|
Advantages
|
Disadvantages
|
| I. Soil water measurement |
|
|
| (a) Soil water potential (tensiometers, psychrometers, etc.) |
Easy to apply in practice; can be quite precise; at least water content measures indicate ‘how much’ water to apply; many commercial systems available; some sensors (especially capacitance and time domain sensors) readily automated |
Soil heterogeneity requires many sensors (often expensive) or extensive monitoring programme (e.g. neutron probe); selecting position that is representative of the root-zone is difficult; sensors do not generally measure water status at root surface (which depends on evaporative demand) |
| (b) Soil water content (gravimetric; capacitance/TDR; neutron probe) |
|
|
| II. Soil water balance calculations |
|
|
| (Require estimate of evaporation and rainfall) |
Easy to apply in principle; indicate ‘how much’ water to apply |
Not as accurate as direct measurement; need accurate local estimates of precipitation/runoff; evapotranspiration estimates require good estimates of crop coefficients (which depend on crop development, rooting depth, etc.); errors are cumulative, so regular recalibration needed |
| III. Plant ‘stress’ sensing |
|
|
| (Includes both water status measurement and plant response measurement) |
Measures the plant stress response directly; integrates environmental effects; potentially very sensitive |
In general, does not indicate ‘how much’ water to apply; calibration required to determine ‘control thresholds’; still largely at research/development stage and little used yet for routine agronomy (except for thermal sensing in some situations) |
| (a) Tissue water status |
It has often been argued that leaf water status is the most appropriate measure for many physiological processes (e.g. photosynthesis), but this argument is generally erroneous (as it ignores root–shoot signalling) |
All measures are subject to homeostatic regulation (especially leaf water status), therefore not sensitive (isohydric plants); sensitive to environmental conditions which can lead to short-term fluctuations greater than treatment differences |
| (i) Visible wilting |
Easy to detect |
Not precise; yield reduction often occurs before visible symptoms; hard to automate |
(ii) Pressure chamber ( ) |
Widely accepted reference technique; most useful if estimating stem water potential (SWP), using either bagged leaves or suckers |
Slow and labour intensive (therefore expensive, especially for predawn measurements); unsuitable for automation |
| (iii) Psychrometer () |
Valuable, thermodynamically based measure of water status; can be automated |
Requires sophisticated equipment and high level of technical skill, yet still unreliable in the long term |
(iv) Tissue water content (RWC, leaf thickness [ - or ß-ray thickness sensors], fruit or stem diameter) |
Changes in tissue water content are easier to measure and automate than water potential measurements; RWC more directly related to physiological function than is total water potential in many cases; commercial micromorphometric sensors available |
Instrumentation generally complex or expensive, so difficult to get adequate replication; water content measures (and diameter changes) subject to same problems as other water status measures; leaf thickness sensitivity limited by lateral shrinkage |
| (v) Pressure probe |
Can measure the pressure component of water potential which is the driving force for xylem flow and much cell function (e.g. growth) |
Only suitable for experimental or laboratory systems |
| (vi) Xylem cavitation |
Can be sensitive to increasing water stress |
Cavitation frequency depends on stress prehistory; cavitation–water status curve shows hysteresis, with most cavitations occurring during drying, so cannot indicate successful rehydration |
| (b) Physiological responses |
Potentially more sensitive than measures of tissue (especially leaf) water status |
Often require sophisticated or complex equipment; require calibration to determine ‘control thresholds’ |
| (i) Stomatal conductance |
Generally a very sensitive response, except in some anisohydric species |
Large leaf-to-leaf variation requires much replication for reliable data |
| – Porometer |
Accurate: the benchmark for research studies |
Labour intensive so not suitable for commercial application; not readily automated (though some attempts have been made) |
| – Thermal sensing |
Can be used remotely; capable of scaling up to large areas of crop (especially with imaging); imaging effectively averages many leaves; simple thermometers cheap and portable; well suited for monitoring purposes |
Canopy temperature is affected by environmental conditions as well as by stomatal aperture, so needs calibration (e.g. using wet and dry reference surfaces) |
| – Sap-flow sensors |
Sensitive |
Only indirectly estimates changes in conductance, as flow is also very dependent on atmospheric conditions; requires complex instrumentation and technical expertise; needs calibration for each tree and for definition of irrigation control thresholds |
(ii) Growth rate
|
Probably the most sensitive indicator of water deficit stress
|
Instrumentation delicate and generally expensive
|
Answers to all your Biology Questions
