standing biomass, leaf area and The model was applied to answer four questions that are currently relevant to cocoa production. (1) Which are the most important yield-determining parameters? Sensitivity analyses revealed that these parameters were chiefly related to the morphology of fruits, photosynthesis and maintenance respiration. (2) To what extent can cocoa yield be predicted by rainfall and irradiance data? Regression analyses showed that over 70% of the variation in simulated bean yield could be explained by a combination of annual radiation and rainfall during the two driest months. (3) How large is the cocoa yield gap due to water limitation? Yield gaps were large -up to 50% -for locations with a strong dry season combined with an unfavourable (clayey or sandy) soil. The calculated yield gaps decreased exponentially with the amount of rain during the two driest months. (4) What are the consequences of shading on cocoa yield? Our simulations showed that moderate shade levels hardly affected bean yield, whereas heavy shading (>60%) reduced yields by more than one-third.

SUMMARYIn two cultivar ¾ density trials for oil palms (Elaeis guineensis) planted in Indonesia, single leaf area, number of green leaves per tree, leaf opening rate per year and rachis length of leaves were followed over fourteen years. The data were analysed to determine the time course of canopy leaf area and to predict the moment of canopy closure.Growth functions were ®tted to the observed data. Estimates of leaf area index (L) were based on single leaf area, number of green leaves, leaf opening and planting density. The time course of L was modelled on the basis of the ®tted functions to the components. The moment of canopy closure was calculated from the planting density and the functions ®tted for rachis length.The modelled time course of L was considerably dierent from the function ®tted to the single leaf area data. The expansion of L was not as rapid as expected from the area growth of single leaves and, after maximum L was reached, a steady decline was observed. The continuously declining number of green leaves was the main cause of these two observations.The time course of L diered considerably between the two experiments. Not only were there large dierences in the number of green leaves maintained per tree in the experiments but also the ®nal area of single leaves diered between both experiments. The ®rst factor was a result of the management of the experiments, whereas the second factor was most likely in¯uenced by a dierence in soil-related factors at the two locations.Leaf areas and numbers of leaves per tree were dierent for each cultivar, as was L. This was also the parameter most sensitive to planting density. Individual leaf area and leaf number per tree were not aected by planting density, but rachis length was aected by the planting density treatment. The moment of canopy closure was similar in both experiments. Planting density was the main factor that determined the onset of canopy closure.

Since the last two decades, Wageningen UR Library has been involved in bibliometric analyses for the evaluation of scientific output of staff, chair groups and research institutes of Wageningen UR. In these advanced bibliometric analyses several indicator scores, such as the number of publications, number of citations and citation impacts, are calculated. For a fair comparison of scientific output from staff, chair groups or research institutes (that each work in a different scientific discipline with specific publication and

The natural habitat of the oil palm comprises very wet and relatively dry niches in the lowland rain forest in West and Central Africa. The domestication of the oil palm started with the extraction of fruits from wild forest resources. When forests were cleared for shifting cultivation, oil palms were not felled and in the subsequent regeneration period they obtained a favourable position resulting in semi-wild palm groves. Thinning of groves gave rise to semi-permanent or permanent intercropping systems of palms and food crops. After the transfer of oil palm to SE Asia in the 19th century, a mono-crop oil palm evolved. Its success was based on a favourable climate, breeding, improved cultivation and processing practices and the absence of major pests and diseases. The high-yielding production systems are sustainable at high input levels and pollution can be kept within acceptable limits. Oil yields and production costs compare favourably to those from other oil crops. The domestication of oil palm for oil yield so far can be considered as a success story. Physiological studies indicate that there is still considerable scope for further increase in yield. The adaptation of oil palm to new environments will continue and produce diversification puts new demands on domestication. This paper reviews the different stages in the domestication process especially adaptation to plantation agriculture, the simultaneous genetic improvement, and the prospects of reaching full yield potential in different environments.

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