In my experiments with peanut and soybean, there are differences in leaf chlorophyl content between lines that are tolerance and sensitive to dehydration stress. There are gradual changes in leaf color from dark green to yellowish green among tolerance to sensitive lines. Different in leaf chlorophyl content should have different leaf reflectance, therefore, it should be possible to differentiate such different responses against dehydration stress. The question remain, how to catch such differences in an efficient and effective way. Good luck...

I am not familiar with the method, but I have already implemented the Chl a fluorescence in the assessment of the impact of drought (and other stresses) on plants. I think leaf reflectance may provide some data not only about Chl content, but also about morphological and anatomical alterations. Does the vendor provide any information about this?

The Water Index (WI) is the ratio between the spectral reflectance at 970 nm (a water absorption band) and the spectral reflectance at 900 (reference band) has been proposed as an useful indicator of plant water content, especially at the canopy level. For more info, see:

PEÑUELAS J., FILELLA I., SERRANO L., BIEL C., SAVE R. 1993. The reflectance at the 950-970 nm region as an indicator of plant water status. International Journal of Remote Sensing 14(10): 1887-1905.

PEÑUELAS J., PIÑOL J., OGAYA R., FILELLA I. 1997. Estimation of plant water content by the reflectance Water Index WI (R900/R970). International Journal of Remote Sensing 18(13): 2869-2875.

The ratio WI/NDVI (NDVI: Normalized Difference Vegetation Index) has been proposed as more closely correlated with leaf water content. See:

PEÑUELAS J., INOUE Y. 1999. Reflectance indices indicative of changes in water and pigment contents of peanut and wheat leaves. Photosynthetica 36(3): 355-360.

Hope this helps. Best.

I was just seeing publication of my senior published in Phytochemistry (Engineering drought tolerant tomato plants over-expressing BcZAT12 gene encoding a C2H2 zinc finger transcription factor- Avinash Chandra Rai, Major Singh, Kavita Shah)...You can see on page number 2 they found relationship with drought.

Sorry if not correlating with your question.

One of the most important challenges of the future is to develop screening methods to identify salt-tolerant or drought-tolerant genotypes in the glasshouse and field. One method is to use spectral reflectance properties of leaves that indicate photosynthetic efficiency.

I have used a Hansatech chlorophyll fluorescence instrument in the field to track changes during the onset of mid-day water stress and it does that very well. However, it is a big next step to try to use that for screening. You could use it to find individuals that react differently but you have to ask what aspect of stress tolerance are you interested in. Are you interested in the reactions to short-term stress at the individual leaf level or the reaction of the crop yield? Data from individual leaves will not tell you how the whole plant will respond over long time periods.

I'm phenotyping for QTL mapping. I would like to find tools to cover the main plant strategies/features to endure/tolerate (to) drought. Some features that would be good to discriminate drought tolerance. I'm thinking in Electrolyte leakage for Membrane stability; detached leaf desiccation for cuticular transpiration, biomass difference between drought and control treatment . root:shoot ratio, and others ... I'm researching Theobroma cacao (cocoa).

I would strongly recommend the electrolyte leakage parameter. It is relatively easy to be obtained, and reliable. I have implemented it in my studies on various stresses (see some papers attached to my profile). FW/DW is easy and reliable as well. Maybe Chl content measured as so-callled greening index will also discriminate some relationships with the other features. For phenotyping, the combination of various parameters can provide good results.

In my experiment, in last season, I got 355 mm rainfall only for rice drought screening. I noticed that some of the mapping lines stayed green upto harvest but it doesn't given good yield, some of the lines showed the same greenish leaf texture and has given good yield. In this situation, how could we conclude that chlorophyll influences.

Drought is a complex, multiphase stress. So the best idea is looking for several indicators. Of course, finald yield, as it is what is intended, would be an unavoidable indicator. But if you want to understand the reasons for a better performance,

So, answering your first question, yes, leaf reflectance could be an indicator. First of all because it is quick, and with one pass you can get several indices: not only WI, but also green indices (SR, NDVI), and others more directly related with photosynthetical performance (PRI), chlorophyll degradation state (NPQI) or with carotenoid levels (related with photoprotection: SIPI, NPCI). On the bad side, these indices are not always sensitive enough or not easyly related with a specific process, same like yield, but with the possibility to detect early responses, as these are nondestructive measures.

