2014
DOI: 10.2134/agronj13.0531
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Quantifying Temperature Effects on Cotton Reproductive Efficiency and Fiber Quality

Abstract: Quantitative functional relationships between temperature and fiber quality are needed to improve predictive capability of cotton (Gossypium hirsutum L.) models. An experiment was conducted by varying day/night temperatures, 22/14, 26/18, 30/22, and 34/26°C, imposed at flowering. Upland cotton cultivar, TM-1, was seeded in the soil bins using fine sand as the rooting medium and allowed to grow under optimum water and nutrients. Flowers and bolls were tagged daily to estimate the boll maturation period. Plant … Show more

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Cited by 70 publications
(49 citation statements)
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“…Therefore, without any interference of other biotic and environmental stress factors, the effects of water stress on fiber properties can be quantified. However, temperature‐specific fiber quality estimates are needed under optimum water nutrient conditions to estimate the potential fiber quality values (Reddy et al, 1999; Lokhande and Reddy, 2014). Similarly, variety and nutrient‐specific fiber quality indices (Reddy et al, 2004) are also needed to be able to apply under variable weather and soil conditions and management practices across the Cotton Belt.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Therefore, without any interference of other biotic and environmental stress factors, the effects of water stress on fiber properties can be quantified. However, temperature‐specific fiber quality estimates are needed under optimum water nutrient conditions to estimate the potential fiber quality values (Reddy et al, 1999; Lokhande and Reddy, 2014). Similarly, variety and nutrient‐specific fiber quality indices (Reddy et al, 2004) are also needed to be able to apply under variable weather and soil conditions and management practices across the Cotton Belt.…”
Section: Resultsmentioning
confidence: 99%
“…The identified midday leaf potential‐specific indices for fiber properties should be useful and can be incorporated into cotton simulation models to improve management practices under present and future climatic conditions. However, potential temperature‐specific fiber quality indices under optimum water and nutrient conditions and nutrient‐specific indices under optimum water and temperature conditions are needed to develop a fiber model in cotton (Reddy et al, 1999; Lokhande and Reddy, 2014). Models equipped with fiber quality would be useful not only for production optimization of natural resources such as water and nutrients, but also useful in assisting planting dates in the current environment and in policy decisions for the hypothesized changes in global environmental change on cotton production in the future.…”
Section: Discussionmentioning
confidence: 99%
“…Wanjura and Barker [8] demonstrated that fiber micronaire and length were positively correlated with temperature during the boll formation period in field experiments. Lokhande and Reddy's [9] growth chamber experiments showed that increased temperature produced a quadratic increase in fiber micronaire and uniformity up to 26.0 • C, but decreased in both variables at higher temperatures. Fiber strength increased linearly with temperature, while fiber length responded similarly to micronaire and uniformity, with length increasing as temperatures rose in the 18.0-22.0 • C range, and decreasing above 22.0 • C. In these experiments micronaire was found to be the most responsive to temperature, with cool temperatures during the latter stages of boll development associated with values in the low-discount range (<3.5).…”
Section: Introductionmentioning
confidence: 98%
“…Previously, different planting dates and shading treatments were established to explore the effects of temperature and light on cotton growth (Zhao et al 2012;Lv et al 2013;Lokhande and Reddy 2014;Liu et al 2015a, b). Researchers had analyzed the effect of cool temperature due to late planting on seedcotton biomass per boll (Bauer et al 1998;Dong et al 2006;Jalota et al 2008;Wrather et al 2008;Boquet and Clawson 2009;Zhao et al 2012).…”
Section: Introductionmentioning
confidence: 99%