I am conducting a field experiment using a randomized complete block design. The layout includes 5 blocks, each of equal land area. Within each block, there are 5 plots, and each plot receives a diffe

 

I am conducting a field experiment using a randomized complete block design. The layout includes 5 blocks, each of equal land area. Within each block, there are 5 plots, and each plot receives a different single treatment. These 5 treatments are repeated across all blocks, so each treatment is replicated five times in total—once per block. 

My question concerns sample collection for a single treatment. What is the scientifically valid and recommended method for collecting samples and analyzing data? 

Option 1: Should I collect multiple sub-samples (e.g., three or more) from each individual plot, calculate their average, and then use that mean for statistical analysis? 

Option 2: Or should I collect one representative sample from the treatment plot in each of the five blocks (i.e., one per replicate), and then use the mean of those five samples for analysis? 

Which approach better represents proper replication, minimizes experimental error, and aligns with standard practices in field-based research?