Agriculture Reference
In-Depth Information
yield data post-correction method is the most accurate one for producing yield maps,
and it is also practical in a commercial setting.
6.2.2 C
OTTON
Q
UALITY
M
APPING
Cotton production is capital-intensive, but as with all row crops, it tends toward low
profit margins. Aside from simply maximizing yield and improving crop marketing,
two potential avenues available for maximizing profit are minimizing input costs
with respect to yield and maximizing fiber quality. Minimizing input costs with
respect to yield requires the ability to monitor yield in the field. Yield monitoring in
cotton is an available technology, and cotton yield monitors are commercially avail-
able on the market for cotton producers.
Fiber quality has a large effect on the price that producers receive for their cot-
ton, and it is well established that spatial variability in cotton quality exists in farm
fields (Elms and Green, 1998; Johnson et al., 1998, 1999; Ping et al., 2004; Ge et al.,
2006a, 2006b, 2007). As yield maps have been essential to understanding spatial
relationships between field-management practices and crop yield, quality maps are
required to understand relationships between field-management and fiber quality.
Additionally, by using both cotton yield maps and fiber-quality maps, revenue maps
can be generated to help the producer determine which parts of fields require higher
or lower levels of agricultural inputs. Going one step further, profit mapping would
allow cotton producers to see specific areas within their fields that are returning
the highest or lowest profits by comparing revenues to input costs (Sjolander et al.,
2011a). Although instruments for cotton fiber quality mapping are not commercially
available at present, research on fiber quality mapping systems has been conducted
and significant strides have been made.
A wireless module-tracking system (WMTS) was developed for cotton fiber
quality mapping (Ge et al., 2012). The system consisted of three functional subsys-
tems installed on the three main machines involved in cotton harvests: a harvester
subsystem (HS), a boll buggy subsystem (BBS), and a module-builder subsystem
(MBS). Integrated into the HS is a GPS unit that records location information while
the harvester moves throughout the field. This GPS information is stored along with
a harvester basket identification number (ID) so the harvest locations of each basket
load of cotton can be known. When this cotton is transferred, the harvester opera-
tor enters data to identify the receiving vehicle, either a boll buggy or a module
builder. If the cotton is being transferred to a boll buggy, the HS sends a message
wirelessly including the basket ID to the BBS. This ID is then held by the BBS
until the boll buggy transfers the cotton to the module builder. When the cotton is
transferred to the module builder, the boll buggy operator presses a button and the
BBS relays to the MBS the wireless message from the harvester with the basket ID.
Upon receiving this message, the MBS automatically sends to the HS a wireless
message containing a module ID. Within the HS, this module ID number is paired
to the corresponding harvester basket ID. In the event that the harvester transfers
cotton directly to the module builder, the HS sends the basket ID message to the
MBS, which automatically sends the module ID message back to the HS (Sjolander
et al., 2011a).
