Science topic

Drought - Science topic

A drought is an extended period of months or years when a region notes a deficiency in its water supply whether surface or underground water.
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We conducted an experiment to test single and mixed effects of heat & drought stress on Canola.
Here is an overview:
We had 16 treatments (4*temperature, 2*drought, 2* stress timing) --> 16 tt
We had eight plants per treatment, which we assessed on the level of four branches (1, 2, 3, and rest) --> 16 tt * 4 branches.
We planted seeds in Petry dishes every dish had 1 g of seeds. We started to account for germinated seeds after 12 hours of planting and removing germinated seeds; we accounted for seeds after 12h, 14h,16h, 18h, 20h, 24h, 36 h,38h, and 40h. so we have a gap in data during the night
Unfortunately, we did not use the same total seeds number.
when we tried to apply the four-parameter hill function 
FourPHFfit(germ.counts = y, intervals = int, total.seeds = 50, tmax = 20, partial = FALSE)
we faced some problems
1. How can we add our data to this function and fit it to our four factors? In the R script, I just added x and y as:
x <- data_frame1$Hour
y <- data_frame1$AGP
2. How can we insert time replication?
3. And how can we insert total seeds as a column, not as an individual value?
I attached the data set and R script
Thank you in advance
Regards
Dima
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Andrew Paul McKenzie Pegman, that is completely true, but I think R is the most flexible program.
thank you for the tip :)
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In my country Nepal, variation in weather patterns and drought are the major climate related problems.
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Flood, Landslides, Soil Erosion, Drought, Delayed monsoon are some
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The decline in agricultural production and exports in many countries is pushing up food prices. The scale of food shortages will increase in many countries and the risk of a food crisis is growing. More and more data confirms that after the recent pandemic economic crisis 2020, the growing economic crisis caused by high inflation, the developing energy crisis in 2023, there will also be a food crisis in many parts of the world. In the current 2022, a number of factors have simultaneously emerged that could lead to a food crisis and hunger in many countries of the world. These include the following factors:
1. the war in Ukraine (production and exports of cereals and other agricultural crops from Russia and Ukraine have fallen significantly).
2. Record heat, drought, forest and crop field fires in many parts of the world (in India, record heat reaching 50 ct. C in the shade; drought throughout the western states of the USA; in central and eastern Africa the worst drought in 40 years).
3. Flooding of farmland in China in 2021 (30 million acres of farmland under water. Chinese authorities have announced that the 2022 crop yield could be the lowest in the context of the previous few decades).
4. postcovid broken chains of international logistics and supplies.
5. in 2020, the Lebanese capital Beirut suffered a gigantic explosion at the port that destroyed all infrastructure, including huge grain silos.
For these and other reasons, the number of people in the world at risk of hunger has increased by 80 per cent in the last five years, from 108 million to 183 million people.
After Vladimir Putin ordered 200,000 Russian troops into Ukraine, the global food situation went from poor to bad. Especially this negative trend is developing in poor countries, where economies are underdeveloped and income levels of citizens are also low.
Before the war, Ukraine was the 5th economy in terms of global wheat exports, 3rd in barley exports, 3rd in maize exports and 1st in oilseed exports (e.g. sunflower). In Ukraine, areas of fertile chernozem extend as far as Manzuria. Before the war, Ukraine produced 9 per cent of the world's wheat, and together with Russia, this is now 30 per cent. Ukraine generated 20 per cent of the world's maize exports. By contrast, Ukraine's exports of sunflower oil account for as much as 75 per cent of the global share. Food exports from Ukraine are also estimated at 1/8 of all calories sold globally. Most of these exports before the war, i.e. before 24 February 2022, were loaded onto ships in Odessa and Novorossiysk and transported to the Middle East and elsewhere in the world. The war has created serious problems for food production and export in Ukraine. The Russians have blockaded the Black Sea ports with their Black Sea fleet.
In view of the above, I address the following question to the honourable community of scientists and researchers:
How can the scale of the development of the food crisis be reduced?
What is your opinion on this topic?
Please reply,
I invite you all to discuss,
Thank you very much,
Regards,
Dariusz Prokopowicz
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@ Dariusz, there are many ways to reduce the food crisis. The most important are: to reduce the food waste, improve trade policies, improve existing infrastructure programme, promote diversification, work to defeat the climate change and close the yield gap.
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What do you think are the key factors that could trigger a food crisis in your country in the next quarters and/or years?
Due to many different factors, a food crisis can develop in many countries. The international supply and supply logistics chains that were interrupted during the SARS-CoV-2 (Covid-19) coronavirus pandemic have not been fully rebuilt. Rising fuel prices are driving up the cost of transporting food products to shops. The decline in fertiliser production is also driving up the cost of producing crops. In addition, the war in Ukraine has resulted in a decline in cereal supplies to many countries. The lack of electricity has caused a decline in the production of nitrogenous fertilisers. This then caused a decrease in the production of CO2, which benefits producers of many types of food products. Many food product factories are raising the prices of their products due to increases in raw material, energy and fuel prices. Many production facilities are reducing the scale of production. There may be job cuts. Consumption is falling due to high inflation. If a downturn in the economy occurs in the next quarters, many companies may go out of business and unemployment will rise. In addition, periods of increasingly severe drought, more and more hot days and less and less rain and more and more frequent fires in many parts of the world are causing a significant drop in crop production in agriculture. On the other hand, further food crises may arise in the future in the long term, which will be the result of a global climate crisis developing on a multi-year scale.
