In recent years, fruit quality has become an increasingly important aspect of
fruit production. For example, in Europe, the new market organization enjoins
farmers to form producer organizations whose goal is to improve fruit quality.
Research efforts directed toward understanding the effects of climate and management techniques on fruit quality are needed, and mathematical models are
useful frameworks for these research efforts (Lescourret and Génard 2005). Fruit
quality, even when reduced to organoleptic qualities (such as sweetness or acidity)
that meet consumer’s demand, is a multicriterion concept. Each quality trait is the
result of a complex chain of biological processes that depend on environmental
conditions. These processes are interrelated (sugar metabolism depends on the
carbon fluxes) and their effects on quality traits may be opposite (enhancing water
fluxes into fruit increases sugar concentration; Génard and Lescourret 2004).
Clearly, a useful fruit quality model must take into account several quality traits,
the underlying processes, and their interactions.
However, following the researches of C.T. de Wit (van Ittersum and Donatelli
2003), most process-based fruit models have focused on carbon relationships
leading to predictions of fruit growth in dry mass. Such photosynthesis-driven
models have been developed for apples (Baumgaertner et al. 1984), grapes
(Gutierrez et al. 1985), kiwifruit (Buwalda 1991), olives (Abdel-Razik 1989),
peaches (Grossman and DeJong 1994), and tomatoes (Heuvelink and Bertin 1994).
Some models have dealt with nitrogen content, representing nitrogen and carbon
dynamics on a similar conceptual basis. Researchers have modeled water accumulation in fruit, considering water uptake and transpiration per unit fruit area as
constant or variable (Génard and Huguet 1996). In a more mechanistic work
applied to tomatoes, the difference between water potentials in the stem and the
fruit was assumed to be the driving force of water import rate (Bussières 1994).
Another tomato water model focused on the role of pedicel resistance and calyx
transpiration (Bussières 2002). A few models of fruit metabolism describing synthesis and degradation processes have been designed for sugar (Génard and Souty
1996) and citric acid accumulation (Lobit et al. 2003 ). However, few models
consider several processes together. Nevertheless, the virtual peach fruit model
proposed by Lescourret and Génard (2005) is the first model to integrate in systemic
framework knowledge of many interrelated processes, resulting in a complex
quality profile and emergent properties that are typical of complex systems. The
model offers various possibilities as a research tool, both for performing theoretical
experiments and for helping to understand experimental results when studying the
effects of technical scenarios for which there is no literature. Lescourret and Génard
(2005) examined relationships between quality traits, physiological variables, and
between both and found patterns that did not derive just from the aggregation of
modeled basic functions. Moreover, the virtual peach fruit model may help in
assessing the relative importance of processes for a given complex function or trait.
Virtual plants are being viewed as a novel means to simulate the genetic variability of plant responses to environmental conditions (Tardieu 2003). Combining
either gene regulatory networks or quantitative trait loci (QTL) and models
(Reymond et al. 2003) are two possible avenues, assuming that a genotype is
70
M. A. Vázquez-Cruz et al.
fruit production. For example, in Europe, the new market organization enjoins
farmers to form producer organizations whose goal is to improve fruit quality.
Research efforts directed toward understanding the effects of climate and management techniques on fruit quality are needed, and mathematical models are
useful frameworks for these research efforts (Lescourret and Génard 2005). Fruit
quality, even when reduced to organoleptic qualities (such as sweetness or acidity)
that meet consumer’s demand, is a multicriterion concept. Each quality trait is the
result of a complex chain of biological processes that depend on environmental
conditions. These processes are interrelated (sugar metabolism depends on the
carbon fluxes) and their effects on quality traits may be opposite (enhancing water
fluxes into fruit increases sugar concentration; Génard and Lescourret 2004).
Clearly, a useful fruit quality model must take into account several quality traits,
the underlying processes, and their interactions.
However, following the researches of C.T. de Wit (van Ittersum and Donatelli
2003), most process-based fruit models have focused on carbon relationships
leading to predictions of fruit growth in dry mass. Such photosynthesis-driven
models have been developed for apples (Baumgaertner et al. 1984), grapes
(Gutierrez et al. 1985), kiwifruit (Buwalda 1991), olives (Abdel-Razik 1989),
peaches (Grossman and DeJong 1994), and tomatoes (Heuvelink and Bertin 1994).
Some models have dealt with nitrogen content, representing nitrogen and carbon
dynamics on a similar conceptual basis. Researchers have modeled water accumulation in fruit, considering water uptake and transpiration per unit fruit area as
constant or variable (Génard and Huguet 1996). In a more mechanistic work
applied to tomatoes, the difference between water potentials in the stem and the
fruit was assumed to be the driving force of water import rate (Bussières 1994).
Another tomato water model focused on the role of pedicel resistance and calyx
transpiration (Bussières 2002). A few models of fruit metabolism describing synthesis and degradation processes have been designed for sugar (Génard and Souty
1996) and citric acid accumulation (Lobit et al. 2003 ). However, few models
consider several processes together. Nevertheless, the virtual peach fruit model
proposed by Lescourret and Génard (2005) is the first model to integrate in systemic
framework knowledge of many interrelated processes, resulting in a complex
quality profile and emergent properties that are typical of complex systems. The
model offers various possibilities as a research tool, both for performing theoretical
experiments and for helping to understand experimental results when studying the
effects of technical scenarios for which there is no literature. Lescourret and Génard
(2005) examined relationships between quality traits, physiological variables, and
between both and found patterns that did not derive just from the aggregation of
modeled basic functions. Moreover, the virtual peach fruit model may help in
assessing the relative importance of processes for a given complex function or trait.
Virtual plants are being viewed as a novel means to simulate the genetic variability of plant responses to environmental conditions (Tardieu 2003). Combining
either gene regulatory networks or quantitative trait loci (QTL) and models
(Reymond et al. 2003) are two possible avenues, assuming that a genotype is
70
M. A. Vázquez-Cruz et al.