Hydraulic Conductance and Stomatal Sensitivity to Changes of Leaf Water Status in Six Deciduous Tree Species

The light sensitivity of the shoot hydraulic conductance in five temperate deciduous tree species was measured using two methods to clarify the role of light sensitivity and the suitability of the methods used to study it. The light sensitivity measured using a method that included an interruption of ≤10 min in shoot light acclimation did not differ from that measured using a method with continuous illumination. The ‘noncontinuous light’ methods are suitable for measuring hydraulic conductance and its light response. Light sensitivity correlated with other leaf water traits as follows: positively with the ion-mediated increase in xylem hydraulic conductance; a relative decrease in the hydraulic conductance of the laminae in response to HgCl2; a relative change in stomatal conductance in response to changes in PAR intensity or atmospheric CO2 concentration, or to a decrease in air humidity or leaf water potential; and with instantaneous water use efficiency. The traits correlated negatively with shoot hydraulic conductance, stomatal conductance and relative increases in stomatal conductance in response to increases in leaf water potential. We suggest that high light sensitivity should be considered as one of the characteristics of conservative water use in trees. Low blue light increased shoot hydraulic conductance to a similar extent to moderate white light and twice as much as moderate red light. Blue light perception is important in the light sensitivity mechanism.

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Employment of artificial neural networks for non-invasive estimation of leaf water status using color features: a case study in Spathiphyllum wallisii

Acta Physiologiae Plantarum ◽

10.1007/s11738-021-03244-y ◽

2021 ◽

Vol 43 (5) ◽

Author(s):

Amin Taheri-Garavand ◽

Abdolhossein Rezaei Nejad ◽

Dimitrios Fanourakis ◽

Soodabeh Fatahi ◽

Masoumeh Ahmadi Majd

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Water Status ◽

Leaf Water ◽

Leaf Water Status ◽

Non Invasive ◽

Color Features ◽

Artificial Neural

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Visual estimation of plant water status in cereals

The Journal of Agricultural Science ◽

10.1017/s0021859600060524 ◽

1979 ◽

Vol 92 (1) ◽

pp. 83-89 ◽

Cited By ~ 13

Author(s):

H. G. Jones

Keyword(s):

Spring Wheat ◽

Water Status ◽

Plant Morphology ◽

Leaf Water ◽

Plant Water Status ◽

Plant Water ◽

Visual Estimation ◽

Leaf Water Status ◽

Visual Scoring ◽

Breeding Programmes

SummaryThe potential offered for plant breeding programmes by visual scoring techniques for plant water status was investigated in rice and spring wheat. It was found that differing plant morphology could seriously bias visual estimates of leaf water potential, particularly in spring wheat. In spite of this problem, it was found that at least for rice, this type of approach may have potential in future breeding programmes where an estimate of leaf water status is required, such as those for drought tolerance, so long as a high intensity of selection is not necessary.

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