In view of the above, I address the following question to the esteemed community of researchers and scientists:
What do you think are the key factors that could trigger a food crisis in your country in the next quarters and/or years?
What should be done to reduce the scale of development of the food crisis?
What is your opinion on the subject?
What do you think about this topic?
Please reply,
I invite you all to discuss,
Thank you very much,
Regards,
Dariusz Prokopowicz
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Dear Dariusz
I dare to assert that all epigenetic factors may initiate a food crisis (Social interaction, war, disease, financial, created deficiencies etc.) More important is to have strategies to contain an emerging problem so that it will not spread globally. To avoid that we formed the UNO. In the post war era we also created the global market. Unfortunately, this is an economic concept that is based on competition and the winner in competition are those with with power. Now we are witnessing the global economy is dividing and consolidating in blocks. Unfortunately, the blocksformation is permananentl restructured and driven by a few war mongers. For them power is more important than food for the global citizen.
Many people are afraid and believe that we have too many people on the globe. For them war is the preferred mode to assure access to food. They cant imagine that with innovation and new circulatory technologies it is possible to multiply food supply. Food shortage is always a distribution problem. There are many actors around that increase value through shortage. The alternative is entrepreneurial collaboration with advanced technologies to assure a very large diversity of healthy food, enhanced with free global trade via internet. Science has failed to convince taxpayer that with sustainable technologies we will always have enough food for everybody.
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Are hotter and hotter summers, more and more frequent droughts, drying up rivers and lakes, less and less rainfall, more and more forest fires the result of climate change and, above all, of the increasingly rapid process of global warming?
Is the current (mid-2022) record low water level in rivers a weather anomaly or another example of a long-term unfavourable trend resulting from accelerating global warming?
As of mid-August 2022, river water levels in several countries in Europe are at a 500-year record low.
It has been reported in the meanstream media that, for example, France's longest river, the Loire, can already be crossed on foot in some places.
Besides, the Loire has never flowed so slowly. The Rhine in Germany, on the other hand, is fast becoming impassable by barges.
In Italy, the water level in the Po is 2 metres lower than usual, with devastating effects on crops.
Is this a weather anomaly or another example of an unfavourable trend realised over a multi-year period as a result of accelerating global warming?
Or is it a combination of various unfavourable factors in 2022, which has resulted in the simultaneous occurrence of weather anomalies and the effects of an accelerating global warming process?
On the one hand, many countries have experienced hotter and hotter summers, more and more hot days in the summer period, increasingly frequent droughts, rivers and lakes drying up, less and less rainfall, etc.
On the other hand, an increase in the scale of forest fires has been reported in many countries. In Poland, from the beginning to the middle of 2022, there have already been as many forest fires as in the whole of the previous 2021.
What is your opinion on this subject?
What is your opinion on this topic?
Please reply,
I invite you all to discuss,
Thank you very much,
Greetings,
Dariusz Prokopowicz
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Drought
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As we know, drought will continue in the Mena region and one of the best strategies to deal with water shortage is water recycling. However, there are only limited experiences in some countries in this regard, so I am looking for broader examples, especially models that are approved by the health monitoring organizations of the countries.
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Dear Dr. Akbarzadeh, there is much research and good work in desert regions.
I refer you to study the biggest one in Oman (BAUER NimrWater Treatment Plant (NWTP)) Currently, 115,000 cubic meters per day of water produced from the nearby oil Well field with EC = 8,000 ms/cm have been formed by using 360 hectares of subsurface flow in Constracted wetlands(SFCW). the chif sintist was Dr Alexandros stefanakis.(Asst. Professor, School of Chemical and Environmental Engineering, Technical University of Crete)
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In the fall of 2005, the Amazon River suddenly dried up (photo attached). At the same time, a little to the north, in the Caribbean, the number of tropical cyclones increased abnormally (the graph is attached). In addition, the formation of tropical cyclones continued until January 2006, see cyclones Delta and Zeta (map attached). It happened in one geographic region. I think these anomalies may have a common cause. I analyzed the gravitational field, which can form an anomaly of high atmospheric pressure in the region. Maybe there are other ideas? In 2010, the drought in the Amazon was not accompanied by an anomaly of tropical cyclogenesis.
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Thanks for the helpful link.
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Researchers frequently think that these terms are synonyms.
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I would say that 'drought' is a period with particularly low precipitation and/or high evapotranspiration, which can be sometimes compared with the long term average of the site over the same period. Then, 'hydric deficit' is the effect of drought on the water reserve (e.g., soil water deficit) as the difference between the max (e.g., field capacity) and the actuel water availability. Finally, 'water stress' refers to the physiological responses of plants (or other organisms) to hydric deficit, which depend on ecological water strategy. However, the definitions may vary a bit according to the scientific community and the scale considered.
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Progressive climate change, including the process of global warming, is causing increasing droughts and desertification of areas. The scale of areas with decreasing rainfall is growing. Surface and sub-surface water resources are decreasing. Water resources for irrigation of agricultural fields are decreasing. Drinking water supplies are also declining.
