A cost effective sampling approach involving composite sampling, identified potential sediment source materials from the four main agricultural fields.
In order to test for hypothesized effects of national culture on management control systems with a cost-effective sample size, most cross-cultural studies rely on large differences in culture in their experimental design.
We describe and demonstrate here a simple method for improving high-throughput short-read sequencing results using a cost-effective sample preparation technique.
We tested a cost-effective sampling method for estimating whole-shrub water status by comparing δ13C values of the plant's largest stem against a composite sample of all stems.
We present a pragmatic approach to estimate harvest at an AR off coastal Sydney, Australia, that combines existing datasets and a cost-effective sampling design from two different time periods.
Hence, finding a modelling method for predicting the presence of soft sediments and enable production of digital maps of where soft sediments are likely to be found would be valuable for developing a cost-effective sampling design.
Two available datasets on a sub-national scale in Italy were used to determine a cost-effective sampling density to be adopted in medium-to-large-scale biomonitoring studies.
After initial PCR amplification, the library pooling strategy was deployed, where each library was pooled prior to ssDNA isolation, enabling time and cost effective sample processing (figure 2).
