Efficiency of product collaborative innovation design based on the attribute and matching task

The degrees that the design agent capacity matches the design task are an important factor affecting the efficiency of collaborative product innovation design. The classification and quantitative calculation of different types of design agent capacity combination is carried out after the characteristic of design agent is analyzed. An efficiency model whose goal is the shortest entire time is constructed based on the definition of task attribute,and then the solving method of efficiency model are designed based on particle swarm optimization algorithm. The collaborative product innovation design of cabin is taken as an example to prove that considering the matching agent attribute with task can shorten the design cycle and improve design efficiency.     

Variance component estimations and allocation of resources for breeding sweetpotato under East African conditions

In Africa, average sweetpotato storage root yields are low and breeding is considered to be an important factor in increasing production. The objectives of this study were to obtain variance component estimations for sweetpotato in this region of the world and then use these to determine the efficiency of variety trials and breeding systems. From an incomplete series of variety trials in Kenya and Uganda (comprising 15 genotypes, three locations, two crop durations and three seasons) variance components were estimated ‐ using the REML method ‐ for the following traits: storage root yield, biomass production, harvest index, storage root dry matter and the Elston index which was used to aggregate all four traits. The storage root yield of clones across all 12 environments ranged from 15.2 to 33.0 t/ha. The variance components were significant for all traits, except the genotype by season interactions for storage root dry matter. The efficiency of selection systems was determined for total test capacities of 450 and 900 plots and using not more than five locations. Two‐stage selection was 17‐81% more efficient than one‐stage selection after two seasons of testing. Two‐stage selection was optimized under the restriction of using at least two locations at step 1. Trials with two locations and one replication at step 1 and five locations and two replications at step 2 were appropriate both for selecting for storage root yield and for simultaneously selecting for storage root yield, biomass production, harvest index and storage root dry matter content by using the Elston index. There are indications that such an allocation of resources for breeding sweetpotato is also appropriate for other regions in Sub‐Saharan Africa.     

Optimum allocation of plots to years,seasons, locations,and replications,and its application to once-over-harvest cucumber trials

Summary Large experiments and breeding trials are often conducted over years, seasons (or planting dates), and locations, and with replication (blocks). This is costly and time-consuming, but it is usually deemed necessary to sample a range of environments. In this paper, we describe a general approach to optimum allocation of sampling effort, and apply it to once-over-harvest cucumber trials. Two criteria for optimality are considered: minimizing the variance of a genotype (or treatment) mean, and minimizing cost per unit information. Costs could include penalties for delaying a breeding program. Thus, costs may depend on the goal, as well as the size, of the experiment or breeding trial.We found that efficient allocation of resources favors using more years and/or season, with fewer locations and/or replications. Using more years with fewer locations and/or replications is suggested when genotypes are to be evaluated by yield alone. When both yield and quality variables are of interest, as is likely, using more seasons with fewer locations and/or replications is recommended.Paper No. 11302 of the Journal Series of the North Carolina Agricultural Research Service, Raleigh, North Carolina, USA 27695–7601.