In view of the above, the question becomes increasingly topical:
What are effective solutions for saving and recovering potable water?
How can field irrigation systems be developed in a situation of water scarcity and increasingly frequent periods of drought?
How can water scarcity problems be solved?
What do you think about this topic?
What is your opinion on this subject?
Please reply,
I invite you all to discuss,
Thank you very much,
Regards,
Dariusz
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Your question is worded very confusingly. Let's break it down into parts, if you don't mind. Despite global warming, the total amount of water in the hydrosphere and atmosphere does not change. I think there is no doubt. During global cooling it is different. During global cooling, the total volume of water in the form of gas and liquid decreases, this water is stored above the ocean surface in glaciers. The ocean level is dropping. Everyone knows this. During global warming, evaporation from the surface of the earth and water increases and water from the hydrosphere passes into the atmosphere. The rain is getting bigger. I think there is no doubt. It rains more and more people die because of the drought. This is true and it is a paradox. If there is interest in this issue, I will continue.
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Does the technique of cloud seeding solve the problem of drought and the expanding water crisis, especially among the riparian countries?
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Recently, cloud seeding has been proposed as a climate change mitigation strategy to brighten cloud backgrounds and increase the proportion of solar radiation that is reflected back into space. Caution must be exercised in undertaking this kind of effort on a global scale, pointing out the historical difficulty in proving causality in local cloud seeding.
Cloud seeding on a global scale does have historical precedents, which manifested themselves, however, in a very unexpected way: through the unintentional active influence on the weather. For example, as a result of volcanic eruptions, particles entered the stratosphere that contributed to a decrease in air temperature at the global level within 2 to 3 years after the eruption (in particular, such eruptions are believed to have contributed to the preservation of the Little Ice Age in the 19th century). Another example of an unintentional active influence on the weather is related to the fact that, as a result of satellite observations, it was found that particles that got into the air with the smoke of steamship pipes change the properties of the upper layer of stratocumulus clouds, increasing the brightness of the cloud background.
When actively influencing the weather, intentionally or unintentionally, "it is important to remember that the atmosphere has no walls." What you add may have a desirable effect near you, but when transferred, it may have an undesirable effect elsewhere.
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What’s a best method of water management in case of an agricultural drought? Which bill provides details for regulation and control of groundwater?
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It all depends on the country's economy i.e., whether it is a developing or a developed country. In the case of developing countries, the management mechanism is problematic and no substantial substructure exists to ameliorate the situation therefore the central government will have to resort to the last recourse, borrowing to import.
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Using R
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Of course, multivariate standardised drought indexes, considering meteorological-agricultural drought or meteorological-hydrological drought are of paramount importance. For example, have a look at the one developed in my article.
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Program or software to calculate EDI
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spss program
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What are the different mechanisms driving abrupt and gradual drought terminations? What are the climate model projections of drought termination characteristics? To what extent are climate and hydrological models able to simulate observed drought termination events?
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The references provided by Ilan Kelman are very useful as background and fundamental material for the definition of droughts. In addition, you might further think about the context of drought in your study. What is the final aim of your study and what is the most appropriate definition of drought connected to that aim?
Once you have a clear drought definition, you can further think about the operationalisation of this definition, e.g. which variables need to be measured and/ or simulated at which spatial and temporal scales to assess drought and possible historic and future changes in drought.
Good luck,
Martijn
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for example SPI, Drought index, seasonality index?
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Dear Suzana,
I'd advise to consult literature and guidelines published by the World Meteorologial Organization (WMO, Geneva, Switzerland). They are a leading authority in these matters. The various IPCC publications will also contain useful explanations as well as more references on climate indices.
PS: Are you conducting research on climate change in Bangladesh?
With best wishes,
Julius
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Hi all,
I have river run-off annual data and a catchment composite mean value of PDSI values (drought index). A simple regression model tells me that the PDSI well predicts the run-off (what can be physiologically expected). I checked the residuals, normality, homocedasticity, p-value. All perform fine, all is significant. The data spans 1869-2012.
Because I have the PDSI values for the period 0-2012, would it be possible to use the results of the model to reconstruct the run-off for the same period?
the model reads:
runoff_1869_2012 = ß0 + ß*PDSI_1869_2012
-> summary(model): ß0 = 1055.363 and ß=55.668
hence, would this make sense:
runoff_0_2012 = 1055.363 + 55.668*PDSI_0_2012
Eventually, I get the reconstructed run-off for the whole period with a certain uncertainty?
Many thanks for suggestions on this very basic question!
all best,
Michael
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Michael -
Are you saying that each year gives you a data point, so 144 data points, and assuming all things else unchanged, you use those points in a simple linear regression, regardless of dates? (I don't know why you have 1869-2012 one place and 0-2012 another???) I would expect heteroscedasticity based on size, as measured by predicted-y, b0 + b1*PDSI_year, with years out of order. Anyway, did you use a "graphical residual analysis" to check fit? "Cross-validation?" What does your intercept represent, or is it noise, and you should use a ratio estimator?
Time series are not my interest, but I have to wonder if you should be considering that. Perhaps there is autocorrelation.
Perhaps I do not understand exactly what you are doing. If you can show a graph, or graphs, that might be helpful for everyone.
