Better sweet corn research, better production
While grain yield is economically important in field corn production, there are other metrics more important in sweet corn grown for processing, said Marty Williams, a USDA-ARS ecologist and University of Illinois crop sciences researcher.
In a study recently published in Field Crops Research, Williams questioned whether the crop yield responses that have been previously reported in sweet corn research are actually helpful to the industry.
“What has been done in the past is analogous to predicting someone’s height based on their shoe size, as opposed to actually measuring their height,” Williams said.
After collecting and studying sweet corn data representing 31 hybrids across 22 locations in Illinois over an 8-year period, Williams said he sees a disconnect in what researchers are measuring in the field and what processors and seed companies need to know in order to make improved production decisions.
In other words, Williams said researchers need to start speaking the same language as the sweet corn industry.
Williams explained that the two variables that affect processor decisions most include recovery (percentage of kernels that can be canned or bagged from the green-ear mass) and case production (cases per acre of processed kernels).
However, he added that nearly all historic and recent field research in processing sweet corn reports neither of these variables, regardless of whether the studies pertained to plant pathology, fertility management, pest control, or sweet corn breeding and genetics.
“Ear number or green-ear mass are often the only crop responses reported in research on field productivity of processing sweet corn. Sometimes, other crop responses are reported, including plant traits such as height or canopy density, or ear traits such as ear length or ear width,” he said.
In his study, Williams looked for relationships between processor variables and 17 crop traits (5 plant traits, 8 ear traits, and 4 yield traits). He determined that none of the crop traits predicted recovery.
“Recovery is something that has to be measured directly. Currently, there’s no way to predict it,” he explained.
When comparing the variability of the estimates in case production based on traits such as green-ear mass, husked-ear mass, and ear number, he determined that fresh kernel mass also was a far superior predictor of case production.
“Essentially, the more a measured yield response physically resembled a case of sweet corn, the more precise and accurate the estimate of case production,” he reported.
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