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ARS Home » Midwest Area » Morris, Minnesota » Soil Management Research » Research » Publications at this Location » Publication #84515

Title: DATA NEEDED TO PREDICT SEED PRODUCTION IN CORN

Author
item Westgate, Mark

Submitted to: Agronomy Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 10/31/1997
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Seed production in maize can be estimated from detailed quantitative information on timing, intensity and duration of silk emergence and pollen shed. Such information is not available, however, for the vast majority of commercial hybrids or their inbred parents because these data are both time consuming and laborious to collect. Since silk emergence and pollen shed follow unique, but predictable patterns, it may be possible to simplify the data set required to predict seed production without sacrificing predictive capability. The objective of this work was to identify a minimum set of quantitative measures of floral development necessary to predict potential seed production under field conditions. Detailed information on silk emergence, pollen shed density, seed set, and grain yield in the field were used to generate logistic flowering functions for predicting seed production. Predicted seed production was within 5% of actual across a broad range of pollen shed densities. Further analysis revealed that only a few parameters were needed to define the flowering functions and predict final seed production. The minimum data set included: two dates for percentage of plants silking (ca. 20 and 80%), two dates for percentage of plants shedding pollen (ca. 20 and 80%), an estimate of pollen production per plant, and final floret number per ear. These results indicate an extensive data set of daily silk emergence and pollen shed is not required to obtain accurate predictions of potential seed production for maize grown under field conditions.