If you can demonstrate that what you have works by dropping data you have and seeing how close you come to predicting it, that could be helpful.
Cheers - Jim
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I have studied the effect of ANE (Ascophylum Nodosum extract) on okra under drought stress. First factor is drought (control, mild stress, severe stress) and second factor is foliar application of ANE (Ascophylum Nodosum extract) (control, 0.1%, 0.2% and 0.3%), The experiment was conducted in pots using statistical design CRD (complete randomized design), same media was used. Drought stress, foliar application of ANE (Ascophylum Nodosum extract) and their interaction significantly effected physiological and biochemical parameters of okra. But the data recorded on control plants of drought, ANE (Ascophylum Nodosum extract) and their interaction is different from each other. Plants growing in control conditions are without any treatment.
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You must increase your replicant in each treatments for reducing errors.
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Drought Monitoring and Detection
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Dear Sandy,
Thank you very much. In your opinion, the images of this satellite, since they have a very low spatial resolution (about 10 km and Modis half a kilometer), will have a good estimation accuracy in monitoring drought in very dry areas. And given the two-year joint course of Modis and AVHRR, what do you think of the relationship between them by regression communication?@Sandy Bartle
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Greetings,
We're working on the cocoa yield estimation based on the SIMPLE crop model ( ). We're looking for a source to estimate the sensitivity of RUE (Radiation use efficiency) to the ARID index (Agricultural Reference Index for Drought) proposed by The original paper called this relationship as S_water.
We truly appreciate your guidance.
Kind regards
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Adding any data needs to be studied, audited, and tabulated so that it can be worked on.
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It is mainly about the transcriptome of plant drought, preferably without a page fee.
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Based on what I think you might be looking for, I have found some possibilities:
The Plant Journal
Plant Science
Journal of Experimental Biology
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While numerous broad-scale studies, meta-analyses, and models have revealed factors associated with drought susceptibility, I have not seen studies addressing fine-scale drought vulnerability. I suspect slope, aspect, openness, soil thickness, etc. may be important, but I am wondering if anyone else has studied this. Thanks!
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fine scales like soil texture also studied sir
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We mostly associate drought with vegetative traits. I wonder if flower characteristics of dryland plants are shaped by drought. Is the presence or absence of the perianth and the type or structure of reproductive parts of a flower affected by this? I need sources on flower buds, flowers, fruit and seeds. Do you have any recommendation on this matter?
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Flowering is stress induced hence production of ethylene. Drought stimulates flowering but majority of flowers fail to produce successful fruits due to enough water and nutrients.
Maybe ovary more resistant to drought as compared to other parts.
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I have used plot() function in base R to produced the attached SPI plot but I have never seen these black dots on the x-axis before. About the grey lines on the plot, I have seen these in other plots too but I don't know what they are. Can somebody please tell me what these things are?
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Normally you are supposed to get a standardized set of your precipitation values. The distribution of the SPI is supposed to follow a normal distribution with a mean of 0, bounded between about 3 and -3. If the standardization is not working well, you lose the whole point of the SPI to determine the precipitation anomalies while considering the annual variability.
Looking at your graph, you have very few negative values. Two suggestions:
-The SPI is not adapted to your time series with the default calculation parameters. Usually Gamma laws are used to standardize the values for each month of the year (in the case of scale = 1). In some climates the Gamma law may not be suitable. In some functions there is the possibility to change this law by default. It is possible that this improves the result.
-There is a problem of choosing the input of the function. The output of the SPI must be an object ? Try to extract the vector corresponding to the SPI calculation and plot in a more classical way to check it.
Some ideas to investigate...
Best regards
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I have calculated Standard Precipitation Index (SPI) values using "SPEI" package in R. Interestingly, I have got some zero values of SPI for about 10 months in the same year and this has happened for multiple years. I was wondering about the possibility of this to happen as I haven't seen anything like this in the papers that I've been through. Please do tell if there is someting wrong here.
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Andrea Galletti I assumed it to be in a Gamma distribution as that's the default setting but I'll take a look just to make sure.
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Hi,
I want to statistically analyse my metabolomics data (18 metabolites). I have two species and four levels of drought. I analysed each species individually by CRD and for mean comparison I used Fisher's LSD (0.05%) by adjusted P-value (FDR). Is this procedure correct or I must use another statistical method?
Thank you all.
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I think that the LSD mean comparison test is appropriate, but it is point that which test plan did you use for the four levels of drought? Are you considering the factorial experiments? However, it could be considered as an alternative test.
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Is it that chlorophyll content and protein level are significantly affected under drought?
Do drought-tolerant genotypes produce specific secondary metabolites? If yes what are the secondary metabolites?
What should one look for (in terms of biochemical parameters) when studying drought tolerance or sensitivity in legume or cereal genotypes.
Please see the link below:
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Dear Colleges
In the RDI (relative drought index) relation
RDI= RWCact/ RWCcrit
Now it is my question, how can estimate the RWCcrit both in field and pot experiments?
Best regards
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Why to measure relative water content, it's not only tedious but erratic as well due sampling errors. Let's measure it directly using precision equipment pressure plate apparatus...
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I am working on factors affecting shoot tips of rice under water deficit and I have some problems to arrange the treatments as moderate and hard drought.
