Production Practices and Quality Assessment of Food Crops. Vol. 1
Production Practices and Quality Assessment of Food Crops. Vol. 1
Production Practices and Quality Assessment of Food Crops. Vol. 1
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Modelling Fruit <strong>Quality</strong> 57<br />
fructose, respectively; ( ph is the proportion <strong>of</strong> sucrose in the phloem sugar pool,<br />
which results from plant metabolism; k 1(t), k 2(t), k 3(t) <strong>and</strong> k 4(t) represent the relative<br />
rates <strong>of</strong> sugar transformation for net sucrose transformation into glucose <strong>and</strong> fructose,<br />
net sorbitol transformation into glucose <strong>and</strong> fructose, <strong>and</strong> the synthesis <strong>of</strong> compounds<br />
other than sugars from glucose <strong>and</strong> fructose.<br />
These relative rates are calculated according to the following equations<br />
k2(t) = k2 k3(t) = k3 1<br />
k4(t) = k4 Wdry dW dry<br />
dt<br />
where k 1, 3 is a constant equal to 1 day –1 , k 1, 1, k 1, 2, k 2, k 3 <strong>and</strong> k 4 are parameters,<br />
<strong>and</strong> W dry is the dry mass <strong>of</strong> the fruit flesh.<br />
(dM ph/dt) <strong>and</strong> (dM re/dt) are the phloem <strong>and</strong> respiration flows <strong>of</strong> carbon into <strong>and</strong><br />
out <strong>of</strong> the fruit, respectively<br />
dM ph<br />
dt<br />
dMdry dMre = σfl + (3)<br />
dt dt<br />
where σ fl is the carbon content <strong>of</strong> flesh.<br />
Sugar concentrations are computed as<br />
Csu = 100Msu , Cso =<br />
σsuWfresh 100Mso , Cgl =<br />
σsoWfresh 100Mgl σglWfresh , C fr = 100M fr<br />
σ frW fresh<br />
where σ su, σ so, σ gl <strong>and</strong> σ fr are the carbon content <strong>of</strong> 1 g <strong>of</strong> sucrose, sorbitol, glucose<br />
<strong>and</strong> fructose, respectively. W fresh is the fresh mass <strong>of</strong> the flesh.<br />
The sweetness <strong>of</strong> each sugar is computed using its sweetness rating according<br />
to Kulp et al. (1991).<br />
Time-step in the model is one day. Daily mean temperature <strong>and</strong> daily dry <strong>and</strong><br />
fresh flesh masses are the inputs <strong>of</strong> SUGAR. Previous studies (Génard <strong>and</strong> Souty,<br />
1996; Génard <strong>and</strong> Huguet, 1999) have shown that the SUGAR model predicts the<br />
sugar content <strong>of</strong> peaches with a fairly good accuracy over a wide range <strong>of</strong> fruit<br />
growth rates.<br />
4.1.2.2. Seasonal variation <strong>of</strong> sugar concentrations <strong>and</strong> sweetness shown by SUGAR<br />
The simulations were performed during the main period <strong>of</strong> flesh development (two<br />
months before maturity for the peach cultivar ‘Suncrest’). Figure 3 presents a typical<br />
output <strong>of</strong> the model. Sucrose concentration presents a seasonal increase whereas<br />
sorbitol is always low, <strong>and</strong> glucose <strong>and</strong> fructose concentrations present almost no<br />
change during the season. Total sweetness increases during the season. The effect<br />
<strong>of</strong> an increase in assimilate supply, due to fruit thinning for example which increases<br />
leaf to fruit ratio, is mainly an increase in sucrose <strong>and</strong> sweetness.<br />
(2)<br />
, (4)