Journal
AGRONOMY JOURNAL
Volume 106, Issue 5, Pages 1795-1804Publisher
WILEY
DOI: 10.2134/agronj14.0067
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Funding
- United States Department of Agriculture (USDA)-NIFA specialty crop research initiative [2009-51181-06071]
- Mississippi Sweetpotato Council
- USDA-NIFA [2013-34263-20931, G-7799-2]
- NIFA [2009-51181-06071, 577738, 2013-34263-20931, 687681] Funding Source: Federal RePORTER
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Temperature impacts several growth and developmental processes in sweetpotato [Ipomoea batatas L. (Lam)] including storage root (SR) initiation. To quantify early season growth and developmental responses of sweetpotato, an experiment was conducted using sunlit growth chambers at a wide range of day/night temperatures, 20/12, 25/17, 30/22, 35/27, and 40/32 degrees C, from transplanting to 59 d using cultivar Beauregard. Growth and developmental rates were estimated from plants harvested at regular intervals. Total and SR numbers recorded at each harvest were analyzed by fitting sigmoidal curves to estimate SR initiation rates. With increasing temperature, SR conversion efficiency increased quadratically with an optimum at 23.9 degrees C. Adventitous and SR developmental rates were increased linearly and quadratically, respectively, with increasing temperature, and maximum rate of SR initiation was reached at 29.5 degrees C in 16.7 d. Vine and leaf area growth rates showed quadratic trends with temperature with maximum rates at 29 and 33 degrees C, respectively. While quadratic functions best described temperature responses of total, stem, and SR biomass, the optimum temperatures varied among them at 29.2, 30.1, and 26.5 degrees C, respectively. Leaf biomass, conversely, increased linearly with temperature. Fraction of biomass partitioned to roots declined linearly and at high temperature it declined by 75%, compared to the fraction at SR optimum temperature. The SR production efficiency declined from 0.43 to 0.08 g SR kg(-1) total weight, and dropped by 81% at high temperature relative to optimum. Quantified growth and developmental responses derived from the developed temperature-dependent functional algorithms will be useful to develop sweetpotato crop models and management decisions.
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