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Rapid determination of leaf water content for monitoring waterlogging in winter wheat based on hyperspectral parameters

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Journal of Integrative Agriculture 2021年第10期20卷 2613-2626页

作者： YANG Fei-fei LIU Tao WANG Qi-yuan DU Ming-zhu YANG Tian-le LIU Da-zhong LI Shi-juan LIU Sheng-ping Key Laboratory of Agri-information Service Technology Ministry of Agriculture and Rural Affairs/Agricultural Information InstituteChinese Academy of Agricultural SciencesBeijing 100081P.R.China Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Agricultural College Yangzhou UniversityYangzhou 225009P.R.China College of Geoscience and Surveying Engineering China University of Mining&TechnologyBeijing 100083P.R.China

waterlogging is becoming an obvious constraint on food production due to the frequent occurrence of extremely high-level rainfall *** water content(LWC)is an important waterlogging indicator,and hyperspectral remote sensing provides a non-destructive,real-time and reliable method to determine ***,based on a pot experiment,winter wheat was subjected to different gradients of waterlogging stress at the jointing *** hyperspectral data and LWC were collected every 7 days after waterlogging treatment until the winter wheat was *** with methods such as vegetation index construction,correlation analysis,regression analysis,BP neural network(BPNN),etc.,we found that the effect of waterlogging stress on LWC had the characteristics of hysteresis and all waterlogging stress led to the decrease of *** decreased faster under severe stress than under slight stress,but the effect of long-term slight stress was greater than that of short-term severe *** sensitive spectral bands of LWC were located in the visible(VIS,400–780 nm)and short-wave infrared(SWIR,1400–2500 nm)*** BPNN Model with the original spectrum at 648 nm,the first derivative spectrum at 500 nm,the red edge position(λr),the new vegetation index RVI(437,466),NDVI(437,466)and NDVI´(747,1956)as independent variables was the best model for inverting the LWC of waterlogging in winter wheat(modeling set:R^(2)=0.889,RMSE=0.138;validation set:R^(2)=0.891,RMSE=0.518).These results have important theoretical significance and practical application value for the precise control of waterlogging stress.

关键词： winter wheat hyperspectral remote sensing leaf water content new vegetation index BP neural network

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Review of theoretical methods and research aspects for detecting leaf water content using terahertz spectroscopy and imaging

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International Journal of Agricultural and Biological Engineering 2018年第5期11卷 27-34页

作者： Fangfang Qu Pengcheng Nie Lei Lin Chengyong Cai Yong He College of Biosystems Engineering and Food Science Zhejiang UniversityHangzhou 310058China Key Laboratory of Spectroscopy Sensing Ministry of Agriculture and Rural AffairsHangzhou 310058China State Key Laboratory of Modern Optical Instrumentation College of Optical Science and EngineeringZhejiang UniversityHangzhou 310058China

The water content in vegetative leaves is an important indicator to plant *** reveals the physiological status of plants and provides valuable information in irrigation ***(THz)as a state-of-the-art technology shows great potential in measuring and monitoring the water status in plant *** paper reviewed the theoretical models for calculating water content in the plant leaves,the methods for eliminating the scattering loss caused by the surface roughness of leaf,the applications of THz spectroscopy and THz imaging for monitoring leaf water content and describing leaf water *** survey of the researches presents the considerable advantages of this emerging and promising THz technology in agriculture.

关键词： terahertz(THz)spectroscopy terahertz imaging leaf water content leaf water distribution theoretical models eliminating scattering loss agriculture

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Estimating leaf water content at the leaf scale in soybean inoculated with arbuscular mycorrhizal fungi from in situ spectral measurements

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International Journal of Agricultural and Biological Engineering 2019年第6期12卷 149-155页

作者： Weiping Kong Wenjiang Huang Xianfeng Zhou Hugh Mortimer Lingling Ma Lingli Tang Chuanrong Li Key Laboratory of Quantitative Remote Sensing Information Technology Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094China Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094China College of Life Information Science and Instrument Engineering Hangzhou Dianzi UniversityHangzhou 310018China Rutherford Appleton Laboratory Harwell Science and Innovations CampusOxfordshireOX110QXUK

leaf water content(LWC)of crops is a suitable parameter for evaluation of plant water status and arbuscular mycorrhizal effect on the host plant under drought *** sensing technology provides an effective avenue to estimate LWC in ***,few LWC retrieval models have been developed specifically for the arbuscular mycorrhizal inoculated *** this study,soybean with inoculation and non-inoculation treatments were planted under the severe drought,moderate drought and normal irrigation *** LWC changes under different treatments at the 30 th,45 th and 64 th day after the inoculation were investigated,and the spectral response characteristics of inoculated and non-inoculated soybean leaves under the three drought stresses were *** types of spectral variables/indices including:raw spectral reflectance(R),continuum-removed spectral reflectance(R C),difference vegetation index(DVI),normalized difference vegetation index(NDVI)and ratio vegetation index(RVI)were applied to determine the best estimator of *** results indicate that LWC decreased as the aggravating of drought stress ***,LWC in inoculated leaves was higher than that in the counterparts under the same drought stress level,and the values of raw reflectance measured at inoculated leaves were lower than the non-inoculated leaves,especially around 1900 nm and 1410 *** water spectral features were more evident in the corresponding continuum-removed spectral *** newly proposed DVI C(2280,1900)index,derived from the continuum-removed spectral reflectance at 2280 nm and the raw spectral reflectance at 1900 nm in DVI type of index,was the most robust for soybean LWC assessment,with R 2 value of 0.72(p<0.01)and root mean square error(RMSE)and mean absolute error(MAE)of 2.12%and 1.75%,*** study provides a means to monitor the mycorrhizal effect on drought-induced crops indirectly and non-destructively.

关键词： leaf water content remote sensing arbuscular mycorrhizal fungi drought crops

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High tolerance to simulated root herbivory in hydroponically grown cuttings of Salix phylicifolia

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Journal of Forestry Research 2021年第6期32卷 2661-2668页

作者： Mikhail V.Kozlov Elena L.Zvereva Department of Biology University of Turku20014TurkuFinland

The shortage of information regarding the effects of root damage on forest plants,especially trees and shrubs,is the most critical gap in our knowledge of belowground insect *** study examines how the tea-leaved willow,Salix phylicifolia,responds to simulated root herbivory and how nutrient availability affects these *** grown cuttings were used to precisely apply the desired levels of root ***:shoot ratios increased proportionally to the intensity of root damage,whereas specific leaf area,leaf water content and chlorophyll fluorescence were not *** removal of 2-64%of roots once in early summer and the removal of 25%of roots three times during the summer did not change biomass production by *** repeated removal of 50 and 75%of roots decreased shoot biomass and,to a lesser extent,total root *** tolerance of tea-leaved willow to root damage was greater in low nutrient treatment than in high nutrient treatment,thus supporting the Growth Rate *** to this model,in low resource conditions plants do not attain their maximum growth rate and therefore have a higher capacity for regrowth after *** conclude that,in the absence of water limitations,tea-leaved willow shows high tolerance to root losses and is unlikely to be affected by realistic levels of root herbivory.

关键词： Belowground herbivory Chlorophyll fluorescence leaf water content Plant growth

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