complicated. One way to keep down the number of variables
in these trials, and keep them small in size, is to design
two or more different experiments. By using only three or
four variables in each trial and choosing groups of
variables that interact frequently (e.g., fertilizer and
cultivars, weed control and plant density) the design is
further simplified. For the evaluation of potential
alternatives, such as introducing a new crop in the
region, the number of treatments can be reduced and the
design will be simplified. These trials are mostly
researcher-managed, though the farmers' previous
experience makes their input and opinions in the design of
treatments essential. A discussion of the types of
exploratory trial designs follows, along with examples for
each case.

SUPERIMPOSED TRIALS

 A relatively simple, convenient, and efficient means
of exploring the effect of different factors in a new area
is a superimposed trial. In this type of trial,


TABLE III-1.


Example of a superimposed six-treatment
N-P-K trial in rice.


 Grain yield
Treatment Farm Number
N P K 1 2 3 4 5 6 x


 (metric ton x 100)

50- 0- 0 336 434 451 411 402 375 401.5
90- 0- 0 439 416 506 459 482 431 455.5
70- 0- 0 443 398 457 370 454 350 412.0
70-30- 0 412 419 412 398 499 386 421.0
70-30-30 416 368 482 370 397 402 405.8
70- 0-30 417 377 493 364 490 387 421.3

 x 410.5 402.0 466.8 395.3 454.0 388.5 419.5

Source: Zandstra et al. (1981), p.107.

treatments are placed on fields which are being managed by
the farmers themselves. Treatments are marked by stakes