As drought affects, of course, water relation, I would check stomatal conductance: this can be done with very complex systems that will give you plenty of information also on all photosynthetic paramenters, or with simple and cheap porometers that will just measure stomatal conductance, but in a very quick way allowing for much more measurements.

Chlorophyll fluorescence, that has appeared here ( I thik sometimes confused with leaf reflectance), will also give you information of the status of photosynthetic apparatus, also primarily affected by drought, although it is not clear if directly affected or indirectly through CO2 shortatge after stomatal conductance reduction resulting in photodamage and oxidative stress (which means that any index of oxidative stress would also help).

The problem with any of those measurements, such as with chlorophyll content as commented by Muthukumar Chelliah, is that they will only reflect a small number of precesses implied in drought, and for most of them will only be indicative for a more or less short period of time. For instace, one of several explanations for what Muthukumar observed is that some of the lines presented a tolerant behavior with respect to drought (they kept, as much as possible, everything working: stomata not so close, phostosynthesis, chlorophyll content... resulting in an still high water use), others would try to avoid drought stress (reduced stomatal conductance, photosynthesis, but with high water savings witing for better times at the cost of no growth) , and other might try to escape drought (by advancing life cycle, producing early seeds and entering in dormancy or dying if annuals like rice). These are strategies to cope with drought, that usually are formed by pieces (processes) working together as a result of natural selection. If you compare species living in drought-prone environments, you can see several of these strategies coexisting, because which is the best strategy depends on a number of parameters such as drought intesity, drought duration, moment of appeareance of drought, presence or absence of intermitent rains, even if they are rare and small, etc., and these parameters are naturally variable from year to year, so what is best one year can be worst the next, resulting in that coexistence. Hence, you can prepare several beatiful experiments and, depending on how you administer growth, you will favor one or another strategy, thus seeing different indices go up or down.

You may put boundaries to that by administering drought imitating several realistic scenarios, and produce results applicable to a specific region (or, more usually, to a specific region in specific years, e.g. the most frequent situation). Then, your QTLs would serve to identify lines with the succesful type of behaviour for that specific scenario, and you would have detected that success either directly per yield or by searching the literature to see which are the most indicative indices in that particular scenario.

Finally, I explained the case for natural populations, were natural selection continually keep the individuals most fit to any particular strategy end eliminates (well, makes less probable its perpetuation) those deviating from it. But in the cases you propose, were natural varibility is preserved or even encouraged, you can produce a similar situation from a single species, with some phenotypic combinations more prone to tolerate drought and ohters more prone to avoide it, and others advancing development in a line of escaping, even if all of them come from a single species that, in general and compared to others, is mostly tolerant, for instance.

So, I hope this looooong contribution helps you to situate your question and find the answer from between all other comments.

Well I am working on IR thermo imaging system. In addition to this I suggest you to do SC, and RWC to exmine the drought stress. Further you can also be used FvlFm ratio as indicator of plant stress in a particular enviornment. I suppose IR thermo imaging is the best non-disttructive method to test the water status in plant in alrge scale.

I agree with Alan Davison and Julia, each data paints some part of the picture, but the whole scenario is never seen. its better to use maximum possible traits with few treatments in precise possible uniform conditions. i have studied wheat with PEG simulated drought stress at seedling stage, coupled with proline content at flowering stage, root length etc, correlation was not found in all cases for all accessions studied. details by Xavier need attention as well.

I have seen several comments presented by my dear researchers. What I think they are presenting their own ideas related to their plan of work . Response of plant against drought is rather complex you can not assess the drought tolerance by doing on one or two physiological or biochemical parameters. Some plant responded drought avoidance rather than tolerance. You should plan your work on the basis of your hypothesis. Leaf reflectance, chlorophyll florescence needs control environment to examine otherwise environmental factors like light, humidity and temperature would affect your observation. Physiological assessments are not very easy task