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The following article is related to your question.
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Traits which can help us for drought tolerance and weeds. when drought condition occur in rice more weeds grows.
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You can read the following article.
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Data of rice, drought areas and growth stages which are affected by drought and yield loss (%) at different stages in Pakistan
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You can read the following article for your information.
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Hello scientists! Drought is on the rise in some areas as a result of climate change. Are there levels and categories of drought?
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Dear Dr Maftuna Karimboeva . Yes. This including :
1. meteorological drought,
2. hydrological drought,
3. agricultural drought, and
4. socioeconomic drought. Meteorological drought happens when dry weather patterns dominate an area. See the link: https://www.ncdc.noaa.gov/monitoring-references/dyk/drought-definition#:~:text=As%20a%20result%2C%20the%20climatological,weather%20patterns%20dominate%20an%20area.
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The 'how' refers to the research methods available in the field of legume seed proteomics.
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In addition, you should also check and go through following link, and attached PDFs.
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I just want to know the proper use of these two words from the researchers who are working on drought stress
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Drought corresponds to a situation of sufficient water deficit to harm, to a greater or lesser degree, vegetation, animals or man. ... This is why water deficit should not be confused with drought. If there is no damage, there is no talk of drought, even if there is a water deficit.
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Reproductive development comprises of a number of stages, all of which can be affected by drought and eventually have an influence on seed filling, seed size and seed yield.
Genotypes better able to maintain seed size and yield must either avoid terminal drought by completing seed filling prior to the commencement of drought (Turner et al., 2001) or tolerate terminal drought and maintain seed filling during drought (Turner et al., 2001).
Please seed the attached picture of pigeon pea, with inadequate seed filling
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Have a look at the following RG link for insight.
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definition
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Qin Liu came across the same question with few answers on Research Gate and felt like sharing with you and the experts above
Hope so this will be helpfull
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The frequency and intensity of drought hazards in the horn of Africa are increasing from time to time along with its numerous and complicated negative impacts.
Weather variability and climate change are also inherent in deriving the changes coupling with anthropogenic factors.
The region is known as being one of the least developed in terms of economic, social, and technological advancements.
The region is also fast growing in terms of population.
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The importance of water resources is evident, and its management through all levels is
imperative, especially in arid and semi-arid countries where water demand is highly required for irrigation and for the drinking.
what are the best methods of water management in the case of an agricultural drought ?
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Incorporation of agronomic management practices so as to either use water efficiency or conserve water in the soil in the form of optimum moisture to support plant life... drought is a situation where annual seasonal rainfall is less than twice the mean deviation allowing excess evapotranspiration over absorption of water...Use of laser land levelling as precision agriculture device for proper water management, used to organic manure allowing more porosity with higher retentive power to hold water thereby good water productivity, use of mulch, sowing in ridges and furrow, use of drip irrigation device or any other precised water use technology, use of raised bed sowing allowing 50% less water use, contingent planning of crop sowing to avoid early and late season drought.. uncertainty of mansoon, erratic rainfall pattern with irregular distribution over an area is one of the most important constraints of Indian agriculture... selection of crops which resist water deficit may be choosen for the sowing.. Keeping the concept of "more crop per drop" in mind, life saving irrigation, microirrigation can be applied to avoid strains... collection, induction, storage and utilisation of water via water harvesting is a good option by making inter plots or tanks or intra plot water harvesting.. Storing water during excess rainfall and utilising it during peak periods of water deficit or stress, one may get remunerative returns by not compromising with yield loss..
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How to calculate SPI drought index for last 30 years using rainfall grid data?
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I have time series data that I collected on soil moisture using sensors deployed at 27 sites, with data logged every 15 minutes. I am wondering if there are well defined metrics to quantify the intensity and duration of drought stress over the whole season. I could do mean soil moisture but this would not take into account the variability of the data and seems like it would be wasting the high resolution data that we have. I really want to know how often soil moisture dipped so low that it could impede plant and microbial activity. Thanks!
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Kindly check also the following useful RG link:
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Can electricity consumption (KWh) be used as an indicator or proxy variable for drought vulnerability assessment? What is the relationship between electricity consumption and drought vulnerability?
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We have worked on the technological package of crops (including electrical consumption) in these manuscripts that can serve you:
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There are lots of softwares for calculating the SPI index and some other indices from which we can get the results, but how to calculate these indices is not clear. When I google it, it provide me with many information but can not clearly describe the calculation procedure. So if someone have a designed excel sheets or know a clear description for calculation of SPI, kindly share it
Thanks
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In order to manage drought due to prolonged dry spell in the presence of crops, there are different techniques are available to manage the situation. Some of them are seed treatment with potassium dihydrogen phosphate or Potassium Chloride, foliar spraying of PPFM fungi, KCl (1 %), humic acid and amino acid etc. Among these product which one is good.
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It depends on the system, the conditions, the physical and economic environment, here are some manuscripts that we have worked on:
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Drought treatments in field experiment include 1/12P, /1/4P, 1/2P, 3/4P , P. P represents the plot receiving natural precipitaion. I do a linear regression between drought treatments and response variables. The reviewer think that this analysis was inappropirate. Can you help me? explain why
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It makes sense to determine the trend over those treatments.
