Identifying management zones (MZs) within a field is challenging because crop yields typically vary over space and time (Lamb, 1997). In-field variability is the focus of precision agriculture – how to manage it, diminish it, or overcome it. In-field variability reduces the ability to determine consistent yield patterns, and thus management zones.
Producers have expressed frustration in obtaining value from yield maps. Griffin (2000) states, “farmers were struggling to find direct benefits from the yield information that they were spending time and effort gathering.” Reasons yield maps are often not generated include: (i) the yield monitor might not be accompanied by GPS, (ii) problems associated with the data analysis, and (iii) owner operators who do little or no field work do not benefit as much from yield maps as those having direct experience with field conditions (Griffin, 2004). Reasons for not utilizing generated data such as yield maps are numerous and include; time to learn electronic skills in order to operate equipment and software, lack of training for producers and industry, uncertainty with using analyzed data to influence decision making, lack of local experts for technical assistance, working with data of differing formats, lack of basic research on yield and soil relationships, and need for a precision agricultural equipment (Kitchen, 2002). Griffin (2004) states, “the inability to process the gathered yield information into meaningful decisions, leads to apathy and discontinuance of future data collection.”