Optimum plant density for crowding stress tolerant processing sweet corn

Autoři: Daljeet S. Dhaliwal aff001;  Martin M. Williams, II aff002
Působiště autorů: Department of Crop Sciences, University of Illinois, Urbana, Illinois, United States of America aff001;  Global Change and Photosynthesis Research Unit, USDA-ARS, Urbana, Illinois, United States of America aff002
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pone.0223107


Globally, gains in sweet corn [Zea mays L.var. rugosa (or saccharata)] are a fraction of the yield advances made in field corn (Zea mays L.) in the last half-century. Grain yield improvement of field corn is associated with increased tolerance to higher plant densities (i.e., crowding stress). Processing sweet corn hybrids that tolerate crowding stress have been identified; however, such hybrids appear to be under-planted in the processing sweet corn. Using crowding stress tolerant (CST) hybrids, the objectives of this study were to: (1) identify optimum plant densities for a range of growing conditions; (2) quantify gaps in production between current and optimum plant densities; and (3) enumerate changes in yield and ear traits when shifting from current to optimum plant densities. Using a CST shrunken-2 (sh2) processing sweet corn hybrid, on-farm plant density trials were conducted in thirty fields across the states of Illinois, Minnesota and Wisconsin, from 2013 to 2017 in order to capture a wide variety of growing conditions. Linear mixed-effects models were used to identify the optimum plant density corresponding to maximum ear mass (Mt ha-1), case production (cases ha-1), and profitability to the processor ($ ha-1). Kernel moisture, indicative of plant development, was unaffected by plant density. Ear traits, such as ear number and ear mass per plant, average ear length, and filled ear length declined linearly with increasing plant density. Nonetheless, there was a large economic benefit to the grower and processor by shifting to higher plant densities in most environments. This research shows that increasing plant densities of CST hybrids from current (58,475 plants ha-1) to optimum (73,075 plants ha-1) could improve processing sweet corn green ear yield and processor profitability on average of 1.13 Mt ha-1 and $525 ha-1, respectively.

Klíčová slova:

Agricultural soil science – Crop management – Crops – Density – Ears – Maize – Plant breeding – Plant resistance to abiotic stress


1. NASS—National Agricultural Statistics Service. Available: https://www.nass.usda.gov/Statistics_by_Subject/index.php

2. Duvick DN, Cassman KG. Post–green revolution trends in yield potential of temperate maize in the North-Central United States. Crop Sci. 1999; 39: 1622–1630.

3. Tollenaar M, Wu J. Yield improvement in temperate maize is attributable to greater stress tolerance. Crop Sci. 1999; 39: 1597–1604.

4. Sangoi L, Gracietti MA, Rampazzo C, Bianchetti P. Response of Brazilian maize hybrids from different eras to changes in plant density. Field Crops Res. 2002; 79: 39–51.

5. Tokatlidis IS, Koutroubas SD. A review of maize hybrids’ dependence on high plant populations and its implications for crop yield stability. Field Crops Res. 2004; 88: 103–114.

6. Tollenaar M, Lee EA. Yield potential, yield stability and stress tolerance in maize. Field Crops Res. 2002; 75: 161–169.

7. Tollenaar M. Physiological basis of genetic improvement of maize hybrids in Ontario from 1959 to 1988. Crop Sci. 1991; 31: 119–124.

8. Bradley JP, Knittle KH, Troyer AF. Statistical methods in seed corn product selection. J Prod Agric. 1988; 1: 34–38.

9. Lertrat K, Pulam T. Breeding for increased sweetness in sweet corn. Int J Plant Breed. 2007; 1: 27–30.

10. Pataky JK, Williams MMII, Headrick JM, Nankam C, Du Toit LJ, Michener PM. Observations from a quarter century of evaluating reactions of sweet corn hybrids in disease nurseries. Plant Disease. 2011; 95: 1492–1506. doi: 10.1094/PDIS-03-11-0236 30732021

11. Williams MMII. Identifying crowding stress-tolerant hybrids in processing sweet corn. Agron J. 2015; 107: 1782–1788.

12. Williams MMII. Relationships among phenotypic traits of sweet corn and tolerance to crowding stress. Field Crops Res. 2016; 185: 45–50.