My opinion is that it would be fine to treat those treatments as quantitative treatments. Having five levels isn't ideal for this application, but I think it makes sense.
Another approach, though, is to conduct the analysis with those treatments treated as categorical treatments (e.g. as in anova). You can then apply polynomial contrasts to determine if there is a linear or quadratic trend over those treatments. This is a traditional technique in agronomic studies. The problem with this in this application is that the treatments are decidedly and intentionally not equally spaced.
This might be helpful with polynomial contrasts: https://www.ndsu.edu/faculty/horsley/Polycnst.pdf
Another idea: You might take a look at my paper at the following link. Here, we treated the treatments as categorical treatments throughout the paper, but then used them as the independent variable in a linear regression (Fig. 6). This approach might be okay with your reviewers.
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Will the world witness climatic extremes, severe drought and a decrease in temperatures from 2021-2026 due to the receding star of the Sun?
I predict a change in climate and its impact on wind and plants
That is, there is no heat, no movement of winds, any lack of pollination and ripening of the fruits, and we will witness an economic disaster and a rocketing rise in global food prices 2021-2026
Therefore, we call for austerity and rationalization of food consumption, the use of artificial intelligence, food technology, tunnel farming, i.e. underground or in tunnels, and the use of alternative and renewable energy such as providing light for plants and appropriate heat and recycling waste water to confront this global crisis that will lead to the collapse of countries and entities and the spread of revolutions, international wars and crises such as famine Global . and mass migrations . and spread of diseases and deadly epidemics and their spread due to the availability of a climate that is low temperatures and weak winds, this is the cause of the global epidemic.
Researcher Aissaoui Adel
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Thank you very much for asking such a question, as it focuses on the impact of climate change on the future of humanity from all dimensions.
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I am screening soybean genotypes for drought tolerance and vulnerability in a screen house. Some literature suggests 3 weeks and others suggest 4 weeks of drought imposition.
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I have calculated the drought indices at monthly basis for 30 years (1985-2015) and I have also collected annual crop yields for 10 years (2000-2010). The crop growing periods are from June to October. I want calculate the correlation coefficient (r) between drought indices and crop yield anomalies for the crop growing periods from June up to October like the sample given on the table below. How can I achieve this objective?
Regards
Nigatu
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Thank you Prof Andrew Paul for you response. but would you explain your answer using xls? please it will help me
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Socio-Hydrology, as a relatively new paradigm in resilient water management, has gained increased attention these days in reconciling contrasting issues in the fields of natural and social sciences.
Hence, there need effective and appropriate tools, models, and approaches to conduct researches so as to enrich this multidisciplinary field of study and ensure effective utilization of this vital but scarce resource, especially in areas where human communities are living in close proximity to natural water systems.
It is a general fact that human societies across the world are being challenged with significant water-related problems such as ecosystem degradation, groundwater depletion, natural and anthropogenic drought, and floods, water-borne health issues, and deforestation which are being exacerbated by climate change.
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Dear Aklile,
Very interesting work. You can visit the link:
  • DOI:10.5194/piahs-374-9-2016
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treatment : 1. heat 2. drought
experiment period : 1 Month
1. heat
twice during the period by weekly.
(2nd week and 4th week)
2. drought
for the whole period.
Plant's response data was measured twice a week.
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This depends on the purpose of your study
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It made me learn a lot of useful things. Thanks for sharing
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To find out a drought tolerant genotype of tomatoes, I want to know the drought linked markers. I couldn't find any study that provide me information about drought linked markers of tomato. Is there any study or database that give me this information.
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Rizwana Begum Syed Nabi Thank you for giving time. Can we get information of specific stress genes of tomato from NCBI? As you mentioned that there are 35 total genes (Perhaps you tell about drought responsive genes). If we can search these specific genes of tomato, please tell me the way, How can I search for such genes?
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I am working on arid watershed and through my literature review I found MSWEP precipitation dataset( ) a potential candidate to do my drought analysis. My struggling in the method of downloading the data which is requiring download another software and working with command line tool. If you have any experience with this dataset , please leave your comment .
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Try to use CHIRPS, it has 5 km spatial resolution and available in Google Earth Engine.
Downscaling precipitation statistically in the arid environment is not easy.
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I read a paper today regarding trends in drought using SPI values. That got me thinking if there is or can be an index for flooding as well. The issue is that drought is usually a long term meteorological phenomenon while flooding occurs in and for a much shorter time period than drought. So I am now thinking along the lines of the concept of rainy days where any day with a daily rainfall more than 2.5 mm is considered a rainy day. Can a similar concept be applied for flooding as well with maybe rainfall and AMC being the decisive factors? Are there any already established criteria this?
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Check on this paper of mine. It depends on the amount of rainfall and impervious surface.
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hello
i want to analyse the drought condition using sattelite images
for this i used the MODIS imagery and download EVI , NDVI (250m) and LST (1km) datasets for my sample area in Turkey
in Matlab i generate VCI and TCI indices and define drought classes as suggested generally e.g. www.un-spider.org/advisory-support/recommended-practices/recommended-practice-drought-monitoring/in-detail
aforementioned classes are defined as follow
% 0-10 Extreme Drought
% 10-20 Severe Drought
% 20-30 Moderate Drought
% 30-40 Light Drought
% >40 No Drought
when i generate drought claasification map based on VCI (using NDVI /EVI) the study area is classified mostly as no drought as presented in fig. 1
but when i use TCI dataset, which i resized to 250m in matlab, most of the area classified as severe drought as presented in fig 2
i check all process several times but the calculations are true
as seen i suppose that the 225th day of year could be representative for assessment (12/13Agustos) for both VCI and TCI
am i wrong?
any one can illustrate that
what is the detailed procedure for this purpose ?
can any one describe practically the data preprocessing for analysis?
