Diversification economies and specialisation efficiencies in a mixed food and coffee smallholder farming system in Papua New Guinea

Smallholder farming systems in Papua New Guinea are characterised by an integrated set of cash cropping and subsistence food cropping activities. In the Highlands provinces, the subsistence food crop sub-system is dominated by sweet potato production. Coffee dominates the cash cropping sub-system, but a limited number of food crops are also grown for cash sale. The dynamics between sub-systems can influence the scope for complementarity between, and technical efficiency of, their operations, especially in light of the seasonality of demand for household labour and management inputs within the farming system. A crucial element of these dynamic processes is diversification into commercial agricultural production, which can influence factor productivity and the efficiency of crop production where smallholders maintain a strong production base in subsistence foods. In this study we use survey data from households engaged in coffee and food crop production in the Benabena district of Eastern Highlands Province to derive technical efficiency indices for each household over two years. A stochastic input distance function approach is used to establish whether diversification economies exist and whether specialisation in coffee, subsistence food or cash food production significantly influences technical efficiency on the sampled smallholdings. Diversification economics are weakly evident between subsistence food production and both coffee and cash food production, but diseconomies of diversification are discerned between coffee and cash food production. A number of factors are tested for their effects on technical efficiency. Significant technical efficiency gains are made from diversification among broad cropping enterprises.

Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.