13. Choe E, Drnevich J, Williams MMII. Identification of crowding stress tolerance co-expression networks involved in sweet corn yield. PLoS One. 2016; 11:e0147418. doi: 10.1371/journal.pone.0147418 26796516.

14. Mansfield BD, Mumm RH. Survey of plant density tolerance in US maize germplasm. Crop Sci. 2014; 54: 157–173.

15. Shelton A, Tracy W. Genetic variation and phenotypic response of 15 sweet corn (Zea mays L.) hybrids to population density. Sustainability. 2013; 5: 2442–2456.

16. Williams MMII. Agronomics and economics of plant population density on processing sweet corn. Field Crops Res. 2012; 128: 55–61.

17. Morris TF, Hamilton G, Harney S. Optimum plant population for fresh-market sweet corn in the northeastern United States. HortTechnology. 2000; 10: 331–336.

18. Rangarajan A, Ingall B, Orfanedes M, Wolfe D. In-row spacing and cultivar affects ear yield and quality of early-planted sweet corn. HortTechnology. 2002; 12: 410–415.

19. Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team. nlme: Linear and Nonlinear Mixed Effects Models; 2018. R package version 3.1–137.

20. Team R. RStudio: integrated development for R. RStudio, Inc., Boston, MA URL http://www.rstudio.com. 2016.

21. Nakagawa S, Schielzeth H. A general and simple method for obtaining R2 from generalized linear mixed‐effects models. Methods in Ecology and Evolution. 2013; 4: 133–142.

22. Francis CA. Credibility of on-farm research in future information networks. In Detail from the Symposium on Alternative Approaches to On-Farm Research and Technology Exchange, Seattle, WA. 1995.

23. Rosen C, Fritz V. Planting date, nitrogen fertilizer, and plant population interactions in processing sweet corn. In: Zeygen RJ, Groth JV, Davis DW, Rosen CJ. Vegetable Crops Res. Rpt., 1987. Minn. Ag. Exp. Stn., pp. 134.

24. Boerboom C, Stevenson W, Wedberg J. Crop Profile for Corn (Sweet) in Wisconsin. 1999. Available: https://ipmdata.ipmcenters.org/documents/cropprofiles/wicorn-sweet.pdf.

25. Tollenaar M, McCullough DE, Dwyer LM. Physiological basis of the genetic improvement of corn. In: Slafer GA(Ed.), Genetic improvement of field crops. Marcel Dekker, Inc. New York; 1994. pp. 183–236.

26. Duvick DN, Smith JS, Cooper M. Long-term selection in a commercial hybrid maize breeding program. Plant Breed Rev. 2004; 24: 109–151.

27. Lee EA, Tollenaar M. Physiological basis of successful breeding strategies for maize grain yield. Crop Sci. 2007; 47: 202–215.

28. Mack HJ. Effects of population density, plant arrangement, and fertilizers on yield of sweet corn. J Amer Soc Hort Sci. 1972; 97: 757–760.

29. Moss JD, Mack HJ. Effects of plant density and nitrogen fertilizer on sweetcorn. HortScience. 1979; 14:176–177.

30. Szymanek M. Processing of Sweet Corn. In: Eissa AA. Trends in Vital Food and Control Engineering. 2012. Available: https://www.intechopen.com/books/trends-in-vital-food-and-control-engineering/processing-of-sweet-corn.

31. Williams MMII Few crop traits accurately predict variables important to productivity of processing sweet corn. Field Crops Res. 2014; 157: 20–26.

32. Tracy WF. Sweet corn. In: Hallauer AR. Specialty Corns. 2nd ed. CRC Press; 2001. pp. 155–197.

Článok vyšiel v časopise


2019 Číslo 9

Najčítanejšie v tomto čísle

Tejto téme sa ďalej venujú…


Zvýšte si kvalifikáciu online z pohodlia domova

Faktory ovlivňující léčbu levotyroxinem
nový kurz

Kurz originály vs. generika

Autori: MUDr. Petr Výborný, CSc., FEBO

Autori: MUDr. Jiří Horažďovský, Ph.D

Klinická farmakokinetika betablokátorů

Všetky kurzy
Zabudnuté heslo

Nemáte účet?  Registrujte sa

Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.


Nemáte účet?  Registrujte sa