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so thanks Nima Karimi
in fact i was prefered Modis becouse of ease of use of them as i was able to get dataset just for my study area not whole of the scene
but now i start to work on earth engine and now i could try other satellite images
best regards
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Why there is larger interest in induction of drought in quinoa crop eventhough it's a drought tolerant crop?
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Researchers often induce stress upon the tolerant varieties to unravel the underlying mechanisms associated with their tolerability so that it can be helpful in further incorporating the mechanisms in the sensitive ones. Any plant that is tolerant to certain stress suggest some internal antioxidant defense mechanism or any kind of stress responsive pathways that works in accordance with certain genes, transcription factors or any kind of second messengers associated downstream of the signaling pathways. So, before proceeding towards any kind of abiotic stress related researches one should thoroughly know about the mechanisms that is actually helping the tolerant varieties withstand such adverse conditions.
Hope this was quite helpful.
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Because of the scarcity and reduction of rainfall will be needing to study on drought
we need to frequency of drought instead of flood
are you help me equations and methods to calculate drought same as flood for example Gumbel, wibell, log person, log normal,...........................
help me please to work drought study of Tigris and Euphrates
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When social scientists study drought, they look at how it affects people, communities, and society, and the ways that people can work together to make drought less harmful to society. Social scientists help us understand: how drought affects rich countries or people in comparison to poor countries or people.
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Can "forest cover" be used as an indicator of "drought vulnerability"? If so, what qualitative relationship can there be between the two?
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Drought may be termed as a hydro-climatic disaster and forest cover can be used as an indicator of drought vulnerability both from environment and socio-economic perspective. Drought vulnerability depends on various socio-economic and environmental indicators in concerned area.
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Hello,
Does anyone have any advice on how to measure soil moisture or hydraulic conductivity in a microbial greenhouse experiment? Seedlings will be grown in D40 cones and half of the sample will be given a drought treatment using drip emitters.
What is the most efficient and reliable way to measure soil moisture or hydraulic conductance in dry soil in a greenhouse setting?
Thanks.
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Soil moisture metres could help.. Measurements can be done at prescribed intervals
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I conduct research on drought tolerance based on morphology and physiology parameters, I use some index tolerance to determine the genotype drought tolerance. I found a genotype that drought tolerance is morphologically but susceptible physiologically or reverse, it is possible?
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It depends on the number and kind of the vegetative traits as well as the age of the selected plants. there are then the role chemical compounds biosynthesis by the tolerant plants. After the morphological selection they should go under deficit irrigation experiments.
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I am running drought experiments on drought tolerance in winter and spring wheat. I have noticed from the data the spring wheat is more drought tolerant than winter.
Do you have the same experiences?
providing references will be highly appreciated as I did not find clear reference for thiat
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Excellent, did the spring wheat have more initial branches than the autumn branches? Ok
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I was carrying out a study on perceptions of drought effects by farmers as influenced by their production environments. Production environments were my predictors and then I ranked drought impacts as scores. That is, respondents would score from 1 to 5 according to severity of impact: EFFECT Rank (1 to 5)
Water shortage
Feed shortage
Heat stress
Cattle mortality
My model was:
The effect of production environment on number of different classes of cattle lost to drought and rank scores for breed preferences, challenges to cattle production, reasons for loss of cattle, severity of drought components, severity of the effects of drought components on cattle production, grazing management problems during drought, types of parasite prevalent during droughts and breed susceptibility to drought were determined using PROC GLM SAS (2008). The model used was:
Yij=µ +EiI+ ɛij
Where:
Yij= response variable (number of cattle lost to drought; rank scores for: severity of the effects of drought attributes on cattle production, severity of the effects of drought on cattle, grazing management problems during drought, types of parasite prevalent during droughts and breed susceptibility to drought)
µ = mean common to all observations;
Ei= effect of production environment (sub-humid areas ; semi-arid areas);
ɛij= residual error ~ N (0; Iσ2).
[MC1]Sounds wrong…some variables are discontinuous.
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Hi Takunda, you can but you should not. The general linear model is for continuous data, you should analyze it was multivariate or you can set the response of yes (1) or not (0) to each rank and then present the % in each rank and you can use a GLIMIX with a binomial distribution.
in sas:
proc glimmix;
class block trt ;
model rank1 = trt block/ dist=binomial ddfm=satterth;
lsmeans trt / pdiff ilink;
run;
good luck
ale
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The maximum length of wet spell means consecutive wet days and is the longest period of consecutive days with at least 1mm of precipitation. My interest stands on estimating dry spells and then, analyzing the maximum lengths of dry spells over different locations for a 60-years period.
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Is it possible to calculate dry/wet spell using RCLIMDEX software for monthly or seasonal because right now I can compute for annual variation
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In order to calculate droughts using SPEI, SPI should the rainfall data be input in daily time scale?
