Research On Growth And Development Strategies Of Light And Moisture Conditions On Clover

Non-destructive measurement of plant phenotype based on 2D image is the current research hotspot of plant phenotypes.In order to accurately obtain the phenotypic characteristics of clover,this study is based on potted clover under different light and soil moisture conditions,based on image analysis technology,that is,in the 66 days of the growth of the clover,a 2D image of the clover is obtained by a digital camera directly above the clover canopy at intervals of 7-10 days;By analyzing the color characteristics of green leaves and yellow leaves in the phenotypic characteristics of clover under different treatments for 66 days,the expressions of the variation range of three color classifications R,G and B which can characterize the color characteristics of green leaves and yellow leaves of clover were extracted.The expression constructs a clover feature classifier that extracts the number of pixels of the green or yellow leaves;The classifier is used to extract the number of pixels of the green leaf of the clover and the number of pixels of the yellow leaf under different processing time,and then binarize;Calculating the area occupied by the unit pixel by extracting the pixel occupied by the calibration object of the known area;After photographing on the 66th day of clover growth,a pot of clover under each treatment(3-4 clover plants per pot)was randomly selected.The destructive sampling analysis method was used to determine the green leaf area and yellow of each pot of clover.The leaf area,the statistical relationship between the green leaf pixel and the green leaf area,and the statistical relationship between the yellow leaf pixel and the yellow leaf area were established.Using the 66th day clover green leaf pixel and the measured area to establish a model for estimating the green leaf area by the calibrated pixel,the yellow leaf pixel and the measured area are established to estimate the area of the yellow leaf by the calibrated pixel;Finally,based on the relationship between the leaf type and the area of the clover phenotypic classifier and the different types of clover,the green leaf area and the yellow leaf area of the clover under different treatment stages were extracted.The differences of phenotypic characteristics of different growth time and the trend and characteristics of green leaves and yellow leaves in 66 days were analyzed,in order to provide a certain method guidance and reference for obtaining the phenotypic characteristics of plants more quickly and accurately,by studying the effects of light and moisture on the growth,survival and reproduction of clover,the impact of global climate change can be avoided to some extent.The main findings are as follows:(1)A classifier for extracting the phenotypic characteristics of clover based on color features is constructed.The range and relationship of the three color components of the extracted green leaves are:62<R<220,82<G<254,34<B<154;R The mean value is 123.8,the mean value of G is 163.1,and the mean value of B is 66.2.The relationship between R,G,and B is:R>0.9G and R>0.85B.(2)The range and relationship of the three color components of the extracted yellow leaves are:152<R<202,133<G<192,65<B<123;the mean value of R is 178.1,the mean value of G is 160.82,the mean value of B It is 91.32;the relationship between R,G,and B is:G>0.65R and B>0.62 R,G≥ 1.1 R and G≥ 1.1 B.(3)For the TKPR-cultivated clover,a regression equation for estimating the green leaf area of the clover using the calibrated 2D green leaf pixel set was constructed:y=5.9628x+6.7556,R2=0.83,where x is the green leaf pixel set,y is Estimated green leaf area of clover;a regression equation for estimating green leaf biomass of clover using a calibrated 2D green leaf pixel set was constructed:y=0.0279x-0.0053,R2=0.72,where x is the green leaf pixel set and y is the estimated The green leaf biomass of clover;a linear regression equation for estimating the biomass of the yellow leaf using the calibrated 2D yellow leaf pixel set:y=0.0378x+0.0191,R2=0.66,where x is the pixel set of the yellow leaf and y is the estimated clover yellow leaf biomass.(4)For the Clover of TNSP,a regression equation for estimating the green leaf area of clover using the calibrated 2D green leaf pixel set was constructed:y=8.341x+0.8472,R2=0.85,where x is the green leaf pixel set,y is Estimated green leaf area of clover;a regression equation for estimating green leaf biomass of clover using a calibrated 2D green leaf pixel set was constructed:y=0.0286x+0.0176,R2=0.77,where x is the green leaf pixel set and y is the estimated Green leaf biomass of clover;a linear regression equation for estimating the biomass of the yellow leaf with a calibrated 2D yellow leaf pixel set was constructed:y=0.036x+0.0274,R2=0.65,where x is the pixel set of the yellow leaf and y is the estimated clover yellow leaf biomass.(5)Statistical analysis of the phenotypic characteristics of clover after 66 days of different treatments was carried out.The results showed that the difference in green leaf area between treatments with significant soil moisture was significant at 0.05 significant levels.There was a significant difference in the area of green leaf between the light intensity treatment,and there was an interaction effect between the light intensity and soil moisture on the green leaf area.At 0.05 level,there were significant differences in the biomass of the yellow leaf between different water treatments.However,there was no significant difference in the biomass of the yellow leaves at different levels of light intensity at 0.05 level;there was an interaction effect between the water conditions and the light intensity on the biomass of the yellow leaves.This study provides a feasible method for non-destructive rapid detection of plant phenotypic characteristics,and can help us understand the strategy of clover growth and survival.