Assessment of functional forms of crop yield loss models of invasive plant species applied in decision support tools and bioeconomic modelling

AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.

Betalain rich functional extract with reduced salts and nitrate content from red beetroot (Beta vulgaris L.) using membrane separation technology

An initial laboratory-scale evaluation of separation characteristics of membranes with nominal molecular weight cut-offs (NMWCO) ranging from 30 kD down to 0.5 kD indicated effective separation of betalains in the 0.5 kD region. Subsequent pilot-level trials using 1 kD, loose reverse osmosis (LRO) and reverse osmosis (RO) spiral-wound membranes showed LRO membrane to be very efficient with up to 96% salt and 47% other dissolved solids removed while retaining majority of the pigment (∼98%) in the betalain rich extract (BRE). The total betalain content in the BRE increased up to 46%, the highest recovery reported so far at pilot scale level. Interestingly, more than 95% of the nitrates were removed from the BRE after the three diafiltrations. These studies indicate that membrane technology is the most efficient technique to produce BRE with highly reduced amounts of salts and nitrate content.