Temperature-driven growth shape simulation and model of greenhouse melon leaves

Abstract

a b s t r a c tMathematical models based on dynamic growth process of greenhouse melon leaves were built. Two experiments, involving different years, organic fertilizer rates and cultivar types in melon, were carried out for data acquisition. In each experiment, time-course observations of leaf morphological properties (leaf length and leaf width) on different leaf positions of melon were obtained. The results showed that the logistic mathematical models were suitable to simulate the dynamic elongation of leaf length and leaf width with the dynamic changes of ∑ TU (accumulated thermal units), logarithmic equation and quadratic curve equation fit the dynamic changes of the final leaf length and the maximum leaf width with different leaf positions well, and the leaf area dynamic changes were simulated by binary regression equation. In addition, the effects of nitrogen conditions on leaf growth were quantified by the effectiveness values of nitrogen concentration in leaves. The model was validated with independent field experiment data, and the results showed that the mean RMSE (root mean square error) of leaf length, leaf width and leaf area under different ∑ TU was 0.54 cm, 1.19 cm, 0.44 cm 2 , respectively.

Modelling sustainable salt water management under deficit irrigation conditions for melon in Spain and Brazil

“…Two parameters must be determined for the GDD calculation: T L (lower threshold temperature for development, in °C) and T U (upper threshold temperature at which the rate of development begins to decrease, in °C). T L may vary from 10 to 13 °C and T U from 34 to 45 °C . The combination of T L and T U values with the lowest coefficient of variation for the field data was selected.…”

“…The T L and T U values that, overall, exhibited the least statistical variability were 10 and 35 ∘ C respectively, which are similar to those proposed by other authors. 12,35 These gave acceptably low coefficients of variability of 6.1% (PiSa) and 9.6% (YeMe) over the entire growth period, equivalent to 7 and 6 days respectively ( Table 2).…”

“…34 Two parameters must be determined for the GDD calculation: T L (lower threshold temperature for development, in ∘ C) and T U (upper threshold temperature at which the rate of development begins to decrease, in ∘ C). T L may vary from 10 to 13 ∘ C and T U from 34 to 45 ∘ C. 12,35 The combination of T L and T U values with the lowest coefficient of variation for the field data was selected. Thus the length of K c and K y stages was determined through the phenological stage monitoring by the irrigation advisory service of Castilla-La Mancha and several authors (Table 1).…”

“…Although some authors have simulated different aspects of melon cropping, the use of models for simulating the development of this crop under different scenarios of water availability is relatively rare. The MOPECO model simulates the effect of saline water on yield and calculates the optimized regulated deficit irrigation (ORDI) strategy that achieves the maximum yield for a certain water deficit target .…”

Why leaves curl with water content varied: Mechanics can illustrate biology

“…In addition, the shapes of plant leaves can be directly simulated via some refined mathematical algorithms. 10 However, a more common phenomenon is that a plant leaf often curls when its water content has changed. Under very strong sunlight, the leaves have to curl to avoid the loss of more water; and vice versa, the leaves can spread when ample water is sucked.…”