KEYWORDS: Photosynthesis, Luminescence, Statistical analysis, Atmospheric modeling, Carbon dioxide, Quantum efficiency, Electron transport, Temperature metrology, Data modeling, Imaging systems
Crop breeding and variety analysis play the important role in the national economy. A lot of sample data and typical
probability distribution are needed in the conventional methods to evaluate the high-yield crop cultivars such as
correlation analysis, regression analysis and grey relational grade analysis etc, which are difficult to be realized. Delayed
fluorescence (DF) can be used to evaluate plant photosynthesis. The current investigation has revealed that there is a
good linear correlation between DF and photosynthesis capacity. More importantly, the slopes of linear fit of the
correlationship for different yield varieties are different. Four known yield crop cultivars from each of the two different
species (Maize and Soybean) are selected as samples to be analyzed. The statistical results show that the slope of
high-yield variety is smaller than that of low-yield. We thus conclude that the slope of linear fit of correlation between
DF and photosynthesis capacity is an excellent marker for high-yield crop cultivars identification. Compared with the
conventional methods, the presented method needs less samples and it's fast and easy to be measured.
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