my faba bean plants were naturally exposed to frost stress in the field. Some plant did emerge but after exposing to frost they died. If I take a correlation between winter survival rate and 1000 seed weight. In case of survival rate, the value will be zero but what is the value for 1000 kernel weight (or day of flowering, days to maturity, yield) for the same genotype. Other suggest to remove these genotypes or put star instead of zero, arguing that they do not know the 1000 kernel weight of this genotypes. For me, I convince to put a value of zero for 1000 kernel weight and yield because it reflected the symptoms of frost. I mean I can say that I do not 1000 kernel weight of that plant if the plant did not emerge but the fact is it did emerge and was killed by frost. what is your opinions?
the correlation size will be different in the both cases.
I believe it is wrong to have a zero value for 1000 seed weight (I wouldn't use the word kernal in this case as it is a legume) because the genotype has a 1000 seed weight under normal conditions and it produces seed under normal conditions. Seed weight is highly genetically controlled and is one of the lowest affected by the environmental conditions compared to other primary yield components (number of pods, seeds per pod). If you are analysing genotypes in your correlation analysis and want to understand the genotypic correlations for frost hardiness, then it would make sense to conduct the same experiment under non-frost conditions (may be greenhouse) and get the seed weight, yield etc. and then give a 1-10 scale for frost hardiness (no zero there, 1 for most susceptible) in the frosted year and analyse data.
The analysis must have an objective and I assume your objective is to understand if there is a genetic relationship between any of the yield components and frost hardiness. If that is the objective, I would correlate the yield components from a normal year with the scale of frost hardiness as described above.
You use the words "for the same genotype" above, so I assume you are trying to work out the genotypic correlations for your breeding programme. You may even use the data from non-frost years to get values for the yield components.
If you decide to use zero, use 0.001 instead.
Apparently cold-hardy (winter type) faba bean exists and a good paper on this is attached.
I believe it is wrong to have a zero value for 1000 seed weight (I wouldn't use the word kernal in this case as it is a legume) because the genotype has a 1000 seed weight under normal conditions and it produces seed under normal conditions. Seed weight is highly genetically controlled and is one of the lowest affected by the environmental conditions compared to other primary yield components (number of pods, seeds per pod). If you are analysing genotypes in your correlation analysis and want to understand the genotypic correlations for frost hardiness, then it would make sense to conduct the same experiment under non-frost conditions (may be greenhouse) and get the seed weight, yield etc. and then give a 1-10 scale for frost hardiness (no zero there, 1 for most susceptible) in the frosted year and analyse data.
The analysis must have an objective and I assume your objective is to understand if there is a genetic relationship between any of the yield components and frost hardiness. If that is the objective, I would correlate the yield components from a normal year with the scale of frost hardiness as described above.
You use the words "for the same genotype" above, so I assume you are trying to work out the genotypic correlations for your breeding programme. You may even use the data from non-frost years to get values for the yield components.
If you decide to use zero, use 0.001 instead.
Apparently cold-hardy (winter type) faba bean exists and a good paper on this is attached.
Thank you for your answer. I did score overwintering using scale ranged from 1 to 9. As the objective of my research is to screen elite genotypes for their resistant to winter hardiness. I have most tolerant genotypes and most susceptible which did not survive after frost. The in my point of view is the value of zero reflects the effect of frost on susceptible genotypes. So, I have scores for winter survival (%), overwintering (1-9), yield, and 1000 seed weight. Unfortunately, there were some problems to conducted control experiment. My problem is how to score 1000 kernel weight for those did after frost. If I dealt it with missing values, the correlation analysis will not consider these genotypes for 1000-SW. To summarize, my proposal is 1000-SW for tolerant genotypes is a value (e.g. 25 g) and for susceptible is also a value (zero) because both of the were exposed to frost and their performances were due to the effect of frost.
do agree with me?
The argument is treated in Vicia literature for frost selection, If you got the opportunity you may take reference to Winter hardiness in faba bean: Physiology and breeding
W. Link , C. Balko , F.L. Stoddard in Field Crop Research 2008 journal. Goettingen University has copies on line. Usually you can not be craetive about selection: It seems that seed weight is not available, but day of emrgence is. Earliness is an important character and you may use it instead. Control runs in warm conditions are necessary
I did not find a promising correlation between days to flowering and winter hardiness. I put missing value to those did after frost. The frost test was in Germany and started from Feb. to end of March. The flowering normally in late of June or beginning of July. In this case, I do not know the days of flowering of the susceptible genotype. So, I agree to put a missing value for this trait.
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