Study On Hyperspectral Characteristics And Quantitative Monitor On Physiological Parameter Of Winter Wheat(Triticum Aestivum L.) Under Water Stress

In recent years,the frequent occurrence of abiotic stress such as drought disaster has seriously affected the normal growth of winter wheat.After the occurrence of drought disaster,as the loss of water of winter wheat,there will be some changes in physiological and biochemical parameters,which will eventually lead to the reduction of yield and quality in different degrees.There are many characteristics of drought disaster,including slow development process,complex influencing factors and widely spread.Therefore,it is difficult to grasp the drought situation of winter wheat in real time by using traditional management technology,and there are some shortcomings such as large manpower and material input,delay,etc.With the popularization and application of hyperspectral remote sensing technology in the field of agricultural production,it provides a certain technical means for real-time,rapid and nondestructive monitoring of winter wheat growth after drought disaster.This study was based on the winter wheat water stress tests in 2017?2018 and2018?2019.Physiological parameters,including Leaf water content(LWC),Chlorophyll density(ChD),Proline content(Pro)and Superoxide dismutase(SOD),Catalase(CAT)and Peroxidase(POD)activity in winter wheat leaves were selected as the study subjects.The comprehensive drought index of winter wheat(CDI)was constructed by using the Principal component analysis method(PCR).The spectral reflectance was extracted by Correlation analysis and Stepwise multiple linear regression(CA +SMLR),Partial least squares and Stepwise multiple linear regression(PLS +SMLR)and Principal Component Analysis(SPA).The monitoring of physiological,biochemical and CDI indexes of winter wheat was studied by stoichiometry.The main conclusions were made as follows:1.After the occurrence of water stress,the physiological parameters changed with the increase of stress time.The ChD and Pro increased first and then decreased.The POD kept increasing with the change of growth period.The activities of LWC and SOD were relatively insignificant with the change of growth period.With the increase of water stress after the same post-seeding days,the basic changes in physiological indicators that were positively correlated were Pro,SOD,CAT,and POD,and the negatively related physiological indicators were LWC and ChD.Among them,the main indicators that were sensitive to water stress were group indicators ChD,osmoregulatory Pro,and POD activity in antioxidant enzymes,and the CAT activity responsed poor with stress.2.The spectral reflectance curve of canopy of winter wheat under water stress treatment basically accorded with the general spectral characteristics for green plants.The "green peaks"(540?560nm)and "red valleys"(670?690nm)appeared in the visible light band range.The "red edge" position(680?780nm)showed a sharp rise and formed a high reflectance platform in the near-infrared(NIR)spectrum.The correlation analysis of spectral reflectance and physiological parameters of canopy showed that the correlation coefficients between SOD and CAT and spectral reflectance of canopy were low,while the LWC?ChD?Pro and POD were high,which indicated that canopy spectral reflectance were sensitive to ChD,Pro and POD and water stress of winter wheat as well.3.In the correlation analysis between the single physiological biochemical index and the comprehensive index CDI constructed by the PCR method,the correlation were significantly,which realized the effective fusion of the relevant physiological and biochemical index information of winter wheat after water stress.4.The characteristic bands of physiological parameters extracted by integrating different characteristic band extraction methods were as follows: LWC(761,853,887 and 938nm),ChD(427,434,749 and 814nm),Pro(756 and 761nm),SOD(1068nm),CAT(744 and1350nm),POD(939nm).However,the number of characteristic bands of CDI extracted by different methods was large and distributed in all spectral reflectance regions.5.The PLSR monitoring model based on full-spectra was better than MLR and SMLR model based on characteristic bands.The Pro model performed best(R~2=0.845,RMSEC=0.131,RPD=2.540;R2=0.741,RMSEP=0.174,RPD=1.935).And it was found that the PLSR model of CDI had the best monitoring performance,and the fitting degree of the model was high(R~2=0.885,RMSEC=0.221,RPD=2.772;R~2=0.631,RMSEP=0.441,RPD=1.625),indicating that the model had certain universality and applicability.Besides,it was found in the models based on the characteristic bands that PLS+SMLR and SPA could realize the optimization and simplification of the model,which proved that There is practical significance in monitoring winter wheat by using CDI.