Quantification of Temperature Effects on Stem Elongation in Poinsettia

Berghage, Robert; Heins, Royal D.

doi:10.21273/jashs.116.1.14

Cited by 48 publications

(35 citation statements)

References 7 publications

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“…Clarke, Xanthium strumarium L., Lycopersicon esculentum L., Z. mays, Salvia splendens F., Impatiens wallerana Hook, Nephrolepsis exaltata L., Fuchsia × hybrida Vilm. , Dendranthema × grandiflora Tzvelev, , Campanula isophylla Moretti (Moe and Heins, 1990;Moe et al, 1991), Euphorbia pulcherrima Klotz (Berghage and Heins, 1991), and L. longiflorum was best described by DIF, and increased as DIF increased. Likewise, dahlia was responsive to DIF, with primary shoot length linearly and positively related to DIF, except at and perhaps below NT of 10C (Fig.…”

Section: Discussionmentioning

confidence: 97%

Modeling Temperature and Photoperiod Effects on Growth and Development of Dahlia

Brondum¹,

Heins²

1993

jashs

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Effects of temperature and photoperiod on growth rates and morphological development of Dahlia pinnata Cav. 'Royal Dahlietta Yellow' were determined by growing plants under 45 combinations of day and night temperatures (DT and NT, respectively, and photoperiod. DT and NT ranged from 10 to 30C and photoperiods from 10 to 24 hours·day -1 . Photoperiod influenced vegetative development more than reproductive development as plants flowered in all photoperiods. Lateral shoot count and length decreased and tuberous root weight increased as photoperiod decreased from 16 to 10 hours. Temperature interacted with photoperiod to greatly increase tuberous root formation as temperature decreased from 25 to 15C. Increasing temperature from 20 to 30C increased the number of nodes below the first flower. Flower count and diameter decreased as average daily temperature increased. Nonlinear regression analysis was used to estimate the maximum rate and the minimum, optimum, and maximum temperatures for leaf-pair unfolding rate (0.29 leaf pair/day, 5.5, 24.6, and 34.9C, respectively), flower development rate from pinch to visible bud (0.07 flower/day, 2.4, 22.4, and 31.1C, respectively), and flower development rate from visible bud to flower (0.054 flowers/day, 5.2, 24.4, and 31.1C, respectively). The results collectively indicate a relatively narrow set of conditions for optimal 'Royal Dahlietta Yellow' dahlia flowering, with optimal defined as fast-developing plants with many large flower buds and satisfactory plant height. These conditions were a 12-to 14-hour photoperiod and ≈ ≈ 20C.

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Section: Discussionmentioning

confidence: 97%

Modeling Temperature and Photoperiod Effects on Growth and Development of Dahlia

Brondum¹,

Heins²

1993

jashs

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“…; Niu et al, 2000), and poinsettia (Euphorbia pulcherrima Willd. ex Klotz; Berghage and Heins, 1991). For example, Erwin et al (1989) reported that plant height of Easter lily increased by 129% as DIF increased from -16 to +16°C.…”

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confidence: 99%

The Influence of Day and Night Temperature Fluctuations on Growth and Flowering of Annual Bedding Plants and Greenhouse Heating Cost Predictions

Blanchard¹,

Runkle²

2011

horts

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Volatile energy costs and lower profit margins have motivated many greenhouse growers in temperate climates to improve the energy efficiency of crop production. We performed experiments with dahlia (Dahlia ×hybrida Cav. ‘Figaro Mix’), French marigold (Tagetes patula L. ‘Janie Flame’), and zinnia (Zinnia elegans Jacq. ‘Magellan Pink’) to quantify the effects of constant and fluctuating temperatures on growth and flowering during the finish stage. Plants were grown in glass-glazed greenhouses with a day/night (16 h/8 h) temperature of 20/14, 18/18, 16/22 (means of 18 °C), 24/18, 22/22, or 20/26 °C (means of 22 °C) with a 16-h photoperiod and under a photosynthetic daily light integral of 11 to 19 mol·m−2·d−1. Flowering times of dahlia, French marigold, and zinnia (Year 2 only) were similar among treatments with the same mean daily air temperature (MDT). All species grown at 20/14 °C were 10% to 41% taller than those grown at 16/22 °C. Crop timing data and computer software that estimates energy consumption for heating (Virtual Grower) were then used to estimate energy consumption for greenhouse heating on a per-crop basis. Energy costs to produce these crops in Charlotte, NC, Grand Rapids, MI, and Minneapolis, MN, for a finish date of 15 Apr. or 15 May and grown at the same MDT were estimated to be 3% to 42% lower at a +6 °C day/night temperature difference (DIF) compared with a 0 °C DIF and 2% to 90% higher at a −6 °C DIF versus a 0 °C DIF. This information could be used by greenhouse growers to reduce energy inputs for heating on a per-crop basis.

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“…Even if some parameters to some extent are given a biological interpretation (e.g. Berghage and Heins, 1991;Fisher, Heins and Lieth, 1996a), the danger of over-or underfitting to data is obvious, especially in view of the complexity of biological processes. With a softer model that adapts to data, and with a proper model selection procedure, we can choose the optimal model complexity for prediction given the available data.…”

Section: X2 Resultsmentioning

confidence: 99%

Predicting Plant Height of Greenhouse Grown Crops with a Polynomial Growth Rate Model

Snipen¹

1998

Biom. J.

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A prediction model for the growth of plant height is developed, using polynomials in time to describe the growth rate. The growth rate is affected by forcing factors through the polynomial coefficients. A random slope model is used to describe the difference in growth rate for plants grown under similar conditions. Maximum likelihood estimates of model parameters are obtained and a selection procedure is employed to estimate the model complexity using Schwarz' bayesian criterion as a measure of predictive power. The procedure is applied to data sets for greenhouse grown poinsettias. The use of polynomials to describe the time effects on the growth rate makes the strategy versatile, and it can be used to predict the growth of many different crops. Many forcing factors of different types can be incorporated simultaneously in the model. Confidence of predictions are also quantifies, which is important when the results are applied in a practical situation, e.g. in climate control of commercial greenhouses.

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Quantification of Temperature Effects on Stem Elongation in Poinsettia

Cited by 48 publications

References 7 publications

Modeling Temperature and Photoperiod Effects on Growth and Development of Dahlia

Modeling Temperature and Photoperiod Effects on Growth and Development of Dahlia

The Influence of Day and Night Temperature Fluctuations on Growth and Flowering of Annual Bedding Plants and Greenhouse Heating Cost Predictions

Predicting Plant Height of Greenhouse Grown Crops with a Polynomial Growth Rate Model

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