Abstract. Water status plays an important role for fruit quality and quantity in tomato (Solanum lycopersicum L.).
However, determination of the plant water status via measurements of sap flow (FH2O) or stem diameter (D) cannot be done
unambiguously since these variables are influenced by other effectors than the water status. We performed a semi-seasonal
and a diurnal analysis of the simultaneous response of FH2O and D to environmental conditions, which allowed us to
distinguish different influences on DD such as plant age, fruit load and water status and to reveal close diurnal relationships
between FH2O and DD. In addition, an analysis of the diurnal mechanistic link between both variables was done by applying
a slightly modified version of a water flow and storage model for trees. Tomato stems, in contrast with trees, seemed to
maintain growth while transpiring because a large difference between turgor pressure (Yp) and the yield threshold (G) was
maintained. Finally, the simultaneous response of D and FH2O on irrigation events showed a possibility to detect water
shortages.
Introduction
Because of its economic importance, tomato (Solanum
lycopersicum L.) is widely studied, in particular, its traits for
improving fruit organoleptic and nutritional quality (Dorais et al.
2001). Many reports (Mitchell et al. 1991; Cuartero and
Fernandez-Munoz 1999; Veit-Köhler et al. 1999; Plaut et al.
2004) show that salinity and water deficit influence the tomato
fruit soluble solids content and thus quality. Therefore, plant
water status appears to influence fruit quality to a large extent.
However, because previous research has reported an inverse
relationship between fruit soluble solids content and fresh
yield, a compromise must be found between reduced fruit
production and enhanced fruit quality. This balance is as
difficult to achieve as it is to maintain because the growth and
the development of a fruit is part of the integrated processes in the
whole plant in which water economy and intra-plant competition
mechanisms play a substantial role. Therefore, an understanding
of the plant’s water status and the mechanisms between water
status and growth is a topic of great interest.
Currently, several methods are available for automated
monitoring of plant water status. First, measurements of stem
sap flow (FH2O) can give information on the plant’s water status
since high transpiration rates (and thus high FH2O) lead to more
negative tensions inside the stem xylem. Vermeulen et al. (2007)
described the possibility of using stem sap flow measurements as
an indicator of water deficit. Since FH2O is a direct response of the
plant to the environmental conditions such as the atmospheric
water demand andthe substrate water supply,its measurement has
potential in the perspective of estimating plant water status (Jones
2004). However, data on FH2O cannot be unequivocally
interpreted because FH2O results from both atmospheric
conditions and substrate water availability. As such, low
midday sap flow rates might result from low water availability
(drought stress) as well as from low water demand by the
atmosphere (low vapour pressure deficit, VPD) (De Swaef
et al. 2009).
A second automated method consists of measuring the stem
diameter variations (DD). These variations result from the radial
water transport between xylem and the surrounding storage
tissues. In trees, the interaction mechanism between DD and
water status has been studied extensively (e.g. Zweifel et al.
1999; Génard et al. 2001; Steppe et al. 2006), while the
application in tomato is rather limited (Gallardo et al. 2006;
Vermeulen et al. 2008). In trees, DD does not provide
unambiguous information about plant water status since other
factors such as plant age and fruit load affect DD (Intrigliolo and
Castel 2006; Intrigliolo and Castel 2007). The underlying
mechanisms of these influences are probably similar for
herbaceous vascular plants such as tomato. However, the
anatomical and dimensional differences between trees and
herbaceous plants may lead to a different response of DD in
tomato compared with trees. In addition, tomato plants have a
rather constant fruit load throughout a large part of
the growing season because fruits are set and picked
continuously. In contrast, tree fruits generally set, grow and
ripen simultaneously.
Both FH2O and DD measurements have important information
with respect to plant water status. However, an unambiguous
determination and interpretation of the plant water status could
only be achieved by simultaneously considering both variables
and mechanistic modelling. Based on measurements of FH2O
and DD, the mathematical flow and storage model of Steppe
et al. (2006) enabled simulation of physiological variables in
young trees which are not easy to measure such as stem water
potential (Y) and stem turgor pressure (Yp). Furthermore,
simulation of Yp revealed the relationship between FH2O and
DD since it was a main driving variable for irreversible cell
(and tissue) expansion. The equation of irreversible relative
cell expansion by Lockhart (1965) could be applied on tissue,
and as such, directly links stem water status and content to radial
stem growth:
Relative irreversible cell expansion ¼ f ðYp GÞ ð1Þ
where f is cell wall extensibility (MPa–1 h–1
) and G is the
threshold pressure at which wall yielding occurs (MPa).
Ortega (1985) complemented this model of irreversible
(i.e. plastic) cell expansion with a term for reversible (i.e.
elastic) cell dimensional changes. Steppe et al. (2006)
implemented these principles in a model for young trees to
directly link FH2O and DD via the simulation of Yp. This
approach allows making a distinction between reversible and
irreversible cell expansion.
This study focuses on the discrimination of three different
effectors (plant age, fruit load and plant water status) on DD in
tomato by considering the simultaneous response of FH2O and D
to environmental conditions on a semi-seasonal and a diurnal
scale. It also reports on the analysis of the diurnal mechanistic link
between both variables and the distinction between irreversible
growth and reversible DD by applying the slightly modified
model of Steppe et al. (2006).