We grew 84 different corn (Zea mays L.) performance tests in paired-density comparisons averaging 51 600 and 64 500 plants per hectare over a 9-year period to examine the utility of higher plant densities for corn performance tests. The higher density reduced yield test means from 76 to 73 q/ha, increased ranges among hybrids from 40 to 44 q/ha, and decreased hybrid F values for tests from 3.6 to 3.2. Broken stalk test means increased from 10 to 12%, ranges among hybrids increased from 35 to 39%, and hybrid F values for tests increased from 2.5 to 2.9 with the higher density. Dropped ears showed a large period-of-years effect due to effective selection. Testing at above optimum plant densities increased barrenness, stalk breakage, and ear droppage; it also increased the range among entries, thereby increasing the ease of selection against these traits. We analyzed 5 years' data from 250 strip tests comparing two widely grown hybrids at three plant densities and found that increased densities reduced number of tests needed to differentiate the hybrids. On the average twenty strip tests with alternate check strips grown at plant densities at or above 56 000 plants per hectare successfully differentiated (P = ca. 0.05) 7% yield at 75 q/ha average yield, 1.8% broken stalks at 5% average broken, and 2.4% root lodged at 2.5% average lodged; the two hybrids did not differ for dropped ears. Superior commercial hybrids resulted via higher plant density testing.
Kernel samples from all possible F1 combinations among eight inbred lines of sweet corn, including reciprocals, were analyzed quantitatively for reducing sugars, sucrose, and water‐soluble polysaccharides. The F2 kernels produced on a diallel set of F1 plants involving five of the inbreds were analyzed also.Analysis of covariance was used to remove the effects of maturity (percent moisture) on the carbohydrate fractions. Genotypic variability for reducing sugars, sucrose, and water‐soluble polysaccharides was partitioned into general and specific combining ability variances. Highly signiifcant GCA variances and nonsignificant SCA variances for each character indicate the inheritance of these carbohydrate fractions is highly additive. GCA effects corresponded closely in relative rank with inbred means.
Reducing sugars, sucrose, and water‐soluble polysaccharides were quantitatively determined for kernels of eight inbred lines of sweet corn and their Fl combinations, including reciprocals, 25 days after pollination. A second harvest was taken from the inbred parents at 28 days. The inbreds differed significantly for percent moisture and for each carbohydrate fraction. Moisture content and carbohydrate composition changed at significantly different rates for the eight lines.Analysis of covariance was used to remove effects of maturity on F1 kernels. There were highly significant differences among maternal half‐sib groups for percent moisture, reducing sugars, sucrose, and water‐soluble polysaccharides. Differences within half‐sib groups were significant for all variables except reducing sugars. Differences among reciprocal crosses were attributed to maternal effects and gene‐dosage relationships in the endosperm. Regression coefficients showed that content of reducing sugars and sucrose decreased, but content of water‐soluble polysaccharides rapidly increased with advancing maturity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.