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It is calculated at weekly interval. But dry spell between first moisture to current determine the drought.
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I am working on Agricultural drought monitoring using Nova avhrr data from 1986 to 2015 so how to calculate correlation bln NDVI & crop yield anomaly in arcgis
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Dear colleagues,
300 accessions of Dolichos lablab have been screened for drought tolerance in the green-house based on Augmented block design.
In this screening project, two consecutive experiments were conducted to involve 10 weeks each. In each experiment, the project involved drought inducing period by withholding water as well as water supplying period to induce plant recovery.
Both quantitative and qualitative data were collected during germination and seedling stage of the plants. The data included chlorophyll content, height of the plants, number of leaves, wilting%, overall wilting scales, recovery%, shifting and folding of leaves etc.
I would like therefore to request for your advice on the best approach on data analysis so that I can determine the best drought tolerant genotypes.
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Dear all,
I'm working on drought indices comparison. Can you please suggest an insight into the drought indices that are comparable?
Is there any prerequisite to be taken into consideration?
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This handbook on drought indices produced by the World Meteorological Organization may also be of use if you've not come across it before see
This paper may be of interest: https://www.mdpi.com/2076-3263/8/3/81/pdf
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Wheat production is severely hampered by the drought and heat stresses which generally coincides and augment the stress effect. It is difficult to remove the confounding effect of each stress on the other mainly in the field conditions. Although in irrigated areas, applying irrigation at the time of heat stress can control heat to a certain extent but in rainfed areas, there is no choice for timely irrigation. So, considering the depleting water table, the only solution seems feasible is to develop multi-stress (heat and drought) tolerant wheat cultivars. But it will require the focused effort to improve component traits related to photosynthesis and respiration. Which will be the most critical physiological traits that need to be targeted to combat both stresses together under predicted climate change? Can the heat-tolerant cultivars with a tendency (adaptation) to flower early morning and late evening to avoid heat stress can prove to be a game-changer?
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The Precipitation Condition drought Index (PCI) is widely used for defining rainfall concentration and rainfall erosion. There are some papers and thesis available which have used this index. But none of them have mentioned any calculation procedure clearly. So if anyone can provide that or any such reference that explains clearly, it will be of immense help for me.
I appreciate any feedback you may have.
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Dear Vahid,
This is an excellent question. I think non-parametric trend tests like Mann-Kendall and Spearman’s rho can be used in your case.
Regards
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India is the largest producer, consumer and importer of oilseeds in the world. Oilseeds are mostly grown with rainfed conditions in marginal to sub-marginal lands. Total production of oilseeds is 31 million tons. Our demand outstrips domestic production, resultantly, importing oil becomes an annual feature in India. Out of total vegetable oil demand of 24 million tons, 14-15 million ton oil is imported and we could produce only 9-10 million tons. But success of oilseeds production is largely dependent upon the monsoon climate. In this backdrop, I am tossing up following issues to be addressed with probable solutions/ interventions for strategizing the production and productivity of oilseeds:
  • How can development and adoption of drought tolerant varieties come as rescue to the existing problem of oilseeds?
  • How can the production of oilseeds be sustained under moisture limiting/excess conditions, since crop is predominantly raised under rainfed conditions?. How can we safeguard the standing oilseed crop in field through supplemental irrigation ?.
  • Why have the past attempts on adoption of resource conservation techniques such as raised- bed planting, drip irrigation and mulching , been failing so consistently?.
  • Whether, you foresee a better promise with growing two or more crops together from farmers income perspective and standout against fragility of rainfed farming.
  • What promise, the application of micronutrients and biofertilizers hold in the entire gamut of management strategies in production of oilseeds?
  • What are the other secondary sources which could be tapped for supplementing huge demand.
  • Can we become self sufficient in oil seeds production and what should be the strategy to reduce import?
I shall regard your responses.
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Rainfed ecosystem where farmers grow them, has several challenges for oilseeds
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As water means life, and under the worse circumstances of gradual scarcity of water resources, desalination technology has became urgent to be applied on a wide range than any other time of the past. Therefore, I open the topic to have feedback of the modern desalination technologies and solutions.
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Desalination is the solution for water scarcity in the world but it is expensive. It depends on energy use. Renewable energy (solar, wind) can be used especially if it is available in the country. Desalination Integration with Renewable energy can be used as in the link:
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Evaluation of Spatial-Temporal Variability of Drought Events in Iran Using Palmer Drought Severity Index and Its Principal Factors (through 1951-2005)
See Table 2 for a published example of PDSI and soil moisture.
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Water budget is determined by both hydrological and thermal processes, characteristics often represented by so called ‘‘drought indices’’ to manifest the actual hydrological conditions in a single number. According to their characteristics, drought indices can be sorted as: precipitation indices, water budget indices, soil moisture indices, hydrological and various aridity indices, all of them meant to indicate from different points of view moisture conditions, deficiency or surplus of water, for a given area. One of the most common indices is the Palmer Drought Severity Index (PDSI), introduced by Palmer (1965) to simulate moisture content of the soil month by month and to compare its monthly anomalies at regions having totally different climate and seasons. Source: Relevnt PDFs...
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